Simon John Eaves BA, PGCE, MSc.
Submitted April 2006 for the degree of Doctor of Philosophy University of Wales
Director of Studies: Professor Mike Hughes (U\ilIC) Supervisors: Dr Kevin Lamb (University of Chester); Professor Roger Bartlett (University of Otago) DECLARATION
This work has not previously been accepted in substance for any degree and is not being concurrently submitted in candidature for any degree.
Signed. ...(candidate)
Date. lLo
This thesis is the result of my own investigation, except where otherwise stated. Other sources are acknowledged by reference in text.
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I hereby give consent for my thesis, if accepted, to be available for inter-library loan or photocopying
(subject to the law of copyright), and for the title arid summary to be made available to outside organisations.
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Date À9-a.t 2.Ð*b CONTENTS
List of tables
List of figures lv
Aclarowledgements tx
Abstract The'Convergence of the Tlvain': A notational analysis of rugby x league and rugby union football (1988 - 2002)
Chapter 1 Introduction 1
Chapter 2 Review of Literature 10
Chapter 3 Methods 49
Chapter 4 Reliability and normative profiles 7S
Chaptcr 5 G¡me profiles 103
Chapter 6 Performance indicators 206
Chapter 7 Summary and conclusions 257
References 275 LIST OF TABLE,S
Page
Chapter 2 Review of Literaturc 10
2.1 A synthesis ofrugby union and rugby league papers since 2001 22 addressing the key issues in notational analysis
2.2 Frequency and percentages for key variables calculated ûom the raw 36 data presented by Potter (1997)
2,3 Performance indicators for RWC furals 1987-1995 38
2.4 I\zlean frequency of total game actions for Five Nations rugby 1992- 44 1994 anó RWC l99l and 1995
2.5 Stand offpossession options inthe 1992-1994 Five Nations 45 Championships
Chapter 3 Methods 49
3.1 Rugby league games analysed by Period and Era 67
3.2 Rugby union games analysed by Period and Era 68
Chapter 4 Reliability and normative profiles 75
4.\ Intra-observer level of agreemenr(%) for timing of variables rugby 17 union and rugby league
4.2 Intra-observer level of agreement (%) for the identification of selected EO variables in rugby union and rugby league
4.3 Intra-observer level ofagreement (70) for the frequency ofselected 81 variables in rugby union and rugby league
4.4 Intra-observer level of agreement (7o) for player identification in rugby 82 union and rugby league
4.5 Number of game quarters to reach stable means to within +1% (*r5o/o, 85 {"k +10%) of the overall mean for time variables in rugby union
4.6 Number of game quarters to reach stable means to within +lo/o (*+5yo, 8ó x* +10%) of the overall mean for time variables in rugby league
4.7 Number of game quarters to reach stable means ø within +1% (*+syq 86 ** +10%) of the overall mean for offence variables in rugby union
4.8 Number of game quarters to re¿ch stable means to within +l% (*+5yo, 87 ** +l}Yo) of the overall mean for offence variables in rugby league
4.9 Number of game quart€rs to reach stable means to within +1olo (*+5o/o, 88 ** +10%) of the overall mean for defence variables in rugby union
4.10 Number of game quarters to reaoh stable means to within *lo/o (**5o/o, E9 'Ì* +10%) ofthe overall mean for defence variables in rugby league 4,ll Number of game quarters to reach süable means to within +1% (*+5yo, 90 ** +l}yo) of the overall mean for game action variables in rugby union
4.12 Number of game quarters to reach stable means to within +1% (*+5yo, 90 ** +lOVo) of the overall mean for game action variables in rugby league
4.13 Number of games for offence and defence variables to stabilise to 9l withn+5%o (*+10%o) of the overall mean for the hooker in rugby union games by Period
4.t4 Number of games for offence and defence variables to stabilise to 92 within +5% (*+10%) of the overall mean for the no. 8 in rugby union games þ Period
4.15 Number of games for offence and defence variables to stabilise to 92 within +5% (*+10%) of the overall mean for the st¿nd offin rugby union games by Period
4.L6 Number of games for offence and defence variables to stabilise to 93 within +5% (*+107o) of the overall mean for the hooker in rugby league games by Period
4.17 Number of games for offence and defence variables to stabilise to 93 within +5% (*+10%) of the overall mean for the loose forward in rugby league games by Period
4.1E Number of games for offence and defence variables to st¿bilise to 94 within +5% (*t10%Ð of the overall mean for the stand offin rugby league games by Period
4.19 Summary of problematic intra-observer reliability analyses and the 101 effect of subsequent amendments to systems
Chapter 5 Game profiles 103
5.1 Code comparison for time variables by Era and Period 106
5.2 Percentage change (%L) n mean time variables between Periods by 108 Code
5.3 Code comparison for ofÊence and defence variables by Era and Period 109
5.4 Pøcentage change (%Â) in the frequency of offence and defence 111 variables by Period by Code
5.5 Offence and defence variable frequenoies per unit possession time by 112 Era and Period by Code
5.6 Code comparison for game action variable frequencies by Era and tt4 Period
5.7 Percentage change (%L) in game action variables by Period by Code tt6
5.8 Game action frequency per unit possession time (frequency/min ball in tt1 play, meøn time (secs) between actions) by Era and Period by Code
5.9 Mean +SD tackle type perc€ntage per game by Era and Period by Code t6
ll 5.10 Summary of game variables, factors influencing change in 196 performance profiles and the predominant direction of any code convergence
Chapter 6 Performance indicators 2M
6.1 Time performance indicators (s) by Game Result by Period for rugby 209 union
6,2 Time performance indicators (s) by Game Quarter Outcome by Period 2to for rugby union
6.3 Time performance indicators (s) by Game Result by Period for rugby 2tt league
6.4 Time performance indicators (s) by Game Quarter Outcome by Period 212 for rugby league
6.5 Offence and defence performance indictors (mean, median (range)), 2t3 Game Result by Period for rugby uruon
6.6 Ofrence and defence performance indicators (mear¡ mediar, (range)) 216 Game Quarter Outcome by Period for rugby union
6.7 Offence and defence performance indictors (mearl median (range)), 218 Game Result by Pøiod for rugby league
6.8 Offenoe and defence performance indicators (mear¡ median, (range)), 221 Game Quarter Outcome byPeriod for rugby league
6.9 Summary of performance indicators (by Game Resuh (GR) and Game 255 Quarter Outcome (GQO)) by Code by Period
rlt LIST OF FIGURES
Page
Chapter 1 Introduction 1
1.1 Key externaf events and independent variables in rugby union and 6 rugby league 1988-2002.
Chapter 2 Review of litemture 10
2.1 Example of raw sequential data for the analysis of netball. 18
2.2 Schema for developing a performanoe profile. 30
Chapter 3 Methods 49
3.1 Example of initial notation system for collecting time dat¿ in both 51 codes of rugby football.
3,2 Short hand symbols for offence actions in both codes ofrugby. 51
3.3 Example of initial notation system for the collection of offence 53 variables in rugby union.
3.4 Short hand symbols for defence actions in both codes ofrugby. 53
3.5 Initial notation system for the collection of defence daø in rugby 54 umon.
3.6 Example of a team sheet with secondary identification characteristics 56 of players.
3.7 Example ofthe final notation system for time variables (s) in both 62 rugby Codes.
3.8 Final notation system for the collection ofoffence and defence deta in 63 both rugby union
3.9 Decision model for statistical procedures on notational analysis data. 74
Chapter 4 Reliability and Normative profiles 75
4.t Intra-observer level of agreement - distribution of time differences for 78 'play the ball' time in rugby league.
4.2 Intra-observer level of agreement - distribution of time differences for 78 ruck time in rugby union.
4.3 Intra-observer level of agreement - distribution of time differences for 79 'play the ball' time in rugby league - test 2.
4.4 Inta-observer level of agreement - distribution of time differences for 80 ruck time in rugby unio n - tæt 2.
4.5 Data input discrepancies for ruok frequency analysts. 83
lv 4.6 Data input discrepanoies for maul frequency analysis. 84
4.7 Normative profile for rugby union ball in play time 1988-92. 85
4.8 Normative profile for rugby league total ball carries 1988-92. 87
4.9 Nornutive profile for rugby union total ball canies 1988-92. 89
4.10 Normative profile for rugby league single tackles 2000'02. 89
Chapter 5 Game profiles 111
5.1 Median (Inter-quartile range) total ball in play time per game by Period 119 by Code.
5.2 Mean +SD ruck time per game by Period by Code. 120
5.3 Mean +SD total ruck time per game by Period by Code. l2t
5.4 Mean +SD activity time per game by Period by Code. 123
5.3 Mean +SD total activity time per game by Period by Code. 124
5.6 Median (Inter-quartile range) set possession time per game by Period t2s by Code.
5,7 Mean +SD continuous possession time per game by Period by Code. 126
5.8 Median (Inter-quartile range) continuous ball in play time per game by 127 Period by Code.
5.9 Median (Inter-quartile range) frequency of total ball carries per game 129 by Period by Code.
5.10 Mean +SD frequency of total ball c¿rries per unit time by Period by 130 Code.
5.11 Median (Inter-quartile range) frequencies of total passes per game by t32 Period by Code.
5.12 Median (Inter-quartile range) frequencies of total passes per unit time 132 by Period by Code,
5.13 Median (Inter-quartile range) frequencies of dummy half passes per 133 game by Period by Code.
5.14 Mean +SD frequency of dummy/scrum half passes per unit time by 134 Period by Code.
5.ls Median (Inter-quartile range) frequencies of open play passes per game 134 by Period by Code.
5.16 Me¿n +SD frequenoies of open play passes per unit time by Period by 135 Code.
s.l7 Median (Inter-quartile range) frequencies of ofiloads per game by 135 Period by Code.
v 5.18 Median (Inter-quartile range) frequencies of offloads per unit time by Period by Code.
5.19 Median (Inter-quartile range) frequency of total carries into contact per game by Period by Code.
5.20 Median (Inter-quartile range) frequency of total carries into contact per unit time by Period by Code.
5.21 Median (Inter-quartile range) frequencies of total tackle attempts per game by Period by Code.
5.22 Median (Inter-quartile range) frequencies of total tackle attempts per unit time by Period by Code.
5.23 Median (Inter-quartile range) frequency of single tackles per game by Period by Code.
5.24 Me¿n +SD frequencies of single tackles per unit time by Period by Code.
5.25 Median (Inter-quartile range) frequencies of double tackles per game by Period by Code.
s.26 Median (Inter-quartile range) frequencies of mob tackles per game by Period by Code.
5.27 Median (Inter-quartile range) frequencies of double taokles per unit time by Period by Code.
5.2E Mean +SD single tackle percentages per game by Period by Code,
5.29 Median (Inter-quartile range) frequency of missed taokles per game by Period by Code.
5.30 Mean +SD percentages of missed tackles by Period by Code.
5.3r. Median (Inter-quartile range) frequencies of total kicks per game by Period by Code.
s.32 Median (Inter-quartile range) frequencies of kicks out of play per game by Period by Code.
5.33 Median (Inter-quartile range) frequencies of total kicks per unit time per game by Period by Code.
5.34 Median (Inter-quartile range) frequencies of kicks out of play per unit time per game by Period by Code.
5.35 Median (Inter-quartile range) frequencies of rucks per game by Period by Code.
5.36 Median (Inter-quartile range) frequencies of rucks per unit time per game by Period by Code.
s.37 IVledian (Inter-quartile range) frequencies of scrums per game by Period by Code.
5.38 Median (Inter-quartile range) frequencies of scrums per minute by Period by Code. vl 5.39 Median (Inter-quartile range) set possession frequencies per game by Period by Code.
5.40 Median (Inter-quartile range) set possession frequencies per unit time by Period by Code.
5.41 Median (Inter-quartile range) activity/phase frequencies per game by Period by Code.
5.42 Median (Inter-quartile range) aotivity/phase frequencies per minute per game by Period by Code.
Chapter 6 Performance ind icators
6.1 Mean * SD total possession time per game in rugby union by Game Quarter Outcome.
6.2 Mean + SD set possession time per game for rugby union by Game Quarter Outcome.
6.3 Me¿n * SD set possession time per game for rugby league by Game Result.
6,4 l\¡fean + SD continuous possession time per game for rugby union by Game Quarter Outcome.
6.5 Median (Inter-quartile range) continuous possession time per game for rugby league by Game Result.
6.6 I\¡fean * SD ruck time per game for rugby union by Game Quarter Outcome.
6.7 Mean * SD ruck time per game for rugby league by Game Quarter Outcome.
6.8 Mean * SD percentage 'fast' ball, per game in rugby union by Game Quarter Outcome.
6.9 Median (Inter-quartile range) percentage 'fast' ball, per game in rugby league by Game Resuh.
6.10 Median (Inter-quartile range) percentage 'slow' ball, per game in rugby league by Game Result.
6.11 Median (Inter-quartile range) percentage 'slow' ball, per game in rugby league by Game Quarter Outcome.
6.12 Median (inter-quartile range) carries into contact per minute for rugby league by Period by Game Result.
6.13 Median (inter-quartile range) frequencies of offloads per game in rugby league by Period by Game Result.
6.14 Median (inter-quartile range) offload to contåct ratio per game in rugby league by Period by Game Result.
6.15 Median (inter-quartile range) frequency of successful tackles per game in rugby union by Game Result by Period.
vll 6.16 Median (inter-quartile range) frequency of successful tackles per 235 minute in rugby union by Game Resuft byPeriod.
6.17 Median (Inter-quartile range) frequency of successful t¿ckles in rugby 2X league per game by Game Result by Period.
6.18 Median (Inter-quartile range) frequenoy of successful tackles per min 237 in rugby league per game by Game Result by Period.
6.19 Median (Inter-quartile range) percentage of single tackles per game in 238 rugby union by Game Result by Period.
6.20 Median (Inter-quartile range) percentage of double tackles per game in 238 rugby union by Game Result by Period.
6.21 Median (Inter-quartile range) frequencies of missed taokles per game 240 in rugby league by Game Quarter Outcome by Period.
Chapter 7 Summary and conclusions 257
7.1 Integrated model of factor influencing convergence in time variables. 267
7.2 Integrated model offactor influencing convergence in offence and 268 defence variables.
7.3 Integrated model of faotor influencing convergence in game action 269 variables.
vlll ACKNOWLEDGEMENTS
I would like to express my great appreciation to my Director of Studies Professor Mike Hughes for his guidance and support over the past four years. His subject expertise is second to none and this thesis is in part testimony to that weahh of knowledge. I would also like to thank my second supervisors, in particular Dr. Kevin Lamb, whose constant encouragement, positive feedback and thoroughness were always greatly appreciated.
Finally, I must express my deep appreciation to my wife Dr Rebecca Eaves (nee Kendall) for her assistance, encouragement and patience, particularly in the frnal stages of this 'epic journey'.
1X ABSTRACT
The principal aim of this study was to create longitudinal profiles (1988-2002) for the games of rugby union and rugby league football in order to identify whether changes in time, offence, defence and game action variables, and positional and game performance indicators were a reflection that the two codes of rugby were 'converging', Anecdotal evidence had suggested that due to certain administrative developments within this time ûame many facets of the two games were becoming similar, thereþ spawning the notion of a future single, unified game of 'rugby'. This thesis presents the first empirical and objeotive assessment of whether such convergence has occurred. The data for this study were extracted from 48 video-taped recordings of First Grade rugby league and International rugby union in the Northern hemisphere over the specified time frame. The matches were identifiable by Era (pre-/post-professional) and Period (1988-92, 1993-95, 1997-99 and2000-02). Key aspects of play or performance were distinguished via game models and expert opinion and were scrutinised via a series of specifically designed and validated hand notation systeÍls. Initial analysis considered (and established) the reliability of these systems, thereafter parametric and non-parametric inferential statistical teohniques were employed to identify Era and Period effects within each Code, with the additional analyses to consider the effects of Game Resuh and Game Quarter Outcomes. The findings from these analyses, particulaily the observed increase in ball in play time, changes at the ruck, maul, and lineout, and alterations in defence pattems of play, have provided a strong argument that the two Codes underwent a discernable degree of convergence over the years being considered. It was concluded that the introduction of professional playing status (rugby union), the summer playing season Gugby league), and law changes were likely causes of the two games being now similar in many respects. Although additional analyses should be encouraged to corroborate the present findings, the case for the development of a single Code of rugby can now be made.
Key words: Rugby league, rugby union, longitudinal mapping, notational analysis, reliability, convergence.
X CHAPTER 1 . INTRODUCTION
1.1 Rationale 2
1.2 Alms of the study 7
1.3 Main objectives 7
1.4 Limitations (internal validity) and delimitations (external validity) 8
1.5 Definition of terms 9
1 1.1 Rationale
On August 26ú lgg5 the International Rugby Football Board (later to become the International Rugby Board
(R,B) declared rugby union as an 'open' game, free of the previous restrictions of amateurism. On March
29ú lg96,the inaugural Super League season kicked off, with rugby league football changing from a 'winter' game to a summer playing season. Since then, however, there has been a paucity of published research which has attempted to address the impact of these signiflrcant changes in either code of rugby. Some researchers have examined the incidence of injuries in professional rugby (Garraway et al., 2000, Gssane, et al., 2001) and the physiological and anthropometric characteristics of players (Duthie et al.,2003; Gabbett, 2002;Meir et a1.,200I; O'Connor, 1996; Olds, 2001), though few studies have sought to assess the impact of tactical, technical, and match variables to provide game, team and/or individual player performance profiles. In rugby union, only Long and Hughes QO04) have presented profìles comparing pre-professional rugby with the professional game. In contrast, no similar research has been undertaken in rugby league football.
In rugby union, since 7995, a number of law changes have been introduced, ostensibly for either safety or commercial/entertainment reasons. Changes have been made to all facets of the game:- the'use it or lose it' laws and 'entering though the gate' at the ruck and maul, supporting and lifting in the lineout, ensuring
'suitably qualified' front row players are available for scrums, and the introduction of the sin bin - to name a few. Similarly, in rugby league, the introduction of the'seventh'tackle, orwhat has been called the 'zero tackle' rule, the 40-20 kick, and the marker at the 'play the ball' not being allowed to strike for the ball have all been introduced in the Super League era. The impact of these rule and law changes has yet to be fully explored, with only Williams et al. (2003); \{illiams (200$; Williams, Thomas et al. (2005) and Williams,
Hughes et al. (2005) having examined the impact of law changes in rugby union in the professional game. In rugby league, only Meir, Colla et al. (2001) have examined the impact of a rule change (1992-93 offside rule) in the game.
Many of these law changes in rugby union could be viewed as reducing the competition for the ball at the set piece and breakdown situation. For example, Martin et al. (2001) reported that the lineout has become less contested in recent times, the laws governing the ruck (to prevent slowing the ball recycling) have resulted in a reduction in challenging for the ball by defending players, and the 'use it or lose it' law in the maul has effectively negated its use as an attacking strategy, resulting in a reduction of mauls in the professional era, Add to this the recent IRB proposal to amend the laws of the game @ills, 2006) which will ) allow players to 'pull down' a maul, throw the ball towards their own players at 'quick' lineouts, and reduce the opportunities to kick the ball to touch 'on the full' (without bouncing in-field first), points to the game becoming more like rugby league (by removing or reducing key constituents of the union game). In addition, in rugby league a recent rule change (40-20 rule), which ostensibly rewa¡ds teams who kick the ball out of play, seems to be directing the game towards a more 'union style' of play. This may not seem strange given the cross-code movements of players, coaches and administrators, particularly in the professional era.
Since 1995, the player diffusion from rugby union to rugby league has reversed, with high profìle rugby league players like Jason Robinson, Iestin Harris, Andrew Farrell and Henry Paul (amongst others)
'transferring' to rugby union. In addition, ex-rugby union converts for example, Jonathan Davies, Alan Tait,
Martin Ofnah and Scott Quinnell have been lured back to the 'professional' union game. Moreove¡ and
perhaps more influential was the almost worldwide policy of rugby unions employing rugby league coaches.
Ex-rugby league players and coaches are at present involved in some capacity in most Six Nations
international sides; Dave Aldred, Joe Lydon, and Phil Larder in England, Clive Griflith in Wales, Alan Tait
in Scotland, Dave Ellis in France and Mike Ford in Ireland. It is therefore not incongruous to suggest that
'professional' rugby union has been strongly influenced by rugby league players, coaches and coaching
methods.
Considering the rule/law changes in both codes of rugby, the diffusion of players and coaches between
codes, and the change in playing status in rugby union, it is not out of place to suggest that the games are
becoming more alike. In recent times, the 'thawing' of relations between the'rival' codes has become more
apparent, with the England rugby union side training alongside Super League side Leeds Rhinos, the union
and league teams in Leeds (Tykes and Rhinos) sharing a ground, and most notably London Broncos (rugby
league) and Harlequins (rugby union) merging in 2006
In addition, Olds (2001) has suggested that due to the increases in body mass index (Blntr), body mass and
mesomorphy in rugby union players, the differential between this sporting population and the source
population is widening, and more importantly, accelerating. As a consequence, he argued that there is a
'dwindling pool' ofpotential players, and hence, unions have increasingly sought foreign players to bolster
their squads, a fact highlighted by 72Yo of players in the 1997 Rugby World Cup @WC) being born in
countries outside of their national squad, and in the case of Scotland 42Yo of the squad (Olds, 2001). To
counteract this increasing trend, rule changes were introduced in 2000 which disallowed players from
'swapping' nationalities. The impact of this change in rules has yet to be fully assessed; however, it is not
J inconceivable that to increase the 'dwindling pool' ofplayers, unions are increasingly likely to poach players from other sports, most notably rugby league. If this is the case, then it may be that the IRB is introducing law changes that make the game more similar to rugby league, and hence, increase the potential pool of
players for the union game. The implications are clear; if the codes of rugby are converging, the formation of
a single-code game is a possibility, or less controversially, union and league teams not only sharing grounds
and names, but also coaches and players. The question has to be can the two codes co-exist, or is the obvious
destiny - one code of rugby? Whatever the outcome, it is in the best interest of players, coaches and
administrators to identifo how the games are developing so that objective decisions can be made regarding their future.
Whether or not the two codes of rugby ever merge to become a single code at the professional level, there
may be merit it devising a single game at school and junior level, based on the core elements of both codes.
This has clear advantages to both the rugby union and rugby league. Expanding the game beyond its traditional'heartland' (Lancashire, Yorkshire, Cumbria) is vital if the development of the league game is to
continue. By devising and introducing a'unified' game of rugby at school and junior club level, the sharing
of facilities, coaches and players may aú. as a catalyst to initiate greater interest in areas which cannot, or will
not at present support professional rugby league. For rugby union increasing the potential 'pool' of players
and continued sharing of 'good' practice with rugby league coaches can only benefìt the game. Hence, if the
games of rugby are becoming more alike, key game variables and indicators can be identified, which would
form the basis ofthe single code game.
To date, there is no empirical evidence to suggest that the games of rugby union and rugby league are
converging and hence, are likely some time in the future to result in a single code game. To ascertain whether this is a possibility, it is important to track the performance aspects of the games over time. The principle
problem, however, is that there is a lack ofpublished research addressing any tactical and technical variables
or performance indicators in rugby league; hence mapping the game over time (longitudinal analyses) is not possible. The same concern is less apparent in rugby union, since this code of rugby has been more
extensively researched; with publications focussed on tactical, technical, and match variables, and
performance indicators. Even so, there are many concerns regarding the validity ofthe findings presented by
researchers in this field. Hughes et al. (2002) reported that as many as 80% ofpapers in notational analysis of
sport failed to address the issue or used inappropriate methods in their assessment of their system's reliability. In addition, Hughes, Evans e/ al. (2001) reported serious concerns that most researchers failed to
4 take note of whether or not in presenting performance profiles the variable means stabilised, which then casts
doubts on whether these profiles could be viewed as representative of the 'population' of rugby matches.
As a consequence, most of the results of studies presenting performance profïles in rugby union must be viewed with cautior¡ and therefore, similar to rugby league no longitudinal profile for this game can be
clearly defìned for any ofthe key performance indicators. Hence, there is a need for researchers to adopt a more systematic approach to their analyses in order to establish extensive performance profiles for both
codes of rugby football, which are set in context with the key external events and rule changes over time.
Only when these profiles have been validated can inferences be made regarding whether or not the two codes
of rugby are becoming more alike. Figure 1.1 presents key rule changes and independent variables which may have been contributory factors in changing performance profìles in both codes of rugby football.
However, it must be noted that other factors which span several years, for example changes in player fitness,
changes in coaching and player personnel and the evolving impact ofsports science support may also have
had an influence on the changing performance profïles.
5 Rugby League Rugby Union
Courage Leagues replace 1988 Merit Tables
1989
1990
l99l
Four points for a try replaced by five points for a try 1992
l0-m offside rule replaces 5-m 'Use it or Lose it' maul law 1993 offside rule introduced
1994 IRB sanction professional a Professional rugby moves from playing status a winter to summer playing season. 199s a Inception of Super League Introduction of supported lineout 1996 jumpers
Rules changes:- Introduction Introduction of o Introduction of 'video'referees 1997 'non-injury' ofthe zero substitutions tackle o Six player interchanges 1998 replace four a Scrum laws amended:- interchanges wheeling and 'use it or lose it' o Ball stealing a Ruck law change to prevent Introduction of40- 1999 in the 'slowing the release of the ball' 20 kick rule multiple tackle outlawed 2000 Tackle law - o Striking out a 'Uso it or lose it' players External timekeeper maul law required to at the 'play replaces referee as amended, enter rucks the ball' arbiter of game time allowing and mauls outlawed 2001 attacking team an from behind o Forward exFa five seconds the tackle play from to 'use'the ball player Twelve player the 'play the Use of 'suitably a Video interchanges replace 2002 ball' qualified'front rçferee and previously allowed outlawed rowreplacements sin bin six interchanges intoduced inhoduced
Figure 1.1 Key external events and independent variables in rugby union and rugby league 1988-2002
6 1.2 Aim of the study
The aim ofthe study vvas to:
Establish whether the games of rugby union and rugby league are becoming more alike and identi$, the impact ofkey factors influencing any code convergence.
1.3 Main objectives
This was achieved by the following main objectives:
1, The establishment of a framework for intra-operator reliability and normative profiles for key time, offence, defence, game action and positional profiles in rugby union and rugby league football between 1988
anó2002.
2. The construction of longitudinal time, offence, defence and game action profìles for rugby union and rugby league in four periods spanning 1988 and 2002 io assess the impact ofkey factors on these profiles which may have resulted in a converging ofthe Codes.
3. Assessment of changes and factors influencing change in key performance indicators (by game result and
successful game quarters) in rugby union and rugby league in four periods spanning 1988 and 2002 to assess the impact of these factors on the common performance indicators which may have resulted in a converging ofthe Codes.
7 1.4 Limitations (internal validity) and delimitations (external validity)
This study examined Northern hemisphere international rugby union (Five and Six Nations Championships) and domestic rugby league (Challenge Cup, Premiership, Regal Trophy and Super League) in four distinct periods spanning 1988-2002. The rationale for examining Domestic rugby league rather than International rugby league was twofold. Firstly, in rugby league there have been very few international games between
Northern hemisphere team, since at International level individual home unions have predominantly combined to play as a Great Britain team. In addition, after the 2006 Tri-Nations tournament the Rugby Football
League (RFL) has declared that the Great Britain team will be 'retired', so that players will be able to represent their home countries at International level. Secondly, the domestic game (in general) is representative of a higher standard of play than the international version in the Northern hemisphere. For example, in August 1996 ühe Ireland versus Scotland game included only seven professional players (Alan
Tait, Matt Crowther, Danny Russell, Darren Shaw, Martin Crompton, James Lowes and Bernard Dwyer), the remaining players being from the lower leagues. In contrast, the Challenge Cup final (Domestic game) played in 1993 included a whole team of International players (Wigan) and a team (Widnes) predominantly made up of International players including Kurt Sorensen, Jonathan Davies, Bobby Goulding and John
Devereux, to name a few.
This study relied on pre-recorded video-taped footage of games of rugby. Hence, there was no control of the amount of 'missing' live action caused by action replays and cameras focusing on peripheral images
(crowd, coaches, substitutes etc.). In addition, due to the success of Wigan rugby league club in the pre- professional era (1988-1995), no full game footage was available for analysis that did not include this team.
I 1.4 Definition of terms
For this study the following definitions will apply;
Challenge Cup, Regal Trophy and Premiership - annual knock-out competitions in Northern hemisphere rugby league (the Regal Trophy and Premiership ceased to exist at the inception of Super League in 1995).
The Challenge Cup has been played every year since 1896.
Five (5N) and Six Nations (6N) Championships - an annual international competition played between
England, Ireland, France, Scotland and Wales (Five Nations) and Italy after 2000 (Six Nations).
Grand Slam - when a team in the 5N or 6N Championships defeats all other sides in the tournament.
International Rugby Board (IRB) - the world governing and law making body for the game of Rugby
Union.
Rugby Football League (RFL) - the governing body for rugby league in the United Kingdom.
Rugby Football Union (RFU) - the governing body for rugby union in England.
Rugby World Cup (RWC) - a world-wide International tournament first played in 1987 and every four
years since.
Super League - the only full-time professional domestic rugby league competition in the Northern
hemisphere.
Tri-Nations Championship - an annual International competition played between Australia, New Zealand
and South Africa.
9 CIIAPTER 2 - REVTEW OF' LITERATURE
2,1 Introduction 11
2.2 Problems associated with subjective observation of performance 11
2.2.1 Accuracy of observation t2 2.2.2 Recall t4
2.3 Notational analysis t4
2.3.I History and development t4 2.3,2 Types and uses of notational analysis 15
2.4 Issues in notational analysis 16
2.4.1 Reliability analyses 16 2.4.2 Normative profiles l8 2.4.3 Statistical analyses 20 2,4.4 Performance indicators 2l
2.5 Issues in notational analysis - Rugby football (as an exemplar) 22
2.5.1 Reliability analyses 23 2.5.2 Normative profiles 25 2.5.3 Statistical analyses 25 2.s.4 Performance indicators 26 2.5.5 Implications 2'I
2.6 Analysis and modelling of sport 28
2.6.1 Time and motion analysis 28 2.6.2 Performance profiles 29 2.6.3 Mapping the game - rule changes and longitudinal analysis 31
2.7 Analysis and modelling sport (rugby football- as an exemplar) 33
2.7,1 Time and motion analysis 33 2.1.2 Performance profiles 35 2.7.3 Mapping the game - rule changes and longitudinal analysis 40
2.E Problem 46
10 2.1 Introduction
The following review of literature provides an in-depth appraisal of the problems associated with the subjective observation of sports performance and the need for notational analysis as a more objective and systematic approach in performance analysis (section 2.2). The key developments and the main types of notational analysis are reviewed in section 2.3. These initial sections are not meant to be a comprehensive review of the literature, but merely to provide the context for the current research. For a more thorough review of the issues discussed in these sections the reader is referred to the review by Simmons and King
(1994) and Hughes and Franks' (1997 &,2004) texts.
The main body of this section (2.4 - 2.7) reviews the contemporary issues in performance analysis, namely, the issues relating to reliability analyses, normative profiles, statistical analyses and the use of non- dimensional (normalised) performance indicators, and then discusses these issues using rugby football as an exemplar. The final two sections deal with general issues in modelling sports performance and then as with the previous sub-sections, use rugby football as an exemplar.
2.2 Problems associated with subjective observation of performance
Coaching intervention has been traditionally based on subjective assessments of the athlete or team performance (Franks, 2004). That is to say, the coach observes the performance and then provides feedback based on his or her recollection of the events. This method is naturally flawed, particularly in team games where the duration ofthe activity often exceeds an hour, the playing area is large and there are a high number of interactisns between as many as thirty-six players (Australian Rules Football). The observation problem is exacerbated in sports which are fast moving andlor where play is often congested, for example the rugby union ruck or maul. Hence, the expectation that an individual is able to observe, assimilate and recall events, often many hours or even days later is unrealistic.
Subjective assessment, according to Franks and Miller (1986) does have a role in coaching. However, it is clear that there are a number of limitations with the observation to recall process, notably the accuracy of coaches' analyses and issues with the validity oftheir subsequent recall ofevents.
11 2.2.1 Accuracy of observation
The concern, as previously noted, particularly in the qualitative analysis of performance, is that much of the information gathered is based on subjective observation (Smyth et al., 1998). making bias and distorted perceptions of performance more likely (MacDonald, 1984). Franks eî aI. (1983) suggested that in analysis of game performance the accuracy of observation is affected by a number of factors; the observer's focus of
attentior¡ the time and conditions of analysig and prior conditioning and prejudice.
Focus of Attentíon
In team game$, which are characterised by many interacting variables, and often a confusing display, the
observer is immediately presented with Iarge amounts of information. Selecting the important information
from the background 'noise' is essential, since if the 'observers do not selectively attend to the critical
features...they will not be able to extract the necessary information' (Canoll & Bandur4 1982, p.165). In
addition, Franks and Miller (1986) noted that the assimilation of peripheral information is limited when the
obseryer's attention focuses on central critical features. However, this view is based more on extensive
research on criminal events ratherthan on sports situations. Franks (20t4,p.I3)believed 'research cornpleted
on eye-witness testimony is very relevant to the sports coacl/scientist', and cited the work of Wells and
Leippe (1981), who suggested that witnesses of a staged crime who could identi$ the thief oorrectly were
less accurate in providing peripheral information. In addition, the observers who failed to identify the thief
correctly were much better at providing peripheral details. Hence, if it is accepted that observation of crimes
can be correlated to observation of sport then the notion of Hughes and Franks (1997) regarding the
relationship of attention to critical and peripheral features in sport may be well founded. This view may,
however, be flawed, since the subjects used as eyewitnesses in the study were neither trained observers, nor
is it made clea¡ that they worked in an indusry where observation w¿s a key component of their daily labour
(in contrast to the work of sports coaches). As such, relating the responses of 'untrained' observers in a
highly stressful þerhaps fearful) short duration event to 'experienced observers' in the freld of coaching,
where the durations are protracted, and whilst stressful at times, is unlikely to involve 'fear', may be
somewhat tenuous. Nevertheless, Franks (1993), in a study on gymnastics coaches reported that experienced
coaches were not significantly better at detecting differences in performance compared to novice coaches. In
fact, he suggestod that experienced coaches lry€r€ more likely to observe differences where none actually
existed. These fïndings are supported by Bard et ø1. (1980} who noted that there were no differences in the
eye movements of experienced nationally certified judges and local non-certified gymnastics judges when
t2 observing performance. Likewise, Petrakis (1986; 1987 as cited in Simmons & King, 1994) reported no significant differences in the number and duration of gymnastics and dance fixationg although, similar to
B.ard et al., (198A), the location of fixation differed. These findings appear compatible with studies undertaken by Armstrong and Hoffman (1979); Skrinar and Hoffman (1979) and Imwold and Hoffman
(1983), assessing differences in observations between novices and experts in a range of athletic performances. Simmons and King (1994) presented a comprehensive review of studíes in indirect and direct methods of assessing observation and the subjective analysis of performance, albeit pertaining to technique analysis rather than to matcå analysis. Based on their review of studies addressing the differences in error detection between experienced and novice observers (Bard & Fleury, 1976; Bard et al., 1980; Petrakis, 1986;
1987) they concluded that the attention to relevant cues was more pronounced in experienced observers than novices.
Durøtion ø,nd condìtìons of observøtìons
In addition to the atterition focus of the observer, Franks and Miller (1986) suggested that the length of time the observer is required to attend to the game shows an inverse relationship with quality of observations.
Moreover, the conditions under which observations take place may also influence the quality, for example the lighting, viewing location, crowd presence and the speed of movement which are typical of many sports.
The proximity ofthe observer to the field ofplay and the degree ofelevation are also factors that are likely to affect the precision of observation. In many sports the coaches are positioned relatively close to the field of play, but quite often at ground level making spatial assessments more difficult. This has been partially overcome in some sports like American Football where coaching assistants are seated in elevated positions,
allowing detailed feedback to be given to the head coach on the sideline. Increasingly, subjective assessment of games indicates that this appears to be have been adopted by mainstream sports in the United Kingdom
(Rugby League and Rugby Union Football).
híor condítìoníng ønd priming
Franks and Miller (1986) suggested that coaches are possibly prone to pre-conditioning and as a consequence may bring pre-set views and prejudices to the observation arena. If observation accuracy is to be improved, then such prejudices and biases need to be acknowledged and addressed. In particular, McDonald (1984)
suggested that four key psychological errors need to be considered; the halo effect, logical error, leniency effors and ceritral tendency errors. Hencg the coach may judge the performance of an athlete oû one aspect of play based on his or her performance in another aspect of play. He/she may also make judgements because
13 they appear logical and avoid giving players' a low rating or 'scoring' the performance as neither very good nor very bad. In addition, Hughes and Franks (1997, p.8), suggesfed that 'highlighted features of play' may distort a coach's overall perception, as these are likely to be the most remembered events.
2.2.2 Recall
In a study designed to identify how successful coaches ïvere at observing and recalling events in a soccer game, Franks and Miller (1936) reported that the probability of recalling critical events was only 0.42, whereas they were more successful at recalling set plays, for example corners and free kicks. This clearly demonstrates a limitation of the human memory system. According to Franks Q004), the rapid forgetting of events is unsurprising, and €vents that are considered non-critical are less €asy to remember. To this end
'extemal memory devices' can be used to assist in the recording and subsequent recall of events. These may be a simple pen and paper, videotape recordings, or more recently the use of commercially available systems e.g. SportsCode, Prozone, Quintic, Dartfish. Franks and Miller (1991) ventured as fr as suggesting that without the use of an external memory device the coach is 'generally un¡eliable and inaccurate in their ability to recall pertinent, sequential facts from a sporting environment' (p.286). Arguably, the need for such devices in conjunction with a more systematic approach to observation is essential in accurately recalling relatively complex events and behaviours which are characteristic of many sporting situations. This more systematic approach (notational analysis) involves defining and identifying the critical elements of performances and then developing appropriate methods of data collection. As a consequence, higher degrees of observer objectivity have resulted and subjective analyses are less likely (More & Franks, 1996).
2.3 Notational analysis
2.3.1 History and development
Early notational analysis in sport, not surprisingly appears to have started in North America. According to
Hughes and Franks QOO4), the first publications on notation in sport were Fullerton's assessment of player
actions in baseball in l9l2 and Messersmith and Bucher's analysis of movement patterns in basketball in
1939. Lloyd Lowell Messersmith could be considered a pioneer in sports notation, publishing an additional
t4 frve papers assessing basketball, field hockey and American football. For a comprehensive review of
Messersmith's work refer to Lyons (1997).
Despite the paucity of pubtished research in notational analysis aft.er 1944 (Messersmith's final paper), data gathering systems were clearly being employed in other sports. Reep and Benjamin (1968) analysed 3,213 soccer garnes over a frfteen-year period (1958-63) and Downey (1973 as ciæd in Hughes and Franks, 2004) developed a detailed hand notation system for lawn tennis. According to Hughes and Franks (2004, p. 69), the motion analysis of soccer by Reilly and Thomas (1976) is a seminal paper and 'has become the standard against which other similar research projects can c,ompar€ their results and procedures'. lmportantly, Reilly and Thomas (1976) adopted a systematic approach to their analysis and emphasised the importance of the reliability and the validity of their system; something which has still not been universally adopted by researchers in performance analysis (refer to section 2.4.1).
The development of'user friendly' computers in the late 1970s and early 1980s resulted in researchers developing specific systems to assess sporting behaviour, allowing the game to be 'digitally represented via data collectiûn directly onto the cornputer' ftIughes & Franks, 2004 p.81). This allowed for the storage of vast amounts of information and the development of databases, which could be potentially used for predictions of future performance. Further developments of computer systems have included specifically designed keyboard systems such as the concept keyboard (Church & Hughes, 1986), systems linking video footage to data (Gerisch & Reichelt, 1993), and sports specific systems, for example NETSTAT (Croucher,
1997) and a rugby union contact analysis system (Smyth et al.,1998).
More recently commercial systems have become readily available which enable analysts and coaches to provide athletes with almost instantaneous feedback. Such systems allow the analyst not only to provide quantitative feedback, but also to recall and edit clips of perfiormance. However, the drawbacks of such systems are that they are still relatively expensive, take many hours of training to master and, according to
Hughes and Franks Q004, p.106) are no better than simple pen and paper analysis, as long as the results produced by these more simple systems are accurate, reliable and easy for coaches to understand.
2.3.2 Types and uses of notational analysis
The types ofdata collected by notation analysts are varied and depend on the requirements ofthe coach. It has been suggested that one of the purposes of notational analysis is to provide information on player movements (Hughes & Franks, 2004). These types of analyses provide information such as distances
covered, work-to-rest ratios, time spent in high and low intensity activities, and therefore enable the coach to
15 devise more specific conditioning progtammes. Often these types of data are presented in conjunction with heart rate profìles, and /or blood lactate readings; however, both of these methods have limitations (refer to section 2.6. l). Notation systems have also been developed to collect data on specific performance indicators, which can be tactical, technical or match indicators. Such systems have been used to assess team and individual performances in an aüempt to provide a profile of the performance, which enable comparisons to previous performances, comparisons to others' performances, and íf databases are large enough, to predict future performance. In additioq according to Franks et al. (1983) the information derived from notational analysis can be used to identify areas of improvement in the athlete, for scouting and team selection.
Holever, the fundamental use of notational analysis is to provide objective, reliable and valid feedback to the athlete either immediately, or some time post-event. Hence, notational analysis can be viewed as a fundamental cog in the prûcess of performance improvement in sport.
2.4 Issues in notational analysis
2.4. I Reliability analyses
In designing new analysis systems, it is fundamental that repeatability and accuracy of the system are clearly established. In the field of notation analysis Hughes et al. (2O02) have identified that scant regard has been given to reliability analysis, in fact they suggested that as many as 70%o of research papers fail to address reliability in any form. This is somewhat surprising sincg in the oft cited research by Reilly and Thomas
(1976) the importance of establishing the reliability and objectivþ of the system was clearly reported. An additional concern identified by Hughes et al. (2002) was that a further 15% of studies utilised inappropriate methods such as the Pearson's correlation coeffrcient and ANOVA, techniques questioned by Bland and
Altman (1986). These authors made a number of pertinent points arguing against the use of correlation coeftÌcients, fundamentally stating that a 'change in scale of measurement does not affect the conelatior¡ but it certainly does the agreement' (p.308). Similarly, Atkinson and Nevill (1998) suggested that correlations do not assess the within-subjects agreement between repeated measures. The common misconception is that
Pearson's correlation addresses agreement rather than the level ofthe linear relationship between variables.
In addition, the common test-retest procedure predominantly used in reliability assessment is univariate, whereas Pearson's correlation coefücient is a bivariate test. Even so, this test and the Intraclass Correlation
t6 Coeffrcient (ICC) in assessing reliability are still utilised, for example, Liddle and Murphy's (2001) analysis of badminton and more recently Palao et al. (2005) in volleyball. According to Lamb er al. (2004) this may be due to these methods being simpler to understand and traditionally more popular than alternative methods
such as the use of calculating the 95%o limits of agreement (LoA), advocated by Bland and Altman (1986).
Whilst the use af 95% limits of agreement may be deemed a mor€ appropriate method of assessing
reliability, its use in notational analysis may be limited due to the level of measurement of the dependent variables and the assumptions of normal distribution of data. Often in notational analysis the data are nominal or categorical and/or not normally distributed, therefore LoA cannot be used, since the agreement is
calculated assuming the distribution of data is normal. Since in notational analysis the data are more likely to be Bernoulli or Poisson distributions (Nevill et a1.,2002) the use of LoA is not appropriate.
However, influenced by Bland and Altman's plots, Hughes et øL (2AO2) presented 'modified plots' as a
visual representation ofthe level of agreemenlerror between observations. These plots represent the mean
score, differences (both negative and positive), and the range ofthe differences in the scores. This enables
analysts to identift any outliers in the data set which may severely reduce the level of agreemsnt. This visual
representation also provides an immediate illustration of where the measurements are likely to fall beyond
the established limits of agreement. A further benefit of this method is that the assessment is based on raw
data rather than processed data. According to Hughes et al. (2O02) this is important, as using the sum of
variable frequencies (processed data) can mask true error values. Hence, whether adopting the 'modified
plot' representation or the calculation ofthe percentage difference between observations, it is imperative that
analysts use raw data. Consider the example of two analysts recording the position of turnovers in a game of
netball. Each analyst records 21 turnovers in the game, which represents 100% agreement, or Oplo error,
However, when these ðata are further analysed with respect to the three court thirds, analyst A recorded 6,
12, a¡d 3 turnovers in the defending, centre and attacking thìrd, respectively, whereas analyst B recorded 7,
I I and 3 in the same court areas. In this more in-depth analysis, there are two differences in the twenty-one
observations, hence the error p€rcentage is actually 9.5Yø rather than the OYo initially calculated. However,
this score still may not provide the 'true' error percentage, since, for example it is unclear whether or not the
three turnovers recorded in the attacking third by both analysts were the same turnovers, To ascertain
whether this is the casg the original raw sequential data must be examined, Figure 2.1 represents the original
sequence of data collection by the two analysts, using codes for attacking (a), centre (c) and defending (d)
court thirds, with the observer differences represented by the asterisk.
17 A ac a dc c c a c ac a c ac c ddc c c
B ccaacccacadacaccddscc
** tl. ¡t
Figure 2.1 Example of raw sequential data for the analysis of netball.
Adopting the more thorough approach shows tåat there were four observation differences between the
analysts out of the total of twenty-one observation, representing a l9Yo error percentage. This clearly
illustrates that in reliability analyses the sequentiality ofthe data should be retained so that item by item cross
checks can be made (Hugheset a1.,2002). If thisprocess is not followed the level of agreement between
observers or within the obsewer may be over-inflated. This concern is more evident in analyses using
multiple court or pitch cells; a common practice in notational analysis of sports. In football analysis, Hughes,
Langridge et ø1. Q}Ol) and Larson et al. Q}Olj both subdivided the pitch into multiple cells. The problem
with these playing area divisions is the number and size of cell boundaries increase exponentially as the
number of cells increases. For example, Hughes, Langridge et al. (2001) used a nine-cell pitch (representing twelve cell boundaries) compared to a forty.cell pitch (sixty-swen cell boundaries) utilised by Grehaigne el al. (1997). As such, the areas of the court or pitch where observations are 'uncertain' is multiplied as a
function of the number of cell divisions, hence, possibly further decreasing the observer level of agreement.
Consequentl¡ it is imperative that in undertaking reliability assessments in performance analysis the data
are examined where possible in their raw form and retain their sequentiality. Researchers must consider the
appropriate balance of gaining 'meaningful' results in positional (using cells) analyses against the increased
risk ofaccumulated errors due to the nature ofassessing performance in pitch or court areas. In additioq it is
advised that for technical, tactical and match variables, the use ofthe percentage error equation, advocated by
Ìfughes et aI. (2002) is adopted rather than inappropriafe statistical tests (ANOVAq I testg conelations),
2.4.2 Normative profiles
Sports performances are by their very nature variable, hence in presenting a proflle of performance it is
diffrcult to ascertain whether the particular performance is relatively consistent. That is to say, the means of the variables under consideration have stabilised to a level to which the data can be considered representative
of a 'typical' performance. For example, in one game of rugby union a player may score four drop goals and three penalty goals, yet in the next game fail to score at all. The question here is whether the first game or
18 second game data should be used to present the perfiormance profìle. Clearly neither is the 'norm', but is indicative ofthe variant nature ofthe sports performance. It has been argued that a better approach would be to present the mean score of the two games, or assess many games to get a larger sample that may be more representative of the 'average' performance. Hughes, Evans et al. Q00l) suggested that in notational analysis
it h¿s been previously been an 'implicit assumption .. . that in presenting a performance profïle of a team or
of an individual a normative profile has been achieved'. That is to say, previous researchers have assumed the data means would stabilise (be typical) if enough performances were analysed. As a consequence most of the previous research in notational analysis must be viewed with some caution, since often few games were
analysed and their data means may not have stabilised, and hence may not be representative of the
performance, In contrast, analysing too many performances may result in the 'mean' performance becoming insensitive to important changes when more recent performances are added to the 'database'. It is therefore
important that analysts identift how many games or individual performances are necessary for a stable, normative profìle to be reached, otherwise, according to Hughes, Evans et al. Q00l) any conclusions made based on these data must be questioned. Three basic methods have been presented in an attempt to identify
the number of games necessary to establish a normative profile. The most widely used to date are plots
showing how the data of the cumulative means of variables stabilise to within a pre-determined limit of error,
a method outlined by Hughes, Evans el al. Q00l). Alternative approaches have been presented by
O'Donoghue (2005) and James et al. (2005). O'Donoghue (2005) criticised the method advocated by
Hughes, Evans el al. Q00l) on a number of levels. Firstly, he implied that the technique risks interpreting a
difference as tolerable since the evolving means are related to the eventual total mean. Secondly, he
suggested that some athletic performances are 'erratic' in relation to certain performance indicators and may
not easily stabilise. Instead O'Donoghue (2005, p.107) has presented an alternative procedure based on the use of percentiles established from 'data from hundreds of performers to establish norms'. However, in
establishing norms for performance indicators O'Donoghue (2005) did not consider the differences in the
level of performance, For example, consider his example of tennis. In this sport it is not uncommon for a
player ranked number one in the world to play someone ranked much lower. These performances are likely to
affect the norm values to a point where they may not be a true representation of player performance.
A second alternativetothetechniqueproposed by Hughes, Evans e/ al. (2001) was presented by James ef al. (2005) who indicated that the use of confrdence intervals was a better method of identifying the stability
of the data set, particulady for the applied practitioner, in that 'performance profiles of individual and team behaviours can be established after the collection of relatively few data sets' (p. 71). Howwer, this method is based on the calculation ofconfïdence intervals for a successive number ofperformances and appears to be
19 overly onerous. By contrast the method presented by Hughes, Evans et al. (2001) whilst also onerous as it is based on the calculations of cumulative means of variables for 2,3, 4... and N performances, does provide a visual interpretation of the stability of the data set. As a consequence, this method of assessing the data in
relation to achieving a normative profÌle of performance has been most widely employed, notably in
volleyball @aniel & Hughes, 2001), and squash and badminton (Hughes, Evans et a1.,2007).
Irrespective of the methods employed to ascertain the stability of the índivídual or team data set, ít remains
that the data and inferences made in previous notational analysis research which fail to address the stability
of the profiles may not represent a 'true' performancæ profile. In addition, this problem confounds the issues
of comparing the findings of current analyses to previous research. Hence, there is a need to establish
normative profiles not only for teams and individuals in the contemporary time frame, but also for previous
periods, without which any studies that make inferences based on previous research must also be viewed with
caution.
2.4.3 Statistical analyses
Hughes et al. (2002) have identified that in notational analysis research analysts often use inappropriate
methods to measure the level of agreement between observations. The same problem is often also prevalent
in the subsequent statistical analyses of the data. To this end Nevill et al. (2002) have suggested that it has
been common practice for researchers in performance analysis to use parametric techniques on unsuitable
non-parametric data. Most notably, they suggested that performance indicators are predominantly discrete,
not continuous events, and as such do not follow a normal distribution since the normal distribution is a
continuous probability rather than a discrete probability distribution. As a consequence, the use of parametric
statistical tests on these performance indicators is inappropriate sìnce one of the assumptions for using such
tests is that data are normally distributed. Nevill e/ al. (2002) therefore suggested that the use of non-
parametric chi-square analyses is an acceptable approach to handling frequency data. This test has been
widely employed in performance analysis, particularly in relation to positional data using pitch or court cells,
for example, more recently, Yiannakos et ø1. (2005) in handball, Smith el al. (2005) and Taylor et al. (2005)
in soccer, Evanelos et al. (2005) in basketball, and Michalopoulou et al. (20O5) in beach volleyball. In
addition to employing chi-square, other non-parametric techniques have been recently utilised to identify
significant differences and main effects (Kruskal -Wallis, Mann-Whitney U, Freidman ANOVA), most
notably by Williams Q004), and Williams, Thomas et al. (20O5) in their analyses of rugby union. However,
an issue emanating from these analyses is the subsequent use of post-hoc tests. Howell (1997) highlighted
20 that in making multiple @ost-hoc) comparisons on groups there is an increased risk of committing a Type I error, hence, a correction facfor musl be made to the alpha (P) value to offset this increased risk. This matter was not recognised by \ì/itliams, Thomas et al. (20A5), and hence the results they reported and their interpretations must be viewed with caution. One approach that they might have used is the Bonferroni adjusment, where fåe 'nomi¡ated P-vzLus [is] divided by the number of tests' (Winter et ol., 2001, p.772).
This correction is quite conservative and witl increase the likelihood of a Type II error, therefore a less conservative correction can be employed. Future research employing such post-hoc tests are encouraged to consider the use of corrections of the P- value.
2.4,4 P erformance Indicato rs
A performance indicator is 'a selection or combination of action variables that aims to define some aspect of performance' (Hughes & Bartlett, 2002, p.739). These are used to assess individuals, teams and team units, oftan by comparing to opponents or other teams and athletes to provide a measure of successful performance.
However, according to Hughes and Bartlett (2002), analysts often do not present data for both sets of
performers, which may be misleading, and hence lead to incorrect inferences and conclusions. For example,
in,rugby league considerteãm A nraking 10 'cleaîtrreaks' in a game, and team B (the opponents) making 15.
The obvious conclusion from these data is that team B is more successful in breaking the advantage line;
however, no account has been taken ofthe relative proportion ofpossession. The inferences and conclusions
would be very diflerent if one considered that team A had 60 possessions and team B 120 possessions. With
this additional data it is apparent that the breaks relative to possession for team A is l/6 compared to 1/8 for
team B. Hence, team A, make 6¡çs line breaks.per possessionthan team B, The inportflqpp,pf using ratios or
percentages, whiôh are non-dimensional (or normalised) data is blearly evident. Huþhes and Fraùks (2005)
demonstrated the importance of this is their normalisation of football performance analysis data, suggesting
that 'different interpretatirrns can be obtained from the same data usi.ng different analyses (p. 513).
This approach to data analysis has yet to be universally adopted in performance analysis research. Hughes
and Bartlett (2002) concluded that all technical and tactical indictors should be normalised (proportional)
with the total frequencies of the action variable, A further consideration, however, is that presenting non-
dimensionalised data alone does not provide the athlete and/or coach with the full information regarding the
performance. As such Hughes and Bartlett (2002) correctly suggested that the non-dimensionalised data
should be presented alongside the processed data or raw frequencies.
2l 2.5 Issues in rugby notational analysis - Rugby Football (as an exemplar)
If the results of studies assessing key indicators in rugby football are to be deemed valid, it is essential that a systematic, in-depth assessment of the system and the data generated is undertaken. Such an assessment must incorporateareliability analysis and an examination of the cumulative means of data to establish whether a 'appropriate normative profile has been aohieved. Consideration must alio bè given to th'e use of statistiòal' procedures and the presentation ofraw or processed data alongside non-dimensional or normalised data.
Table 2.1 presents a sumnary of somq key papÊrs on notational.anal.ysis and.rugþ football since 2001, fo illustrate the degree to which researchers have or have not addressed the key issues (reliability analysis, appropriate statistical procedures, normative profiles and the use of non-dimensional indicators) regarding their,systerns and data
Table 2.1 A synthesis of rugby union and rugby league* papers since 2001 addressing thekey issues in notational analysis
Reliability Statistics Normative Indicator type analysis profile
Par^sons et øI Q001) Undertaken Non-parametric Yes Frequency but none only presented
J¡ckson and Hughes (200f) Undertaken, Non-parametrie No Frequency but none only presented
Martin et øL (2001) Presented total None No Frequency and actions percentage
Vivian et øL (2001) Undertaken, Non-parametrig Yes Frequency but none (no posl4ne tests) only presented
Eerftseheú d, Qgez) Notrs* Pararnet¡ie No Frequeney, percentage and time Boddingtun and Lambert None Nou-parametric None Fercentage (2004) only
James, Garish and Hughes Presented Non-parametric No Frequency. (2004) individual time, ratio and variables percentage
Jones, Mellalieu and James Presented Non-parametric No Frequency and (2004') individual percentage variables
Jo¡cs, Mell¡lieq James and Undertaken, Non-parametric No Percentage Moise (2004) but unclear only
22 Reliability Statistics Normative Indicator type analysis profrle
Long and Hughes (2004) Presented total Non-parametric No Frequency actions only ,
Thomas (2004) Presented Non-parametric No Percentage individual only variables Williams (2004) Presented total Non-parametric No Percentage actions
Hughes and Jones (2005) Presented Non-parametric Yes Frequency and individual percentage variables
James, Mellalieu and Jones Presented Non-parametric Yes - Frequency (200s) individual (confidence only variables intervals)
Sasaki etdl (2005) None Parametric No Frequency, ratio and regression Sayers and Washington- None Non-parametric No Percentage King (2005) only
Williams,Hughesef øl Presented total Non-parametric No Time (200s) actions
Williams,ThamaselaL Presenled total Non-parametric No Frequency and (200s) actions percentage
2.5.1 Reliability analyses
Hughes et al. (2002) reported that in notational analysis 85Yo of published papers (n:67) either failed to address reliability issues or use questionable statistical methods, notabþ parametric statistical tests (ANOVA,
/ test, Pearson's correlation) on non-parametric frequency óata. Morewer; ft€hss et aL (2002)'correctly
asserted that any reliability analysis undertaken should be to the same level as the intended subsequent
statistical analysis, a directive for the most part disregarded in previous research in rugby football. It has been more common for researchers (who use appropriate statistical procedures) to state percentage error or
agreement for the total system, and not for the individual variables under examination. Even in more recent studies @oddington & Lambert, 2004; Sayers & Washington-King, 2005) tle authors failed to present any
results for their reliability analyses. Additional studies (Jackson & Hughes, 2001; Parsons et a1.,200I; Vivian
et al., 2001) repofted undertaking in-depth analysis, yet likewise failed to present the results of their
-assessment. Furthermore, ryhilst both Ma¡tin et aI {%Dl) and Long and lfughes (2001) undertook more
appropriate analyses fbr the iätra-operator assessment, they merely presented one overall percentage,
23 seemingly to represent the accumulated level of error for all variables. This approach, whilst an improvement on failing to address the level of observer agreement, does not identiS the problems that emerge when individual variables are considered. The assessment of individual variables is more rigorous in that discrepancies between data sets are not 'masked', that is to say, adding frequency data from two different sources can hide differences.
It should be acknowledged, however, that since Hughes et al. (2002) reported their concerns regarding the assessment of reliability in notational analysis research, there has been a marked improvement in more recent studies. Based on the sample of papers þost-2001) presented in Table 2.1, 21o/o fail to address reliability at
all, 32Yo either failed to address or did not report the reliability of their systems, and 32%o of studies correctly reported either intra-operator or inter-operator level ofagreement for individual variables rather than for the total variable frequencies. Nevertheless, it remains that nearly 70% ofstudies still either fail to addreslreport reliability or base their reliability on accumulated differences for variables. Clearly, the important message from Hughes et al. Q002) that the reliability assessments should be to the same level of the intended analyses has yet to be fully accepted by researchers, who either choose to ignore, or fail to realise the potential impact of this on the validity of their analysis.
A further important aspect of the reliability analysis that has been widely ignored is the difference between actually 'counting' the variables and 'identifuing' the variables. The reliability analyses should have at least two aspects; (i) assessing the level of agreement for the initial identification of the variable, and (ii) the assessment ofthe frequency ofthe variable occurrences. Ifthese are addressed as a combined analysis then it is diffrcult for the researcher to identify where the effors occur, and consequently, where the system may need modification. This is particularly evident when player or positional profrles are the focus of the research. To date, no research on player or positional analysis in either rugby union (Hughes & \ryhite, 1997;
James e/ al., 2005; Long & Hughes 2001; Parsons et al., 2001; Vivian et al., 2001\ or rugby league (Meir,
Colla et al., 200 1) has addressed the issue of the reliability of player identification.
A final consideration particular to hand notation analyses which has not been previously addressed is the identification of inputting errors which are likely to ocour when transferring data from the notation sheet into the computer spreadsheet. To overcome this likelihood, dalz should be inputted twice and the difference between the two sets of data calculated to identify and rectifu any erors.
24 2.5.2 Normative profiles
Only a few studies in rugby union (Hughes, Kitchen et al,, 1997; James e/ a1.,2005; Marshall & Hughes,
2001; Parson s et ql., 2001; Vivian et al., 2001) have sought to identify how many games should be analysed to ensure that a normative profïle has been reached. With the exception of James et al. (2005), all of these
studies have adopted the technique outlined by Hughes, Evans et al. (2001). The results ofthese analyses indicate that for most variables normative profiles are attained within six games, hence, it might be that future research could use these findings as a benchmark for deciding how many games need to be analysed.
2.5.3 Statistical analyses
In addition to the problem of many studies using inappropriate statistical techniques to assess reliability
Nevill el al. (2002) have also questioned the use of some statistical methods for analysing performance
analysis data, in particular the use of parametric tests when a non-parametric approach is more appropriate
given the discrete probability distribution ofthe data.
In rugby union most studies prior to 2001 simply presented summary data rather than undertaking
inferential statistical analyses. There were some exceptions to this, namely Hughes et al. (1997) and Hughes
and White (1997), who both used chi-square and I tests in their analysis of international rugby union, and the
assessment of forward play in the 1991 Rugby World Cup, respectively. In addition, Treadwell (1988)
utilised one-way analysis of variance (ANOVA) in his analysis of soccer and rugby, but interestingly only on
the soccer data, (seemingly due to the number of games of rugby (7) in the sarnple). Similarly, IN'f;cKerøie et.
al. (1959) r¡tilised ANOVA in their assessment of the contact situation in the inaugural Rugby \{orld Cup in
1987. Other studies (Herbert & Tong, 1997; Stanhope & Hughes,1997) also used inferential statistics in their
analysis of scoring in the 199tr Rugby World Cup and positional profìles of wingers and back row players,
respectively; however, both these studies failed to report what statistical tests were used on their data. Whilst
the use ofthe chi-square test is an appropriate method for assessing differences in discrete data (Nevill el ø/.,
2002), the / test and ANOVA are not, since these are parametric tests, and therefore requiring data to be
normally distributed.
In more recent publications (post-2001), the majority of studies have adopted more appropriate statistical
procedures (Table 2.1). However, it must be noted that some studies have been excluded from this synthesis
(Carter & Potter, 2001a; b;McCorry et a1,,200I; Potter & Carter, 2001a; b), since they were published in
25 2001, yet \¡/ere presented at the Third Wodd Congress of Notational Analysis of Sport in 1996, and hence the
statistical techniques employed were more reflective of the earlier period.
Based on the synthesis of rugby research (Table 2.1), 95% of studies used inferential statistical analysis on their data, of which 89% utilised non-parametric tests. It is, however, important that even if non-parametric tests are used the appropriate tests are selected and adjustments are made to the alpha value to protect against the increased risk of a Type I error that accompanies the multiple pair-wise comparisons that are typically made. For example, in their analysis of rugby sevens Long and Hughes (2004) used a Wilcoxon signed-rank test on their data. This test is the non-parametric equivalent to a dependent I test; however, the data were not paired, since the same teams were not examined under different conditions. The appropriate procedure should have been the Mann Whitney-U test. Similarl¡ whilst Vivian et al., (2001) did utilise the correct non- parametric test on their data (Kruskal Wallis), they failed to examine further the th¡ee significant Level main
effects they identified with an apprvtlrateposl-hoc procedure.
2.5.4 Performance indicators
It is still common for researchers in notational analysis of rugby union to present frequency data alone
(Jackson & Hughes, 2001; James et a1.,2005; Long & Ilughes, 2004; Parsons et al., 2001;Yivran et ø1.,
2001). This approach, according to Hughes and Bartlett (2002) may result in a loss of information being made available. For example, whilst Parsons et al. (2001) undertook a comprehensive player profile analysis of Welsh International, European and Domestic rugby football, in presenting frequency data alone they have made comparisons to other studies difficult, since it is impossible to state that the differences between the levels of performance were not affected by differences in possession and/or ball in play time. In presenting data which are not normalised to either total frequencies or time renders the conclusions incorrect. For
example, Long and Hughes (2004) reported back row players being involved in more rucks in professional rugby than in pre-professional rugby, and suggested that the role of these players have evolved to ensure they arrive at the breakdown first to secure possession. However, evidence from published research indicated that
'ball in play' time increased notably since the introduction of professional rugby; a fact not accounted for by
Long and Hughes (2004). Had Long and Hughes (2004) normalised their data to either time or total frequencies, they would have found that back row players actually took part less in the breakdown situation in the professional game than in the pre-professional game. As such, similar to other studies that only present frequencies, the results and inferences made rmrst bs carefully re-examined to ascertain whether they actually contribute to the evolving knowledge of the game.
26 The presentation of percentages (normalised data) has become more common in recent studies in rugby football. However, many of these studies present percentages alone @oddington & Lambert, 2004; Jones,
Mellalieu, James & Moise, 2004; Sayers & Washington-King, 2005; Thomas,2004; Williams, 2004), whict¡ similar to presenting frequency data only, may result in a loss of information. This is clearly evident in the results presented by Sayers and Washington-King (2005) in their comparison of the contact situation in the
Northern and Southern hemisphere. They reported that in the Northern hemisphere 4lYo of otrloads resulted in gains of five metres or more, compared to 40Yo in Southern hemisphere teams. Whilst this shows a similarity in this aspect of play between the hemispheres, it does not provide the complete detail, since 40olo can represent frequencies of4 in 10, 8 in 20,40 in 100 etc. Hence, the percentages presented indicate that the outcomes of offloads are similar, but do not reflect the differences in playing patterns. A more appropriate approach is to present frequency data and data in a non-dimensionalised form together. This method was seemingly used by Iames et al. (2005), but they presented frequencies (medians) for some variables and percentages for others, hence there was still a loss of information. It is important that the data are presented both in the raw or processed form and as non-dimensional ratios or percentages. This more correct approach was adopted in earlier research (McCorry et a1.,2001; Potter 1997; Potter & Carter 2}0la; b; Stanhope &
Hughes 1997).In addition, Carter and Potter (2001b) presented their results relative to time in their analysis of tries in the 1995 Rugby World Cup, These approaches from earlier analyses in rugby union were for the most part not mirrored in later research.
2.5.5 Implications
In general, there is a dearth of published research assessing tactical, technieal and game indicators in both codes of rugby which has adopted sound scientific systematic approaches in their methods. In the studies which have addressed the reliability of their systems, it is not uncommon for researchers to present one error percentage, which seemingly reflects the system as a whole. This technique is flawed, since it does not provide any information on the practical diffrculty in identifying individual variables. Even in more recent studies some researchers still adopt inappropriate methods ofassessing reliability or fail to present the results of their analyses. Moreover, it is seldom made clear whether perceritage error and agreement results are based on raw or processed data" hence, it is diffrcult to ascertain the true level of error/agreement.
Whilst there has been an improvement in the number of studies which have included inter-operator and/or intra-operator reliability analyses, few of these addressed the important aspect of identiô'ing normative profiles for the variables under investigation. As such, it can not be stated unequivocally that the means of
27 these variables have stabilised, and therefore inferences based onthe results ofthe subsequent data analyses may be compromised.
The use/misuse of statistical procedures in performance analysis research has previously been questioned
(Nevill et a1.,2002), ostensibly due to parametric statistical tests being used on non-parametric data. In recent studies there has been a marked improvement, witlt most resea¡chers employing non-parametric tests on discrete data. However, some studies still use incorrect statistical tests, or fail to recognise the importance of adjusting the alpha value (P) when undertaking multiple pair-wise comparisons.
In most rugby football performance analysis studies, variable frequencies (means or medians) are typically presented. This unfortunately may result in the loss of important information, since these do not reflect teams' share of possession, nor their time in possession. It is therefore important that it becomes more common practice to pres€nt either raw or processed data alongside non-dimensionalised (normalised) datq represented as ratios, percentages or in reference to possession time.
Considering that very few studies in rugby football have adopted the appropriate approach to their analyses, the results, and hence the conclusion made in most studies must be questioned. A more rigorous, systematic approach to performance analysis research in rugby football must be adopted by researchers in this field.
2.6 AnalysiS and modelling of sport
2.6.1 Time and motion analysis
Investigations into the physiological demands of invasion games are of paramount importance in providing coaches with objective information on which to base training and conditioning programmes. To this end many different methods of investigation have been employed in an attempt quantify the demands of the game, including heart rate analysis (Ali & Fanelly, l99l; Deutsch et al.l998), blood lactates (Bangsbo et al.,
1991; Deutschet q1.,1998) and movement ortime-motion analysis @eutsch et a1.,2002;Docherty et al.,
1988; Mclean, 1992; O:Donoghue & King, 2005; Reilly & Thomas, 1976; Withers et al., 1982). However, it is not clear whether these methods are appropriate to games involving more physical engagement. It has been suggested for example that the 'physiological demands of rugby league involve a complex combination of factors that contribute to performance' (Dzutsch et al., 2002, p, 106). Hence, if specificity is deemed to be fundamental in training design, an important prerequisite of methodological design must include a modelling
28 process to identi$r critical game elements. Hence, in accepting the view of Deutsch et al. (20O2) that in physical conditioning for sport, specificity is the key paradigm, it is essential that the individual game components are fully understood before attempting to develop appropriate methodologies. Adopting this approach, it is clear that attempting to ascertain the game demands of rugby union by analysis of movement pafterns alone is flawed, since players also engage in many static and non-locomotion activities.
In additiog in team games there is a dearth of published research which has sought to identify how time
rugby union where the speed of re-cyoling the ball at the ruck have been suggested as an important performance indicator (Kear, 1996; Smith, 2002). However, to date no published research has being undertaken to examine fully the important time variables any of the major team games.
2,6.2 P erlormance Profiles
In recognition ofthe need to identify clearly the process of developing a performance profile Hughes (2004, p.99) presented a schematic chart to map the key stages. This schema, however, does not correctly relate the
complete process, and the design implies that the important aspects of reliability and normative profiles are
'side issues', in that the diagram is not cyclical. Moreover, it appears to indicate that there is a direct route
from the analyst to the perfonnance profile which can be achieved independent of what appear to be
'peripheral' but in reality are vital aspects of the process. An alternative schema (based on Hughes's (2004)
model is presented overleaf for consideration as a more appropriate design (Figare2.2).
29 Identify the problem Consider design Use oÊ issues e.g. need for o Experts a control o Game models Identification and selection o Research of performance indicators
Considèr data presentation Unacceptable level System design re: normalisation. Use of: of agreement e Time o Possession o Total frequencies
Pre-observation phase Identi$r initial system problems Consider: . Type . Depth . Use of raw Observation sample for døta reliability analysis o Sequential data Undertake Howmany games reliability analysis for means to stabilise? Use of- Full game o Empirical Acceptable level of observation methods agreement and data . Variance collection o Norms
Consider processing Data processing Normative profile efTors
Performance Consider the level of profile dat¿ andthe o Comparison appropriate o Modelling statistical analyses o Frediction
Figure 2.2 Schema for developing a performance profìle.
30 This modified schema importantly includes a cyclical process for reliability analysis, that is to say that this aspect cannot be ci¡cumvented and poor reliability should tlerefore lead to a re-design of the original system. This process continues until an acceptable level ofagreement is achieved. At each stage the broken lines represent important aspects researchers should consider. For example, Hughes (2004) has suggested that research should identifu appropriate performance indicators as a priority if commentaries on sports are to be relevant and valid. However, the identification of relevant indicators has often not been systematic and consistent. Many researchers have used previous research to guide their choice, for example, Garganta and
Goncalves (1997) in football, Hayrinen et al. Q004) in volleyball, and Ortega et al. (2004) in basketball.
Others have consulted known 'experts' (Jones el al., 2004), or not specifred (Hughes & Jones, 2005; Hughes
& Churchill,2005).
Researchers also need to consider the problems associated with data processing errors, particularly in transferring data from hand notation record sheets into the computer. This issue has not previously been reported; however, it is suggested that to protect against the possibility of errors occurring in transferring data to the (SPSS) spreadsheet, all data are input twice. This enables inputting errors to be identified by computing the differences between data columns. The use of this process is important, since the problems associated with inputting data are likely to add to the overall error ofthe subsequent output.
A final consideration regarding the research design is the use of'controls'. This is often difficult to achieve in research using notational analysis, since for example, in the analysis of the impact of rule changes, it is not possible to follow a team in the same period playing under 'old' and 'new' rules. Hence, studies have adopted a pre- and post- analysis v/ithout a control condition. In an attempt to 'control' for confounding variables, researchers should attempt to contextualise their analysis by comparing any changes due to the intervention against established longitudinal trends.
2.6.3 Mapping the game - rule changes and longitudinal analysis
Concerned with the growing dominance and success of fusociation Football, it is not surprising that a rugby union sub-committee was appointed to change the laws 'in order to make the game less violent, more attractive for spectators and to increase its chances of competing successfully with soccer' (Dunning &
Sheard 2005, p.185). This statement highlights clearly three major reasons for rule changes, reduction of violence and potential for injury; enhanced entertainment and increased commercialisation. What is
surprising is that the sub-committee was formed in the late 1890s at the inaugural Annual General Meeting
(AGM) of the Northern Rugby Football Union, later to become the Rugby Football League!
31 The spectator appeal of sport has always been a principal consideration for de changes. Consider two examples from baseball and cricket. In baseball, Rader (2002) reported that with teams finding it diffrcult to score runs, the rules were changed in 1893 making the pitching distance greater, which resulted in runs scored increasing dramatically. Two further rules imposed in 1907 and 1913 (increasing homeplate from 12 to 17 inches across allowed pitchers more leeway. In addition, the first two foul balls were counted as strikes where previously foul balls meant nothing. The result of the according to Rader (2002) was that strikeouts increased by 50Yo and the average runs per game droppedto 6.7. Hitters also complained of the practice of pitchers smearing the ball with dirt and tobacco juice to make it more diffrcult to see. Whilst on the surface such rule changes appear to be causal, one must also consider tactics employed by coaches. In the period
l90l-04, according to Rader (2002, p.98) starting pitchers completed more than 85% of games, this reduced to 54Yo by the mid-1910s, coaches opting to utilise the'bullpen' more for relief pitchers. The increase in pitching distance also coincided with player size increasing by 1,5 inches and 12lbs on average (comparing
1894 to 1908 pitchers). The same change in size and physique was not seen in hitters. Rader (2002, p. 100) undertook a multiple linear regression analysis showing that taller and heavier pitchers in 1908 tended to be more effective than their smaller lighter counterparts. Other tactics employed to counteract the new pitching
dominance were to use the bunt and base steal in an effort to move players into scoring positions rather than rely on the home run for scoring. In 1969 the strike zone \ryas decreased and the mound lowered, and in 1973 the American League (AL) adopted the designated hitter (a hitter not required to field, hence the pitcher need
not bat) which resulted only in slight improvements in hitting statistics. Changes in hitting and home runs
have also been attributed to rule changes, ball manipulation, more home run friendly stadia, like Mile High
stadium in Denver where runs are scored at a rate3}Yohigher than the league average.
In cricket in the 1920s and 30s debate raged as to whether the leg before wicket (LB!Ð law should be
changed. It had become common practice for batsmen to employ 'the unsporting tactic of using their pads to
defend the stumps' (Williams 1999, p.77). This had resulted in cautious batting and slow run scoring.
According to Williams (1999) changes were made to the laws of cricket to'stimulate spectator interest by
encouraging less defensive batting and by helping bowlers' (p.165). The ball was made smaller in L921, the
wickets larger in 1931 and in 1935 the LBW law was amended so that batsman could no longer pad the ball
away outside off stump. What effect these rule changes had on the game is not noted, although analysis of
spectators watching first class county cricket between 1934 and 1936 indicated a decline from 1,338,000 to
1,242,000 (Williams 1999, p.55), suggesting the LBW rule change had little impact on spectator appeal.
Seward (2002) argued that identifying mechanisms that relate to injury has become the biggest influence on
rule changes in sport. Whilst this may be true for some sports where high levels of contact are involved,
32 Seward (2002) did not address non-contact sports. A review of more recent literature shows that injury is a
consideration in sports like rugby union (Noakes & Jakoet, 1995; Williams, Hughes et aL,2005; Williams,
Thomas el ql., 2005); however, by far the largest influences on rule changes are commerce and
entertainment. Bills (2006) suggested that recent proposals to change the laws of rugby union drastically would speed up the game and reduce the impact of penalty kicks. Similarly, Hughes and Clarke (199$;
Williams, Hughes et al. (2005) and Williams, Thomas et al. (2005) all inferred that specific rule changes in
rugby union were introduced to make the game more attractive for spectators. Martin et al. (2001) suggested rule changes in limited overs cricket (30 yd frelding circle for the fìrst 15 overs) resulted in a 'more exciting
opening to the innings' (p. 9l). In football, Hughes and Sykes (1994) examined the back pass rule,
introduced to prevent time wasting, increase the likelihood of defensive errors and result in more shots on goal, thus making the game more exciting. In racket sports researchers have assessed rule changes which
were introduced to improve spectator appeal, notably (Hughes & Knight, 1995) in squash, and more recently
Pritchard et al. Q00l) in badminton.
In an attanpt to identifu the impact of a rule change, researchers often examine key performance indicators
in small time frames pre- and post- the introduction of the rule. This is a problem, since it represents a
'snapshot' ofthe change in performance indicators under examination, but takes no account ofthe trend in
these data. For example, Williams, Thomas et al. Q005) concluded that 1999law changes in rugby union had
resulted in a decrease in the number of scrums in Six Nations rugby union. The results show clearly that after
1999 there was a downward trend in scrum frequency. However, these researchers took no account of the
trend in frequencies prior to 1999, and as such their findings are not placed in context.
2.7 Ànalysis and modelling sports (rugby football- as an exemplar)
2.7.1 Time and time and motion analysis
To date very little published research has focussed on time and motion analysis in rugby league football, with
only Meir et al. (1993) and Meir, Colla et al. (2001) contributing to the body of knowledge . Meir et ol.
(1993) sought to record activities ofprofessional players and identifu any positional differences (prop,
hooker, half back and winger) in player movements. The results of these studies indicated that the game in
the early 1990s was predominantly made up of low intensity activity.
JJ In a follow up study Meir, Colla et al. Q00l) observed the movements of players in an attempt to assess the impact of the 1992-93 change in the offside rule. Prior to this period defences were required to retreat five metres from the ruck. In 1992-93 this was extended to ten metres, ostensibly to make the game 'more open'.
Meir, Colla et al. (20O1) compared games played under the l0-m rule to the results previously presented by llleir et ql. (1993) to games played under the 5-m rule. They reported that the rule change had resulted in the
distances covered by both forwards and backs increasing; 6647 m to 9929 m for forwards and 7336 m to
8458 m for backs. Forwards also spent more time in intense activity (sprinting and jogging backwards) increasing from 0.8% to 3.3%o of total game activity. Interestingly, the work to rest ratios for forwards in
1993 of l:6 increased to l:10 for the hooker and l:7 for the prop. More striking was the change in backs, with ratios of 1:8 in 1993, increasing to l:12 and l:28 for half backs and wingers, respectively. According to
Meir, Colla el al. (2001) this reflected an increase in game intensity, and therefore players required longer rest periods to recover from increased intensity action,
The results of both these studies, however, must be viewed with çil¡tion, since there are serious concerns with the methods employed. Both studies used small samples; four games in 1993 and only two in 2001. As
such, it is unclear whether the means of these data would have stabilised (normative profìle) and therefore considered representative. In addition, the authors base their distance calculations on a cadence x stride length method; hence, the results are no more than 'estimates'. Finally, in neither study did the authors undertake any form of reliability assessment in order to validate their systems. Hence, the poor design and methods employed in these studies render the results presented and inferences made (based on the data) as invalid. As a consequence, to date it remains that no empirical evidence exists regarding time and motion analysis in rugby league football.
The scarcity of research addressing time and motion analysis in rugby league is not mirrored in rugby union. Most of the work in this code of rugby has focused on the time spent in different movement categories and work to rest ratio analysis (Carter, 1997; Deutsch et ql., 1998; Deutsch et al., 2002;Dochefi et al.,
1988; Duthie et al., 2OO5; Herbert & Tong, 1994) and time and motion with heart rate analysis (Carter, 1997;
Herbert & Tong, 1994) rather than assessing total distance covered during games (Deutsch et al., 1998;
Morton, 1978). Whilst all the of these studies assessing movement patterns in rugby union over the past 30 years attempted to address important time variables in the gamg there'has been a'lack of research which has addressed important team rather than individual time performance indicators. Given the importance placed on quick re-cycling of the ball at the ruck in rugby union - Ireland Coach Eddie O'Sullivan (as cited in Schwarz,
2004) suggesting that if a ruck is slow it has no value - and the view of Williams et al. (2005) regarding the change in the laws governing the ruck which were introduced in 1999 which to prevent slowing down the
34 I quick recycling ofthe ball, the lack ofresearch on this aspect ofperformance is perplexing. In addition, in
rugby league, the fast ruck ball ('play the ball') has been reported as being even more important. The battle
for controlling lhis aspect of the game is highlighted by Smith QO02, p.5) who suggested that whilst the 'play
the ball' may only take a few seconds, 'winning this part of the game can make a difference in the end
result'. Sharp (2002) further suggested that controlling the ruck area is fundamentally mediated by
controlling the speed of the 'play the ball' which is achieved by being dominant in the tackle. Fanar (2002,
p.4) summed up the importance of the 'play the ball' stating that his team (St. George Illawarra) now have [in
20021 better training drills and techniques to 'make players play the ball quicker when you have got the ball
or force the opposition to play the ball slowly when you haven't got the ball'.
To date no published studies have sought to identify the importance of time performance indicators in either rugby league or rugby union football. As sucl¡ there is a need to explore fully all time va¡iables in both
codes of rugby and further analyse these variables to identifu how they may be related to successful
performance.
2.7 .2 P erlormance P rofiles
In rugby union and to a lesser extent rugby league football, resëarchers have profiled both team performance
and individual player performance in an attempt to provide templates onto which performances can be
mapped and predictors of successful performance identifìed. One of the first studies to profile team
performance in rugby union (Hughes & Williams, 1988) assessed the differences in playing patterns of
successful and unsuccessful teams in Five Nations (5N) rugby 1985-87. rtrhilst they reported that there were
no significant differences between successful and unsuccessful teamq there were team differenceq inasmuch
as the England and Wales teams used more kicking and less passing than the other three teams (France,
Ireland and Scotland). Later analysis of 5N rugby by Potter (1997) did not seek to identify performance
indicators; however, his presentation of England's data, the opponent's datq and the full game data enabled
calculations to be made based on the known results of these games. The results of these calculations are
presented inTable2.2.
35 Table 2.2 Frequency and percentages for key vuiables calculated from the raw data presented by PÕnèr (tee7)
Winning teams Losing teams Winners percentage share
1992 1993 1994 1992 1993 1994 1992 1993 1994
Kicks 49.0 58.3 56.0 46.3 55.0 57.5 51.4 51.4 49.3
Passes 91.8 71.3 78.0 74.0 90.5 78.3 55.4 44.1 49.9
Lineouts 20.3 24.3 20.8 19.5 27.3 24.8 50.9 47.1 45.6
Scrums 12.5 17,5 11.5 12,8 11.5 12.3 49.s ó0.3 48.4
Penalties/Free 11.8 15,8 14.3 15.0 12.5 10.5 43.9 55.8 57.6 kicks conceded
t(ucxs/måuts 25.5 31.0 35.5 25.3 30.8 31.5 50.3 50.2 53.0
According to this assessment, in both 1993 and 1994 winning teams conceded more penalties and free kicks,
and had slightly fewer throws into the lineout than losing teams. The higher percentage of passes and lower
percentage for penaltieVfree kicks in1992 was probably more reflective of England's style of play rather
than the difference between winning and losing, as this was England's Grand Slam year, and is an illustration
of problems of such analyses. The question here is, do the data reflect the individual style of play of the team
or are they related to successful performance? A further problem with the data presented by Potter (1997)
was that there is no indication of individual team possession time, therefore, it is diffrcult to identify whether
differences in scores are not merely due to the differences in the percentage share ofpossession.
In addition to the analysis of performance indicators in the 5N tournament, the Rugby World Cup (RWC)
has also been extensively researched. McKenzie et al. (1989) used a computer based system to examine the
inaugural RWC in 1987, ässessing in detail the contâct situarion. Although they did not address data by
successful or unsuccessful teams, they assessed three teams who had va¡ied success; New Zealand, who won
the three games, Australia who won two and Canada who won only one, McKenzie et aI" (1989) assessed ball retention in contact in relation to the gain line, in relation to position from original contact, player
position and player actions arriving at the contact situation. They reported that the most successfr¡l team
(New Zealand) was able to retain ball such more (72.4%) tlran the less successful teams (Australia, 61.8Ve
and Canada, 64.2o/o).ln addition, whether teams crossed the advantage line or not influenced the retention of the ball, with the ball being retained by all teams 67Yo of the time when the advantage line was crossed
compared to 4+c/o when the advantage line was not crsssed. New Zealand was more successful in ret*ining possession than Canada and Australia in both these situations. Ball retention was also seen as being inversely
36 related to the distance from the original place of contac! again with New Zealand more successful in both
close (< 5 m) and far contact (> 20 m). However, Australia was found to be the most successful team in
retaining the possession when the ball was at an intermediate distance (5-20 m from the original contact
place). Ball retention was also reported to be higher when the body position was low, with the ball carrier
turned towards supporting players and the supporting players ripping or driving the ball rather than when
accepting a pass, diving on the ball or picking up the ball. In all of these situations New Zealand was
observed to have best retention percentages. There are, however, a number of concerns with the methods
employed by McKenzie et ql. (1989). ANOVA and f tests were utilised to assess whether differences
between teams were signifrcant, but they failed to address whether or not all the assumptions regarding the
use of parametric tests \¡/ere met. In addition, no reliability analysis was undertaken.
Smyth el aL (1998, pl56) also assessed tactical and technical indicators ofsuccess in the contact situation,
examining games involving Ulster between 1996 and 1997, with an aim to identify factors associated with
successful ball retention. These researchers reported results very similar to those presented by McKenzie ef
al. (7989); ball retention in the cont¿ct situation was best when the ball carrier adopted a low body position
and turned towards the supporting player. In addition, Sm¡h et al. (1998\ assessed individual players and at
reported that the second row forwards were most involved in the contact situation and that no. 8 forwards
were most likely and stand offs least likely to carry the ball into contact. Moreover, the open side wing
forward was most often the first support player at the contact area.
In International rugby Hughes and White (1997) undertook a comprehensive hand notation analysis of the
32 final stage games for the 1991 RWC, focusing on the actions of forward players. They reported that
successful teams played a more varied lineout pattern, winning more possession from the middle and the
back of the lineout. They also used a oatch and driveþeel more than unsuccessful teams who were more
likely to use the tap down. Successful teams were also awarded more scrums and had better quality ball
(seemingly based on a subjective assessment) and had more players in rucks and fewer players in the maul
than unsuccessful teams. Most of the rucks were set up by back row players, with the back rows of successful
teams performing better than their unsuccessful counterparts. Exactly how this was measured; however, is unclear. The order of arrival at rucks was also assessed, and according to Hughes and White (1997) locks
from successful teams outplayed locks from unsuccessful teams, This is perhaps an indication of a change'in
locks' playing patterns, adopting a more mobile back row style of play. There are, however, several concerns with this study. The stated inter and intra- observer reliability appears remarkably high for a study of this nature (r:0.93 to 0.97), not to mention theuse of the correlation in assessing the levels of agreement. In particular, it is very diffrcult to identify players in the close contact situation, and often players arrive off
37 camera. Additionally, it is even more diffrcult to assess the order in which players arrive, again due to off camera arrivalg identification difficulties and simultaneous arrivals- a problem also reported by Smyth et al.
(1998). \Uhilst this is now made easier by the use of slow and super slow motion facilities, these do not
always assist, and often a backtracking method needs to be employed in player identification. Assessment of
rucks and mauls also poses further problems in identiffing whether players are contributing to the breakdown
or are merely in the 'immediate viciníty'. As a consequence, it is difficult to decide whether to include these
'peripheral' players and players who arrive late or leave the contact situation early. None of these issues were
addressed in this shrdy, casting some doubt on the validity of the results presented.
Potter and Carter (2001b) presented data for Rugby World Cup (RV[C) finals from 1987 to 1995. Table 2.3
indicates the main findings of this work. These data, although based on only one match, provide an insight into the tactics employed by winning teams. Most noticeable was the very low frequency and percentage
share of passes by winning teams in each final. This indicates that RWC winners appear to adopt a more
conservative, tight game. The much greater percentagç share of the scrums by winning teams was also
marked. Assessing the data from all RWCs, 7987-1995 revealed that winners kicked av/ay more possession
and were awarded more scrums, whilst losing teams made more passes, had more lineout th¡ows and
conceded more penalties/free kioks.
Table 2.3 Performance indicators for RWC finals 1987-1995
Winners Losers Winnors percentage share
1987 1991 1995 1987 l99l 1995 1987 t99l 1995
Kicl¡s 47 56 56 38 59 53 55.3 50.8 51,4
Passes 65 67 67 102 166 107 38.9 25.6 38.5
Lineouts t7 24 24 JJ 24 24 34.0 47.8 50:0
Scrums 23 l8 18 18 15 l2 56. I 55.9 60.0
Penalties/tr'ree 8 6 6 l2 8 11 40.0 68.0 35.3 kicks conceded
Stanhope and Hughes (1997) presented data on more specific indicators for the 1991 Rugby W-orld Cup,
assessing the time, position and breakdown of scoring opportunities for successful and unsuccessful teams. It
was no surprise that successfi¡l teams scored more tries, conversions, penalties and drop goals. The main
differences between successful and unsuccessful teams, was in the success rate of scores. Successful teams
had higher success rates for drop goals (38% compared to 28yo for unsuccessful teams) and much higher
38 penalty goal success (560lo comparedto33yo for unsuccessful teams). According to Stanhope and Hughes
(1997) successful teams scored more tries in frrst phase play than unsuccessful teams. Moreover, they suggested that as the phase number increased the likelihood ofscoring atry or a drop goal also increased for both successful and unsuccessful teams. For tries, the increase was exponential, increasing from 4.0Yo for first phase ball to 1,9.2o/o for frfth phase ball. This was different from the more linear increase for unsuccessful teams, with first phase ball accounting for 2.2%o or tries compared to 61Yo for fifth phase. This highlighted the importance of continuity and maintaining possession in the process of scoring tries. Stanhope and Hughes (1997) also reported that successful teams' starting point for scoring tries was nearer the opponent's line than for unsuccessful teams. They inferred that this was due to better kicking to touch and winning the subsequent lineout.
More recently Jones, Mellalieu and James Q004) analysed a First Grade European team over tvventy games in the 2002-03 season. This paper differed from previous ones in that the results of the analyses were
presented as medians rather than means. Whilst this is fundamentally correct in assessment of non-parametric
data, no analysis was undertaken to assess whether the mean and median score differed markedly. Moreover,
only presenting median scores may restrict understanding by non-academics, as most people recognise the
mean as the most used measure ofcentral tendency. Perhaps the authors ofthis paper could have presented both medians and means.
Whilst Jones, Mellalieu and James (2004) selected arange of performance indicators based on the research
team's combined 40 years experience in the game, some of these are rather strange. For example, with such
experience one would expect these researchers to recognise that scrums won on opposition ball are extremely
rare in the modern game. These researchers, however, did attempt to present more meaningful results in non-
dimensional form, as suggested by Hughes and Bartlett (2002). Whilst this is good practice, the authors did
not present any frequency counts, hence, assessing the differences between successful and unsuccessful
teams was made more diffrcult. For example, a frequency difference of 2 compared to 3 represents a 50%o
difference, as does the difference between 60 and 90; but the inferences made from such rezults may be very
different. The main findings reported by Jones, Mellalieu and James (2004) were similar to those reported by
Stanhope and Hughes (1997), with successful teams scoring more tries and winning more opposition lineout
ball. The lineout suocess, according to the authors, was consistent with the frndings of Hughes and White
(1997), who reported that the forwards in winning teams were more dominant in the lineout than players in
unsuccessful teams.
In addition to the assessment of team performance indicators, researchers have also focussed (to a lesser
extent) on the analyses of individual players or positions. These performance profiles include movement
39 profiles in rugby union (Caner,1997; Herbert & Tong, 1997) and rugby league (Meir et al., 1993;Meir,
Colla el al., 2O0l), profiles of ruck and maul engagements (Hughes & White, 1997) facricaVfechnical analysis (Hughes, 2001; Parsons et ql., 2001; Potter, 1997; Yivian et al., 200I), women's rugby union
(Hughes et al., 1997), mapping changes over time (Long & Hughes, 2004), and actions related to successful and unsuccessful performance (James et a1.,2005).
In rugby union, research has predominantly focussed on back row players, with only one study (Hughes ef al., 1997) not including these players in their analysis. Whilst some researchers include analysis of the backs, few studies actually focussed on these positions. With the exception of two studies which provided profïles for all positions (James et al., 2005; Parsons et a1.,2001\, only one study sought to profile fullbacks, centres and wingers (Herbert & Tong, 1997). In addition, given the importance of the role of the half backs in rugby union, there is a lack of research addressing the playing patterns of these positions. Only Potter (1997) has provided results for the performance of the stand off in Rugby World Cup 1995. Similarly, the impoftance of the hooker's role has not been the focus ofany published study. In rugby league, to date no tactical, technical or matchprofile exists for any playing position; the only studies in this sport have examined time and motion of forwards and backs @eck & O'Donoghue,2004) and specific positions (Meir e/ al., 1993).
Given the lack of individual profiles in both codes, specifrcally examining tactical and technical performance indicators, and the diversity of subjects, research focus, the time frame of these analyses and the selection of performance indicators, it is diffrcult to ascertain a definitive profile for any position. For example, a review of literature profiling the no.8 forward revealed the subjects have included Welsh
International players, professional European rugby players, Rugby World Cup players and pre-professional and professional International players from Northern hemisphere rugby. The periods ranged from 1991 -
2002, and the focus of research has included match indicators (lineouts, scrums etc.) time indicators and technical and taøical indicators. As suc[ comparisons between these studies are extremely diffìcult to make.
2.7.3 Mapping the game - rule changes and longitudinal analysis
Rule Changes
Notational analysis has been recently used to assess the impact of rule changes in both codes of rugby
football. In rugby union Hughes and Clarke (1994) undertook a notational analysis to assess the impact ofthe
introduction of the 'use it or lose it' law inthe 1992-93 season which was introduced to make the game 'more
attractive'. The results of this analysis indicated the game changed over this time frame, with more open play
action, and the ball being released to the backs more frequently. However, whether this was a more attractive
40 spectacle is open to debate. In addition, whether these changes were a direct result of the law change is uncertain. Unless the game is mapped over a greater period of time to established longitudinal trends, it is not possible to establish conclusively the true relationship between the rule change and the variable under examination.
In 1999, the IRB introduced laws to prevent defending players slowing down the recycling of the ball at the tackle area. Williams et al. Q003) assessed the impact of this law change and reported an increase in the frequency of breakdowns in the subsequent three years in Tri-Nations (3N) rugby (726 to 168 in the first year after the law ohange) and a small increase in Six Nations (6N) rugby (127 to 145 in the first year after the law change). The frequency and percentage ofstoppages due to unplayable ball also reduced notably in the three years after 1999, as did the frequency and percentage of scrums awarded in both 6N and 3N. It must be noted that scrum frequencies v/€r€ very low in all assessed years (1999-2002). As a result, minor changes in frequencies, may merely be due to individual game differences. The authors also reported that the law change appeared to have had an immediate effect in the year after the introduction of the law change, but in subsequent years reverted to the values reported in 1999,
In addition to laws changes at the breakdown, the IRB also introduced the 'use it or lose it' law at the
scrum. According to Williams, Thomas et al. (2005) this was meant to improve the scrum by reducing the time spent on reformation, especially at the 5-m scrum. They reported that the rule change had an immediate
effect in 6N rugby increasing the percentage of clean scrums (those won directly by either team) from l3Vo in
1999 to 23Yo inthe following year. However, the values in the following two years reduced to lSyo znd l7%io,
respectively. In 3N rugby the law change had the opposite effect, reducing clean scrum percentages from
ISYoin 1999 to 7Yoin2000. Similar to the trend in 6N rugby, the values in the subsequent years reverted
towards the original 1999 values. The conclusions of Williamg Thomas et al. (2005) ærd Williams Q004)
were that whilst law changes appear to have had an immediate effect (positive or negative), a period of
acclimatisation followed, and as such they appear to have 'no real lasting effect' (Williams,2004, p.520).
The impact of law changes in rugby union on time variables has also been exarnined, in particular by
Williams, Hughes et al. 2005, who monitored the effect of a number of rule changes over a five-season
period (1999-2003) and reported that both ball in play and match time increased significantly across the time
frame in Northern and Southern hemisphere rugby. However, as in prwious studies no account was taken of
the trend in variables prior to the law change, with researchers focussing on the post-intervention analysis
rather than both pre- and postJaw changes. As a consequence, problems associated with this design mean
that definitive conclusions regarding the impact of such law changes are diffìcuh to make.
4t In rugby league football Meir, Colla et al. (2001) examined the effect of the 1992-93 rule change regarding defensive players moving back l0 m after the tackle, compared to the previous rule playing under a 5-m offside line. Meir et al. (1993) suggested that this rule would impact on the distance covered by players during the game and, in addition, this would impact more on forwards than backs. These hypotheses \ ¡ere correct, Meir, Colla et al. (2001) reported forwards distance covered increased by 3282 m to just short of
10,000 m per game (49.4% increase). Not surprisingly, the increase in distance covered was accompanied by an increase in high-intensity work, predominantly due to an increase in jogging (4.0% - 13.5%), with most of this increase being in the backward rather than forward direction. High-intensity work for forwards rose from
0.8Yoto 3.3% of the total game, indicating the rule change had resulted in the game becoming more intense for forward players. This, according to Meir, Colla et al. Q00l) meant there was a need for greater rest periods, with the work: rest ratios increasing from 1:6 for forwards in 1993 to l:7 for props and 1:10 for hookers in the post-1993 period. For backs the increases in distance covered were not as large (7336 m to
8458 m). Interestingly, in the pre-1993 period backs covered the most distance; however, since the introduction of the rule change, forwards cover the most distance. The increase in work: rest ratio for backs was found to be greater than in forwards (1:8 in the pre-1993 period to 1:12 for half backs and l:28 for wingers). The latter ratio for wingers was ostensibly due to increased walking activity Q7.l%to 37.5Yo).
The results presented by Meir, Colla er at. (2001) indicate that the lO-m rule change in 1992-93 caused changes in player movement profiles. However, there are serious concerns with the research design of this study (refer to section 2.7.1). In addition, the follow up analysis sampled only two games, and took no account of other rule changes in the intervening period, even though these researchers acknowledged that
'rugby league has had a number of these [rule changes] in the past five years' (p. 42).
In addition to improvements in spectator appeal and commercial interests, the reduction of violence and potential injury to players has long been considered a rationale for rule changes in sport. Such changes are not modern phenomena. It has been suggested that the bifurcation of football into soccer and rugby in 1863 was due in part to the Rugby-Eton rivalry, and the protracted debate over the acceptance of'hacking' and
'running in' (Dunning & Sheard, 2005). Whilst this argument ultimately resulted in the formation of the
Football Association in 1861, the abolition of hacking and the development of a separate'Rugby' game, the
argument continued regarding the use of hacking in the rugby [union] game. With growing concerns regarding the injurious nature of hacking the newly formed Rugby Football Union ßFU) declared hacking to be contrary to the spirit of the Rugby game and it was forbidden.
Whilst these law changes aim to make games safer they often have unintended consequences. According to
Dunning and Sheard (2005) the aforementioned abolition of hacking changed the game completely. The role
42 of what Thomas Hughes (author of Tom Brown's Schooldays) called dodger (ostensibly backs) was lessened
as play focussed around the scrummage, due to a lack of hacking breaking up this part of the game. The
result was an emphasis on strength rather than skill, and hence the heavy chargers (forwards) became more
prominent in the game.
The unintended consequences of law changes have also been reported by Quanie et al. Q002), who
suggested that the scrum law changes implemented in 1963 led to an increase in serious ínjury. This they
claimed was due to the slowing of the ball emerging from the scrum resulting in flankers remaining bound
and therefore contributed to the push. Similarly, the sanctioned use of head protection by the RFU in 1996
and upper body protection in 1998 may have resulted in an increase in injury rates. This was the contention
of Garraway et al. (2000) who reported the proportion of players who were injured doubled after the
introduction of professional rugby in 1995. They suggested that the IRB should place a moratorium on the
use of protective equipment until its impact has been assessed fully. Other similar research on the use of
protective equipment in rugby union has failed to reach any definitive conclusions (Bird et al., 1998).
Clearly, whatever the rationale for rule changes in both codes of rugby, more extensive research is required
to establish how such changes impact on all aspects of play. To do this effectively, it is imperative to map the
key performance indicators across time, so that the ladrule changes can be better assessed.
Longitudinal Analyses
Mapping the game over time (longitudinal analysis) has been undertaken by a number of researchers in rugby
union, and is important in developing an understanding of how the game has changed over time. Most
notably, research has focussed on changes in the game between Rugby World Cups @otter 2001; Potter &
Carter 2001a), across Five and Six Nations Championships @otter, 1997, Williams, Hughes et al., 2A05;
rililliams, Thomas et a1.,2005), and Tri-Nations Championships (Williams, Hughes et a1.,2005; Williams,
Thomas et al., 2005). Research has also focussed on women's rugby (Marshall & Hughes, 2001) and
individual player profrles (Potter, 1997). In addition the IRB Centre, based at UWIC has also mapped the
game of rugby union throughout the world (Martin et a1.,2001).
Potter (1997) presented a comprehensive longitudinal analysis of England's performance and total game
data over three 5N seasons (1992-1994). Whilst Potter undertook no inferential analysis and made no
referenoe to the reliability of his analysis, the data he presented are highly informative of changes over time.
Table 2.4 summarises the mean frequencies for the measured game data variables presented by Potter (1997)
for 5N rugby (1992-1994) and data presented by Potter and Carter (2001a) for RWC (1991 &.1995\.
43 Table2.4 Mean frequency of total game actions for England in Five Nations rugby 1992-1994 and RWC l99l and 1995
1991 1992 1993 1994 1995 ßWC) (st\I) (sr{) (st9 ßwq
Kicks 102 95 113 174 96
Passes 170 t66 t62 156 179
Lineouts 38 40 52 46 37
Scrums 34 25 29 24 27
RucVmauls 48 5l 62 67 69
% ball in play time 29 30 32 32 32
Examination of the data indicates that over these seasons the frequency of ruck/mauls increased.
Interestingly, in the 1992 Grand Slam season England had approximately a 50% share of all measured variables, with the exception of passing. In this season Potter (1997) observed England made 10olo more
passes than their opponents. In the subsequent championships England's scrum share (41% in 1993 and 38To
in 1994) was perhaps indicative of less successful seasons.
As well as the Five Nations Championship, the Rugby World Cup @WC) has been the focus of
longitudinal notational analysis research. Potter and Carter (2001a) assessed the relative frequencies of match
and time indicators between the 1991 and 1995 tournaments. Again, similar to Potter (1997) no reliability
analysis or inferential statistical analyses were undertaken and no methodology was presented, thus
replication of the study is not possible. There is also some confusion due to a lack of operational definitions;
hence, it is not clear whether the pass variable includes all passes or excludes specific passes such as
offloads. Potter and Carter (2001a) did define the kick variable; however, they combined ruck and maul
frequencies. Irrespective ofthese concerns, the presentation of summary data enabled the authors to identi$
changes that occurred in the four years between tournaments. The key results revealed an increase in scrum
frequency (48 to 69, a 44Yo increase) between 1991 and 1995 and an increase in ruck/maul frequency,
reflecting the increasing trend over time reported by Potter (1997) and Potter and Carter (2001a)(Table 2.4).
In addition, the mean frequency of tries per game increased from 5 to 6 and goal kicking success from52Yo
to ílYo,which according to Potter and Carter (200Ia) was primarily due to conditions being dryer underfoot (
games played in a rarefied atmosphere at some locations in South Africa), law changes upgrading tries to 5
points, lineouts being awarded to teams kicking the ball to touch from penalties and the 'use it or lose it' law
at the ruck and maul being implemented in the period between tournaments. Potter and Carter (2001a) also
reported increased ball in play times in the 1995 tournament, which was in line with the upward trend
44 reported by Potter (1997)(Table 2.4). However, the ball in play times reported in all these studies indicated that in both 5N and RWC small increases over time were evident; a trend which according to Thomas (2001) is continuing in the professional game þost-1995). Thomas (2001) also reported the percentage ball in play times of 34.7% in RWC 1999 and 35.9% in the 6N 1999-2000.
In addition to mapping game and team dat4 individual player contributions have been mapped over time.
Potter (1997) presented data on the contribution of the stand off for England in the 1992-1994 5N tournaments. A summary of the frequencies and percentages calculated from Potter's (1997) data are presented in Table 2.5
Table 2.5 Stand offpossession options in the 1992-1994 Five Nations Championships
1992 o/o 1993 o/o 1994 Vo
Kick 42 37.8 53 47.3 66 48.2
Pass 67 60.4 55 49.t 54 39.4
Run t 1.8 4 3.6 t7 t2.4
The results of this analysis show that over these periods there was a small increase in the stand off opting to
kick away possession, and a gradual reduction in the passing option. Most interesting was the large increase
in the frequency of runs in the 1994 tournament. However, this still only represents a run every nine
possessions. It must also be noted that during these tournaments England utilised three different players at
this positior¡ who had very different styles, notably the kicking style of Rob Andrew compared to the more
'ball in hand' game of Stuart Barnes. This problem of presenting a positional profile has been highlighted by
Iames et aL Q005'), who reported significant differences in performance indicators in different players
playing the same position.
In contrast to rugby union the game of rugby league has been less extensively examined, with only Meir,
Colla et al. Q001) examining changes in the game over time. As such, to date very little published research
evidence exists regarding how the games of rugby have changed over time.
45 2.8 Problem
At present there is a paucity of published research addressing tactical, technical or time analysis of rugby league football. In additior¡ no researchers have sought to define performance indicators in this code of rugby or develop player or positional profiles. Despite a significant development in the game (change of playing season) in the Northern hemisphere and several major rule changes, only Meir, Colla et al, (20O1) have reported on the changing structure of the game. In contrast, rugby union has been examined extensively, with researchers focussing on identifying performance indicators and developing performance profiles for teams and individuals. Researchers have attended to key rule changes, mapped the changes in the game over time, and extensively examined the game to identify performance indicators for success. To date, however, only
Long and Hughes, 2004 have identified changes in the game since the introduction of professional playing status in 1995, Moreover, whilst time and motion analyses are relatively prevalent, no studies have addressed the important issue of key time performance indicators.
Despite such a body of knowledge, there remain several fundamental issues which invalidate many of the findings of these studies. Whilst Hughes et al. (2002) outlined clearly the need for more thorough reliability assessments many researchers still fail to address this issue or fail to assess variables to the same level as the subsequent data analyses. This is particularly evident in researchers presenting a percentage level of agreement for the 'total' system rather than for individual variables. Moreover, it is often unclear whether these researchers have used raw or processed data in calculating the level of agreements. Additionally, in presenting player profiles few studies have addressed player identification as a separate assessment from the presentation ofthe level ofagreement for variable identification.
It has been suggested that in presenting a performance profile, it is essential that researchers ensure that the variable means are stable, that is to say, present a normative profile. Similar to the assessment of system reliability, there is scant evidence that this has been adopted in notational analysis research in either code of rugby. Where resea¡chers have acknowledged the importance of this aspect of the process, single line profiles have been presented that do not account for the shape ofthe profile being influenced by the order in which data are inputted into the computer.
In more recent studies, researchers have used statistical analyses to identify whether differences in means/medians are significant. However, often such studies use inappropriate methods of analysis; using parametric tests on non-parametric data, using incorrect non-parametric tests, and failing to examine significant main effects further with appropriate posl-hoc tests.
46 In addition, few studies have presented data in non-dimensional (normalised) form. Hence incorrect conclusions have been made, since no account has been made regarding possession frequency or time in possession.
Considering the concerns over poor assessment of system reliability, failing to address the importance of stable variable means and the use of inappropriate statistical analyses in rugby union, the failure to use non- dimensional indicators and the almost complete lack of research addressing performance profiles in rugby league, there is a clear need to develop profiles which are based on objective and reliable systems. In developing such systems, not only can profiles be identified for the 'contemporary' game, but also for performances over time (longitudinal profiles) which will establish trends in key variables and performance indicators. As sucl¡ both games can be mapped to establish explicitly how the games have changed. This is important, since in examining the effects of interventions, for example rule changes, the outcome of the analyses may be placed in the context of the established trends, and hence, more definitive statements made on the influence of the intervention. In addition, the longitudinal mapping of the game will enable other significant e'r'ents in the games (change in playing season in rugby league and the introduction of professional playing status in rugby union) to be examined. Moreover, the changing profiles in the games will provide an insight into whether the anecdotal evidence of the convergence of the two games is correct, and importantly, whether this may result in a single game of 'rugby' some time in the future. To date, no publications have attempted to address this important issue in the future development of both codes of rugby.
A further concern with research addressing performance indicators in rugby football is that the comparisons between winning and losing teams are all based on fulI game data. Whilst this research provides information regarding how winning and losing teams may differ, it does not identify unequivocally which particular aspects of the performance are related to success/failure. By using full game data alone, no account is made of changes in performance during sections of the game. For example, a team may lose the game but score more points in the first half. In this case any identifrcation of performance indicators for success/failure may be masked. That is to say, those indicators which may have been related to zuccess in the first half of play will actually be reporled as indicators of failure in the fu1l game data. Hence, it is not possible to establish clearly which performance indicators are related to success in the game. A more appropriate method may be to examine the gameby successful sections of play. However, there are several considerations which need to be addressed before adopting this approach. The section ofplay which is to be analysed needs to be relatively short in duration so that the positive and negative sub-sections ofplay by one team do not cancel each other out and there,fore become masked. However, the duration must be suffrciently long to identify (by score) a successful performance and ensure that sufflcient data are collected for a normative profile to be aohieved.
47 Moreover, it is necessary for longer durations of play to be analysed so that less frequently occurring game performance indicators can be identified. To this end it is suggested that game quarters (2O-minute periods) may be a more appropriate examination time period for research which seeks to report performance indicators in rugby union and rugby league football. Whilst this method does not account for how ateam may change its performance relating to the stage of the game (whilst winning or losing during the game), or how a team may change its performance in the later stages of the game, either to protect a lead or seek to secure a winning score, it will possibly enable performance indicators to be identified more clearly than reporting full game data. It is therefore suggest€d that there is a need to establish the extent to which successful game quarter data differ from full game data and how these differences influence the overall performance profiles.
Accordingly, there is a need for research to examine fully key va¡iables and performance indicators in both codes of rugby football and to identifr cleady longitudinal profiles which may be used to contextualise the results of research examining key interventions. In additioq the comparison of these code profiles is the first
step in identi$ring the changing relationship of key variables and performance indicators in these games, which may result in identi$ing commonalities that might be used to develop a 'unified' game of nrgby.
To this end, the aim of this study was to establish whether the games of rugby union and rugby league are becoming more alike and identiff the impact of key factors influencing any convergence of codes.
48 CHAPTER 3 _ METHODS
3.1 Intruduction 50
3.2 Equipment 50
3.2.1 Iferdware 50 3,2.2 Systems 51 3.2,3 Pilot studies 54 3.2.4 Operatiorral definitions and final systems 57 3,2,4,1 Rugby League 57 3,2.4,2 RugbyUnion 60 3.2.4,3 Í'inal systems 62 3.2.5 Reliability studies 63 3.2.6 Normative profiling &
3.3 Data sampling 65
3.3.1 Rugby league 6 3.3,2 Rugby union 67
3.4 Procedurcs 68
3.4.1 Time vari¡bles analysis 68 3.4.2 Tactic¡Vtechnical, game and positional analyses 69
3.5 Data processing ?0
3.5.1 Reliability 70 3.5.2 Normative profïles 70 3.5.3 Statistic¡l analyses 70
49 3.1 Introduction
In order to undertake a full taøic¿l evaluation of both codes of rugby football, tkee separate notation procedures were developed and validated. These hand notation systems were employed to provide objective data on time variables, defence action variables, offence action variables and game action variables. In addition, data were collected for time, offence and defence performance indicators. To assist the reader, each sub-section of the methods is further sub-divided to address each of these components for both rugby league and rugby union
3.2 Equipment
3.2.1 Hardware
The analyses of all va¡iables were undertaken using the following equipment:
¡ An Aiwa VX-T149 combined remote controlled television and video system with slow motion and
frame-by-frame movement capabilities.
¡ A Quantum stopwatch with lap split time åcility.
o l0 pre-recorded videotaped rugby league games purchased from Micron Video, Wigan and Rugby
League World Bridgeford, Yorks.
o 32 pre.recorded videotapes of first grade rugby league games borrowed ûom the personal
collections of Rae rWilloughb¡ and William Moore, Blackpool.
¡ 24 pre-recorded videotapes of International rugby union games form the Centre of Performance
Analysis, UWIC.
. Coloured fibre tip ink pens.
50 3.2.2 Systems
Tìme vøriøbles slstem
The initial system devised to assess the time variables in both oodes of rugby football is presented as Figure 3.1.
The times for each individual action were recorded in separate cells, with each row representing a separate possession. The sum of all cells was calculated to identify the total ball in play time.
.E .È. .l J( J¿ & &o Jlo .à o o o 9 o 3 o ú ú ú & ú 371 192
950 148 6.03 2.96 2t5
r022
829
Figure 3.1 Example of initial notation system for colleøing time data in both codes of rugby football.
Olfence varfubles syslem
For the development of the offence variables notation system game models were developed in conjunction with game experts (Rugby Union Development Officer for Cheshirg Coact/Coach educator fievel IIIÆV], RFU tr¡tor/assessor, ex professional rugby league player, ld grade rugby league and union fitness conditioner). From these models and subsequent discussions the key offence variables were identified. A sequential data collecting system using short hand symbols (Figure 3.2) was then designed and tested.
+ Pass. e Change of pass direotion.
1 Offload.
J Offload on ground.
9 Indicates player in possession of the ball,
51 o Indicates player tackled in possession ofthe ball.
9 Indicates a pass from dummy half or at the base of a ruck or maul and the player ---t involved. T Try
2 Unknown player
K Kick in play
Kr Kick recovered by opposition
Kt Kick out of play
Kdg Drop goal attempt
Kdg* Drop goal successful
Kdo Goal line or 22-m drop out
K40 40-20 kick (rugby league only)
Ko Knock on
P Penalty
Pt Penalty - quick tap taken
PK Penalty - kick at goal
* Missed aøion o Complete set
S+ Scrum won s- Scrum lost
L+ Lineout won
L- Lineout lost
R Ruck (rugby union only)
R.3.s.6.7 Ruok indicating players involve.d in offence (rugby union only)
M Maul (rugby union only)
IùÁ2.3.4.6 N{aul indicating players involved in offence (rugby union only)
T Turnover
Na No advantage deemed - play called back ø previous offence
Figure 3.2 Short hand symbols for offence actions in both codes of rugby
s2 An example of the short hand notation system is presented in Figure 3.3. This example shows player 14 passed from the dummy/sorum half position to player 15, who in turn passed to player 7. This player was tackled and a ruck is formed including players 6, 13 and 4. From this ruok player l0 ran from the dummy/scrum half position and was tackled, a maul formed involving players' 15, 8 and 5. From the maul, player 14 ran with the ball and passed to player 13, who made a kick in play, which was recovered by the opposition (playet 3). The opposition playø 3 passed to player 7 who knocked on. No advantage ensued and a scrum was awarded, which was won by the team with the scrum feed.
74 (+ 15 - Ø R.6.13.4) (@ M. 15. 8. 5) (14 +13 Kr)
3 --+7ko Na S+
Figure 3,3 Example of initial notation system for the collection of offence data in rugby union.
Detencevartailes syslem
Fol the develÒpment of the defence variables systerq the same procedure was followed as for the offence variables data collection system. A sequential daø colleption system was then designed for these variables, which used specific short hand symbols (Figure 3.a). The numerical expressions in the left hand column represent the individual players, as indicted by their shirt number.
2 Single tackle
2* Missed tackle
2-3 I\4ain taokler (fust) and assist tackler/s (second)
213 Joint t¿ckle
2/416 Mob tackle (more than two players)
2I Offload in tackle
R Ruck (rugby union only)
R.3.5.6.7 Ruck indioating players involved in defence (rugby union only)
M Maul (rugby union only)
53 M2.3.4.6 I\4aul indicating players involved in defence (rugby union only)
? Unknown tackler
0 Complete set
Figure 3.4 Short hand symbols for defence actions in both codes of rugby
An example of the sequent øl data collecting system for defence variables is presented as Figure 3. 5.
(?M7. 5.4. l, 8) (2R8.s) (l 2-8R6)
(r3R7) (loR) (8/21 4)
Figure 3.5 Initial notation system for the colleotion of defence data in rugby union.
This example shows that a player who could not be identified made a single tackle which resulted in a maul
(included players 7, 5, 4, I and 8). The next phase of play was halted by player 2 who made a single tacklg resulting in a ruck being formed which included players 8 and 5. In the final phase of play player 12 made an initial taokle and was then assisted in oompleting the t¿ckle by player 8. A ruck was formed including player number 6, in which possession was lost.
3.2.3 Pilot studies
Several pilot studies were completed to assess the hand notation data collection systems. Twenty-minute sections of play were notated from the games Bradford versus St. Helens (2002), Leeds versus Hull (2002), \Vigan versus 'Wanington (1996), England versus France (2002), and Sale Sharks versus London Irish (2002)
For both the offence and defence variable analysis each game was notated twice, frstly to assess the effectiveness ofthe observer to identiff players and actions, and secondly to assess the consistency ofrecording the frequencies ofthe variables.
54 Timevaríøbles
Initial attempts at using this system were time consuming due to recording activrty time and ruck time separately.
The use of a split time stopwatch resolved this problem and enabled the recording of both elements simultaneously. The benefit of this continuous method of timing rather than individual timing was that an accurate total set time could also be recorded.
The results ofthese trials indicated that the recording sheet needed amending to enable the inclusion ofspecific written comments, predominantly to identift end of phase actions and to include identification of missing footage due to action replays or cameras focussing away from the game. The total time of missing footage was recorded and used to identifu an acceptable mean time for missing action. It was concluded that games would be excluded from the study where more than 5Yo of toøl game time wß mlssrng.
The use of different coloured pens was found to be benefrcial in the classification of individual team data and extremely useful when subsequently inputting data into SPSS spreadsheets. A double line symbol was introduced to identifr where ruck/aøivity times were unclear or missing due to the change of c¿mera focus, or when a held tackle was called (see Figure 3.7).
Olfence va¡iablæ
Tkee sections (twenty-minutes duration) of the games were notated using the offence variable notation system
(Figure 3.3). Initial attempts at usrng the system for notating rugby league revealed some minor concerns. It was found to be diffìcult to recognise players' numbers, particularly when attacking in the defence half, due to the primary identification feature -shirt numbers- being apparent only on the back of the shirt. Indeed, this was much more of a concÆrn in notating rugby union games, particularly at the ruck and maul situation where large numbers of players may be involved in the action. This problem was revealed in the high perc€ntage error calculated in the intra-ob,server reliability analyss. In an attempt to rectifr this, a pre-viewing of a game section wari used to identifu key distinctive characteristics of players. These included arm guards, head guards, boot colours, distinotive hairstyles and strapping. Some players were also identified by specific idiosyncrasies, for example the running style of Jason Robinson and Simon Geoghegan. Others were recognised merely by familiarity, and in some cases ethnicity. For each game a team sheet was produced which outlined these specific player characteristics. This was then used to identify players during the subsequent analysis. An example of this sheet is presented in Figure 3.6.
55 X'rance vs. Scotland 2002
X'rance Scotland
Sadourney 15 Læe
White hÀir Bernat-Salle t4 Stanger
Lamaison 13 Tait
Glas t2 Townsend
Knee band Dominici 11 Logan
White boots Castaignede 10 Chalmers Long sleeves
Carbonneau 9 Armstrong
Black cycle shorts læiwemont T 8 Walton Black headband/leg strapoing Yellow cycle I\{agne 7 Holmes Bald/headband shorts Long sleeves Leiwemont, M 6 Wainwright Head band
Glove Brouzet 5 Weir White headband and red cycle shorts Headband Pelous 4 Cronin Black knee strapping
Skinhead Totrnaire 3 Stewart Left knee strapping
Black hair Ibanez 2 Bullock
Left wrist band Califano I Hilton Blue head band/shirt out
Figure 3.6 Example of a team sheet with secondary identifioation characteristics of players.
To assist rn player identification, particularly at rucks and mauls, slow motion replay and frame-by-frame
analysis were necessary. The slow motion rewind and forward facility was also utilised to traok players to a
position where identifìcation was possible. Although time consuming, this enabled most players to be identified.
For rugby league (based on one game quarter - Bradford v. St. Helens 2002) the percentage of players who could
not be identified only exceeded 5%o for the variables oflloads (13.7%) and open play passes (6.3%). These,
however, were due to very low frequenoy counts in these variables in this game quarter. For rugby union (based
on one game quarter - England v. Francg 2002) rhe percentage of players who could not be identified only
exceeded 5o/o in the observation of pþers in the ruok (7.6%). This was deemed acceptable as in each of the 8
occasions that a player could not be identified; this was due to the player not being in ûame for sufficient time, or
56 the secondary identification characteristic being hidden. A subsequent analysis of another game quarter of the same game did not result in a notable improvement (6.8% of players being unidentifiable).
Defmce variøhlcs
The problerns highlighted in the analyses ofoffence variables were also apparent in the analyses ofthe defence variables. In addition, distinguishing the type of tackle was also found to be problematic. This was predominantly due to the high speed of the action and the poor or inappropriate camera focus. In rugby league the main problem was in establishing whether the assisting tackler actually contributed to the tackle. In rugby union the main problem was that many tackles were close to the congested ruck/maul situation, and in some cases the tackle was completely hidden by players emerging from a previous ruck, maul or sarum
3.2.4 Operational defïnitions and final systems
3.2.4,1Rugby League
All operational defrnitions were developed in consultation with the International I¿ws of the game 2C[.2 andlor direct or modified defuritions cited on the Superleague offrcial website (wwwsuperleague.co.uÐ. Where new terms were utilised in the study the author's own definitions are presented (in green).
Offence varíables
Ball Cørry - A run that results in forward progress of the ball in contact with the ball-carrier.
Run frrnt dutnm¡, hulf - A run by the acting half back direct from the 'play the ball'.
Pass - The tb¡ow ofthe ball from one player to another.
Opcn pla¡t pøss - All passes excluding passes direct from the dummy half position and ofiloads. Pass.from ilumm¡, lrulf - A.pass from the aoting half back directly after the 'play the ball'. This is only deemed a pass from dummy half position if the acting half back makes no attempt to run forward with the ball (run from dummy half).
Otfload - A pass made when the ball oarrier is in the process of being tåckled.
L'uttttcl cfltry, - A ball carry which is ended by a tackle or an oftload. Contnct cflff), (trd lilckle - Atp,ll carry which is ended by completion of a successful tackle.
57 Tutttovcr - A loss of possession due to an error in open pla¡ resulting in the opposition gaining possession
(handovers are not included).
Delence varí¿bles
Tøchle- Aplayer is deemed to be tackled if-
a. he is held by one or more opposing players and the ball or hand or arm carrying the ball comes into
contact with the ground.
b. he is held by one or more opposing players in such a manner that he can make no further progress or
part with the ball.
c. when he is lying on the ground and an opponent places a hand on him.
Sìngle tockle - a tackle which is completed by a single player without assistance from any team-mate. The action will also be classified as a single taokle if the tackle is near completion when additional player/s assist the single tackler.
Joinl tackle - an action in which two players simultaneously contact the ball carrier and complete the tackle. Assisted tuckle - a t¿ckle in which an initial single taokler is assisted by another player to complete the tackle after the initial contact.
Moh tøckle - a tackle in which tluee or more players are engaged in compløing the tackle. Double tackle - a taokle which is complaed by two players, with both notably contributing to effecting the actlon.
Game aúion vstíøhlq
Ruch ('Pløy the hall') - The 'play the ball' consists of the tackled player regaining his feet, facing his opponents' goal line, placing the ball on the floor and immediately heeling the ball backwards. The ball is deemed in play when it moves backwards.
Kick in play -When the ball is kicked intentionally, with the aim of keeping it within the field of play
Kick out qf pluy - When the ball is kicked intentionally, with the aim of putting it out of play (dead).
58 40-20 kíck - when a kick from inside the attacking te¿m's 40-m ling bounces into touch between the opponents'
20-m line and goal-line. The usual decision to awa¡d the scrum feed to the non-kicking team when the ball enters touch is then reversed.
Scrum - A scrum is, not more tftan tluee players from either team interlocking to create a tunnel. Two 2nd row players form immediately behind and a loose forward behind the second rows- all bound at right angles to the tunnel. The scrum is formed to restårt play when play is not restarted by a kick-oü drop orrt, penahy kick or play the ball.
Tíme va¡íables
Ruck tìme - time taken from tackle being completed to the ball being returned back in play by the 'play the ball'
Adivttl tíme-timetaken from the ball being deemed 'back in play'to the completion of the subsequenttackle.
Ball in pløy líme -The total time excluding the ball out of play time (when the ball has gone outside the playing aræ and remains therg or when the referee has blown his whistle to stop play or for a conversion kick to be taken).
Sel posscssiott tinrc - A continuous period of time ûom the start of a team's possession to the subsequent stoppage, due to either the ball becoming out of play or the referee signalling a stop in play.
Conlinuous possession linte - A continuous period of time from the start of one team's possession to its termination (the ball may go orrt of play during this time, but this time is not included in the recorded time).
Ct¡ntinuous ball irt ploy tinrc - A continuous period of time from the ball being deemed in play to the subsequent ball being out of play. During this time either team may be in possession of the ball.
F'ast ball - A ruck time less than 3.0 seconds.
Slotv holl - A ruck time greater than 5.0 seconds.
59 3.2.4.2 RugbyUnion
All operational definitions were developed in consultation with the International I-aws of the game 2004. Where new terms were utilised in the study the author's own definitions are presented (in green).
Ollence va¡ìables
Ilttll Ctrry, - A run that results in forward progress of the ball in contact with the ball-carrier. Pass - A player th¡ows the ball to another player. It is also a pass if a player hands the ball to another player without throwing it.
Opcu ¡tla¡, ¡tnr.r - All passes excluding passes direct from the dummy half position and offloads.
Ptss fntm tlunutÐ,/s¿¡urn Imlf - A pass from the acting half back directly after the 'play the ball'. This is only deemed a pass from dummy half position if the acting half back makes no attempt to run forward with the ball
(run from dummy half).
Offlortd - Apass made when the ball carrier is in the process of being tackled.
Pqt puss - A pass made immediately after the t¿ckle has been completed when the taokled player has been grounded.
Contacl carry - A ball carry which is ended by a tackle or an offload. Conlacl carqr ¡¡¡¡¡l ¡,r"¡le - Atp'll carry which is ended by completion of a successful tackle. T\trnotcr - Aloss of possession due to an error in open pla¡ resulting in the opposition gaining possession. Pla¡,¿¡ itt llrc ruck/nnul - A player is only credited with being in the ruck/maul if he significantly contributes
(approx. 50% of the total time) to the breakdown situation. Players leaning on the ruck or maul or being 'trapped' in the breakdown are not consider to be contributing.
Defence variables
Tackle (see Law 15, p.7l-72) - A player is deemed to be tackled when-
The ball-carrier is held by one or more opponents and is brought to ground. The term 'brought to ground' is defined as when the ball-carrier has one or two knees in contact with the ground.
Single lackle - a t¿ckle that is completed by a single player without assistance from any team-mate. The action will also be olassified as a single tackle if the tackle is near completion when additional player/s assist single t¿ckler.
60 ,Ioinl ht*le - an action in which two players simultaneously contact the ball carrier and complete the tackle.
Assislcd tnckle - a tackle in which an initial single tackler is assisted by another player to complete the tackle after the initial contact.
Mob tuckle - a tackle in which three or more players are engaged in completing the tackle. Douhle tuckle - a tackle which is completed by two playets, with both notably contributing to effecting the actron.
Game sdìon vø¡ìøblø
Ruck (Law 16, p78) - A phase of play where one or more players from each team are in physical contact on their feet close around the ball in contact with the ground. The ruck is deemed to end when the ball leaves the ruck.
Maul (Law 17, p,83) - A maul occurs when a ball-ca¡rier is held up by one or more opponents and one or more ofthe ball carrier's team mates bind onto the ball-carrier.
Líneoul (Law 19, p. 89) - Arætafito the game after the ball has gone into toucb with a throw between two lines of players.
Scrum (Law 20, p. 99) - A method of restarting the game after an infringement. It is formed when eight players
ûom each sidg bound together in three rows, close up with their opponents so thei¡ heads interlock. This creates a tunnel into which the sqrum half tlrows the ball so that the front row players can compete for possession
Tímevørtøbbs
Ruck tìme - time taken from tackle being effeøed to the ball leaving the ruck Hence, 'back in play' signified by ball being picked up by a member of either tearn
Adìvþ time -time taken from the ball being deemed 'back in play' to the completion of the subsequent tackle.
Ball ìn play tíme-The total time excluding the ball out of play time (when the ball has gone outside the playing area and remains there, or when the referee has blown his whistle to stop play or for a conversion kick to be takÐ.
Sel possessíon tinrc - A continuous period of time from the start of a team's possession to the subsequent stoppagg due to either the ball becoming out of play or the referee signalling a stop in play.
Conlìnuous possession linrc - A continuous period of time from the st¿rt of one t@m's possession to its termination (the ball may go out of play during this time, but this time is not included in the recorded time).
6l Conlinuous hall in plny tinte - Acontinuous period of time from the ball being deemed in play to the subsequent ball being out of play During this time either team may þ in possession of the ball.
Fast hsll - Aruck time less than 2.0 seconds. Slott hull - A ruck time greater than 4.0 seconds.
3.2.4.3 X'inal Systems
Timevøriables
The final system for time elements of the games (Fþure 3.7) was adapted from the initial system (Figure 3.1) based on the findings of the pilot studies. The inolusion of a total set possession time on the notation sheet ensured that lengthy calculations of possession time were avoided. A column was also included to mark the end of the play action. This was used to assess the possible relationship between time and game actions.
o x â h I P a, J¿ J1 J4 J1 a€) 9 o () o o o t) u o t) () €) o ú ú ú ú=l (o È Ës* tt.7 3.32 3.51 3.U 4.61 324 3,48 3.83 8.93 45.86 KI
5.65 3.38 3.30 3.80 4.13 4.60 7.93 1.39 8.47 42.65 K¡
4.16 3.34 4.06- 2.41 13.97 PenKt
6.86 4.19 3.03 1.21 s.64 2,06 8.47 3.75 5.59 40.80 Kt
Figure 3.7 Example of the frnal notation system for the collection of time data in both rugby Codes.
Olfence and Defence varíables
The frnal system for defence actions was amended to address the concerns highlighted in the pilot study; namely the difficulty in identification oftackle type (assisted orjoint). The new system categorised the tackles as either single (one player), double (two players) or mob (more than two players). The notation sheets for offence and defence actions were also combined in order to identifu which offence and defence players were active in key actions (tackles, rucks, mauls etc.). A column was also included to identifu how the possession ended, and for any specific notes (sin binned players, substitutions, injuries etc.). An example of the final system for offence and defence actions is presented in Figure 3.8. Although the notation sheets for actions were combined the data
62 collection for offence and defence variables were undert¿ken separately. This double entry system also facilitated a second check on offence actions to be undertaken,
9 (@Mt.3.11.7)(+ t0*ØR s.7.?)(---+ @ tvt+,0¡ Pk player 6 sin Eng binned. (20:31)
(? M7.5.4.8.r) ( 3R2.8.5)( 12M3.2\ Scot
Figure 3.8 Final notation system for the collection of offence and defence data in both rugby union.
3.2.5 Reliability Studies
In designing new analysis systems, it is fundamental that 'repeatability and accuracy' of the systsm is clærly established (Hughes et al., 20O2, p.2). In the field of notation analysis Hughes et al. (2002) have identified that scant regard has been given to reliability analysis, in fact they suggested that as many as 850/o ofresea¡ch papers either use questionable methods of assessing reliability or fail to address reliability issues at all.
The two most relevant methods of assessing reliability in notational analysis are stability testing and objectivrty testing, or intra- and inter-ob,server testing respectively. Often in such tests correlation coefficients are calculated to measwe the strength of agreement between the test and retest score of the measured variables. However, the use of correlation coeffïcients in assessing inter- and intra-observer reliability has been questioned. Bland and
Altman (1986) made a number of pertinent points arguing against the use of correlation coefftcients, fundament¿lly stating that a 'change in scale of measurement does not affe¿t the conelatioq but it certainly does the agreement'. Similarly, Atkinson and Nevill (1998) suggested that conelations do not assess the within- subjects agreement between repeated measures. However, the Pearson and (intraclass correlation) coeffrcients are still utilised in assessing reliability. According to I¿mb et al. (2003) this may be due to these methods being more simple to understand and traditionally more popular than alternative methods, such as that of calculating the
95%Iimrf of agreement (LoA) as advocated by Bland and Altman (1986)
The use of 95o/o limits of agreement nìay be deemed a more appropriate method of assessing reliabilit¡ though its use in notational analysis may be restricted due to the level of measurement of the dependent variables and the assumptions of normal distribution of data. Often in notational analysis the data are nominal and./or not normally
63 distributed; therefore LoA cannot be used since the teohnþe c¿lculates the bias and standard deviation of the test retest differences and assumes the distributions of the differences are normal.
Instead the use of the reliability equation ((% enor : (X(mod[Vr-Vz])/ V-*)*1,O0 W advocated by Hughes er al. (2002) may provide an appropriate indication as to the level of agreement between observations; however, in the case of time data, the use of expressing reliability as percentåges may be flawed. The greater the time phase the less the error will be when expressed as a percentage of the mean time. Altematively expressing the data in raw terms may also lead to misinterpretation. For examplg a mean difference in time observations of 2 seconds in recording marathon times m4y be deemed reliable, but this would not be the case if timing were involved in obsewing a 100-m sprint. Consequently, in this case the use of 'modified plots' (Hughes et a1.,2002) provides a more appropriate method of presenting reliability, in that they provide a visual representation of how much data fall within a pre-determined range (usually 5%). The plot displays the mean scorg differences both negative and positive and the range of the differences in score, and identifies outliers which may severely reduce the level of agreement when using the calculation presented by Hughes et al. Q002). This visual representation also provides an immediate illustration of where the measurements are likely to frll beyond the established limits of agreement.
As a consequence it was decided to express the reliabilþ of the measures in both formats, one based on Bland and Altman (1986) and the other based on Hughes et al. (2002).
3.2.6 Normative profrling
If comparisons are to be made from notational analysis data, and conclusions made from these data, it is important that resea¡chers are sure that a consistent average of the performance has been achieved. Hughes,
Evans et al. (2001) suggested that in previous notation research this has not be the case, and that there has been an assumption that a 'normative profile' will be reached if enough games are analysed. They pose the important question though - how many games are enough? If too few games are analysed, the profile may not be stable and hence not be representative of the 'average' performance. If too many games are analysed and included in subsequent databases, the database becomes more insensitive to changes in performance, therefore, the identification of the minimum number of games is essential for notational analysts.
Hughes, Evans eú al. (2001) suggested that using graphical plots of the cumulative means should be used to establish the normative profile. This method, according to O'Donoghue (2005, p. 105) reduces the variability due to individual match effects by basing performance indicators on multiple match data'. Whilst Hughes, Evans et
64 al. (2OOl) recognisd the results fromthese plots may be limited and O'Donoghue (2005) criticised the method in his presentation of an alternative procedwe for normative performance profiling, the present study will adopt the procedure outlined by Hughes, Evans et al. (2C0l). This is in consideration that the method suggested by
O'Donoghue (2005, p. 107) is based on percentiles and 'requires data from hundreds of performers to establish
nornìri'. These data are not available for all the variables under analysis in rugby union and rugby league football.
In rugby football only l\4arshall and Hughes' (2001) analysis of the elite women's games and studies on
Internation¿l Northern hemisphere rugby union has attempted to establish how many gam€s are required to
achieve a stable profile using this method. As suclU in men's International rugby union no normative proñles
have yet been established. In fnst grade rugby league similarly no normative profiles exist for any variable.
The profiles presented in this study are double line profiles, since the cumulative means of any variable are
influenced by the order in which data a¡e inputted into the data sheet. The double line profiles are based on two
randomly selected orders of data input for each variable. The subsequent cumulative means are then used to
produce the double line plot.
3.3 Data sampling
Initially, two periods were to be analysed:- before and after the change to summer rugby league footboll (and
ostensibly full-time professionalism) and the introduction of professional playing status in rugby union in 1995.
The earliest year selected was 1988, as prior to 7987, rugby union had no defined league structure, Accordìng to
Dunning and Sheard (2005, p. 259) the emergence ofthe 'Courage Leagues' in this year increased the frequency
of meaningful frxtures. Implicitly, they suggested that this was the catalyst in the push towards players being
what they referred to as 'openly professional'. They cited ex-England flanker David Cooke, who stated in the
'Rugby World and Posl' (September 1987) that potentially, the league would 'hasten the arrival of professional
rugby'(p. 253).
The 1988-1995 period (subsequently refered to as the pre.professional Era) was sub-divided into two parts,
(initially 1988-91 and 1992-95), selected to reflect a period in the early 1990s that Dunning and Sheard (2005)
suggested was for all intentions professional in rugby union, but without open payment. However, in account of
65 the important law change pertaining to offside in rugby league (1992-93) and the lack of available full game footage in this code of rugby, these Periods were amended to 1988-92 and 1993-95.
T\e 1997-2002 Era was also subdivided to match the pre-professional Er4 the professional parts, later oalled
Periods being 1997-1999 and 2000-2002.
3.3.1 Rugby League
Twenty-four games of First Grade domestic rugby league were randomly selected for analysis (Table 3.1). Six games wer€ assigned from a pool of eight games available from Challenge Cup Finals, Premiership Finals and
Semi-Finals in the 1988-92 Period. A second group of six games was assigned from a pool of eight games taken from Challenge Cup Finals and Premiership Finals in the 1993-95 Period. A third group of six games was assigned from an available pool of nine games taken from Challenge Cup Finals, Regal Trophy Finals and Super
League Grand Finals inthe 1997-99 Period. The final group of games was assigned from a pool of l7 available games in the 2000-02 Period. Initially, the 1996 Premiership Final between Wigan and St. Helens was selected for analysis; however, this was later discounted from the study due to the level of missing footage (4 min 22 s in one half of play). This violated the 5Vo level of missing footage deemed acceptable based on the mean time of missed action revealed in the pilot study. Games from the Challenge Cup, Premiership, Regal Trophy Cup and
Super League games were selected as being indicative of top grade rugby league football in the Northern hemisphere.
66 Table 3.1 Rugby league games analysed by Period and Era
Era Period Games Competition
Pre.professional 1988-92 Ilalifax v Wigan Challenge Cup Final 1988 Preprofessional 1988-92 Wigan v Warrington Challenge Cup Semi-Final 1989 Pr+professional 1988-92 Wigan v St. Helens Challenge Cup Final 1989 Pre-professional 7988-92 WiganvHalifax Regal Trophy Final 1990 Pre-professional t988-92 St. Helens v Wigan Challenge Cup Final l99l Preprofessional 1988-92 Castleford v Wigan Challenge Cup Final 1992 Pre.professional 1993-95 Wigan vWidnes Challenge Cup Final 1993 Preprofessional 1993-95 Wigan v Castleford Premiership Final 1994 Pre-professional 1993-95 Wigan v Leeds Challenge Cup Final 1994 Pre-professional 1993-95 Leeds v \Vigan Challenge Cup Final 1995 Preprofessional 1993-95 Warrington v Wgan Regal Trophy Final 1995 Pre-professional 1993-95 Wigan v Leeds Premiership Final 1995 Professional 7997-99 Leeds vWigan Super League Crrand Final 1998 Professional 1997-99 London v læeds Challenge Cup Final 1999 Professional 1997-99 Wiæn v Sheffield Challenge Cup Final 1998 Professional t997-99 St. Helens v Bradford Super League Grand Final 1999 Professional 1997-99 Bradford v St. Helens Challenge Cup Final 1997 Professional 1997-99 Wigan v St. Helens Premiership Biml1997 Professional 2000-02 Wigan v Bradford Super League 2002 Professional 2000-02 Bradford v Leeds Super League 2002 Professional 2000-02 Bradford v Wigan Super League 2002 Professional 2000-02 Wigan v St. Helens Super League 2002 Professional 2000-02 St Helens v Bradford Super League 2002 Professional 2000-02 Leeds v Hull Super League 2002
3.3.2 Rugby Union
Twenty-four games of international Five and Six Nations Rugby Union were randomly selected for analyses
(Table 3.2). Six games were selected from each of the Periods 1988-92, 1993-95, 199'7-99, and 2000-02.
Originally the games France v. England 2001 and England v. Scotland 2000 were seleoted; however, these were discounted due to the poor quality of the video footage making player identification impossible.
67 Table3.Z Rugby union games analysed by Period and Era
Era Period Games Competition
Pre-professional 1988-92 Wales v Scotland Five Nations Championships 1988 Pre'professional 1988-92 Englandv Wales Five Nations Championships 1988 Pre.professional 1988-92 Ireland v ÌVales Five Nations Championships 1988 Pre-professional 7988-92 Wales v Scotland Five Nations Championships 1990 Pre.professional 1988-92 Ireland v Wales Five Nations Championships 1990 Pre.professional 1988-92 France v England Five Nations Championships 1990 Pre-professional 1993-95 Wales v England Five Nations Champiorships 1993 Pre-professional t993-95 Wales vlreland Five Nations Championships 1994 Preprofessional 1993-95 Scotland v France Five Nations Championships 1994 Pre'professional 1993-95 Ireland v Scotland Five Nations Championships 1993 Pre-profssional 1993-95 Ireland v England Five Nations Championships 1993 Pre-professional 1993-95 England v France Five Nations Championships 1993 Professional 1997-99 France v Ireland Five Nations Championships 1998 Professional 1997-99 Ireland v Wales Five Nations Championships 1998 Professional 1997-99 Ireland v Scotland Five Nations Championships 1998 Professional 1997-99 France v England Five Nations Championships 1998 Professional 1997-99 Scotland v France Five Nations Championships 1998 Professional 1997-99 France v Scotland Five Nations Championships 1999 Professional 2000-02 England v France Six Nations Championships 20O2 Professional 2000-02 England v Ireland Six Nations Championships 2002 Professional 2000-02 Ireland v Wales Six Nations Championships 2002 Professional 2000-02 Wales v Scotland S ix Nations Championshi ps 2002 Professional 2000-02 Scotland v Ireland S ix Nations Championshi ps 2002 Professional 2000-02 England v Scotland S ix Nations Championshi ps 2O02
3.4 Procedures
3.4.1 Time variables analysis
For both codes of rugby, games were analysed in twenty-minute segments using the final system outlined previously (Figure 3.7). Each phase of play was recorded using the split time stopwatch (accurate to 1/100m s), the video-recorder paused, and then individual ruck, activity and phase times reoalled from the stopwatch and transcribed onto the time data notation sheet using the appropriate coloured pen. The end of phase action was also recorded before the video-recorder was resta¡ted and the time/notation procedure repeated. At the end of twenty minutes of footage the end of game quarter was noted on the notation sheet and the observer rested for a time
68 exceeding five minutes to offset the possible effects of fatþue. At the end of each full game the observer rested for a time not less than one hour. No more than two full games were notated in one twenty-four hour period.
3.4.2 T acticalltechnical, game and positional analyses
Prior to undertaking the full notation, a twenty-minute segment of footage was played in order to identi$ and record secondary identification characteristics ofplayers on the appropriate record sheet (Figure 3.6). In additiorl where player lineups for National Anthems were include{ this section was also viewed to assist in player identification.
For rugby league games, offence actions were notated in twenty-minute of game time; however, due to the diffrculty in observing rugby unior¡ games in this code were notated in ten-minute game time periods. At the end of each data collection phase the observer rested for a period exceeding five minutes.
For rugby league the video recorder was set on slow play (approx. 50% of real time). The short hand system developed to record ofÊence actions (Figure 3.8) was utilised. Each phase of play was recorded on a separate line, leaving a line between phases for the inclusion of defence data notated at a subsequent time. At the end of each phase the videotape was rewound and the shorthand notation record checked for errors and omissions. Where observations were diffrcult to make, the use of the frame'by-frame function was used to assist the identification ofplayers.
For rugby union, a more systematio procedure was required due to the diffioulties in observations outlined previously. The video recorder was set on slow play (approx 25o/o of realtime). Each game was observed twice to identifl specific features systematioally. The first play though was usd to notate all game actions (passes, scrurq lineouts, rucks, rnauls etc.) and the second to identifu players.
Each game was analysed phase-by-phase and recorded appropriately using the short hand system outlined in
Figure 3.2.ßor the analysis for rugby league, each phase was recorded on a separate line, leaving a blank line between each phase for subsequent analysis and notation of defence actions. On completion of the offence analyses, the defence actions were notated. The same systematic procedure outlined for the offence actions was observed, with two full plays of all game footage. The first observation was utilised to identify tackle type
(single, double or mob) and number of players engaged in defence rucks and mauls and the second observation to identify players.
69 3.5 Data processing
3.5.1 Retiability
Data from the two separate observations of the same game were input into a SPSS v. ll data sheet. These data columns were checked and aligned to account for any missing data. The 'comlrute ' and ' transforrn ' functions were used to calculate the observed difference between each variable. These data were subsequently used to produce modified Bland and Altman plots and calculate reliability in the manner outlined by Hughes er ø/.
(2002).
The use of multiple spreadsheets led to c,oncerns with regard to inputting error. To rectifr this problem data were inputted, then cheoked against the orþinal notation system and then inputted again in an adjoining column.
This approach enabled all data to be checked thoroughly for errors.
3.5.2 Normative Prcfiles
For each Period, data for each game quarter were imported into the data sheet direøly from the SPSS output table to ensure that inputting errors were minimised. In order to negate potential concems with the profiles being affected by the sequence of data inpuuing, a second column was introduced and the original data randomised before being inputted a second time. Mean scores for both columns were calculated, one row \ry¡ß then deleted and scores re-calculated. This procedure was repeated until the cumulative mean scores were identified for game qurirters ranging from2 to 24. These cumulative means ìilere then used to produce a double line normative profile for each variable, in each game period. The profrle was used to identi$ when each variable profile reached a stable mean.
70 3.5.3 Statistical Analysis
Multívørfule and univaríate ønaþses
Often in research the analysis of several dependent variables is warranted. One approach to dealing with multiple
dependent variables is to undertake multiple univariate analyses. However, according to Vincent (7999, p.2I3) this may invite a Type I error. In additio4 Field (2005, p. 572) suggested that if several univariate analyses are
conducted on each dependent variable the possible relationship between these variables is ignored. One method
of overcoming these problems is to use multivariate analyses, since in multivariate analysis of variance
(MANOVA) a new dependent variable (omnibus,F) is formed from several dependent variables (Vincent, 1999,
p.217). This new dependent variable is then analysed with univariate analysis of variance (ANOVA) to
determine if there are any differences. This method helps protect against a Type I error since only one dependent
variable is tested.
There are several conc€rns with adopting this multivariate approach to the analysis of such data. Firstly, if any
signifioant difference is found in the omnibus F then further univariate analysis of the original dependent
variables may be required, since according to Tabachnick and Fidell (2001, p.323) MANOVA does not relate
which dependent variables are sensitive to the independent variable. This is somewhat perplexing. For example,
in utilising a ons.way ANOVA subsequent to the MANOVA the issue of the inflation of the Type I error must be
apparent, although it could be argued that ANOVA is 'protected' by the original MANOVA Field (2005, p. 572),
however, suggested that this notion of 'protection' is 'somewhat fallacious' because a significant MANOVA
more often than not does not reflect a significant difference in all of the dependent variables.
Secondly, the MANOVA is often more conseryative (less powerful) than ANOVA (Vincent, 1999, p.217), n
that when only one or two of several dependent variables are significang the non-significant variables may mask
the effect of the signifrcant dependent variables, producing a non-significant omnibus F'and result in a Type II
error (accepting the null hypothesis for all dependent variables when it is frlse for at least one of them). In
addition, Field (2005, p.572) suggested that the power of the MANOVA decreases as the corelation between the
dependent variables increases, hence its usefulness is limited if the dependent variables are correlated.
Thidly, there are limitations on the number of dependent variables that can be included in MANOVA.
According to Giles (2002, p.27-28), whilst adding variables does not increase the error rate (as in ANOVA), it
does reduce the power. In additiorl the subjeots per group to dependent variables ratio has to be considered since
this also influences the power of MANOVA. According to Vincent (1999, p.218) some statistioians feel that this
7l ratio should be at least 3 to l, and must defuritely be more than 1 to l, as at this ratio the power of MANOVA becomes severely limited.
Finally, the MANOVA is 'substantially more complicated than the ANOVA' (Vurcent, 1999, p.217) and there is often ambiguity in the interpretation of the effect of the independent variable on any single dependent variable and unlike univariate analysis the process is neither straightforward nor is there a conseruius amongst experts on exactly how to proceed (Shuhz & Sands, 1995, p.2i78).
As a consequence of the problems and difficulties in interpretation of the results of the MANOVA the use of univariate analyses with Bonferroni adjustments has been suggested as a more appropriate method of dealing with multiple dependent variables @ield, 1999; Tabachnick & Fidell, 2001, Vincent,2005). Additionally, if
'each ofthe dependent variables is ofautonomous interest' univariate analyses should be used (Vincent, 1999, p.217) rather than multivariate analyses which are more appropriate if the underlying factors of the dependent variables are of more interest.
Taking into consideration the diffioulties and problems when employing multivariate techniques, the fact that in the present study the dependent variables are of autonomous interest, particularly in the assessment of performance indicators and the low subjects to dependent variables ratio (due to limited available full-game footage in rugby league) the use of univariate statistical analyses were adopted.
Pø¡ametric and no n-paramebìc ønøþses
The fundamental assumptions regarding the use of parametric tests, namely that the level of the dependent variables were interval or ratio, the distribution of the dependent variable is normal, the error variance of the dependent variable is equal across groups and the scores within groups are urdependent of each other were assessed. For frequency/discrete data non-parametric tests were utilised, however, for time data the Shapiro-
Wilk's test was employed to identify whether or not data were normally distributed. According to Chen and Zhu
(2001), where violations of normality are not severe, the robustness of F tests is sufficient to allow proceeding with parametric analysis. Winter et al. QOOI) considered this to be contingent on equality of variance and sample number not being low in number (>10). A concern here is that these authors fril to indicate the exact sample size, ahhough Chen and Zhu (2001) suggested a sample number greater ttøn 25. Seemingly, no definite sample size has been est¿blished with regard to this issue.
To test for equality of variance the Levene's test was employed. Whilst there are many tests to assess homogeneity of variance, this selection was based on the test being less sensitive to the data distribution (Chen &
72 Zhu, 2001). Thereforg where violations on normality of distribution are minor, subsequent checks on homogeneity are not significantly affected. Where these conditions were satisfied data were subsequently analysed using ANOVA. Where major violations of equality of variance were indioated several options were
available. The use of transformations (Logarithm andlor Square Root) was considered. Whilst concerns have
been expressed with regard to such procedures, namely in back transformation, in accordance with the views of
Chen and Zhu (2001) it was deemed appropriate only where both equality of variance and normalþ of
distribution were violated. Where the normal distnbution of data was not violated, but equality of variance was,
the decision whether to use conventional parametric analyses or non-parametric methods was based on the
skewness of the data. If skewnæs <1.5, deta were analysed using parametric methods. If skewness >1.5 non-
parametric equivalent tests were employed, namely the Freidman ANOVA (for Game Quarter analyses), the
Kruskal Wallis test (for Period analyses) and the Mann-Whitney U test (for Er4 Code and Game Outcome
analyses). In terms of sample numbers this decision is in conflict with the view of Chen and Zhu (2001), who
suggested with sample sizes < 25, a non-inferential statistical approach should be considered, it was felt that this
study's sample size (n: 24) was suffrcient considering the suggested size reported by Winter et al. (2O01).
A further c,oncerr! particularly relevant to repeate.d-measures analysis is that of spherioity, or the assessment of
'Where homogeneity of covariance. To check that sphericþ was not violated the lMauohley's W test was utilised.
sphericity was not met (indicated by P < 0.05) there is an increased risk of a Type I e,rror, therefore to offset this
inflated risk a correction factor must be applied to the degrees of freedom to raise the critical value of F (Winter
et al., 2001). The two main options for correction are the Greenhouse-Geisser and the Huynh-Feldt procedures.
According to Vincent (1999) the former is rather conservative and the latter too liberal. The main concem being
that with the overly conservative C'reenhouse-Geisser method too many null hypotheses fail to be rejected
(Huynh & Feldt 1976 as cited in Field 2000, pp. 333-334).It has therefore been suggested that where epsilon for
Greenhouse-Geisser >0.75 the alternative Huynh-Feldt correction be employed. Hence, correction factors were
selected according to the Greenhouse-Geisser epsilon value. For a more comprehensive discussion, the reader is
directed to the Vincent (1999) text þp.174-175). To assist the reader a decision model is presented in Figure 3.9.
Where significant main effects were identified, post-hoc comparisons were made. For significant Period main
effects the Tukey HSD test was employed due to its 'frrm control over Type I errors' albeit with some loss of
power (Ilowell1997, p. 378). Field (2000, p.276) suggested that as long as sample sizes are equal Tukey HSD is
appropriate not only in terms of control of the Type I error rate but also due to having good power. For the Game
73 Quarter main effects multiple dependent t-tests were utilised, To proteçt against the increased risk of a Type I
error, that accompanies multiple comparisons, the Bonferroni adjustment was made (0.05/ no. of comparìsons).
For data analysed using the Freidman ANOVA" the Wilcoxon match paired test was employed as the equivalent post-hoc procedure, again employing the Bonferroni adjustment. For data analysed using the Kruskal Wallis test,
the Mann rilhitney U was utilised as an appropriate post-hoctæt.
Normal distibution Normal dishibution Normal distibution Normal disfibution -no - yes -no - yes Equality ofvariance Equality of variance Equality of variance Equalrty ofvariance no - yes - yes -no
Skewness Skewness < 1.5 > 1.5
Data transformation Repeaûed measures Freidman ANOVA ANOVA and Kruskal-Wallis
Spherioity of data met Sphericity of data not met @ > 0.05) - no correction (P<0.05)-correction factor employed factor employed
Epsilon < 0.75 Epsilon > 0.75
Greenhouse- Geisser Huynh-Feldt correction emploved correotion employed
Figure 3.9 Decision model for statistical procedures for intervaVratio daø.
74 CHAPTER 4 RELIABILITY AND NORMATTVE PROFILES
4.1 Introduction 76
4,2 Results 77
4.2,1 Reliability 77 4.2.2 Norm¡tive profiles t4
4.3 Discussion 94
4.3.1 Reliabilþ 94 4.3.2 Normative profiles 99
4.4 Summary 100
75 4.1 Introduction
In designing new systems to collect notational analysis data it is imperative that the repeatability and accuracy of these systems are rigorously and systematically assessed. According to Hughes et al. (2002) studies which have presented such evidence are the exception rather than the norm, and hence the validity of the subsequent reported frndings may be questioned. In addition, Hughes et al. (2002) also suggested that many research papers which do present evidence ofundertaking reliability analyses used inappropriate
statistical tests, often using parametric tests on non-parametric data. A simpler approach to assessing system reliability is using a percentage agÍeement calculation. Whilst this method is straight-forward it is often not clear whether reliability calculations were based on raw data (retaining sequentiality) or processed data
(accumulated totals of frequencies). Moreover, the values derived from the percentage calculations represent two features ofthe analysis, the identifïcation ofvariables and the frequency ofvariables. Ifthese separate aspects are combined it is diffrcult to ascertain where enors exist, and hence makes inferences on the validity
of the system more difficult. A further problem - particular to hand notational analysis - which has yet to be fully addressed is the effect of processing errors. That is to say errors which may occur in transferring data from a hand notation sheet into the computer. To date no publication using hand notation systems to collect
data has addressed this issue.
In addition to assessing the reliability of performance analysis systems it is also vital to identify how many
performances need to be analysed for a profile to stabilise, and hence be representative ofan average
performance. According to Hughes, Evans et al. (2001) if a normative profile is not achieved then the
conclusions drawn from the data may be questioned. To date few published papers have presented normative
profiles @aniel & Hughes, 2001; Hughes, Evans et a1.,2001) and these have used a single line profile as a
method of identif,ing how many games needed be assessed. This single line profile, however, does not
account for the order in which data are inputted into a spreadsheet. To overcome this problem the use of
double profiles can be used with the second line being developed from a different order of data inputting. To
date no publications have adopted this system ofnormative prohling, hence the previously reported data
based on these profÌles may be flawed.
In rugby union and rugby league there is scant evidence of published research which has addressed either
the reliability of systems to the same depth of the intended analyses, or established normative profiles for key
variables and performance indicators. As a consequence the results reported and inferences made from these
76 data must be questioned. It is therefore imperative that both the reliability of systems and normative profiles for all variables are explored fi.rlly before any data analyses are undertaken and performance profiles presented.
To this end, the objective of this study was to establish a framework for intra-operator reliability and normative profiles for key time, offence, defence, game action and positional profiles in rugby union and rugby league football between 1988 and 2002.
4.2 Results
4.2.r Reliability
Timevaríables
The intra-observer levels of agreements for the time variables for rugby union and rugby league are presented
in Table 4.1.
Table 4. I Intra-observer level of agreement (%) for time va¡iables rugby union and rugby league
Rugby League Rugby Union
Test l-Test 2 Test 2'Test 3 Test l-Test 2 Test 2-Test 3
Activity time 97.7 ¡1. 96.0 +
Ruck time 94.5 96.6 88.0 955
Set possession time 99.3 * 98.0 *
Ball in play time 100.0 {. 100.0 ,1.
* No retest necessary
For the ruck time - 'play the ball' time in rugby league - the intra-observer level of agreement was found to
be below 95%oinboth rugby union and rugby league. In an attempt to identifr the measurements thatwere in
danger oftransgressing the level of agreement (Ilughes et al., 2002) these data were also presented as scatter
plots (Fþres 4.1 and 4.2).
77 1.0 tr
.5 tr o o cl o tro Èt oootr cào oo o o Eb o trtr Otr qDo oE oot o otrr 0.0 o odf, ooo cl) o o o tro o o o o o (tt E otr oC) É o 0) 5 l< ql.í.) E o) FE -1.0 0 20 40 60 80 100 t20
Phase Figure 4.1 Intra-observer level of agreement - distribution of time differences for 'play the ball' time in rugby league.
2.5
2.0
1.5
1.0 rt o o çt) o 5 o o (I) o o o tr OtrErOtr .o tr q 0.0 'E o o E o F 5 0 l0 20 30
Phase
Figure 4.2Intra-observer level of agreement - distribution oftime difïerences for ruck time in rugby union.
In the measurement of the 'play the ball' time in rugby league (Figure 4.1) there were seven discrepancies of more than 0,5 s which were likely to have had a marked influence on the overall level of agreement. It was
78 interesting to note that six of these values were on the positive side of the plot, indicating that the time measurements were gteater in the first observation than the second observation. The same trend was noted for the data for rugby union (Figure 4.2). Here three measurement differences exceeding 0.5 s were obsewed, again in the positive direction, Further concerns with these data were the two values exceeding 1.0 s. These
'extreme' values (outliers) clearly negatively influenced the percentage agreement, particulady in this case where total variable observations were small (< 30). One option with these outliers was to exclude them from the overall calculations. lVhilst this was considered, it was felt that a second reliability test should be undertaken, to identi$ if such large extreme values were likely to be a common occurrence in subsequent analyses. The results presented in Table 4.1 suggest that the second test resulted in an increased level ofintra- observation agreement.
In both rugby union and rugby league, the data plots of the second analysis revealed a marked reduction in the level of observation diflerences between tests. The number and magnitude of the outliers decreased resulting in a reduction in the intra-observation percentage error (Figures 4.3 and 4.4).
For both codes of rugby the initial reliability assessment of aøivity time, set possession time and ball in play time resulted in scores exceeding 95ol0, therefore no secondary analyses were undertaken (Table 4.1).
1.0
o .5 o al h tro %tr o qP tr e o o oo o o o 0.0 É tr o rf È U) o o u) o o o lrt) 5 ql-11) 'E o FE -1.0 0 20 40 60 80
Phase
Figure 4.3 Intra-observer level of agfeement - distribution of time differences for 'play the ball' time in rugby league - test 2.
79 2.5
2.0
1.5
1.0
at() dl .tt .5 oc) c o tr) Cl o li otr o c¡ .(t¡ cl tr H 0.0 E |l) o Ê F 5 0 10 20 30
Phase
Figure 4.4 Intra-observer level of agreement - distribution of time differences for ruck time in rugby union - test 2.
Iilenlíficatíon and frequency of vuiables
The intra-observer levels ofagreement for the identifioation ofva¡iables and the frequency ofvariables for rugby union and rugby league are presented in Table 4.2 and 4.3, respectively.
Table 4.2lntra-observer level of agreement (%) for the identification of selected variables in rugby union and rugby league
Rugby League Rugby Union
Test l-Test 2 Test 2-Test 3 Test l-Test 2 Test 2-Test 3
Ruck 100 ,s 98.5 *
Maul N/A N/A 98.5 ¡t
All tackle types 84.6 98.8 86.7 100
Single tackles 95.8 :t 96.3 {q * Joint tackles 76.5 '|t 66.7
Assisted tackles 56.2 * 80.0 t
* Mob tackles 100 100 'it
Double tackles N/A 96.0 N/A 100
* Passes 100 88.9 97,7
80 Table 4.3 Intra-observer level of agreement (%) îor the frequency of selected variables in rugby union and rugby league
Rugby League Rugby Union
Test l-Test 2 Test 2-Test 3 Test l-Test 2 Test 2-Test 3
Ball carries 99.3 rt 95.4 ,t
Tackles 96.2 * 95.6 rl.
Rucks/mauls N/A ¡1. 98.5 ,ß
Scrums 100 rl. 100 *
Lineouts N/A N/A 100 N/A
¡t Passes 100 * 96.0
OfIIoads 100 t 100 t
Kicks in play 100 * 100 ¡lc
Kicks out of play 100 {. 100 *
* No retest necessary
In both rugby union and rugby league the identification of all tackle types (single; joint and assisted) resulted in 'low' peroentage agreement between observations. Further analyses of these data indicated that the
observation errors were unacceptably high for the identification of both joint and assisted tackles. The
diflìculty in distinguishing between the joint and assisted tackle, and to a lesser extent between assisted tackles and single tackles resulted in the need to re-classifuing the tackle types. A subsequent re-analysis using the new 'double tackle' classification resulted in a marked improvement in the observation level of
agreement in both codes (Table 4.2). For single and mob tackle identification the level of agreement
exceeded the accepted 95%o,hence no secondary tests were undertaken on these variables.
The level of agreement between the initial observations (Tl - T2) was below 9OYo for the identification of
passes, probably due to an ambiguous operational definition and diffrculties in notating quick passing
interchanges when observing real time. A second analysis (T2 - T3) undertaken using an amended
operational definition for passing and the game footage played at a reduced speed resulted in an improved
and acceptable agreement level (97.7%).
In both codes of rugby the intra-observer level of agreement exceeded 95%o for the frequency of all
variables.
81 Plqer ídentificøtion
The intra-observer levels of agreement for player identifìcation for rugby union and rugby league are presented in Table 4.4.
Table 4. lntra-observer level of agreement (%) for player identification in rugby union and rugby league
Rugby League Rugby Union
Test 1- Test 2- Test 1- Test 2- Test 3- Test 2 Test 3 Test 2 Test 3 Test 4
Player identilication 96.0 * 89.9 100.0 * in offence actions Player identification N/A N/A 83.5 93.7 92.8 in the ruck/maul (offence)
Player identification N/A N/A 85.0 100.0 * in the rucl¡/maul (defence)
Player identifrcation 97.6 * 80.4 94.1 * (all tackles)
Player identification 100 * 92.3 96.2 * (Single tackles)
Player identification 96.0 ¡i 58.3 ,ß * (Joint tackles)
Player identification 96.0 * 75.0 rl. ,1. (Assisted tackles)
Player identilication :* 94.0 rl. 92.0 * @ouble tackles) Player identification 100 d. 100 :1. * (Mob tacHes)
Passing player 91 8 98.0 91.7 95.2 * identific¡tion
No. of players in the N/A NiA 50.0 88.0 96.0 rucldmaul (offence)
No. of players in the N/A N/A 46.4 68.0 88.0 ruck/maul (defence)
No. of players in the 94.6 * 86.7 100 :* tackle
* No retest necessary
The main concernwith intra-observer level of agreements was in the identification of players and the number
of players engaged in rucks, mauls and tackles (Table 4.4). A second test was therefore undertaken using
secondary identihcation characteristics (refer to Figure 3.6), slow motion, freeze frame and forward and
backward tracking of players. This led to a marked improvement in the observation agreement, particularly in
player identifïcation. The diffrculty in assessing how many players were engaged in the breakdown was
addressed using more specific operational definitions. This resulted in further improvements in the level of
observer agreement in both the offence and defence situations. It is, however, important to note that the
82 consistency of identifying players engaging in defence rucks was still prone to an error level exceeding 5Yo
(Table 4.4).
In general the identification of player resulted in the lowest level of agreements between observations, particularly evident in the tackle and the ruclc/maul situation. As a result of these reliability analyses, subsequent player profiles for tackling were undertaken; however, no player profiles were presented for either rucks or maulg since the level of agreement for player identification violated the accepted 95Yo level and the identification ofthe frequency ofplayers involved in defence breakdowns was prone to a I2%o enor.
Datø hnndlíng and processing
Assessment of the reliability of transferring data from the hand notation recording sheet into the computer spreadsheet revealed some interesting results. In assessing the ruck and maul frequency, 2ó07 individual actions were inputted into a spreadsheet, A second inputting of the same data resulted in 2603 actions, indicating a 99.9Yo level of agreement for transferring data. However, further analysis of these data revealed
112 discrepancies between analyses, indicating an overall error level of 43Yo. Figures 4.5 and 4.6 indicate data input discrepancies for rucks and mauls, respectively.
4
J o c)LÉ. tro tr d o 4ãl ocr o EEr OE EDOO O cr @tr oo &o 9o !@ EIITEE@ID @ @EE fI¡trCIIITI[t Ê .Ê _1 o o o o oo oo tr o tr o Cd €rË É_) tr o o o) g-3C) .c) H /l -+ 0 20 40 60 80 100 120 140 160
No, of game quarters
Figure 4.5 Data input discrepancies for ruck frequency analysis.
83 J
E2 E o É o) = o doo o)ør 4r g:ì0 GIE @ È É-l otr o trootr o cE cú €GI Ê-2 clE c¡ (t) (D o (l)É) o
-(1) H â-4 0 20 40 60 80 100 120 140 160
No. of garne quarters
Figure 4.6Data input discrepancies for maul frequency analysis.
To address this problem the inputting ofall subsequent data was subject to a rigorous checking procedure prior to undertaking any statistical analyses.
4.2.2 Normative Profiles
Tímevariahles
For rugby union, the profiles for all the time variables stabilised to within 5Yo of the overall mean within 24 game quarters in all Periods (Table 4.5). For ball in play time, whilst the profiles stabilised within this time frame, the profïle for the Period 2000-02 only just stabilised atthe 5Yo level (Table 4.5) The profìle for 1988-
92 (Figure 4.7) whilst appearing to stabilise, should not be considered st¿ble (at the 5% limit of error) as this profile merely shows an 'end effect'. That is to say, a profile which appears to stabilise, but in reality only falls within the pre-defined limit due to the cumulative mean being based on a number of games close to the total number assessed.
84 Table 4.5 Number of game quarters to reach stable means to within +l% (lsyo*, +l}yo*") of the overall mean for time variables in rugby union
1988-92 1993-95 1997-99 2000-02
Activity time 16* l0* 8'l' 8*
Ruck time 10* 20* 8{' 6*
Set possession time 4'|. 19* 7* 15*
Ball in play time 12** 12* gt l8*
30 random order ofdata inputting. _ data inputted in reverse order. 28
+ 5Yo of the mean
26 Mean
24 - 5Vo of the mean
22
20
19 È O\ oo H H llJ N) tJ OI:)AO\oooN)È- -
No. of game quarters
Figure 4.7 Normative profile for rugby union ball in play time 1988-92.
For rugby league the profiles of all time variables stabilised to within 5% of the overall mean within 24 game quarters in all Periods (Table 4.6).
85 Table 4.6 Number of game quarters to reach stable means to within +lo/o (!syo*, +l0olo**) of the overall mean for time variables in rugby league
198E-92 1993-95 t997-99 2000-02
Activity time 16 2tt ztt g'ß
Ruck time 10 l8* 6* l2*
Set possession time 3* g* 4tr r4*
Ball in play time 72* 16* 8* 20*
Offencevariables
For all offence variables in rugby league, stable means were reached in less game quarters than in rugby union (Tables 4.7 and 4.8), vyith in some cases (1988-92) stable means being achieved atthe 5Yo level within a single game (Figure 4.8). For the comparative analysis in rugby union the means only stabilised atthe 5%o level within five games (Figure 4.9).Ir both Codes the means for the offence variables stabilised within the
24 game quarters, albeit less impressively for offloads in rugby union (Table 4.7).
Table 4.7 Number of game quarters to reach stable means to within +lyo (!5yo*,+lÙyo"*) of the overall mean for offence variables in rugby union
1988-92 1993-95 1997-99 2000-02
Total ball carries 14+* 6** 10** g*
Non-contact ball carries 14** l0* I l*,r, g**
Ball carries ending in successful I g*+ 17* l1* 5t' tackle
Pass frequency l4** 4',t ll** l4*
Oflloads 16** l4** 20** 19**
Total contact ball carries l4* g** g** 6*
86 Table 4.8 Number of game quarters to reach stable means to within +7yo (!5yo*, +10%'r'+) ofthe overall mean for offence variables in rugby league
1988-92 1993.95 1997-99 2000-02
Total batl carries 4* 18 20* 19*
Non-contact ball carries 8'l. 12* 20* l6*
Ball carries ending in successful 16 lg* lg* 20* tackle
Pass frequency '7* 5{' 17** l5*
Oflloads l0** 20* 18 16**
Total contact ball carries 16* 10* 18* 20x
t2 random order ofdata inputting. _data inputted in reverse I order.
i 5o/o of the mean I 11 q)É g o L Mean tu l1
- 5o/o of the mean 1
1
t..) O\OOTJHH- lJ f.') t\) Ot95O\oo ot.JÀ No. of game quarten¡
Figure 4.8 Normative profile for rugby league total ball carries 1988-92.
87 _ random inputting of dat¿. _ data imputed in reverse order.
+ 5% of the mean
(¿ Mean (l)T I l-r ¡-¡
€J L tr - 5% of the mean
5
40
N)NJN) Ot\)èO\æ O¡9È No. of game quarters
Figure 4.9 Normative profile for rugby union total ball canies 1988-92
Defence varíahles
For defence variables all means stabilised within the 24 game quarters at the TOYo level in both rugby union
and rugby league (Tables 4.9 and 4.10). Worthy of note here is the value of double line profiles for the single tackle results for rugby league in 2000-02 (Figure 4. l0). In this case the upper profile line stabilised to within
5% within ten game quarters, whereas the lower line of identical data, inputted into the data sheet in a
different order rezulted in the profile not stabilising until twenty-two game quarters.
Table 4.9 Number of game quarters to reach stable means to within +l%o (!5o/o*, +10%**) of the overall mean for defence va¡iables in rugby union
1988-92 1993-95 1997-99 2000-02
Total tackles 17* 12** 12* lg*
Single tackles l6** l9*'k 1g* l9'r'
Double tackles 10** 7** 14** 1g*
Mob tackles Did not stabilise Did not stabilise Did not stabilise Did not stabilise
88 Table 4.l0 Number of game quarters to reach stable means to within (!lyo,+syo*, +10%**) of the overall mean for defence variables in rugby league
1988-92 1993-95 1997-99 2000-02
Total tackles 16* gr( g* 72*
Single tackles 1g* g{, 8* l0**
Double tackles l4* lg* 1g* g*
Mob tackles 1g* l6* 20** 20**
55 _ random inputting ofdata. _ data imputed in reverse order.
45 c¡ É €) + 5o/o of the mean 40 q)5 L FI Mean 35 - 5Yo of the mean 30
25
Ì\) O)@r I J J tut\)N o l\) Ào)æ ONÈ No. of game quarters
Figure 4.10 Normative profile for rugby league single tackles 2000-02.
Gamc rctionvaria.bles
For both Codes stable means were achieved within 24 game quarters; however, for some variables the means
only stabilised at the 10% level (Tables 4.ll and 4.12)
89 Table 4.1 1 Number of game quarters to reach stable means to within (!lyo, +syo*, +l)yo**) of the overall mean for game action variables in rugby union
1988-92 1993-95 1997-99 2000-02
Ruck frequency 20** 6** 10* 5**
Maul frequency 77** 1g** lg* 20**
Activity/phase frequency 12* 10* g:r. 13*
Kick in play frequency 1g* 1g* 2l** 14**
Kick out of play frequency g** 12+* l6** l7**
All kicks in open play 77* l6* 2l** g*
Scrum frequency 7** l7** 7** l3*
Lineout frequency l0* l1* 17** I 1**
Table4.l2Numberofgamequarterstoreachstablemeanstowithin (tlyo,+syo*,+l0Yo**)oftheoverall mean for game action va¡iables in rugby league
1988-92 1993-95 1997-99 2000-02
Ruck frequency 20* 18* 18* 10*
Activity/phase frequency 20* 14* 1g* l0*
Kick in play frequency g** 14** 11** I 1**
Kick out of play frequency 20** 22** 22** 1g**
All kicks in open play 79** l7* lg* 1g*
Scrum frequency l7* 2l** 10{'* l6*{'
In both Codes of rugby the kick variables were the least stable, with the means for kicks in play in rugby union in 1997-99 and kicks out of play in rugby league (1993-95 and 1997-99) failing to stabilise within the
90 24Games Qua¡ters(Tables4.ll and 4.12).[n2000-02 theprofileforkickingoutof playinrugbyleague could not be determined due to the very low frequency counts ofthese actions in several games.
Posítional profiles
The number of games for the player profiles to stabilise (or not) for the hooker, no.8 (loose forward) and stand offin rugby union are presented in Tables 4.13 - 4.75 and in Tables 4.76 - 4.18 for rugby league.
In the professional Periods the use of squad numbers, multiple substitutions and players playing different positions in the same game made positional identifications very difficult. As a consequence no analysis was possible for the 1997-99 Period, and the 2000-02 analyses was based on six rather than twelve performances.
Table 4.13 Number of games for offence and defence variables to stabilise to within +5%o (*+l1o/o) of the overall mean for the hooker in rugby union games by Period
1988-92 1993-95 1997-99 2000-02
Possessions 4* 9t¡ 7* 2rr
Open play passes Did not stabilise Did not stabilise Did not stabilise Did not stabilise
Carries into contact Did not stabilise g+ 9* 6*
Oflloads Did not stabilise Did not stabilise Did not stabilise Did not søbilise
Total tackles 9{' 8tl' Did not stabilise 6*
Single tackles Did not stabilise Did not stabilise Did not st¿bilise 7*
Double tackles g* Did not stabilise Did not stabilise Did not stabilise
Mob tacHes Did not stabilise Did not stabilise Did not stabilise Did not stabilise
Missed tacHes Did not stabilise Did not stabilise 6* Did not stabilise
91 Table 4.14 Number of games for offence and defence variables to stabilise to within +syo (*+l0yo) of the overall mean for the no. 8 in rugby union games by Period
1988-92 1993-95 1997-99 2000-02
Possessions 7 8* 2* 6
Open play passes 6* Did not stabilise Did not stabilise Did not stabilise
Carries into contact Did not stabilise Did not stabilise Did not stabilise 8
Oflloads Did not stabilise Did not stabilise Did not stabilise 9
Total tackles 7't 9 7 9
Single tackles g* Did not stabilise Did not stabilise Did not stabilise
Double tackles Did not stabilise Did not stabilise 8* 8'¡
Mob tackles Did not stabilise g* Did not stabilise 7*
Missed tackles Did not stabilise Did not stabilise Did not stabilise Did not stabilise
Table 4.15 Number of games for offence and defence variables to stabilise to within +syo (*+l0yo) of the overall mean for the stand offin rugby union games by Period
1988-92 1993-95 1997-99 2000-02
Possessions 7 6 l0* 10
Open play passes 8't' 8¡t 9,É 2rr
Carries into contact Did not stabilise 10* 7* 1l
Oflloads l0 Did not stabilise 9 Did not stabilise
Kicls 8 8 Did not stabilise 9
Total tackles 6* 10 7* l0
Single tackles 6* l0 8 l0*
Double tackles Did not stabilise g* Did not stabilise l0
Mob tackles Did not stabilise Did not stabilise Did not stabilise Did not stabilise
Missed tackles Did not stabilise Did not stabilise Did not stabilise g*
92 Table 4.16 Number of games for offence and defence variables to stabilise to within +syo (*+l0yo) ofthe overall mean for the hooker in rugby league games by Period
1988-92 1993-95 1997-99a 2000-02
Possessions 8'l' 3:r Did not stabilise
Open play passes l0* Did not stabilise Did not stabilise
Dummy passes Did not stabilise 4 2
Carries into contact 8* Did not stabilise Did not stabilise
Oflloads Did not stabilise 7* Did not stabilise
Runs from dummy half 7* 9 Did not stabilise
Total tackles 5 5 5
Single tackles g{, 9:l' 5
Double tackles 6 6* 2*
Mob tackles l0 l0* 4*
Missed tackles 9 10* 3*
a Note: Analysis not possible due to player identification diffrculties
Table 4.17 Number of games for offence and defence variables to stabilise to within +5% (*+10%) of the overall mean for the loose forward in rugby league games by Period
1988-92 1993-95 1997-99a 2000-02
Possessions g* '1* Did not stabilise
Open play passes Did not stabilise 8* Did not stabilise
Dummy passes 9* 6:r. 4
Carries into contact 7* 7* Did not stabilise
Oflloads Did not stabilise Did not stabilise Did not stabilise
Kicks Did not stabilise Did not stabilise Did not stabilise
Total tackles 7 9 3*
Single tackles 9 4!r 3*
Double tackles 6 4* J
Mob tackles Did not stabilise 4* Did not stabilise
Missed tackles Did not stabilise 6't Did not stabilise
A Note: Analysis not possible due to player identification diffrculties
93 Table 4.18 Number of games for offence and defence variables to stabilise to within +syo (*+lOVo) of the overall mean for the stand offin rugby league games by Period
1988-92 1993-95 1997-99a 2000-02
Possessions 8 8 3*
Open play passes g* g* Did not stabilise
a Dummy passes 10'r' 9tr
Caries into contact 8 10* Did not stabilise
Oflloads Did not stabilise Did not stabilise 3'F
Kicks l0* Did not stabilise Did not stabilise
Total tackles 7 l0 4
Single tackles 9 4* Did not stabilise
Double tackles 7 10+ 2*
Mob tackles 10 l0* Did not stabilise
Missed tackles 7 9x' Did not stabilise a Note: Analysis not possible due to player identifìcation diffrculties
4.3 Discussion
4.3.1 Reliability
Tímevariables
In assessing the reliability of time variables in both codes of rugby football the use of the scatter plots
advocated by Hughes et aL (2002) and the calculated percentage agreements provided both a quantitative and visual representation of the accuracy of the system. The levels of agreement for all time variables in rugby league were shown to exceed 95%o, albeit requiring a second (modified) test for'play the ball' time. In this
case the use of the modified plots identified several extreme values (outliers). These were mainly positive values indicating that recorded times were lower in the second observation than the first observation. This was due to the time for completion of the 'play the ball' in the fÌrst observation being indicated by the
dummy half touching the ball and by the tackled player playing the ball (signiflred by placing his foot on the
ball) in the second observation. This was an operator error and was rectified merely by checking the stated
operational definition for this variable.
94 In terms of the level of agreement as a function of time engaged in the notational analysis, no increase in the difference between observations was noted (evidenced by no notable change in the scatter plot patterns
across time), indicating that the method employed to offset the effects of fatigue (analysing games in 20 min
periods) was successful.
In rugby union the main concern with regard to the intra-observer level of agreement was revealed to be in
results of the ruck time analysis . The 12Yo error found in this study was much greater than the initial 5.5%
error in the league code. This increased error may be due to three factors. Firstly, the more congested ruck
situation in rugby union makes clear identification of the precise tackle completion and subsequent
presentation of the ball more difficult, Secondly the number of observations in rugby union was much less
than in rugby league for the same tÌventy-minute period. In retrospecl it may have been more prudent to
observe a set number of rucks, ratherthan observe for a pre-determined period of play. Thirdly, the plot of
observation differences (Figure 4.2) shows clearly three extreme values (outliers), representing
approximately l0% (3/30) of the sample. Such extreme values in a small sample were likely to inflate the
obsewation error, particularly when expressing these data as percentages. The improvement in the percentage
agreement in the second reliability test is a demonstration of the improvement due to a 'learning effect'. This
highlights the need for analysts to test their system fully before embarking on full data collection.
I d e ntífi c atío n a nd fr equ en cy of v øriøb le s
In previous research using notational analysis (where a reliability study has been undertaken on key
variables) researchers have often presented their findings as a percentage agreement. These percentage scores
represent two features ofthe analysis:- the ability to identify the variable correctly and the ability to record
the frequency of these variables consistently. If researchers combine these aspects of the analysis it is
diffrcult to ascertain where the errors are in the system, and hence makes inferences on the validity of the
system more diffrcult. For example Hughes et al. (2002) presented the results of a comprehensive reliability
study on rugby union. Frequency data from t\ ro separate observations for several variables were reported;
however, where there were differences between the observations it was not made clea¡ whether these were
due to difficulties in identification or due to inconsistent counting and recording of the variables under
examination. In the same paper, Hughes et al. (2002) suggested that diffrculties may arise in identifying ruck
and mauls; therefore it is probable that the error they report for rucks was due to the different interpretations
of the operational definitions. The same was probably not true of the lineout and scrums since these set
pieces are more obviously defined; hence the differences were more likely due to counting errors. For the
95 other variables (pass, tackle and kick) the differences could be either due to inconsistent counting or identification problems, or both.
The results f¡om the variable identification reliability analysis in the present study indicated that there were diffrculties in distinguishing between joint tackles (two players tackling simultaneously) and assisted tackles (one main tackler being helped to complete the tackle). In addition, distinguishing between a single tackle and an assisted tackle was problematic, particularly in rugby league where players would often 'assist' when the tackle was complete or nearly complete, in order to slow the subsequent 'play the ball'. Both of these problems were rectified by modifying the original operational definitions. Whilst it is acknowledged that these'new' definitions still included some level of subjectivity, the subsequent re-analysis resulted in an improvement in the intra-observer level of agreement in both codes of rugby.
The level of agreement between observations for the frequency of all variables was greater than 95%. The observer level of error in tackles (4.4%), passes (4.0%), rucks/mauls (1.5%), and scrums (0%) is consistent with the score reported by Hughes et al. (2002), with the median percentage enor of 3.7Yo for iaclrJes,2.0Yo for passes, 4.0Yo for rucks, and ÙYo for scrums. For lineouts (0%) the percentage error is notably different from that reported by Hughes et al. (2002), the median score being 2.6%o. However, the error in lineout frequency was, according to these researchers, due to four ofthe operators recording a lineout which formed but did not take place.
Player ídentíficatían
In rugby leagu.e the level of agreement between observations was only below 95Yo for passing player identification (91.8%) and for the identification of how many players were involved in the tackle (94.6Yo).
The use of secondary identification characteristic and forward and backward tracking of players resulted in a notable improvement for passing player identifïcation (98 0%); however, this proved to be very time consuming, with games (on average) taking in excess of four hours to analyse. In one game, (\üigan v
Castleford, 1992), the lack of secondary identification characteristics for Castleford players meant the full game took over t hours to notate completely.
In rugby union the level of agreement between observations was less than in rugby league. According to
Hughes et al. Q002). in rugby union some observations are more difficult to make than others. This is particularly true of player identification, when players carry the ball into a congested area (double or mob tackle), carry the ball close to the rucldmaul on the blind side of the camera and most diffrcult when players
are engaged in the actual breakdown (rucks and mauls). In these cases the shirt number is often obscured form the vieq therefore, relying on this as the sole identification characteristic resulted in an error rate ofone
96 in ten for the offence variable analysis and one in five for the tackle analysis. Similar diffrculties were reported by James et al. (2005, p.9), who suggested that the 'camera angle... occasionally made the identification of players problematic.'
Further analysis ofthe tackle variable by tackle type revealed that the problem in identifying players was predominantly in the joint tackle (58.3% agreement) and the assisted tackle (75.0%). This was primarily due to the action after the tackle. Since most tackles result in a ruck or a maul forming, and often occur close to the breakdown, sometimes on the blind side, identification is hindered by the melee of players. Whilst the modified system using slow motion/freeze frame, secondary identification oharacteristics and tracking resulted in an improved level of agreement for the double tackle, this was less than the similar agreement in rugby league Qa%) nd still represented an unacceptably high observation error. This difference in the level of agreement between the codes was due to the ruck and maul in rugby union making forward tracking of players impossible, and meant only back tracking could be used. This process was also very time consuming, taking (on average) between six to eight hours per game.
The modified system was used in the second analysis of rucks and maul, as a result of the poor level of agreement for player identification and the number of players engaged in the breakdown. The initial levels of agreement for player identification in offence and defence rucks were 8O4% and 85Yo, respectively. The improvement in the subsequent re-analysis (Table 4.4) was greater for defending player identification than for offence identifÌcation, possibly due to less defending players being involved in the breakdown making systematic identification much easier. With larger numbers of players involved in offence, and usually moving at speed into the contact (ruck), the identification was much more diffrcult. The difficulty of analysing the breakdown was further highlighted by the very low level of agreement for identifying player numbers, initially only 50.0% for attacking players and 46.4Yo for defending players. Whilst re-analyses using the modiflred system improved the agreement, there was slill a l2Yo error for defending player number identification. This was ostensibly due to difficulties in clearly identifying whether or not players were in the ruck or maul. Even with the improved operational defìnition, there was still a relatively large lçvel of
subjectivity with this type of analysis.
Such low levels of agreement between observations for both player identification and player numbers in the ruck and maul does cast some doubts of the validity of the findings reported previously, particularly those that present player profiles. Hughes and White (1991) not only identified players in the ruck and mauls, but also claim to have successfully identified the order in which players arrived at the breakdown. Unfortunately, whilst these authors addressed the reliability of their system, it was not as Hughes et al. (2002) suggested
'examined to the same depth of analysis of the data processing'. Similarly, Parsons and Hughes (2001)
97 reported extensive player profiles for International, European and Domestic games. Again the level of reliability analysis was basic, merely stating the system was tested, but no results of this analysis were presented or commented upon. This once more casts doubts on the validity of the reported findings.
James e/ al. Q005, p.9) reported intra-observer reliability assessment was undertaken on all the variables they examined in their work on positional profiles, and whilst they highlighted there were some problems associated with player identification in their discussion, they failed to address an important aspect of the reliability analysis- player identification. This is somewhat perplexing, since they stated clearly 'these (player identification) difficulties inevitably add to the error associated with this type of analysis and reinforce the need for ... adequate reliability measure to aid inferences.'
The frndings of the present study clearly reveal the problematic nature of notating players in rugby union, and its impact on the reliability of such systems. Even using a very systematic approach, slow motionlfreeze frame, tracking, and secondary player identification cha¡acteristics the associated error can still exceed l0olo for the breakdown situation. This relatively poor level of agreement is compounded by the fact that in some cases player identification is impossible. In no previous publication has this issue been identified or discussed; therefore, it is not clear whether or not the player identifications (in previous studies) were based on a 'best guess' approach or whether the unidentifïable players were discounted from the subsequent analyses.
Døía handling and processìng
One of the problems associated with hand notation systems is that for detailed analyses the data have to be transcribed from the original data recording sheet into the computer spreadsheet. In using hand notation systems to collect the data and computer system to process the data, the problem oferrors due to transferring these data into the computer must be considered. The larger the data set, the greater the chance of incuning inputting errors. The results of the ruclc/maul analysis in the present study indicated that in transcribing over
2000 data the inputting was seemingly 99.9Yo accurate. However, as Hughes el al. (2002) conectly suggested, using processed data rather than raw data can result in inflated levels of agreement. In retaining the sequentiality of the data and accounting for missing data, the true level of error in the present study was identifred as slightly less than 5%. V this inputting error is added to the identification and frequency reliability error level, then the overall error level in recording and processing these data becomes notably higher. To reduce the inputting error, all data were input into the spreadsheet twice. This enabled any errors to be easily identifìed and rectifred. Since these errors have not been previously reported in studies using
98 hand notation in rugby football, it must be assumed that this potential error in the process was ignored, and as such may have impacted on the accuracy of the reported findings.
4.3.2 Normative profiles
The importance of assessing a data set to establish whether a normative profìle has stabilised cannot be understated. This enables an appraisal ofwhether sufficient games have been analysed for the variable means to be considered representative of the 'population' . Hughes, Evans el al. QAO\ suggested that the normative profile should stabilise within a pre-determined and set'limit of error'- usually SYoto l}Yo - otherwise the data should not be considered representative. Hughes, Evans et al. (2O01) provided a good example based on two previous studies, Hughes el al. (1997) and Marshall and Hughes (2001). Ma¡shall and Hughes (2001) demonstrated that in their assessment of elite women's rugby the variables under analysis stabilised within three to seven games. This, according to Hughes, Evans et al. (2001, p. 23) challenged the inferences made in an earlier study by Hughes et al. (1997) which examined only five games. Hence, the findings reported in this study 'may not be a true representation of elite women's rugby'.
It must be noted that the number of games identified by Hughes, Evans et al. Q00l) are based on frequencies derived from a single line normative profile. However, this type of plot does not account for the effect of the sequence of data inputting, hence, the use of a double line plot (the second line based on a random input of the original data) is deemed more appropriate. The importance of using the double line profile rather than the single line is highlighted by the single tackle results for rugby league in 2000-02
(Figure 4.10). In this case one of the profile lines stabilised (5% limit of error) within ten game quarters, whereas the second profrle based on the same data inputted into the data sheet in a different order, resulted in the profile not stabilising until twenty-two game quarters. Had the initial normative profile been used to identi$ the appropriate game frequency then it would have been incorrectly noted that the data were representative within two and a half games rather than the more correct six games. This demonstrates the importance of using a double line profiling system rather than the single line profile.
The adoption of the double line normative profiles to assess offence and defence variables in the current study in both codes of rugby resulted in the profiles stabilising for all variables (except mob tackles in rugby union) within six games. The profiles for the mob tackle in rugby union were difficult to produce due to very low frequency counts in this variable in all Periods, even when adopting a lÙYo limit of error. A similar outcome was evident in the normative profiles for player position data, in that for many positions low frequency counts and large inter-player variability meant that the profiles for certain variables failed to
99 stabilise within the twelve performances analysed (Tables 4.13 - 4.18). In rugby union this was particularly evident in the defence variables and offloads for all th¡ee positions. However, the profiles did change notably across the four Periods. For example, the kick frequency for stand offs in 1993-95 stabilised within two games (10% level of error), but failed to stabilise within twelve games in the following Period. Likewise, the frequency of missed tackles by the hooker could not be deemed representative in any Period except 1997-99.
Simila¡ trends in the data were evident in rugby league, although exact comparisons across the Periods are more diffrcult since no profile could be formed for the 1997-99 Period and those for 2000-02 were based on only six games (due to player identification diffrculties).
The current study has clearly identified that the relative stability of normative profìles for all types of variables in both codes of rugby and has clearly identifred how these profiles for all types of variables (time, offence, defence, game action, position profiles) fluctuate across time. In addition, the in-depth analyses of profiles across the Periods presented here are extremely imporlant as they will act as a guideline to identify whether or not comparisons to previous research can be made (based on whether previous data are representative). In the field of notational analysis no previous studies (even those presenting normative profiles) have highlighted the potential problems of comparing their results to other studies in which no indications were presented of how many games should have been assessed to ensure that the normative profiles were stable.
4.4 Summary
The objectives of this study were to establish a framework for intra-operator reliabilþ and identify normative profiles for key time, offence, defence, game action and positional profiles in rugby union and rugby league football between 1988 and 2002.
For the in-depth analyses of all variables there were several initial concerns (Table 4.19). Amendments to operational definitions, the use of slow motion analysis, forward and back tracking of players and using
secondary identifìcation characteristics resulted in improved level of agreements in all variables in the
subsequent tests. However, an unacceptably high enor level was still apparent for the recording of the number of players in rucks and mauls. Moreover, the error level for the identifrcation of players in ofFence rucks and mauls also exceeded 5% (Table 4.19). It was therefore concluded that due to the low level of
100 reliability associated with profïling the breakdown situation in rugby union no such profiles would be subsequently presented.
Table 4.19 Summary of problematic intra-observer reliability analyses and the effect of subsequent amendments to systems
Problematic variable (Code) Initial 7o Amendment(s) Final %o Agreement agreement
Ruck time (rugby union) 88.0 Modified operational definition 95.5
Tackle type identification 84.6 Modified operational definition 98.8 (rugby league)
Tackle type identification 86.7 Modified operational definition 100.0 (rugby union)
Player identification in 89.9 Slow motior/freeze frame, secondary 100.0 offence actions (rugby union) identification characteristics and forward and back tracking
Player identification in 83.5 Slow motion/f¡eeze frame, secondary 93.7 offence rucks/mauls (rugby identification characteristics and forward and union) back tracking
Player identification in 85.0 Slow motior/freeze frame, secondary 100.0 defence rucks/mauls (ru gby identifi cation characteristics and forward and union) back tracking
Player identification in the 80.4 Slow motion/freeze frame, secondary 94.1 tackle (rugby union) identification characteristics and forward and back tracking
Player identification for 91.7 Slow motion/freeze frame, secondary 95.2 passing (rugby union) identifi cation characteristics and forward and back tracking
Player identification for 91.8 Slow motior/freeze frame, secondary 98.0 passing (rugby league) identification characteristics and forward and back tracking
No. of players in offence 50.0 Slow motior/freeze frame, secondary 96.0 rucks/mauls (rugby union) identification characteristics and forward and back tracking
No. of players in defence 46.4 Slow motion/freeze frame, secondary 88.0 rucl¡s/mauls (rugby union) identifìcation characteristics and forward and back tracking
No. of players in the tackle 86.7 Slow motion/freeze frame, secondary 100.0 (rugby union) identification characteristics and forward and back tracking
A further problem associated with computer analysis of hand notation data was the error associated with transferring data from the notation recording sheet into the computer spreadsheet. To overcome this problem all data were inputted twice and the 'compute' function in SPSS used to identi$ where the inputted
101 differences were. Once these differences \ryere identified they were checked against the original notation
sheet and the spreadsheet amended accordingly.
In both codes of rugby whist normative profiles for all time, offence, defence and game action variables stabilised within six games. The same, however, was not true for positional/player profiles. For the most part the proñles failed to stabilise within the number of performances analysed. One approach to dealing with this problem would be to analyse more games, however, due to the limited full game footage available for rugby league this was not possible. Further problems with the analysis of rugby league were that players often changed positions during the game, frequent interchanges took plaoe off camera and the use of squad numbers (in the professional era) made positional identification extremely diffrcult. The result of these problems was that profiles could only be established based on six games in 2000-02 and no positional profile could be identified for the 1997-99 Period.
Considering the poor positional profile stability in both codes of rugby and the identification problems inherent in rugby league in the professional periods no positional profiles were subsequently presented since it could not be stated unequivocally that such profiles were representative of playing positions in any of the four periods in either code of rugby. However, a framework for intra-operator reliability and normative profiles for key time, offence, defence, and game action variables in rugby union and rugby league football between 1988 and 2002 was established. As a consequence, full game profiles (Chapter 5) and performance indicator profiles were undertaken (Chapter 6).
r02 CIIAPTER 5 GAME PROFILES
5.1 Introduction 104 s.2 Summary data 105
5.3 Statistical analyses 118
5.3.1 Total ball in play time 118 5.3.2 Ruck time ttg 5.3.3 Total rucktime 120 5.3.4 Activity time 122 5.3.5 Total activþ time 123 5.3.6 Set possession time 124 5.3.7 Continuous possession time t2s 5.3.8 Continuous ball in play time 127 5.3.9 Total ball carries 128 5.3.10 Passing 130 5.3.11 Ball carries into contact 13ó 5.3.12 Tackle attempts 139 5.3.13 Tackle type 140 5.3.14 Tackle erroñ t47 5.3.15 Lineouts 150 5.3.16 Kicking 150 5.3.17 Rucks and mauls 156 5.3.18 Scrums 1s8 5.3.19 Set possessions 160 5.3.20 ActivityÆhases t62
5.4 Discussion L64
5.4.1 Total ball in play time 164 5.4.2 Ruck time t67 s.4.3 Activity time 169 5.4.4 Set possession time 170 5.4.5 Continuous possession time 173 5.4.6 Continuous ball in play time 173 s.4.7 Total ball carries r74 5.4.8 Passing 175 5.4.9 Ball carries into contact 178 s.4.10 Tackle att€mpts 179 5.4.11 Tackle type 182 s.4.12 Tackle errors 184 5.4.13 Lineouts 186 5.4,14 Kicking 18E 5.4.15 Rucks and mauls 190 5.4.16 Scrums 192 s.4.17 Set possession 193 5.4.1E Activity/Phases 194
5.5 Summary 195
Note: Some of the data from this chapter wero published in Eaves, S. and Hughes, M, (2003). Pattems of play in international rugby wrion teams before and after the intoduction of professional status. Intemational Joumal of Pedormance Analysìs in Sporl, 3(2),103-111 and
Eaves, S. J., Hughes, M. D. and Lænb, K.L. (2m5). The impact of the introduction of professional playing status on game action variables in intemational nolhem hemisphere rugby union football. Intematiotwl Joumal of Perþrmance Anaþsis in Sport, 5Q), 58-86.
103 5.1 Introduction
To establish whether the games of rugby union and rugby league are becoming more similar full profiles of both codes of rugby need to be developed so that comparisons rnay be made. Whilst for rugby union it may be possible to construct profiles based on daø from previously published studies, there a¡e several concems with adopting this approach. It is still conìmon for researchers presenting rugby union profiles to omit presenting reliability analyses (Boddington & Lambert, 2004; Sayers & Washington-King, 2005) or present a percentage agreement for the whole system rather than for individual variables (Long & Hughes, 2001; Martin et a1.,2001).
In additioru few studies Qlughes, Kitchen et al., 1997 Jamæ et al., 2OO5 Marshall & Hughes, 2001 ; Parsons er al., 2001 Vivian et al., 2001) have sought to identifu how many games should be analysed to ensure that the profile has stabilised. It is therefore important to develop game profiles for rugby union which are based on data which have been proven to be both reliable and where the means of the variables under examination have stabilised. In contrast to rugby union no game profiles have yet been published for rugby league, hence, there is also a need to develop these profiles which are also based on reliable and stable data.
The in-depth analysis of both systems reliability and normative profiles in the present study (Chapter 4) has demonstrated that the systems for collecting time data, offence data, defence data, and game action data to be reliable and to st¿bilise within six full games. As such, these systems were deemed appropriate to enable the collection of data and the subsequent construction of time, offencg defence and game action profiles for both rugby union and rugby league.
The objective of this study was úo construct longitudinal time, offence, defenoe and game action profiles for rugby union and rugby league in four periods spanning 1988 and 2002 and to assess the impact ofkey factors on these proflrles which may have resulted in a converging of the codes.
t04 5.2 Summary data
Tables 5.1 and 5.2 present the summary data for the mean time variables by Period and Era and percentage change in mean time variables across the Periods. The summary data for the mean frequencies of offence and defence variables by Period and Era, the percentage change in frequencies across the Periods and the frequencies normalised to time are presented in Tables 5.3,5.4 and 5.5, respectively. Tables 5.6, 5.7 and 5.8 present the summary data for mean game action variables by Period and Era, the percentage change in the frequencies across the Periods and the frequencies normalised to time, respeotively.
105 Table 5.1 Code comparison for time variables by Era and Period (mean +SD)
RugbyUnion Rugby League
1988-92 1993-95 1997-99 2000-02 Pre- Professional f988-92 1993-95 1997-99 2000-02 Pre. Profession¿l professional Era professional Era Era Era
Rucktime (s) 2.74 3.30 3.t2 3.07 3.02 3.10 4.56 3.72 3.28 3.65 4.74 3.47 (0.20) (o 32) (0.21) (o ls) (0.38) (0.18) (0.28) (0.47) (0.1e) (0.18) (0.s8) (0.26)
Total ruck time 169.2 256.5 389.9 469.1 212.9 429.5 1123.8 884.2 862.s 840.4 1004.0 851.4 (s) (s4.8) (M.3) (86. l) (6s.7) (6s.e) (83.e) (66 r) (1s3.0) (17s.e) (130.2) (168 2) (148.1)
Activity time (s) 6.72 6.07 5.82 5.74 6.39 s.78 5.s2 s.9t 5.s8 5.88 5.72 5.73 (0.42\ (0.30) (0.3e) (0.36) (0.4e) (0.36) (0. l2) (0.26) (0.22\ (0.32) (0.28) (0.30)
Total activity 1104.3 I108.7 1233.5 1373.4 1106.5 1303.5 1862.8 t933.2 r983.6 1846.5 1898.0 1905.0 o\ time (s) (10r.0) (63.7) (r7o.2) (87.8) (80.6) (r73.e) (1e7.7) (130.4) (220.6) (176.8) (163.4) (207.s)
Set possession 10.0 l0.s 14.4 16.4 10.3 t5.4 36.5 38.1 36.7 36. I 37.3 36.4 time (s) (0.8) (0.7) (2.0) (1 3) (0.78) (1.e5) (3 l) (2.s) (2.e) (3.8) (2 8) (3.2)
Continuous 15.6 13.8 20.9 23.3 14.7 22.1 49.2 55.3 47.1 55.5 52.2 51.3 possession time (2.r\ (1.7) (3.0) (1.5) (2.r) (2.6) (2 l) (3 6) (r.2> (s 8) (4.2) (6.0) (s)
Total ball in play 7273.5 1365.2 1623.5 1842.s 1319.4 1733.0 2986.6 2817.4 2846.1 2666.9 2902.0 2756.5 time (s) (t41.2) (85.e) (227.3) (221.6) (t21.3) (242.7) (2s2.2) (236.7) (383.2) (288.6) (24e.4) (336.7) RugbyUnion Rugby League
1988-92 1993-95 1997-99 2000-02 Pre Professional 19t&92 199395 1997-99 2000-02 Pre Profession¡l professional Era professional Era Era Era
Continuous ball t3.2 13.8 20.6 25.6 13.5 23.1 68.3 67.7 62.9 61.6 68.0 62.3 in play time (s) (1.s) (0.e) (2.s) (3.6) (r.2) (4.0) (13.8) (r3.2) (l r.4) (10.4) (12.7) (10.4)
Percentage brll 25.s 26.9 3r.9 35.0 26.2 33.5 60.3 55.0 58.0 55.6 57.6 56.8 in play time (2.8) Q.2) (4 3) (3.s) (2.s') (4.1) (s l) (4 6) (8.7) (6 0) (s 4) Q.3)
\ìO Table 5,2 Percentage change (o/o|)in mean time variables betweenPeriods by Code
7o between 198& %oÅ between 1993 7o between 1997- %o across all 92 and 199&.95 95 and 1997-99 99 and 200lù,02 Periods
Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby union League union League union League union League
Total ball in 7.2 -5.7 18.9 1.0 13.5 -6.3 44.7 -t0.7 play time
Ruck time 20.4 -18.6 -5.s -11.6 -1.6 1 1.3 12.0 -20.0
Total ruck time 51.6 -21.3 51.7 -2.5 203 -2.6 177.2 -25.2
Activity time -9.7 7.1 -4.t -5.6 -t.4 5.4 -14.6 6.5
Total activity 0.4 3.8 11.3 2.6 11.3 -6.9 24.4 -0.9 time
Set possession 4.6 4.4 35.4 -3.7 13.6 -1,6 64.0 -1. I time
Continuous -l1.5 6.1 5t.4 -14.8 I1.5 17.8 49.4 t2.8 possession timc
Continuous ball 4.5 -0.9 49.3 -7.t 24.3 -2.1 93.9 -9.8 in play time
108 5.3 Code comparison for offence and defence variables by Era and Period (mear¡ median, (range))
Rugby Union Rugby League
t98t-92 1993-95 1997-99 2000-02 Pre. Professional 1988-92 1993-95 1997-99 2000-02 Pre. Professio professional Era professional nal Era Ira E¡:l¡
Total ball 244.3 253.2 315.5 37r.8 248.8 343.7 455.5 441.7 473.0 425.5 448.6 449.3 carries 247.0 246.5 307.0 378.0 246.5 359.0 465.0 446.0 459.0 4l1.5 449.5 432.0 (t94 -2e2) Q4t-282) (248-392) (3 l8-4lo) (194-292) (248-410) (400-47e) (402474) (39e-s46) (384-482) (400-47e) (384-546)
Dummy 53.5 62.5 88.2 t23.5 58.0 105.8 2t5.5 223.0 243.8 213.3 219.3 228.6 /scrum 50.5 63.0 80.5 t 33.0 s6.5 t06.5 2t5.5 222.0 242.s 207.5 216.s 2r9.0 (se-147) (203-281) (200-235) (183-243) (200-281) half passes (45-70) (ss-72) (se-126) (86-t47) (4s-72) (183-248) (207-240)
Open play t22.8 132.0 t42.8 t76.8 r27.4 159.8 149.5 141.8 148.3 129.2 r45.7 138.8 passes I t8.0 t 33.5 141.5 169.5 r 24.0 t64.0 149.0 142.0 I s7.0 t28.0 t44.5 t28.5 (87-t62) (tt4-t4e) (tt4-t77) (r58-202) (87-t62) (r44-202) (135-r68) (133-150) (1 l5-le3) (r 13-148) (r33-168) (1 l3-193)
Oflloads 32.8 20.8 3t.7 29.3 26.8 30.5 35.2 31.8 27.5 29.7 33.5 28.6 O 32.5 20.0 27.5 29.0 25.5 27.5 33.0 31.0 25.5 27.5 33.0 26.0 \o (244s) (r4-27) (17-s7) (2r40) (1445) (t7-s7) (25-50) (1e43) (22-34) (2244) (le-50) (le-50)
Oflload to 25.2 16.2 16.6 14.5 20.7 15.8 I1.4 10.5 8.6 l0.l 11.0 9.3 contact 23.5 I5.7 15.4 t4.3 22.2 15.3 10.8 I0.l 7.6 9.7 t0.8 8.8 percentage (22.t-34.4) (tL.e-22.3) (r2.t-2s.e) (10.7-18.5) (l1.9-34.4) (r0.7-2s.e) (8.3-14.6) (6.7-13.9) (7.1-ll.e) (7.3-12.8) (6.7-14.6) 7 t-r2.8
Pop passes 9.1 5.2 7.5 5.0 7.2 6.3 N/A N/A N/A N/A NiA N/A 8.5 5.5 8.5 4.5 7.5 6.3 (3-16) (l-e) (o-13) (0-l 1) (l-16) (0-13)
Total 209.2 2t5.3 262.7 329.7 212.3 296.2 400.2 396.7 4r9.7 37r.7 398.4 395.9 passes 2t2.5 216.5 241.5 339.0 216.s 3t 1.0 405.0 401.5 404.0 370.0 405.0 384.5 (158-254) (200-23 1) (202-346) (286-373) (158-2s4) Q02-373 (3sl-430) (36s-419) (3s3-4ee) (336-412) (351430) (336-4ee)
Total 121.5 721.2 172.',| 195.0 12t.3 183.8 306.0 299.8 324.7 296.3 302.9 310.5 carries into I I7.s 121.0 172.0 198.5 1T7.5 188.5 305.0 300.5 335.0 288.0 302.5 3l1.0 contâct (100-lss) (l0s-r33) (t34-2ts) (rss-216) (100-lss) (t34-216) (260-342) (26e-331\ (271-367) (2sl-345) Q6o-342) (2st-367) Rugby Union Rugby League
198&92 1993-95 1997-99 20m42 Pre. Profession 1988-92 1993-9s t997-99 2W042 Pre- Profession profeseíonal al Era professional al Er¿ Er¡ Ere
Contact to 50.0 47.9 54.8 52.4 48.9 53.6 67.t 67.8 68.8 69.5 67.5 69.2 carry 48.9 47.2 5i.9 5 t.5 47.4 5i.7 66.0 67.6 67.1 70.9 66.9 69.3 percent (44.s-s6.2) (43.2-s3.4) (51.4-60.8) (58.6-58.8) (43.2-s6.2) (s 1.4-60.8) (64.3-7r.7) (65.7-69.8) (64.7-7s.s) (62.9-73.t) (64.3-7r.7) (62.9-7s.5)
Total tacHe t23.2 1t7.5 r72.2 197 5 t20.3 184.8 353.7 362.2 362.s 322.7 3s8.0 342.5 attempts 123.0 I t6.5 177.5 202.5 I18.0 198.5 35 3.5 363.5 368.0 i13.0 357.5 335.5 (83-166) (105-14l) (t3e-20e) (15 1-228) (83-166) (t3e-228) (283-4t6) (330-392) (313-407) (280-382) Q834t6) Q80-407)
Total ttt.7 105.2 156.8 t82.2 108.4 169.5 312.3 304.3 327.3 29t.5 308.4 309.4 successful I10.5 101.0 159.0 t85.5 101.5 t69.5 308.5 305.0 333.5 286.5 307.5 302.0 tacHes (78-lsl) (96-134) (r25-r99) (14l-21 l) (78-15 1) (r25-zrt) (260-356) (26s-337) (2u-370) (2s6-332) (260-356) (2s6-370)
Single 75.7 76.8 rt2.0 r25.5 76.3 I18.8 r52.8 150.8 154.5 I18.2 151.8 136.3 tackles 72.5 72.0 tr1.0 127.0 72.s 114.0 16t.5 157.0 158.0 I17.0 161.5 t 35.0 (54-100) (68-l03) (e0-148) (e3-150) (54-103) (e0-150) (120-180) (l l9-r85) (133-l7r) (89-ls3) (l re-l8s) (8e-l7l)
Double 31.8 24.8 42-0 52.7 28.3 47.3 t33.7 t29.3 t47.0 147.3 131.5 147.2 tackles 34.0 24.0 45.5 53.0 27.0 50.0 13t.0 t28.5 146.5 147.0 t29.5 147.0 (2t4s) (21-30) (27-st) (44-61) (2t4s) (27-6r) (1 l3-156) (l 14-1,+4) (t27-t68) (120-l6e) (l 13-ls6) (t20-169)
Mob tackles 4.2 3.5 2.8 4.0 3.8 3.4 25.8 24.2 25.8 26.0 25.0 25.9 4.5 3.0 3.0 4.0 4.0 4.0 24.0 23.5 26.0 28.5 23.5 26.5 (2-6) (1-8) (l-5) (0-7) (l-8) (0-7) (2r-36) (t7-32) Q0-34) (t4-34) (t7-36) (14-34)
Missed 11.5 12.3 15.3 15.3 11.9 15.3 41.5 57.8 35.0 3t.2 49.7 33. I tackles 11.0 t2.0 16.0 j,5.5 12.0 15.5 43.5 57.0 35.0 29.0 5s.5 33.5 (3-2t) (7-18) (r0-le) (10-21) (3-2t) (10-21) (23{,0) (46:n) (2643) (20-50) (23-7r) (20-50) Table 5.4 Percentage change (%A) in the frequency of offence and defence variables by Period by Code
7o between oá between 7oÅ between 7oÀ across all 1988-92 and 1993-95 and 1997-99 a;nd Periods 1993-95 1997-99 2000-02
Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby union league union league union league union league
Total ball 3.6 -3.0 24.6 7.1 17.8 0.3 s2.2 4.1 carries
Dummy 16.8 3.5 4r.t 9,3 40.O -12,5 130.8 -1.0 /scrum half pssses Open play 7.5 -5.2 8.2 4.6 23.8 -12.9 44.0 -13.6 passes
Oflloads -37.5 -9.7 54.6 -13.5 -7.6 8.0 -10.7 -15.6
Oflload to -35.7 -7.9 2.5 -18.1 -12.7 17.4 -42.5 -t1.4 contact %o
Pop passes 42.e N/A 44.2 N/A -33.3 N/A -4s.1 N/A
Total passes 2.9 -0.9 22.0 5.8 25.5 -11.4 57.6 -7.1
Total carries -0.3 -2.0 42.5 8.3 12.9 -8.7 60.5 -3.2 into contact
Contact to -4.2 1.0 14.4 1.5 -4.4 1.0 4.8 3.6 carry percent
Total tackle -4.6 2.4 46.6 0.1 r4.7 -11.0 60.3 -8.8 attempts
Total -5.8 -2.6 49.0 7.6 16.2 -10.9 63.1 -6.7 successful t¡ckles Single tackles 1.5 -1.3 45.8 2.5 t2.t -23.5 65.8 -22.6
Double tackles -22.0 -3.3 69.4 13.7 25.5 0.2 65.7 t0.2
Mob tackles -t6.t -6.2 -20.0 6.6 42.9 0.8 -4.8 0.8
Missed tackles 7.0 39.3 24.4 -39.4 0.0 -10.9 33.0 -24.8
111 Table 5.5 Offence and defence variable frequencies per unit possession time by Era and Period by Code (frequency/min ball in play, mean time (secs) between actions)
19E8-92 1993-95 Preprofessional 1997-99 2000-02 Professional Era Era
Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby union league union league union league union league union league union league
Total ball I1.5 9.2 11.1 9.4 t 1.3 9.3 tt.7 10.0 12.2 9.5 I1.9 9.8 carries 5.3 6.5 5.4 6.4 5.3 6.5 5.2 6.0 4.9 6.4 5.1 6.2
Dummy 2.5 4.3 2.8 4.8 2.6 4.6 3.2 5.1 4.O 4.8 3.6 5.0 /scrum half 24.0 I3.8 22. I 12.6 23.1 I3.2 19.2 I1.7 15.2 12.7 17.2 r2.2 passes Open play 5.8 3.0 5.8 3.0 5.8 3.0 5.3 3.1 5.8 )a 5.5 3.0 passes 10.7 20.0 10.4 19.9 10.6 20.0 I1.5 19.9 10.4 21. I I1.0 20.5
N) Oflloads 1.5 o.7 0.9 0.7 1.2 0.7 1.1 0.7 1.0 o.7 1.1 0.6 40.0 89.0 70.2 9s.5 5s. I 92.2 57.1 106.6 67. I 94.7 62.1 100.6
Total passes 9.8 8.1 9.5 8.5 9.7 8.3 9.6 8.9 10.8 8.3 10.2 8.6 6.2 7.4 6.4 7.1 10.9 6.3 7.3 6.8 5.6 7.3 5.9 7.0
Total carries 5.7 6.2 5.3 6.4 5.5 6.3 6.4 6.9 6.4 6.6 6.4 6.7 into contact 10.5 9.7 I1.s 9.4 10.9 9.6 9.5 8.8 9.5 9.2 9.5 9.0
Total tackle 5.7 7.1 5.2 7.7 5.5 7.4 6.4 7.7 6.5 7.3 6.4 7.5 attempts 10.6 8.5 r 1.7 7.8 I1.2 8.1 9.5 7.8 9.4 8.3 9.4 8.1
Total 5.2 6.3 4.6 6.5 4.9 6.4 5.8 6.9 6.0 6_6 5.9 6.7 successful I1.6 9.6 I3.I 9.3 12.4 9.4 10.5 8.7 10.2 9.2 10.3 8.9 tackles 19t8-92 1993-95 Preprofessional 1997-99 2üXt-02 Professional Era Era
Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby union league union union league union leaguc union league union league
Single teckles 3.6 3.1 3.4 3.2 3.5 3.1 4.r J.J 4.t 2.7 4.1 3.0 I7.T 19.8 I8.I 19.0 17.6 19.4 14.7 18.4 14.9 23.2 14.8 20.8
Double tackles 1.5 2.7 1.1 2.8 1.3 2.7 1.5 3.1 1.7 3.3 1.6 3.2 41.9 22.4 56.1 21.9 49.0 ))) 40.1 19.4 35.1 18.2 37.6 18.8
Mob tackles 0.2 0.5 0.2 0.5 0.2 0.5 0.1 0.5 0.1 0.6 0.1 0.6 344.2 I T9.9 707.9 122.3 526.0 I2].1 857.6 111.6 400.9 II].2 650.0 11T,4
Missed tackles 0.5 0.8 0.5 1.2 0.5 1.0 0.6 0.8 0.5 0.7 0.5 o.7 (, 170.1 82.1 124.2 49.8 141.7 65.9 I I2.I 83.9 129.7 92.2 120.9 88.1 5.6 Code comparison for game action variable frequencies by Era and Period (mean, median, Gange)
Rugby Union Rugby League
1988-92 199195 1997-9 20lÙlùÆ,2 Pre- Professional 1988-92 199!95 1997-99 2O{ùlÙ-¡O2 Prç Profession professional Era profession al Era Era al Era
Lineouts 43.5 49.7 29.3 32.0 46.6 30.7 N/A N/A N/A N/A N/A N/A 4t.0 47.5 29.5 33.0 47.0 32.0 (37-ss) (41-62) (te-37) (27-34) (37-62) (re-37)
Kicks - in 28.3 39.5 31.0 32.0 33.9 31.5 30.2 27.2 27.8 29.0 28.7 28.4 play 28.5 4t.0 35.5 32.0 30.0 34.5 3l.s 28.0 28.5 30.5 29.s 28.5 (21-37) (23-s4) (t343) (26-38) (21-s4) (2643) (21-34) (18-34) Q0-35) (l 8-38) (18-34) (18-38)
Kicks - out 28.5 3r.2 15.3 20.2 29.8 17.8 7.3 4.7 5.8 1.3 6.0 3.6 ofplay 29.0 32.0 t4.5 20.0 30.5 r9.5 7.5 4.0 5.0 1.0 6.0 2.5 Q3-33) (22-39) (rt-2t) (t4-2s) Q2-3e) (l l-25) (4-e) (2-10) (3-l 1) (r-2) (2-10) (1-l l)
Kicks - total 56.8 70.5 46.3 52.2 63.7 49.3 37.s 31.8 33.7 30.3 34.7 32.0 5 58.0 73.5 50.0 50.5 60.0 50.5 38.0 32.5 34.5 31.5 36.5 34.5 (5r-60) (56-82) Qe-64) (48-58) (5 l-82) (2e-64) (2843) (22-38) Q440) (le-3e) Q243) (re4o)
Rucks 43.7 61.8 r07.7 t37.7 52.8 t22.7 261.s 2s3.2 279.2 245.0 2s7.3 262.1 39.5 62.5 1j,8.5 t41.5 54.0 120.5 261.0 246.0 284.s 245.5 256.5 256.5 (36-70) (50-71) (82-r22) (l l0-161) (36-7t) (82-l6l) (215-30r) (238-283) (23s-3t7) (206-278) (2ls-301) Q06-317)
Mauls 27.5 24.3 19.5 16.3 2s.9 17.9 N/A N/A N/A N/A N/A N/A 27.5 2 t.5 19.0 15.5 24.5 17.5 Q0-33) (18-41) (1 r-28) (10-23) (184r) (10-28) Rugby Union Rugby League
198&92 1993-95 t997-Ð 20lÙlù4.2 Pre Professionel 1988-92 199395 lÐ7-99 2lùlùlÙ4.2 Pre Profession professional Era profession al Era Era al Era
Scrums 33.0 26.0 30.5 25.5 29.5 28.0 19.8 17.o 18.8 14.0 18.4 16.4 33.0 27.5 31.0 25.0 28.5 29.5 20.5 18.0 r8.0 t4.0 20.0 17.0 Qs4s) (15-33) (2r-37) (20-33) (1545) (20-37) (13-25) (e-24) (15-23) (ll-17) (e-2s) (rr-23)
Set t27.0 13t.7 I15.0 114.2 t29.4 I14.5 82.2 74.7 77.8 75.5 78.4 76.7 possession 127.0 I30.5 1 13.0 I t4.5 128.0 11s.5 80.0 76.5 77.5 73.0 78.0 76.0 frequencies (l l8-136) (r20-r34) (l02-136) (r07-tzt) (l l8-136) (t02-t2t) (76-e7) (67-78) (65-90) (70-85) (67-e7) (65-e0)
Phase/ 164.5 183.5 2t2.0 240.5 t74.0 226.3 334.0 322.0 347.7 309.8 328.0 328.8 Activity 161.0 181.0 214.5 254.0 174.0 223.0 339.0 318.0 353.5 307.0 327.5 319.5 frequencies (157-r84) (166-210) (r82-24e) (208-258) (ts7-2r0) (182-ã8) Q7e-37r) (303-35 l) Qe4-3e7) Q7o-3s6) Q7e-37t) Q70-397)
(Jr Table 5.7 Percentage change (%L) in game action va¡iables by Period by Code
%oÁ between %o between 7oÅ between 7o across all 19E&92 and 1993-95 and 1997-99 and Periods 1993-95 1997-99 2000-02
Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby union league union league union league union league
Ball in 7.2 -5,7 18.9 1.0 13.5 -6.3 44.7 -10.7 play time
Lineouts 14.3 N/A -41.0 N/A 9.2 N/A -26.4 N/A
Kicks in -39.6 -9.9 -2r.5 2.2 3.2 4.3 -13.1 -4.0 play
Kicks out -18.9 -29.2 -51,0 26.1 32.0 -77.6 -29.1 -82.2 of play
Kicks +24,1 -15.9 -34.3 5.9 12.7 -6.8 -7.7 -19.2 total
Rucks 41.4 -4.8 74.7 13.4 n.9 -10.5 215.1 N/A
Mauls -11.6 N/A -19.8 N/A -16.4 N/A -40.7 N/A
Scrums -21.2 -t4.1 17.3 10.6 -16.4 -25.5 -22.7 N/A
Set 3.7 -9.1 -12.7 4.1 -1.0 -3.0 -10.1 -8.2 possession frequencies Phase/ ll.6 -6.3 15.5 12.3 13.4 -9.0 46.2 -4.2 Activity frequencies
116 Table 5.8 Game action frequency per unit possession time (frequency/min ball in play, meæt time (secs) between actions) by Era and Period by Code
Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby union league union league union league union league union league union league
Lineouts 2.t N/A t', N/A 2.1 N/A 1.1 N/A 1.0 N/A 1.l N/A 29.8 27.9 28.9 57.9 58.0 58.0
Kiclis in 1.3 0.6 t.7 0.6 1.5 0.6 1.2 0.6 1.0 0.7 1.1 0.6 play 46.2 IOI.8 s7.4 108.2 41.8 105.0 62.4 105.7 58.7 98.3 60.5 102.0
Kicks out 1.3 0.2 t.4 0.1 1.4 0.1 0.6 0.1 0.7 0.1 0.6 0.1 of play 45.5 4s9.5 45.7 767.0 45.6 603.2 III.] 577.3 94.3 2222.3 r02.7 1399.8
Kicks - 2.7 0.8 3.1 0.6 2.9 0.7 t.7 0.7 1.7 0.7 t.7 o.7 total 22.5 81.2 19.7 891.4 21.2 86.3 38.0 86.9 s5.5 93.5 s6.7 90.2
Ruclrs 2.t 5.3 2.7 5.4 2.4 5.3 4.O 5.9 4.5 5.5 4.2 5.7 { 30.7 r 1.5 22.4 I1.2 26.6 11.4 15.5 10.3 13.6 11.0 14.6 t0.7
Mauls 1.3 N/A 1.1 N/A t.2 N/A 0.7 N/A 0.5 N/A 0.6 N/A 47.6 60.2 53.9 90.s 122.0 106.3
Scrums 1.6 0.4 1.1 0.4 t.4 0.4 1.1 0.4 0.8 0.3 1.0 0.4 40.2 r57.7 55.9 186.1 48.0 171.9 54.9 154.4 74.8 199.6 64.9 177.0
Set 6.0 1.7 5.8 1.6 5.9 1.6 4.3 1.6 3.7 t.7 4.0 1.7 possession 10.1 36.6 10.4 37.9 10.2 37.2 14.3 s6.9 16.2 35.5 Is.2 36.2 frequencies
Phase/ 7.8 6.7 8.1 6.9 7.9 6.8 7.8 7.3 7.8 7.0 7.8 7.2 Activity 7.8 9.0 7.8 8.8 7.8 8.9 7.8 8.3 7.7 8.7 7.8 8.5 frequencies 5.3 Statistical analyses
5.3.1 Total ball in play time
Rugby Uníon
A significant (Z : - 3.70, P < 0.0005) Era difference was identified for total ball in play time, with a median ball in play time of 21 min 59 s Q6.2% of total game time) in the pre-professional Era compared to 28 min
53 s (33.5% of total game time) in the professional Era (Table 5.1). Additionally, a significant (H3 : 15.3, P
< 0.002) Period main effect was noted for total ball in play time, representing a gradual increase in time across the four Periods. Post-hoc analysis ofthis effeø revealed the significant differences to be between the
Periods 1988-92 nd2000-02 (Z: - 2.88, P <0.002) and 1993-95 and2000-O2 (Z: - 2.88,P <0.002).
Rughy League
No significant Era difference was observed for ball in play time, although a 5Yo decrease in total ball in play time was noted between the Eras. Likewise, no significant Period main effect was identified for total ball in play time, although, a decline was evident across the four Periods.
Compartng the Codes
Significant Code differences were identified in both the pre-professional Era (Z: - 4.16, P < 0.0005) and the professional F;ra(Z: - 4.16,P < 0.0005), with ball in play time greater in rugby league in both Eras. It is notable, however, that the time difference between the Codes was substantially less in the professional Era
(17 min 4 s) than the pre-professional F;ra (26 min 23 s) (Table 5.1).
Significant Code differences for total ball in play time were observed in all Periods (Z: - 2.88, P < 0.002), with times being consistently greater in rugby league than in rugby union. It is notable that the converging of the Codes with respect to this variable was predominantly due to increases identified in rugby union between
1993-95 and 1997-99 and 1997-99 and 2000-02, rather than decreases in rugby league, notwithstanding the notable reduction in ball in play time identified between the 1997-99 and 2000-02 Periods in the league Code
@igure s.l).
118 * * 3500 :1. {. 3000 çt) €) 2s00 E 2000 --+-RugbyLeagw
6l 1500 --r- RWbY Union í) 1000 À11 500 0 1988-92 1993-95 1997-99 2000-02 Period
Figure 5.1 Median (Inter-quartile range) total ball in play time per game by Period by Code. + significant Code differenæ P <0.O02.
5.3.2 Ruck time
Rugby Uníon
No significant Era difference was identified for mean ruck time, however, a significant Period main effect was noted for this variable (F t,zo = 6.26, P < 0.004). Post-hoc analysis of this effect revealed the differences to be significant between the Periods 1988-92 and 1993-95 (t:2.72, P < 0.004), with mean time greater in the latterPeriod (Table 5.1).
Rogby League
A signiflrcant (t:3.'lO, P < 0,001) Era difference was identified for mean ruck time, with times greater in the
pre-professional Era (a.la s) than the professional Era (3.47 s) (Table 5.1), representing a l6.2Yo reduction in
mean times across the Eras. A significant (Fz, x : 79 .71, P < 0.0005) Period main effect was identifïed for
mean ruck time, withpost-hoc analysis indicating a greater mean time in the 1988-92 Period than 1993-95 (r :3.79,P<0.005);1997-99(t:9.23,P<0.0005)and2O00-02(t:6.70,P<0.0005)(Table5.1).
Comparìng lhe Codes
Significant Code differences were identified in both the pre-professional Era(t: - 5.60, P < 0.0005) and the
professional Era (t: - 4.03, P < 0.001), with mean ruck times greater in rugby league than rugby union in
both Eras (Table 5.1). A significant (Ft. co : 22.70, P < 0.005) Period x Code interaction was identified for
mean ruck time. Post-hoc analysis of this effect revealed the Code diflerences to be significant in the Periods
119 1988-92 (t: - 12.95, P < 0.0005) aîd2000-02 (t: -6.05, P < 0.0005), with greater mean ruck time being noted in rugby league than rugby union in all Periods, yet representing a converging of the Codes between
1988-92 and 1997-99. However, between 1997-99 and2000-02 a diverging of the Codes was noted for mean ruck times (Figure 5.2).
¡t 5 rf 4 at2 é) a É J +RWbyLeague
2 --t- RWbY Union 6lí) Ë I
0 1988-92 t993-95 1997-99 2000-02 Period
Figure 5.2 Mean +SD ruck time per game by Period by Code. * significant Code difference P < 0.0005.
5.3.3 Total ruck time
Rugby Unìon
A significant Era difference was identified for total ruck time (t: - 7.04, P < 0.0005), with total time in ruck
activity being greater in the professional Era (7 min l0 s) than in the pre-professional Era (3 min 43 s), representing a l02o/o increase across Eras. A significant Period main effect (Ft, zo:26.7, P < 0.0005) was
noted for total ruck time, reflecting an increase in total time engaged in ruck activity across the four Periods.
Post-hoc analysis ofthis effect indicated the differences to be between the Periods 1988-92 and 1997-99 (t:
- 5.30, P < 0.0005); 1988-92 and 2000-02 (/: - 5.89,P < 0.0005); 1993-95 and 1997-99 (t= -3.37,P <
0.007) and 1993-5 and 2000-02 (t: - 6.57, P < 0.0005). These increases represent the largest significant
change in all of the time variables across the Periods, with increases between Periods ranging from 20Yo to
over 52Vo. These changes across the four Periods represent a total increase of l77o/o between 1988 and 2002
(Table 5.2).
120 Rugby League
A significant Era difference was identified for total ruck times (t: 2.36, P < 0.03), with total times being greater in the pre-professional Era (16 min 44 s) than in the professional Era (14 min 11 s). No period main effect was noted for this time variable.
Compañng the Coiles
A significant (Ft, u:26.60, P < 0.0005) Era x Code interaction was noted for mean total ruck time. Post-hoc analysis of this ef|ect revealed Code differences to be significant in both the pre-professional F,ra (t: 15.77.
P < 0.0005) and the professional Era (t : - 8.59, P < 0.0005), with total times being greater in rugby league than rugby union in both Eras, albeit ì /ith a reduced difference in the professional Era (Table 5.1).
A significant (F t,q: 16.9, P < 0.0005) Period x Code interaction was also identified for this variable, with post-hoc analyses revealing significant Code differences in 1988-92 (t: - 27.23, P < 0.0005); 1993-95 (t: -
9.65,P<0.0005);1997-99(/=5,91,P<0.001)and2000-02(t:-6.23,P<0.0005).ThereducingCode difference in mean total ruck times across the four Periods indicated a converging of the Codes for this time variable, which was predominantly due to increases in rugby union rather than decreases in rugby league, not withstanding the large decrease in this Code between 1988-92 and 1993-95 (Figure 5.3).
1400 ¡lc
1200 ¡1. * ,k @ rooo o 800 +RWbyLeagrc 600 --t-RWbYUnion cl (¡) ÀFi 400 200 0 1988-92 1993-95 1.997-99 2000-02 Period
Figure 5.3 Mean +SD total ruck time per game by Period by Code. * signifrcant Code difference P < 0.001.
12l 5.3.4 Activity time
Rugby Union
A significant (t:3.76, P < 0.001) Era difference was identified for mean activity times, with times greater in the pre-professional Era than the professional Era (Table 5.1). A signifìcant (Fz.zo: 10.06, P < 0.0005)
Period main effect was also noted for mean activity times, representing a decrease in mean times across the four Periods (Table 5.1). Post-hoc analysis of this effect revealed the differences to be significant between the Periods 1988-92 and 1997-99 (t:3.82, P < 0.003) and 1988-92 and20O0-02 (t:4.30, P < 0.002).
Although no significant Period main effect was identified between 1988-92 and 1993-95, the decrease in time
(-9.7%) was the largest when considering changes Period by Period (Table 5.2).
Rugby League
No significant Era difference or Period main effect for mean activity time was identified.
Comparíng the Codss
Significant Era x Code (F t, q+: 8.7, P < 0.005) and (F 3, as: 10.2, P < 0.0005) Period x Code @igure 5.4) interactions were identified for mean activity time. Posþhoc analyses of these effects revealed a signifrcant (/
= 3.14, P < 0.005) Code difference in the pre-professional Era, with mean times in rugby union being higher than in rugby league (Table 5.1). In the professional Era, no significant Code difference was identified for this time variable, with less than 2/100 s separating the mean times of each Code. Post-hoc analysis of the
Period x Code interaction revealed a significant Code difference (t : 3.97, P < 0.003) in the 1988-92 Period
only, reflecting a Code convergence across the four Periods (Figure 5,4).
122 8 ¡13
E') 6 €) É +RWbyLeagw 4 E *-Ru8þYUnion GI !.{6J 1à 2
0 1988-92 1993-95 1997-99 2000-02 Period
Figure 5,4 Mean +SD activity time per game by Period by Code. * significant Code difference P < 0.002.
5.3.5 Total activity time
Rugby Union
A signifÌcant (t: - 3.56, P < 0.003) Era main effect was identified for total activity time, with times being gfeater in the professional Era (21 min 43 s) than the pre-professional Era (18 min 26 s) (Table 5.1). A significant (F ,zo: 5.63, P < 0.006) Period main effect was also identified for total activity time, representing an increase over the four Periods. Post-hoc analysis, however, revealed the differences to be non-signifïcantl in all Periods (P > 0.008), although the ll.3Yo increases in this variable between the 1993-95 and 1991-99
and 1997-99 and 2000-02 Periods are worthy of note (Table 5.2).
Rugby Leøgue
No significant Era difference or Period main effect for mean activity time was identified
Comparìng the Coìles
A significant (F t,qo: 4.10,P < 0.05) total activity 'ime Era x Code interaction was identified,with post-hoc analysis of this effect revealing significant Code differences in the pre-professional E,ra (t = 75.02, P <
0.0005) and the professional Era (r: - 7.70, P < 0.0005), with times being greater in rugby league compared to rugby union in both the pre-professional (l3min 11 s difference) and professional (10min 02 s difference)
1 Caused by the conservative nature of the Bonfenoni adjustment.
123 Eras (Table 5.1). Signifïcant Code differences were also noted in all four Periods; 1988-92 (t: - 8.37, P <
0.0005);1993-95(r:13.97,P<0.0005);1997-99(t=-6.60,P<0.0005)and2000-02(t:-4.67,P<
0.001). The converging of the Codes for this time variable @igure 5.5) was predominantly due to increases across time in rugby union (Table 5.1).
2500 rL l€ * * 2000 ún o E 1500 +RWbyLeague É ---r-RugbyUnion crl 1000 6) =à 500
0 1988-92 1993-95 1997-99 2000-A2 Period
Figure 5.5 Mean +SD total activity time per game by Period by Code. * significant Code difference P < 0.001.
5.3.6 Set possession time
Rugby Uníon
A signifÌcant (Z: - 4.16, P < 0.0005) Era difference was identified for median set possession time, with times greater in the professional Era (15.a s) than the pre-professional Era (10.3 s). A significant (iI¡ : 18.5t,
P < 0.0005) Period main effect was also noted, representing a gradual incre¿se in the median duration of set possession across the four Periods (Figure 5.6). Post-hoc analysis ofthis effect revealed the differences to be significant between 1988-92 and 1997-99; 1988-92 and 2000-02; 1993-95 and 1997-99 and 1993-95 and
2OOO-02 (Z: - 2.88, P < 0.002). The most notable of these increases (35.4%) was identified between the
Periods 1993-95 and1997-99 (Table 5.2).
Ragby Leøgae
No significant Era difference was identified for median set possession time, with times being similar in both
Eras. Likewise, no significant Period main effect was noted, times being consistent across all four Periods
(Table 5,1).
124 Comparíng the Codes
Significant (Z: - 4.16, P < 0.0005) Code difference \¡/ere identified for median set possession time in both
Eras, with times greater in rugby league than in ruby union (Table 5.1). Signifìcant set possession time Code differences were also identifïed in all Periods (Z: - 2.88, P < 0.002), with median times being greater in rugby league than in rugby union in all four Periods. The converging of the Codes with respect to this time variable across the four Periods was predominantly due to increases noted in rugby union compared to a more stable profile in rugby league (Figure 5.6).
50 * ¡t {< rf @40 €) .E 30 --+-RWby Leagæ .s 20 ---- Ruåùy Unbn Elo6) 0 1988-92 1993-95 1997-99 2000-02 Period
Figure 5.6 Median (Inter-quartile range) set possession time per game by Period by Code. * significant Code difference P < 0.002.
5.3.7 Continuous possession time
Rugby Uníon
A significant (t: - 7.77, P < 0.0005) Era difference was identified for the mean time in continuous
possession. In the pre-professional Era teams (on average) maintained possession for 14.7 s compared to 22.1
s in the professional Er4 representing a 50.3o/o increase across Eras. A significant (F t,zo:25.36, P < 0.0005)
Period main effect was also identified, with post-hoc analysis of this effect revealing the difierences to be
significant between the Periods 1988-92 and 1997-99 (t: - 3.54, P < 0.005); 1988-92 and 2000-02 (r: -
7.41,P < 0.0005); 1993-95 and7997-99 (t: - 4.99,P< 0.001) and 1993-95 and 2000-02 (t= - 10.23,P <
0.0005). Particularly notable was the large increase (51.a%) observed between the Periods 1993-95 and
1997-99 (Table 5.2).
t2s Rugby Leøgue
No significant Era difference for mean continuous possession time was identified. However, the Period main effect was significant (F s,n:8.31, P < 0.001), with post-hoc analysis of this effect revealing the differences to be significant betw€en the Periods 1993-95 and 1997-99 (t: 5,26, P < 0.0005) and 1997-99 and 2000-02
(t -- - 3.48, P < O.O2\, with continuous possession times being less in 1997-99 than the other Periods (Table
5 l),
Compøríng the Coiles
Significant mean continuous possession time Era x Code (F¡, qo: 12.9, P < 0.008) and Period x Code (F3, co:
13 .3, P < 0.0005) interactions were identifi ed. Posl-hoc analyses of these effects revealed Code differences to be significant in both the pre-professional Era (: - 27.77, P < 0.0005) and the professional Era (f : - 15.57,
P < 0.0005). In both Eras the mean times for continuous possession were greater in rugby league than in rugby union (Table 5.1). Significant Code differences were also observed in all Periods;1988-92 (/: - 28.08,
P < 0.0005); 1993-95 (t: - 25.46,P < 0.0005); 1997-99 (t : - 19.59, P < 0.0005) and 2000-02 (t: - 13.16, P
< 0.0005), with times greater for rugby league than rugby union in all of these Periods (Figure 5.7).
{. 70 rl. tl. 60 {. @so (¡) É40 +RWbyLeagw IJ É30 ---r-RugbYUnbn G¡ à€20 t0 0 1988-92 1993-95 1997-99 2000-02 Period
+ Figure 5.7 Mean +SD continuous possession time per game by Period by Code. significant Code differenceP < 0.0005.
126 5.3.8 Continuous ball in play time
Rugby Union
A significant Era difÏerence (Z: - 4.16, P < 0.0005) was identified for continuous possession time, with median times greater in the professional Era (23.0 Ð than the pre-professional Era (13.7 s). A significant
Period main effect was also observed (¡/3 : 18.60, P < 0.0005), representing an increase in mean times across the four Periods. Post-hoc analysis ofthis effect revealed the differences to be between all Periods (Z = -
2.88, P < 0.002), except between 1988-92 and 1993-95 and 7997-99 and 2000-02, with the g¡eatest change
(+49.3yù noted in the Periods spanning the introduction of professional rugby (Table 5.2).
Rugby League
No significant Era difference or Period main effect was identified for continuous ball in play time, reflecting the relative stability of this variable over time.
Comparúng the Codes
Significant median continuous ball in play time Code differences were identified in both the pre-professional
(Z: - 3.96, P < 0.0005) and professional (Z: - 4.16, P < 0.0005) Eras, with times greater in rugby league than rugby union (Table 5.1). In addition, significant Code differences lvere also identifred in all four
Periods;1988-92 (Z:-2.74,P<0.004);1993-95(Z:-2.74,P<0.004);1997-99(Z='2.88,P<0.002)
and 2000-02 (Z: - 2.88, P < 0.002), with a gradual reduction in times between the Codes across the four
Periods indicating a converging of the Codes for this time variable (Figure 5.8).
100 rl. ,1. {. * :g^80 o .E 60 -+- RWby Leagrc .E 40 *-RugbY Union í)
0 1988-92 t993-9s t997-99 2000-02 Period
Figure 5.8 Median (Inter-quartile range) continuous ball in play time per game by Period by Code. * significant Code difference P < 0.004.
127 5.3.9 Total ball carries
Rugby Uníon
A significant Period main effect was identifred for ball carries (H3:15.73, P < 0.001), representing an increase in the frequency across the four Periods (Table 5.3). Post-hoc analysis of this effect revealed the differences to be significant between the Periods 1988-92 and 2000-02 (Z: - 2.88, P < 0.002) and 1993-95 and 2000-02 (Z: - 2.88, P < 0.002). The most notable non-significant increase between Periods Q4.6yù was noted between 1993-95 and 1997-99 (Table 5.a).
No significant Period main effect was identified for the frequency of ball caries per unit time. However, a gradual increase across the Periods after 1993-95 was noted (Table 5.5).
Rugby Lmgue
No significant Era differences or Period main effects were identified for either the frequency of total ball carries or the frequency per unit time.
Comparíng the Codes
Significant Code differences were revealed in both the pre-professional (Z : - 5.16, P < 0.0005) and professional (Z:-3.78,P<0.0005)Eras,withthemedianfrequencyofballcarriespergameinrugbyunion being consistentþ fewer than in rugby league (Table 5.3). In additiorU significant Code differences were identified for this variable in 1988-92 (Z: - 2.89, P < 0.002);1993-95 (Z: - 2.89, P < 0.002) and 1997-99 (Z
: - 2.73,P < 0.004), with the median frequencies being greater in rugby league than rugby union (Table 5.3).
A converging of the Codes for the median frequency of ball carries per game was predominantly due to increases in rugby union across the 1993-95 and 2000-02 Periods @igure 5.9),
128 600 ¡t lc * C) 500 í)Ê F 400 (l) --+-RWbyLeagæ ë 300 ---¡-RugbyUnion 6l 200 E €) liÅ 100 0 1988-92 1993-95 1997-99 2000-02 Period
Figure 5.9 Median (Inter-quartile range) frequency of total ball caries per game by Period by Code. + significant Code difference P < 0.004.
For the mean frequency of ball carries per unit time a significant Code difference \¡/as observed in both the pre-professional Era (t: 7.88, P < 0.0005) and professional Era (/ : 5.86, P < 0.0005), with more carries per minute occurring in rugby union than rugby league in both Eras (Iable 5,5). Signifïcant Code differences were also identified for the mean frequency of total ball canies perunit time in all four Periods; 1899-92 (t:
5.39, P < 0.002); 1993-95 (l:5.98, P < 0.0005); 1997-99 (t:3.44, P< 0.00ó) and2000-02(t:4.75, P <
0.001), with the mean carries per minute consistently gfeater in rugby union than rugby league (Fþre 5.10).
Whilst significant increases in the median frequency of ball carries were identified in rugby union, the same was not true when this variable was assessed in relation to ball in play time (Figure 5.10). As a consequence no converging ofthe Codes was noted, indicating the convergence in the mean frequency oftotal ball ca¡ries was predominantly related to concomitant increases in ball in play time in rugby union across the four
Periods.
129 tl. rlÉ ¡lr t4 rl.
I l2 o- 10 ttq ùb(uH 8 ->RWbyLeagræ Éa 6 --r-RuSbYUnion 6l 6) 4 =à 2 0 1988-92 1993-9s 1997-99 2000-02 Period
Figure 5.10 Mean +SDlequency of total ball canies per unit time by Period by Code. ' significant Code difference P < 0.006.
5.3.10 Passing
Rryby Union
Significant Era differences were observed for the median frequency of total game passes per game (Z : -
2.15, P < 0.001), passes in open play per game (Z : - 2.80, P < 0.004) and dummy/scrum-half passes per
game (Z = - 3.81, P < 0.0005), with total game passes increasing +26.Oyo, passes in open play increasing
39.6Yo and passes from the dummy/scrum half position increasing from 82.8% across the Eras. Further
analysis of these variables per unit time revealed a significant Era difference for the frequency of passes from
the dummy/scrum half position (Z : - 3.41, P < 0.0005), with a pass occurring (on average) every 23.0 s in
the pre-professional Era compared to every 17.2 sin the professional Era (Table 5.5). No significant Era
differences were indicated for the other passing variables, although both open play passes per unit time (one
every 10.6 s compared to I L0 s) and offloads per unit time (one every 55. 1 s compared to 62.1 s) were lower
in the professional Era than the pre-professional Era (Tables.5).
A significant Period main effect for total game passes was identified (¡1. : 12.93, P < 0.004), reflecting an
increase in the median frequency of passes across the four Periods. The same effect was also identified for
the frequency of passes from the dummy/scrum-half position (H3: 17.57,P < 0.001), withpost-hoc analyses
of these effects revealing the differences for total game passes to be between the Periods 1988-92 and 2000- 02(Z:-2.88,P<0.002)and1993-95and2000-02(Z:-2.88,P<0.002).Forpassesfromthe
dummy/scrum-half position, differences were also significant between these Periods (Z: - 2.88, P < 0.002)
and between the Periods 1988-92 and 1997-99 (Z: - 2.72,P < 0.004), reflecting an increase in the frequency
130 of dummy/scrum half passes across the four Periods (Table 5.3). No significant Period main effects were identified for the frequency of passes in open play or offloads, however, a notable increase (+54.6%) was evident in mean offload frequency between the Periods 7993-95 and 1997-99 (Table 5.4).
Analyses of the pass variables per unit time indicated significant Period main effects for passes from the dummy/scrum half position per unit time (f13 : 14.87, P < 0.02) and offloads per unit time (f13 : 11.29, P <
0.01), with post-hoc analyses indicating that the differences were significant between the Periods 1988-92
(dummy/scrum half pass every 24.0 s) and 2000-02 (dummy/scrum half pass every 15.2 s) (Z = - 2.88, P <
0.009). For the offload per unit time a significant difference (Z = - 2.09, P < 0.04) was noted between the
Periods 1988-92 (one offload every 40.0 s) and 1993-95 (one offload every 70.2 s). Whilst differences between other Periods were non-significant, it was notable that offloads occurred more frequently in 1988-92 than all other Periods (Table 5.5).
Rugby League
No significant Era differences were identified for any of the pass variables, nor were any Period main effects noted. In addition, no significant Era differences were identifìed for any pass variables assessed in relation to ball in play time. However, a signifrcant (¡13 : 12.78, P < 0.005) Period main effect was noted for the mean frequency of dummy/scrum half passes per unit time, with posÞhoc analysis of this effect revealing the difference to be significant between the Periods 1988-92 and 1993-95 (Z: - 2,56, P < 0.009) and 1988-92
and 1997-99 (Z: - 2.88, P < 0.002). This reflected an increase in the mean frequency of dummy/scrum half passes per minute across the Periods between 1938-92 and 1997-99; the largest increase being between 1988-
92 (one every 13.8 s) and 1993-95 (one every 12.6 s) (Table 5.5).
Comparìng the Codes
In the pre-professional Era, significant Code differences were identified for the median frequency of passes from the dummy half position per game (Z: - 4.16, P < 0.0005), total passes per game (Z = - 4.16, P <
0.0005) and passes in open play per game (Z : - 2.22, P < O.02), with median frequencies higher in rugby league than rugby union (Table 5.3). In the professional Era, significant Code differences were also noted for the frequency of passes from the dummy half position (Z: - 4.16, P < 0.0005) and total game pass frequency
(Z=3.70,P<0.0005).AsignificantCodedifference(Z=-2.88,P<0.002)wasidentifiedfortotalgame
passes in all Periods except 2000-02, with higher median frequencies being obsewed in rugby league than
rugby union @igure 5.11). The relative change in the frequency of total passes per game in rugby union and
rugby league indicated a converging of the Codes, which was predominantly due to large increases in median
131 frequencies in rugby union rather than reductions in rugby league (Figure 5.11). However, although significant total pass per unit time Code main effects were identified in 1988-92 (Z: - 2.56, P < 0.009);
1993-95 (Z = - 2.40, P < 0.O2) and 2000-02 (Z : - 2.88, P < 0.002), with frequencies per unit time greater in rugby union than in rugby league, no apparent converging of the Codes was noted (Figure 5.12) indicating thatthe changes in median frequency in rugby union were predominantly due to concomitant increases in ball in play time across the four Periods.
rl. 500 rlc ,r I (¡) 400 ct !) 300 -+-RWbyLeagn ù É ---'- RWbY Union cË 200 Ëí) àtt 100 0 1988-92 1993-9s 1997-99 2000-02 Period
Figure 5.11 Median (Inter-quartile range) frequencies of total passes per game by Period by Code. * significant Code difference P < 0.002.
t4 rt rl. c.) 12 r& c) 10 oÊ 8 +RWbyLeagrc -¡r H 6 --- RWbY Union GlÉ9 tli 4 (¡) à= 2 0 1988-92 1993-95 1997-99 2000-02 Period
Figure 5.12 Median (Inter-quadle range) fiequencies of total passes per unit time by Period by Code. * significant Code difference P < 0.02.
A signiflrcant (Z -- - 2.58, P < 0.002) Code difference was identified for the median frequency of passes from the dummy half position in all Periods, with fewer passes per game in rugby union than in rugby league.
132 Assessment of the relative change in median frequency for this variable across the four Periods indicated a converging ofthe Codes @igure 5.13). The relative percentage change in the variable frequencies revealed the change in rugby union to be greater (+138%) than in rugby league (+l%) across the four Periods (Table s.4).
:r 300 rl. rlr ¡lc zso €)$ =õ 2oo é) +RWbyLeague Ë 150 --r-RugbYUnion Ê l0o Ë50 0 1988-92 1993-95 1997-99 2000-02 Period
Figure 5. 13 Median (Inter-quartile range) frequencies of dummy half passes per game by Period by Code. * significant Code difference P <0.002.
Significant dummy/scrum half pass frequency per unit time Code differences were also identified in the
Periods 1988-92; 1993-95;1997-99 (Z: - 2.81, P < 0.002) and 2000-02 (Z: - 2.40, P < O.02). A converging ofthe Codes was noted, predominantly due to increases in rugby union and decreases in rugby league after
1997-99 (Figure 5.14). Hence, the convergences identified for the median frequency of dummy/scrum half passes per game was not solely due to changes in ball in play time.
133 7 !t }l rlc ¡1. I 6 * c) 5 oÊ 4 +RWbyLeagn -¡r ts a Ég J --+-RWbYUnion €|¡ tar õ 2 ttó) à 1 0 1988-92 t993-9s 1997-99 2000-02 Period
Figure 5.14 Mean +SD frequency of dummy/scrum half passes per unit time by Period by Code. * significant Code difference P < 0.002.
The change in the mean frequency ofopen play passes reflected a converging ofthe Codes, evident across the Periods 1988-92 and 1997-99. However, a Code divergence (cross-over) occurred after 1997-99, with median frequencies higher in rugby union than rugby league in 20O0-02 (Figure 5.15). In this Period only was a significant Code difference identified for this variable (Z : - 2.88, P < 0.002).
,ß 200 >ì c.) (¡) 150
0) -+RWby League ù I 00 --r-RwbY Union cl¡
o) 50 Ålr 0 1988-92 1993-95 1997-99 2000-02 Period
Figure 5.15 Median (Inter-quartile range) frequencies of open play passes per game by Period by Code. * significant Code differenceP < 0.002.
Significant open play pass frequency per unit time Code differences were identified in all four Periods (Z = -
2.88, P < 0.002) (Figure 5.16), indicating the changes in ball in play time across the four Periods were
134 probably the main factor in the apparent convergence ofthe mean frequencies ofopen play passes per game identified previously.
8 :1. ¡t * I>ì * (l)O È;4(l)É --r- RWby Leagw Éq) --r-RugbYUnion 6iÈ Ë. €)L lrÀ 0 1988-92 1993-95 1997-99 2000-02 Period
Figure 5,16 Mean +SD frequencies of open play passes per unit time by Period by Code, * significant Code differenceP < 0.002.
The median frequency of offloads per game in both Codes of rugby were stable across the four Periods, with the exception of a significani (Z: - 2.01, P < 0.04) Code difference identifïed in the 1993-95 Period, with the frequencies less in rugby union than rugby league in this Period (Figure 5.l7), However, when this variable was normalised to ball in play time a significant Code difference was identified in 1988-92 only (Z: - 2.88,
P < 0.002) (Figure 5,18).
b40 {. q)É å30 6) --: RWby League -¡r ;20 RugbY Union 6l -- Eloà 0 1988-92 1993-9s 1997-99 2000-02 PerÍod
Figure 5.17 Median (Inter-quartile range) frequencies of offloads per game by Period by Code. * significant Code differenceP < 0.04.
135 2 :1.
c¿ o I 5 d 6) +RWbyLeagæ .È 1 _*- RWbY Union cl
'tJ6) 0. 5 àE 0 1988-92 1993-9s 1997-99 2000-02 Period
Figure 5. 18 Median (Inter-quartile range) frequencies of offloads per unit time by Period by Code. * significant Code difference P <0.002.
5.3.11 Ball carries into contact
Rugby Union
Signifïcant Era differences were identified for total ball carries into contact (Z: - 4.02, P < 0.0005) and total ball carries into contact per unit time (Z: - 3.58, P < 0.0005), with median frequencies and frequencies per unit time greater in the professional Era than the pre-professional Era (Tables 5.3 and 5.5, respectively).
A significant (Hz = 16.69, P < 0.001) Period main effect was identified for total ball canies into contact, representing an increase (+60.5%) across the four Periods (Table 5.4). Post-hoc analysis of this effect revealed the differences to be between 1988-92 and 199'l-99 (Z: -2.56, P < 0.009); 1988-92 and 2000-O2 (Z
: -2.81,P <0.002);1993-95 and1997-99 (Z:-2.89,P<0.002) and 1993-95 and2000-02(Z: -2.89,P <
0.002), with the most notable increase (+42.5%) occurring between the 1993-95 and 1997-99 Periods (Table s.4).
A signifìcant Period main effect was also identified for the median frequency of ball carries into contact per unit time (H3: 13.65, P < 0.003). However, whtlst post-hoc analysis of this effect revealed the difference to be non-significant when employing the Bonferroni correction, notable differences were noted between the
1993-95 (5.3 contacts per min) and 1997-99 (6.4 contacts per min) Periods and the 1993-95 and 200O-02
Periods (6.4 contacts per min) (Table 5.5).
136 Rugby League
No significant ball carry into contact Era difference or Period main effect was identified. However, a significant (Z : - 2,14, P < 0.03) Era difference was identified for the median frequency of carries into contact per unit time, increasing slightly from 6.4 contacts per min in the pre-professional Erato 6.7 contacts per min in the professional Era. A significant (É13 : 10.61, P < 0.01) Period main effect was also noted for this variable, wiih post-hoc analysis revealing the difference to be between the Periods 1988-92 and 1997-99
(Z: - 2.88, P < 0.002), with carries into contact per unit time increasing from 6.4 per min in 1988-92 to 6.9 permin in1997-99 (Table 5.5).
Comparíng the Codes
Significant Code differences were identified in both the pre-professional and professional (Z -- - 4.76, P <
0.0005) Eras, with median ball carries into contact frequencies in rugby union being less than in rugby leagug albeit by a reduced margin in the professional Era (Table 5.3). Analysis of this variable per unit time revealed a significant (Z = -3.75, P < 0.0005) Code difference in the pre-professional Era only, with 5.5 contacts per minute in rugby union compared to 0.¡ contacts per minute in rugby league. In the professional
Era the median frequency per game in rugby league increased slightly to 6.7 contacts per minute, whilst in rugby union a more notable increase (6.4 contacts per min) was noted (Table 5.5).
Significant Code differences were identified for the median frequency of ball carries into contact in all
Periods (Z: - 2.88,P < 0.002), with frequencies consistently greater in the rugby league than rugby union
(Table 5.3). The reducing dif;lerence between the Codes across the four Periods was predominantly due to increases in the frequency of ball carries into contact in rugby union across the time frame set again more consistent scores in rugby league (Figure 5.19).
400 tl. * ¡1. ,t c¿ €) 300 d 6) + Rugby League ù 200 ---.-RugbYUnion õGI 6) 100 E 0 1988-92 1993-95 1997-99 2000-02 Period
137 Figure 5.19 Median (Inter-quartile range) frequency of total carries into contact per grime by Period by Code. * significant Code difference P < O.002.
Analysis of this variable per unit time revealed significant Code differences in the pre-professional Periods only; 1988-92(Z:-2.08,P<004)and1993-95(Z:-2.88,P<0.002)(Table5.5)indicatingaconverging of the Codes, predominantly due to increases in the median frequencies per unit time in rugby union across the four Periods (Figure 5.20).
8 ¡1. rß
e¿ ooE u.ts ÈI4é¿ Él +- RWby Leagw ---.-RugbY Unbn .E Ë. E1 €,) L à= 0 1988-92 1993-95 1997-99 2000-02 Period
Figure 5.20 Median (Inter-quartile range) frequency of total carries into cont¿ct per unit time by Period by Code. * signifìcant Code dillbrence P < 0.04.
5.3.12 Tackle attempts
Rugby Uníon
A significant (Z: - 3 87,P < 0.0005) Era difference was identifred for total tackle attempts, with the median frequency of tackle attempts per game fewer in pre-professional Era than the professional Era (Table 5.3). A significant Period main effect was also identified (Hz:76.35, P < 0.001), withpost-hoc analysis of this effect revealing the differeuces to be between the Periods 1988-92 and 2000-02 (Z: - 2.72, P < 0.004), 1993-
95 and 1997-99; (Z: - 2.72, P < 0.004) and 1993-95 and 2000-02 (Z: - 2.72, P < 0.002), with total tackle attempts being greater in both the professional Periods than the pre-professional Periods (Table 5.3), The most notable change was noted between the Periods 1993-95 and 1997-99, representing a 46.6Vo inçrease on the previous Period (Table 5.4).
138 A significant F;ra (Z: - 2.89,P < 0.003) difference was identified for the median tackle attempts per unit time, increasing from 5.4 per min in the pre-professional Era to 6.4 per min in the professional Era (Table
5.5). A significant (H3: L0.2'1, P < 0.02) Period main etlect was also identified, with posl-hoc analysis of this effect revealing tle differences to be significant hetween the I 993-95 Period and both the 1997 -99 (Z : -
?.56, P., 0.009) and 2000-02 (Z: - 2;72, P .. 0.004) Periods (Table 5 5).
Rugby League
No significant Era difference or Period main effect for the frequency of tackle attempts were identified. No signiflrcant Era difference or Period main effect, nor any notable trends were identified for tackle attempts per unlt tlme.
Compøríng the Codes
A significant Code difference was identified for the median frequency of tackle attempts in both E;ns (Z: -
4.16, P < 0.0005), with frequencies greater in rugby league than in rugby union (Table 5.3). Significant Code differences were also identified in all four Periods (Z: - 2.88, P < 0. 002), with median tackle attempts greater in rugby league than in rugby union in ¿ll of these Periods (Table 5.3). The relative change in this variable across the four Periods indicated a convergence of the Codes, with the Code difference reducing across the four Periods @igure 5.21). This reduction ì/vas more even notable when assessed relative to ball in play time (Figure 5.22), wlth signifìcant Code differences being identified in all Periods; 1988-92 (Z: -2.72,
P < 0.004); 1993-95 (Z= -2.88, P <0.002);1997-99 (Z: -2.88, P < 0.002) and2000-02 (Z: -2.40, P <
0.02)
139 500 * rl. ¡1. c) * (l) 400 5 (¡) 300 *Rr¡gby Leagæ ,È ---r-RuBbYUnion Érl 200 E 6) 100 Àli 0 1988-92 1993-95 1997-99 2000-02 Period
Figure 5.21 Median (Inter-quartile range) frequencies of total tackle attempts per game by Period by Code. * significant Code difference P < 0.002.
I 0 ¡lr * t( I>ì {. 8 (¡) Èt .= OE 6 kague -¡r Li -+Rugþy Ég ---r-Rugby Union 6¡ llr 4 o Àra 2 0 1988-92 r993-9s 1997-99 2000-02 Period
Figure 5.22 Median (tnter-quartile range) frequencies of total tackle attempts per unit time by Period by Code. * sþnificant Code difference P 5.3.13 Tackle type Rugby Unìon Significant Era differences were identified for the median frequency of single tackles (Z: - 3.81,P < 0.0005) and double tackles (Z: - 3.47, P < 0.0005) per game, with both tackle type frequencies greater in the professional Era.than in the pre-professional Era (Table 5.3). No significant Era difference was identified for the frequency of mob tackles. Significant Period main effects were also noted for the frequency of single tackles per game (I4 : 15.Ot, P < 0.002), tvrth post-hoc analysis of this effect revealing the differences to be significant between 1988-92 anó 1997-99 {Z: - 2.57, P < 0'0O9); 1988-92 and 2000-02 (Z: - 2.73, P < 140 0.004);1993-95 and1997-99 (Z:-2.57,P<0.009) and 1993-95 and2O00-02(Z: -2.73,P<0.004). A significant Period main effect ìilas also identified for the median frequency of double tackles per game (F/3 : 14.89, P < 0.002). Post-hoc analysis of this efï'ect revealed the difìèrences to be signilìcant between 1988-92 and 2000-02 (Z: - 2,73, P < 0.004) 1993-95 and 1997-99 (Z: - 2.57, P < 0.009) and 1993-95 and 2O00-02 (Z : - 2 89, P < 0.002) For both single and double tackles an increase in median frequency over time was noted, with one anomaly apparent for double tackles in the 1993-95 Period (Table 5.3). Significant Era differences were identified for median single tackles per unit time (Z: - 2.94, P < 0.002) and mean double tackles per unit time (Z: - 2.60, P < 0.008), with more tackles of both type made per unit time in the professional Era than the pre-professional Era (Table 5.5). Significant Period main effects were also noted for both single (l/3 : 9.15, P < 0.03) and double (&: 12.90, P < 0.005) tackles per unit time. For the frequency of single tackles per unit hime posl-hoc analysis revealed no signifìcant differences between the Periods when the Bonferroni correction was applied. However, it was notable that single tackle frequencies per minute were greater in both Periods in the Professional Era than in Periods in the pre-professional Era (Table 5.5). Post-hoc analysis of the double tackle per unit time main effect revealed the differences to be significant between the Periods 1993-95 and 1997-99 (Z: - 2.56,P < 0.009) and 1993-95 and2000-02 (Z = - 2.S8, P < 0.008), reflecting an increase in median fi'equency per unit time across these three Periods (Table 5s) Rugby League A signiticant (Z: - 2.14, P < 0.03) Era diflèrence was identifìed fbr the median fiequency of double tackles, with (on average) higher frequencies per game in the professional Era than the pre-professional Era (Table 5.3). The significant (Z= -3.52, P < 0.0005) difference identified per unit time Q7 per min in the pre- protèssional Era,3.2 per min in the professional Era) and the significant (Z = - 3.0O, P < O.002) difference in the double tackle percentage (42.8%o and 47.7Yo, respectively) indicated a change in tackling stratery across the Eras, with no significant changes being observed in either single or mob tackle variables. lt was, howeveq notable that the single tackle frequency and percentage decreased across the Eras, indicating a move towards more multiple player contacts in defence. No significant Period main effects were identified for any of the tackle frequencies, althoughthe median frequency of single tackles was fewer in the 2000-02 Period (118.2 per game) than all other Periods (range 150.8 - 155.0). Signifïcant Period main effects werq however, noted for the double tackle percentage (Ht: 11.96, P < 0.008) and the frequency of double tackles per minute (¡13: 13.09, P < 0.004), reflecting an increase in tackles per minute across the four Periods and an increase in percentage across three Periods t4r (1993-95 to 2000-02). Post-hoc analyses of these effects revealed the differences in the double tackle percentage to be significant between I 988-92 and 2000-02 (Z : - 2.40, P < O.02), the difference for double tackles per unit time between the Periods 1988-92 and 1997-99 (Z: - 2.54,P < 0.009) and the difference in percentage to be between the Periods 1988-92 and 2000-O2 (Z: - 2.72, P < 0.004), Compøríng the Codes In the pre-professional Era signiflrcant (Z : - 4.16, P < 0.0005) Code differences were identified for the median fiequency of singlg doublg and mob tackles, with frequencies consistently greater in rugby league than rugby union (Table 5.3). In the professional Era significant (Z: - 4.17, P < 0.0005) Code differences were also identified for double and mob tackles, with median frequencies greater in rugby league than rugby union (Table 5.3). For single tackles per minute, no significant Code difference was identifÏed in the pre- professional Era" however, a significant (Z: - 3.93, P < 0.0005) difference was identiflred in the professional Era indicating a Code divergence for this variablg with more single tackles per minute being observed in rugby union than rugby league (Table 5.5). Signifìcant Code differences were also identified for double and mob tackles per minute in the pre-professional F;ra (Z : - 4.10, P < 0.0005) and the professional F,ra (Z: - 4.L6, P < 0.0005), with gleater median fiequencies per minute in rugby league than rugby union (Table 5.5). For the median frequency of single tackles per game, signifrcant Code differences r¡i/ere identified in 1988- 92 1993-95 (Z: - 2.89, P < 0.02) and 1997-99 (Z:- 2.56, P < 0.09). Analysis of the relative change in median frequencies for this variable indìcated a Code convergence across the four Periods, with frequencies being greater in rugby union than in rugby league in the 2000-02 Period (Figure 5.23). * 200 + d. () o 150 ct 6) +RWbyLeag.re .¡r 100 É ---.-RugbYUnion cll €J 50 àtl 0 1988-92 1993-95 1997-99 2000-02 Period Figure 5.23 Median (Inter-qualtile range) frequency of single tackles per game by Period by Code. * significant Code difference P < 0.09. 142 For single tackles per unit time signilìcant Code dillèrences were identitìed in 1997-99 (î : 3.14, P < 0.01) and 2000-02 (t: 4.96, P < 0,001), with mean frequencies greater in the union Code than the league Code in all Periods (Figure 5.24). Further assessment of this tackle type per unit time revealed a diverging of the Codes, indicating that the Code convergence for the median frequency of single tackles was ostensibly due, or corresponding to changes in ball in play time (Figure 5.24). 6 * {. >ì I 5 íJ 4 rÉ(l)¡t --*- Rugby Union åb J ÉÈ +RWbyLeagrc cl 2 €) à- 1 0 1988-92 1993-95 1997-99 2000-02 Period Figure 5.24 Mean +SD,frequencies of single tackles per unit time by Period by Code. k significant Code difference P < 0.01. Tn all four Periods significant Code differences were identified for the median frequency of double taskles (Z : - 2.89, P < 00005) and mob tackles (Z: - 2.89, P < 0.0005). Analysis of the relative change in mean frequencies per game for these variables over the tbur Periods indicates that no converging of the Code was evident for either the median frequencies of double tackles (Figure 5.25) or mob tackles per game (Figure s.26). 143 200 ¡& t I>ì rt rl. É t) 1s0 5 o) +RWbyLeagtæ ù 1 00 É -+-Rugby Union sË o) 50 àts 0 t988-92 1993-95 1997-99 2000-02 PerÍod Figure 5.25 Median Qnter-quartile range) frequencies of double tackles per game by Period by Code. * significant Code difference P < 0.0005. d. 40 ,1. !¡ CJ rß E30 ù20(l) +RugbyLeagw --r- RWbY Unbn 6l Elo Ålr 0 1988-92 1993-95 1997-99 2000-02 Period Figure 5.26Median (Inter-quartile range) frequencies of mob tackles per game by Period by Code. * significant Code difference P < 0.0005. Signifìcant Code differenqes were also identified for double tackles per unit time and mob tackles per unit time in all four Periods (Z: - 2.88, P < 0.002), with the median frequencies per game being greater in rugby league than rugby union. The median frequency of mob tackles per unit time for both Codes was consistent across the four Periods (Table 5 5) indicating no converging of the Codes for this variable- Similarly the relative change in frequenoies ofdouble tackles per unit time across the Periods indicated no converging of the Codes (Figure 5.27). 144 4 {! * * CJ * (¡) 5 5.= ,ÈI2OE +RtrgþyLeagræ Ég +-ftsgþyUnion Gl ¡li EI àts 0 1988-92 1993-95 1997-99 2000-02 PerÍod Figure 5.27 Median(Inter-quartile range) frequencies of double tackles per unit time by Period by Code. * significant Code differenceP < 0.002. In the pre-professional Era significant Code differences were identified for the mean single tackle percentage (r: ll.5\ P < 0.0005), double tackle percentage (t : -11,25, P < 0.0005) and mob tackle percentage (t : - 5.4I, P < 0.0005). In the professional Era significant Code differences $/ere also noted for mean single tackle percentage(t=13.27,P<0.0005),doubletacklepercentage(t:-12.65,P<0.0005)andmobtackle percentage (t: - 9.20,P < 0.0005) (Table 5.9). 145 Table 5.9 Mean +SD tackle type percentage per game by Era and Period by Code 1988-92 1993-95 Pre. professional 1997-99 2000-02 Professional Era Era Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby union league union league union league union league union league union league Single 68.0 48.8 72.9 49.3 70.4 49.0 7t.5 47.3 68.7 40.5 70. I 43.9 (6.1) tackles Q.e) (4.3) (s.0) (s.1) (4.6) (s.5) (3.6) (3.3) (2 0) (6 s) (3.2',) Double 28.2 42.8 23.7 42.7 26.0 42.8 26.6 44.8 29.0 50.6 27.8 47.7 tackles (3.4) (2.s) Q.7) (4.6) (3.8) (3.s) (3.6) (2 8) (1.4) (4.4) (2.e\ (4.6\ Mob 3.7 8.4 3.5 8.1 3.6 8.2 1.9 7.9 2.3 8.9 2.t 8.4 tackles (1. 1) (2.3) (2.E) (2.3) (2.0) (2.2) (t 1) (1 1) (1.4) Q.7) (1.2) (2.0) À Or Missed 8.8 71.4 10.6 1ó.0 9.7 13.7 9.2 9.7 7.8 9.5 8.5 9.6 tackles (4.8) (3 3) (3.7) Q.6) (4.2) (3.7) (2 8) (1.7) Q.2) Q.4> Q.s) (2.0) Significant Code differences were also identified for mean percentage single tackles in all Periods;1988-92 (t : 8.16, P < 0.0005); 1993-95 (t: 7.69, P < 0.0005); 1997-99 (t: 12.47, P < 0.0005) and 2000-02 (t :9.9O, P < 0.0005), with mean single tackle percentages being consistent across the four Periods in rugby union, but slightly decreasing in rugby league (Figure 5.28). As a consequence, there is no apparent converging ofthe Codes for tackle type preference, with the preferred tackle type being the single tackle in rugby union and the multiple (double and mob) tackle in rugby league in all four Periods (Table 5.9). I 00 rlr ,1. 6) rß * 80 &'Ë ¡r860 *RWbyLeagæ oÈ40 *-RWbYUnbn cll Ë20 0 1988-92 1993-95 1997-99 2000-02 Period Figure 5.28 Mean +SD single tackle percentages per game by Period by Code. * significant Code differenceP < 0.0005. 5.3.14 Tackle ernors Rughy Uníon No significant Era difference or Period main effect was identified for the median frequency of missed tacHes or the mean frequency of missed tackles per unit time. No Era difference or Period main effect was noted for the percentage of missed tackles, however, a notable decrease across the Periods 1993-95 and 2000-02 for missed tackles expressed in relation to total tackle attempts was noted, with the mean missed tackle percentage falling froml}JYoin1993-95 to9.2Yoin1997-99 and7.7o/oin2000-02 (Table 5.9). Rughy League A significant (Z: - 2.60, P < 0.008) Era difference was identifred for the median frequency of missed tackles, with frequencies greater in the pre-professional Era than the professional Era (Table 5.3). A 747 significant (t : 3.36, P < 0.003) Era difference was also identified for the percentage of missed tackles, with lower mean percentages noted in the professional Era (9.6) than the pre-professional Era (13.7) (Table 5.9). In addition, a signifìcant (t:2.90, P < 0.008) Era difference was identifìed for the median frequency of missed tackles per unit timg with a tackle miss occurring every 66 s in the pre-professional Era compared to one every 88 s ofball in play in the professional Era (Table 5.5). A significant Period main effect was identified for the median frequency of missed tackles (Hz : 10.22, P < 0.02). Post-hoc analysis of this effect revealed the differences to be signifrcant between the Periods 1993-95 and 7997-99 (Z: - 2.88, P < 0.002) and 1993-95 and 2000-02 (Z: - 2.72, P < 0.004), with frequencies gfeater in 1993-95 than all other Periods (Table 5.3). A significant Period main effect was also noted for mean missed tackle percentage (F3,2s : 8.26, P < 0.001). Post-hoc analysis of this effect revealed the diflerences to be significant between the Periods 1993-95 and 7997-99 (t: 4.99,P < 0.001) and 1997-99 and 2000-02 (t : 4.45, P < 0.001), with mean percentages gfeater in 1993-95 than the other two Periods (Table 5.9). In addition, a significant Period main effect was identified for the mean frequency of missed tackles per unit time (Fz,zo: 7.47, P < 0.002). Post-hoc analyses of this effect revealed the differences to be significant between the Periods 1993-95 and 1997-99 (t:4.11, P < 0.002) and 1993-95 and 2000-02 (t: 4.47, P < 0.001), with frequencies per unit time being greater in 1993-95 than all other Periods (Table 5.5). Compañng the Codes Significant Code differences v/ere identified for the median frequency of missed tackles in both the pre- professional F;ra (Z: - 4.16,P < 0.0005) and the professional F;ra (Z : - 4.08, P < 0.0005), with frequencies greater in rugby league than in rugby union in both Eras (Table 5.3). Significant Code differences were also identified in all four Periods; 1988-92 (Z : - 2.89,P < 0.002); 1993-95 (Z: - 2.88, P < 0.002); 7997-99 (Z : - 2.99, P < 0.002) and 20O0-02 (Z : - 2.65, P < 0.004), with frequencies consistently greater in rugby league than in rugby union (Table 5.3). The relative change in the median frequencies across the four Periods indicated a converging of the Codes, with the frequency of missed tackle decreasing in rugby league across the Periods 1993-95 and 2000-02, whilst the mean frequencies in rugby union were more consistent across the same time frame (Figure 5.29). 148 rf rF 70 boo * tss0 ,¡. Þ40 <-RWbyLeagæ, È É30 ---r--Rr¡gby Union GI E20o) 0 1988-92 1993-9s 1997-99 2000-02 Period Figure 5.29 Median (Inter-quartile range) frequency of missed tackles per game by Period by Code. * significant Code difference P < 0.004. It is notable that when these data were normalised to total tackle attempts, significant Code differences were only identified in the pre-professional Era (t : - 2.45, P < O.02).In addition, no significant Code difference was identified in any of the four Periods, although, in all four Periods the mean frequencies of misse.d tackles (expressed as percentage of total tackle attempts) were higher in rugby league than rugby union (Table 5.9). The relative differences in mean percentage missed tackles per game appeared to converge in fhe 1997-99 Period, however, a slight divergence was noted in 2000-02 due to a continued reduction in missed t¿ckle percentage in rugby union (Figure 5.30). 20 6) Þ0 Gt 15 Ê (¡) O +RWbyLeagrc o¡r I 0 È --*- RugbY Union I 5 àti 0 1988-92 1993-95 1997-99 2000-02 Period Figure 5.30 Mean +SD percentages of missed tackles by Period by Code. 149 Significant Code differences were noted for the mean frequency of missed tackles per minute in both the pre- professional Era (t: 4.09, P < 0.0005) and the professional F;ra (t: - 2.71, P < 0.01) (Table 5.5). However a significant (t: - 5.57, P < 0.0005) Code difference was only identified on the 1993-95 Period, due to or corresponding with a greater frequency of tackles per unit time in rugby league in this Period (Table 5.5), indicating no converging ofthe Codes for this variable. 5.3.15 Lineouts A highly significant (Z : - 4.14, P < 0.0005) Era difference was noted for lineout frequency, with (on average) greater median game frequencies in the pre-professional Era than the professional Era (Table 5.6). A highly significant Era difference was also identified for median lineout frequency per unit time (Z = - 4.16, P < 0.0005), with greater frequencies in the pre-professional Era (one lineout every 29 s of ball in play time) than the professional Era (one lineout every 58 s of ball in play time) (Table 5.8). In addition, a highly significant Period (H3: 17.98, P < 0.0005) main effect was identified for the frequency of lineouts per game. Post-hoc analysis revealed the differences to be significant between 1988-92 and 1997-99 (Z: - 2.87, P < 0.002); 1988-92 and 2000-02 (Z: - 2.90, P < 0.002); 1993-95 and 199'1-99 (Z: - 2.89, P < 0.002) and 1993- 95 and 2000-02 (Z: - 2.90, P < 0.002), Most apparent lvas the large reduction in the median frequency between the 1993-95 and 1997-99 Periods, resulting in or corresponding to a large increase in actual ball in play time (Table 5.7). Analyses of these frequencies per unit time indicated a significant Period main effect (H3:17.67, P < 0.001), with post-hoc analyses revealing the differences to be significant between the Periods 1988-92 and 1997-99 (Z: - 2.88, P < 0.002); 1988-92 and 2000-02 (Z: - 2.88, P < 0.002); 1993-95 and 1997-99 (Z: - 2.88,P < 0.002) and 1993-95 and 2000-02 (Z = - 2.88, P < 0.002). 5.3.16 Kicking Ragby Uníon For the median frequency of total kicks per game a significant Era difference was identified (Z: - 3.2I, P < 0.001), with more kicks in the pre-professional Era than the professional Era (Table 5.6), representing a 22.5% decrease in mean frequency per game across the Eras. A similar significant Era difference was noted for the median frequency of kicks out of play per game (Z : - 3.96, P < 0.0005), with median frequencies also greater in the pre-professional Era than the professional Era (Table 5.6). The Era difference for the relative frequency ofkicks out ofplay (expressed as a percentage oftotal kicks) was identified as significant 150 (t : 2.93, P < 0.008), with median percentages per game greater in the pre-professional Era (48%) than the professional Er a (37 %). Significant Era differenoes were identified for total kicks per unit time (Z: - 4.16, P < 0.0005), kicks out of play per unit time (Z: - 4.76,P < 0.0005) and kicks in play per unit time (Z: - 2.54,P < 0.01) representing a kick being made every 21.1 s in the pre-professional Era compared to a kick every 36.7 s of ball in play time in the professional Era. Of these, a kick out of play was made every 45.5 s and kick in play every 41.8 s in the pre-professional Era compared to a kick out of play every 102.7 s and a kick in play every 60.5 s in the professional Era. A significant (&:12.46, P < 0.006) Period main effect was identified for the median frequency of total kicks per game, with post-hoc analysis revealing significant reductions in frequencies between the Periods 1993-95and7997-99(Z:-2.56,P<0.009)and1993-95and,2O0O-02(Z:-2.65,P<0.004).Forthe frequency of kicks out of play a signifrcant Q\: l7.l3,P < 0.001) Period main effect was identified, with post-hoc analysis ofthis effect revealing the differences to be significant between the Periods 1988-92 and 1997-99 (Z: - 2.89, P < 0.002); 1988-92 and 2000-02 (Z: - 2.67, P < 0.004); 1993-95 and 1997-99 (Z -- - 2.89, P < 0.002) and 1993-95 and2000-02 (Z = - 2.59,P < 0.009), reflecting a decrease in the frequency of kicks out of play per game in the Periods in the professional Era compared to the pre-professional Era (Table s.6). Significant Period main effects were identified for the median frequency of total kicks per unit time (l/3 : 77 .90, P < 0.0005) and the median frequency of kicks out of play per unit time (f13 : l7 .59, P < 0.001). Posl- åoc analyses indicated that the differences in the frequency of total kicks per unit time were between the Periods 1988-92 and 1997-99 (Z: - 2.89, P < 0.002);1988-92 and2000-02 (Z: - 2.89, P < 0.002); 1993-95 and 1997-99 (Z: - 2.88, P < 0.002) and 1993-95 and 2000-02 (Z: - 2.89, P < 0.002). Similarly, post-hoc analyses indicated that the differences in the frequency of kicks out of play per unit time were between the Periods 1988-92and1997-99 (Z: -2.89,P <0.002);1988-92and2}0}-02(Z: -2.90,P < 0.002); 1993-95 and1997-99(Z=-2.89,P<0.002)and1993-95and2000-02(Z:-2.90,P<0.002),reflectingadecrease in median frequencies per unit time in the professional Periods compared to the pre-professional Periods (Table 5.8). Rugby League No significant Era differences were identified for either the median frequency of total kicks or kicks in play per game. However, a signifìcant Era difference was noted for kicks out of play (Z: - 2.09, P < 0.04), with frequencies greater in the pre-professional Era than the professional Era (Table 5.6). A significant (Z: - 2.08, 151 P < 0.04) Era difference was also identified for the relative frequency of kicks in play and kicks out of play (expressed as a percentage), with 83% of all kicks kept in play in the pre-professional Era comparedro 89yo in the professional Era. No significant Period main effect was identifred for either the median frequencies of total kicks per game or kicks in play per game. However, a significant Period main effect was identified for the frequency of possession kicked out of play (ft : 14.75, P < 0.002). Post-hoc analysis of this effect revealed the differences in the median frequencies to be between 1988-92 and 2000-02 (Z = - 2.95, P < 0.002); 1993-95 and 2000-02 (Z: - 2.80, P < 0.004) and 1997-99 and 2000-02 (Z: - 2.95, P < 0.002), with frequencies significantly lower in 2000-02 than all other Periods (Table 5.6). The most notable changes (-29Yo\ were found to be between the 1988-92 and 1993-95, and 1997-99 and 2000-02 Periods (Table 5.7). A signifÌcant Period main effect was identified for the percentage distribution of kicks in play and kicks out ofplay (1/3: 13.89, P < 0.003). Post-hoc analysis indicated the differences to be between 1988-92 and 2000- 02 (Z :- 2.88, P < 0.002); 1993-95 and 2000-02 (Z : - 2.72, P < 0.004) and 1997-99 and 2O00-02 (Z : - 2.88, P < 0.002), with the median kick out of play percentage being lower in the 2000-02 Period (4.3%) than all previous Periods (19.5% in I 988-92, 7 4.8Yo in 1993 -95 and l7 .2Yo in 1997 -99). A significant (&: 13.62, P < 0.003) Period main effect for the median frequency of kicks out of play per unit time was identified (Table 5.8).Post-hoc analysis of this effect revealed the differences to be between 1988-92 and 2000-02 (Z: - 2.95,P < 0.002); 1993-95 and 20O0-02 (Z: - 2.62, P < 0.009) and 1997-99 and 2O0O-02 (Z: - 2.95, P < 0.002), with the frequency of kicks per minute being fewer in2000-02 than all other Periods (Table 5.8). No significant Period main effects were noted for the frequencies of kicks in play per unit time or total kicks per unit time. Comparìng the Codcs No signifrcant Code difference was identified for the median frequency of kicks in play in either Era, however, significant Code differences were noted for the frequencies of kicks out of play in both the pre- professional F;ra (Z: - 4.16, P < 0.0005) and the professional F,ra (Z: - 4.14, P < 0.0005), with frequencies greater in rugby union than in rugby league in both Eras (Table 5.6). A significant Code difference was also identified for median total kicks per game in both the pre-professional F;ra (Z : - 4.16, P < 0.0005) and the professional F;ra (Z : - 3.29, P < 0.0005), with frequencies greater in rugby union than in rugby league in both Eras (Table 5.6). 152 Significant median total kick frequency Code differences were identified in 1988-92 (Z : - 2.89, P < 0.002); 1993-95 (Z: - 2.89, P < 0.002); 1997-99 and 2000-O2 (Z: - 2.89, P < 0.02), with frequencies in all Periods being greater in rugby union than in rugby league (Figure 5.31). 100 rl. ËBo t ¡1. g ¡lc l60 +RWbyLeague ù E40 ----RugbYUnion tr920 0 1988-92 1993-9s 1997-99 2000-02 Period Figure 5.31 Median (Inter-quartile range) frequencies of total kicks per game by Period by Code. * significant Code difference P < 0.02. Significant Code differences were also identified for the median frequency of kicks out of play in 1988-92 (Z : - 2.89, P < 0.002); 1993-95 (Z= -2.89,P < 0.002); 1997-99 (Z: -2.82,P< 0.002) and2000-02(Z: - 2.96, P < 0.002), with frequencies in all Periods being greater in rugby union than in rugby league (Figure s.32). 50 tl¡ ¡1. (¡)Ë40 ,1. +RWbyLeagn èl¡o ,ß --r-RugbyUnbn .Ë 20 810à 0 1988-92 1993-95 1997-99 2000-02 Period Figure 5.32 Median (Inter-quartile range) frequencies of kicks out of play per game by Period by Code. * significant Code differenceP < 0.002. 153 Significant Code differences were identified for the median frequency of total kicks per minute in all Periods (Z : - 2.88, P < 0.002), albeit with the differences reducing across the four Periods, indicating a Code convergence for this variable (Figure 5.33). For kicks out of play per minute, Code differences were also noted in all Periods (Z : - 2.89, P < 0.002). Particularly notable were the large reductions in total kicks and kicks out of play per unit time in rugby union between the 1993-95 and 1997-99 Periods @igures 5.34). 4 t c.) * OJ tl. d.ã åI2(f) É :1. + RWby League ---r-RWbYUnion El.Ëå ¡là 0 1988-92 1993-95 1997-99 2000-02 Period Figure 5.33 Median (Inter-quartile range) frequencies of total kicks per unit time per game by Period by Code. * significant Code difFerence P < 0.002. 2 ¡1. {. e) É €) 1.5 é)Éd.= -+RWbyLeagw -li li * ¡1. 1 s{ÈËo ---al- Union 6) 0.5 Àlll 0 1988-92 1993-9s 1997-99 2000-02 Period Figure 5.34 Median (Inter-quartile range) frequencies of kicks out of play per unit time per game by Period by Code. * significant Code difference P < 0.002. ts4 5,3.17 Rucl¡s and mauls Rugby Union Highly significant Era differences ïvere identified for the combined ruck and maul frequency (Z -- - 4.16, P < 0.0005/, median ruck frequency (Z: - 4.16, P < 0.0005) and median maul frequency (Z: - 2.75, P < 0.005), representing percentage changes between Eras of +78.7o/o for ruck/maul frequency, +732.4yo for ruck frequency, and-30.9o/oformaulfrequency(Table5.7). Inaddition,asignificant(Z:-3.58,P<0.0005)Era difference was identifÌed for combined ruck and maul frequency per unit time, with a contact resulting in either a ruck or maul occurring every l7.2 s in the pre-professional Era compared to every 12.6 s in the professional Era. A significant (Z: - 3.81,P < 0.0005) Era difference was also noted for maul frequency per unit time, with a maul occurring every 53.9 s in the pre-professional Era compared to every 106.3 s in the professional Era (Table 5.8), representing a 92.7%o decrease between Eras. In addition, a signifÏcant (f : - 7.12, P < 0.0005) Era difference was identified for ruck frequency per unit time, with a ruck occurring every 26.6 s in the pre-professional Era compared to every 14.6 s in professional Era" representing a 45.1o/o increase between Eras. A significant Period main effect was identified for combined ruck/maul frequency (H3 : 19.06, P < 0.0005), reflecting an increase in the median frequencies across the four Periods. Post-hoc analysis of this effect revealed the differences to be significant (Z : - 2.89, P < 0.002) between the Periods 1988-92 and 1997-99;1988-92 and 2000-02; 1993-95 and 1997-99; and 1993-95 and 2000-02. A highly significant Period main effect was also noted for the frequency of rucks (H3 : 19.67 , P < 0.0005), with the median frequencies increasing across the four Periods (Table 5.6). Post-hoc analysis revealed the differences to be significant (P <0.002)between1988-92and1993-95(Z:-2.89,P<0.002);1988-92and2000-O2(Z:-2.89,P< 0.002); 1993-95 and1997-99 (Z: -2.90,P < 0.002) and 1993-95 and200O-02(Z: -2.90,P < 0.002). No significant Period main effect was identified for maul frequency; however, a notable decrease \Mas apparent across the four Periods (Table 5.6). Further analysis of the relative frequencies of mauls and rucks indicated a progressive increase in the preference for ruck engagement rather than maul engagement at the breakdown across the four Periods (Table 5.6), with the most notable change between the Periods 1993-95and 1997-9 reflecting a 7 5Yo increase in rucks and a 2O%o decrease in mauls (Table 5.7). A significant Period main effect was identified for the median frequency of combined rucks and mauls per unit time (H1:13.95, P < 0.003). Post-hoc analysis of this effect revealed the differences to be signifrcant betweenthePeriodslgsS-92and1997-99(Z=-2.57,P<0.009);1988-92and2000-02(Z:-2.57,P< 155 0.009) and 1993-95 and 2000-02 (Z: - 2.56, P < 0.009), representing an increase in ruck/maul frequency across the Periods. A signifrcant Period main effect was also identified for the median frequency of rucks per unit time (Ft, zo : 20.08, P < 0.0005), vøth post-hoc analysis of this effect revealing the differences to be significant between the Periods 1988-92 and 1997-99 (P < 0.006); 1988-92 and 2000-02 (P < 0.0005);1993- 95 and 7997-99 (P < 0.0005) and 1993-95 and 2000-02 (P < 0.0005), representing a gradual increase in rucks per minute across the four Periods (Table 5.8). In addition, the Period main effect for mean maul frequency per unit time was significant (Hz: 16.29, P < 0.001), *vrth post-hoc analysis of this effect revealing the differences to be significant between the Periods 1988-92 and,1997-99 (Z: - 2.72, P < 0.004); 1988-92 and 2000-02 (Z: -2.88,P < 0.002) and 1993-95 and 2000-02 (Z: -2.88,P < 0.002), reflecting a gradual decrease in the frequency of mauls per minute across the Periods (Table 5.8). Rugby League No significant Era difference was identified for either ruck frequency or ruck frequency per unit time. No significant Period main effects were identified for either ruck frequency or ruck frequency per unit time, although the frequencies per minute in the professional Periods were notably higher than in the pre- professional Periods (Table 5.8). Compañng the Codes Significant Code differences were identified for median ruck frequency and frequency per unit time in both Elras (Z: - 4.16, P < 0.0005). Significant median ruck frequency Code differences were also identified in all Periods (Z: - 2.89,P < 0.002), with frequencies greater in rugby league than in rugby union. Analysis of the relative ruck frequencies indicated a convergence of the Codes, ostensibly due to increases in median frequencies in rugby union compared to a more consistent profìle in rugby league @igure 5.35). 156 t 350 à1. ¡f ¡1. f :oo Ë 2so S zoo +RWbyLeagn É 150 -+- Rugby Unbn GI E 100 0 1988-92 1993-95 1997-99 2000-02 Period Figure 5.35 Median (Inter-quartile range) frequencies of rucks per game by Period by Code. * signifrcant Code difference P < 0.002. A significant (Z: - 2.29, P < 0.002) Code difference was also noted for the frequency per unit time in all Periods except 2000-02, indicting a convergence ofthe Codes, mainly corresponding to greater changes in rugby union than in rugby league across the four Periods (Figure 5.36). 8 ¡N. c) ¡1. * {Jb u.ã .È-4é)É +RWby tæagr¡e g€) ñÈ --+ Rugby Union .õ1 qjlL Åra 0 1988-92 1993-9s 1997-99 2000-02 Períod Figure 5.36 Median (Inter-quartile range) frequencies of rucks per unit time per game by Period by Code. * significant Code difference P < 0.002. 157 5.3.18 Scrums Rugby Union No significant Era difference was noted for the median frequency of scrums per game. However, a significant (Z -- - 2.71, P < 0.006) Era difference was identified for the median frequency of scrums per unit time, with a scrum occurring once every 48.0 s in the pre-professional Era compared to every 64.9 s in the professional Era. This represented a35.2Yo reduction in the frequency of scrums per unit time between Eras. No significant Period main effect was identified for the median frequency of scrums per game. However, a significant Period main effect was identifìed for the frequency of scrums per unit time (I/s = 12.99, P < 0.005). Post-hoc analysis ofthis effect revealed the differences to be significant between the Periods 1988-92 and2000-02 (Z: - 2.88, P < 0.002), with fewer scrums per unit time in the 2000-02 Period (Table 5.8). Rugby Leøgue No signifïcant Era difference of Period main effect was identified for scrum frequency or frequency per unit time. However, a notable (30% decrease) was apparent across the four Periods. Comparíng the Codes In the pre-professional Era significant Code differences were identifìed for median scrum frequency (Z : - 3.53, P < 0.0005) and frequency per unit time (Z: - 4.16, P < 0.0005), with 29.5 scrums (one every 48.0 s) in rugby union compared to 18.4 (one every 171.9 s) in rugby league. In the professional Era significant Code differences were also identified for median scrum frequency (Z: - 3.73, P < 0.0005) and median scrum frequency per unit time (Z : - 4.76, P < 0.0005) with 28.0 scrums in rugby union (one every 64.9 s) compared to 16.4 (one every 177.0 s) in rugby league (Table 5.6 and 5.8). Signifrcant scrum frequency Code differences were also identified in all Periods; 1988-92 (Z: - 2.81, P < 0.002); 1993-95 (Z: - 2.79, P < 0.03); 1997-99 (Z: - 2.57, P < 0.009) and2000-02 (Z: - 2.89, P < 0.002), with median frequencies greater in rugby union than rugby league in all Periods (Figure 5.37), reflecting a relatively stable Code difference in median scrum frequencies across the four Periods. 158 50 r& >ì g40 ¡f í) {. * F¡O +RWbyLeagæ .L -+RWbYUnion .Ë 20 E Å€10 0 1988-92 1993-9s 1997-99 2000-02 Period Figure 5.37 Median (Inter-quartile range) frequencies of scrums per game by Period by Code. * significant Code difference P < 0.03. Significant Code differences were identified for the median frequency of scrums per unit time in all four Periods (Z: - 2.88, P < 0.002), reflecting a convergence of the Codes, ostensibly due to a decrease in frequencies per unit time in rugby union and a relative stability in rugby league across the four Periods (Figure 5.38). ¡f 2 >ì rF c) * l.s õ {. d.= €)Á -+RWby læagrr ÈI I ñÈÉe) ---RWby Union E o.s Å!r 0 1988-92 1993-9s 1997-99 2000-02 Period Figure 5.38 Median (Inter-quartile range) frequencies of scrums per minute by Period by Code. * significant Code difference P < 0.002. 159 5.3.19 Set Possession Rugby Unìon A significant Era difference was identifred for set possession frequency (Z: - 3.15, P < 0.001), with median frequencies higher in the pre-professional Era than the professional Era (Table 5.6). A significant Era difference was also noted for median set possession frequency per unit time (Z: - 4.16, P < 0.0005), with 5.9 sets per minute in the pre-professional Era compared to 4.0 sets per min in the professional Era (Table 5.8). In addition, a significant Period main effect for set possession frequency was also identified (H3:10.16, P < 0.02), withpost-hoc analysis of this effect indicating the differences in frequencies to be significant between the Periods 1993-95 and 1997-99 (Z: - 1,93, P < 0.002) and 1993-95 and 2000-02 (Z: -2.58, P < 0.004), frequencies being fewer in both the professional Periods (Table 5.6). A significant Q\: 18.42, P < 0.0005) Period main effect was also identified for median set possession frequency per unit time, with post-hoc analysis indicating the differences to be between the Periods 1988-92 and 7997-99 (Z: - 2.88, P < 0.002); 1988-92 and 2000-02 (Z: - 2.88, P < 0.002); 1993-95 and 1997-99 (Z: - 2.89, P < 0.002) and 1993-95 and 2000-02 (Z : -2.88, P < 0.002), reflecting a gradual decrease in the median frequency of set possessions per unit time across the four Periods (Table 5.8). Rugby League In rugby league no significant Era difference or Period main effect was identified for either median set possession frequency or median set possession frequency per unit time, nor v/ere any obvious trends in the data apparent, reflecting the stability ofthese variables across the Eras and four Periods. Compañng the Codes Significant Code differences were identified for median set possession frequency in both Eras (Z: - 4.16, P < 0.0005), with frequencies greater in rugby union than rugby leagrre in both Eras (Table 5.6). Significant Code differences were also noted for set possession frequency per unit time (Z: - 4.16, P < 0.0005), with the frequency per unit time reducing across the Eras from 5.9 to 4.0 in rugby union compared to a small increase (1.6 to 1.7) in rugby league (Table 5.8). Significant Code differences were also identified for the median set possession frequency in all Periods (Z: - 2.89, P < 0.002), with frequencies greater in rugby union than in rugby league in all Periods (Table 5.6). Whilst between the 1993-95 and 7997-99 Periods a l2.3Yo reduction in set possession frequency was noted in rugby union, the reductions in frequencies in both Codes across the 160 four Periods were similar (Table 5.6), hence, a Code convergence u/as not apparent for this variable (Figure 5.3e). â& ,F 150 * tl. CJ É c) ã 1 00 6) --+-RWbyLeague ù --t- Union 6l 50 6) Åli 0 1988-92 1993-95 1997-99 2000-02 Period Figure 5.39 Median (Inter-quartile range) set possession frequencies per game by Period by Code. * signifïcant Code difference P < 0.002. Significant Code differences were identified for median set possession per unit time in all fou¡ Periods (Z: - 2.89, P < 0.002), with frequencies greater in rugby union than rugby league (Table 5.8). However, the large reduction in median frequencies per unit time in rugby union matched against more consistent values in rugby league across the four Periods is indicative of a converging of the Codes for this variable, with rugby union becorning more similar to rugby league in the professional Periods (Fþre 5.a0). 7 tf rlr >¡ c) 6 É ¡1. o 5 :1. E.= oEt 4 -+RWbyLeagræ ùi a É€) J _r- RwbY Unbn ¿ri È 2 r-6) À 1 0 1988-92 1993-95 1997-99 2000-02 Period Figure 5.40 Median (Inter-quartile range) set possession frequencies per unit time by Period by Code. * significant Code difference P 161 5.3.20 ActivityÆhases Rugby Uníon A highly significant Era difference was identified for median activity/phase frequency (Z : - 3.85, P < 0.0005), with frequencies greater in the professional Era than the pre-professional Era (Table 5.6). However, no significant Era difference was noted for activity/phase frequency per unit time (Table 5.8), indicating the increase in the activity/phase frequency across the Eras was ostensibly due to a concomitant increase in ball in play time (Table 5.1). A significant Period main effect was identified for median activity/phase frequency (& -- 77.23, P < 0.001), w\th post-hoc analysis indicating that the differences were significant between the Periods 1988-92 and1997-99 (Z= -2.73,P < 0.004); 1988-92 and2000-02 (Z: -2.69,P < 0.002);1993-95 and1997-99 (Z : -2.34, P < 0.02) and 1993-95 arrd 2000-02 (Z : -2.75, P < 0.004), reflecting an increase in median aøivity/phase frequency across the four Periods (Table 5.6). However, no significant Period main effect was identified for activity/phase per unit time (Table 5.8), again indicating that the frequency changes were a reflection of changes in ball in play time rather than changes in the pattern of play. Rugby Leøgue In rugby league no significant Era difference or Period main effect was identified for either activity/phase frequency or activity/phase frequency per unit time, reflecting the stability of these variables across the Eras and four Periods. Comparíng the Codes Significant activity/phase frequency Code differences were identified in both Eras (Z: - 4.16, P < 0.0005), with median frequencies greater in rugby league than rugby union (Table 5.3). For the frequency per unit time, a significant (Z: - 3.70, P <0.0005) Code difference v/as identified in the pre-professional Era only. Significant median activity/phase frequency Code differences were also noted in all four Periods; 1988-92 (Z = -2.89, P < 0.002); 1993-95 (Z: -2.90, P 2.89, P < 0.002), with frequencies greater in rugby league than rugby union in all four Periods, albeit with a reducing difference across these Periods (Figure 5.41) Analysis of the percentage change in this variable (Table 5.7) indicated that the changes across the four Periods were predominantly due to increases in rugby union rather than decreases in rugby league. 162 500 {. I ¡1. É 400 ¡r {. Q) 300 -{- RWby Leagæ år ---r-RugbyUnion cìl 200 õ 100 Å= 0 7988-92 1993-95 1997-99 2000-02 Period Figure 5.41 Median (Inter-quartile range) activity/phase frequencies per game by Period by Code. * significant Code differenceP < 0.002. For activity/phase possession frequency per unit time significant Code differences were only identified in 1988-98 (Z: - 2.41, P < 0.002') and 1993-95 (Z: - 2.74, P < 0.004); however, the frequencies per unit time were found to be greater in rugby union compared to rugby league in all four Periods (Table 5.8). The stability of both rugby union and rugby league profiles indicated the convergence noted for the median activity/phase frequency was predominantly influenced by changes in ball in play time rather than changes in playing pattern (Fþre 5.a2). Ë 1 2 ¡i {. {. (u È I 0 c¿ 8 Ê í) +- RWby Leagrc 6 o) ---|-RWbY Union r¡i¡- 4 E 6 2 'lJ(¡) =à 0 1988-92 1993-9s 1997-99 2000-02 Period Figure 5.42 Median (Inter-quartile range) activity/phase frequencies per minute per game by Period by Code. * significant Code difference P < 0.004. 163 5.4 Discussion 5.4.1 Total ball in play time The greater total ball in play time in rugby league than rugby union can be easily explained in terms of the different game strategies. In rugby union, the use of the kick to gain territorial advantage at the expense of possession has been a common strategy. However, in rugby league with possession almost guaranteed at the ruck, and a greater separation of teams (minimum of 5-m pre-1993 and 10-m post-1993), a greater handling game has evolved over time, with less emphasis being placed on the kicking aspect of the game. In rugby union, the teams are only separated to any extent at the lineout (opposing backs being a minimum of 20 m apart). This makes the running game in rugby union more diffrcult since there is usually less space between the teams than in rugby league. As such, in deep defensive field positions it was ofren advantageous to kick the ball out ofplay, since in the pre-professional Periods (prior to the acceptance of'supporting' and 'lifting') the lineout was fully contested, that is to say, both teams attempted to gain possession from the throw in. Hence, there was a possibility of securing possession from the opposition throw a result less likely in the professional Periods, with fewer lineouts being contested. Hands (2002) suggested that the law change allowing 'supporting' and 'lifting' in the lineout would result in this effect, a fact which was confirmed by Martir¡ Thomas et al. Q00l) who reported that nearly half of all lineouts in the Tri Nations and Six Nations rugby in 1999-2000 were uncontested. Across time (1988-2002) there has been a convergence of the Codes with respect to ball in play time; times reducing slightly across the four Periods in rugby league and increasing over the same time frame in rugby union (Figure 5.1). These times in rugby union were found to be signifïcantly different between all Periods in different Eras. However, the ball in play times in the present study are not consistent with ball in play times reported in previously published studies. Calculations based on the raw data presented by Mclean (1992) indicated the percentage ball in play time was 36%o. This represented a figure lÙYo greater than the flndings of the present study (Table 5.1). However, Mclean's (1992) results are flawed in that the time spent in scrum preparation should not be included, as the ball is not deemed 'in play' until the scrum commences. In addition, the relatively high frequency of scrum collapses and time in preparation in this Period would be likely to inflate severely the ball in play times reported by Mclean (1992).It must also be noted that the ball in play percentages for the Period 1988-92 in the present study were also lower than those reported by Treadwell et al. (1991\ and Minchinelli et al. (1992). The former reported percentage ball in play times of 164 28.3o/o (New Zealand tour of Wales 1989),32.0yo @ritish Lions v Australia 1989), 30.5% (Five Nations Championships 1991) and29.9Yo (New Zealand v British Lions 1991), whilst the latter suggested ball in play times of 3lYo for Five Nations rugby in 1986. A more comprehensive analysis of Five Nations rugby by Potter (1997) reported ball in play times - when expressed as percentages - were higher in 1989/90, 1993 and 1994 than found in the present study. Whilst Potter's (1997) results are year-specifïc, and it is accepted that in the present study the four-year Period 1988-92 analysed may make comparisons difficult (due to individual year differences not being analysed), the same is not true of the 1993-94 results presented by Potter (1997). A mean percentage ball in play time for 1993 and 1994 from Potter (1997) can be compared directly with the results from the Period 1993-5 in this study. Here again Potter's results (31.5yù appear inflated in comparison to the 26.9% established in this study. However, in three of the four games analysed by Potter (1997) the ball in play percentages were found to be less than 30%o. This indicates that an abnormally high ball in play time which occurred in one game had a marked effect on the overall mean score, and perhaps should have been considered as an outlier in the data (or the average represented as a median). It is likely that such an extreme value would result in these data not presenting a normative profile within the four games analysed, and as such would not be considered a stable representation ofthis variable. In addition to the analyses of Five Nations rugby, Potter and Carter (2001a) reported time in play for the 1995 World Cup. Again calculations based on the raw data presented by these authors showed their estimates of ball in play time (33.8% for Home Union teams) to be greater than in the present study. These results - based on estimated game times of 80 minutes (no reported total game time by Potter and Carter, 2001) - mean that this figure is likely to be inflated, since any additional time played would automatically reduce the ball in play percentage. As a consequence, it is suggested that the percentage ball in play times reported in this study are more indicative of the true game profiles for these Periods. The ball in play times for rugby union were found to be significantly less than in rugby league in all Periods, albeit with a decreasing Code difference across the four Periods. This decrease in the time differences was predominantly due to the increased in ball in play time evident across the Periods in rugby union, rather than decreases in rugby league. The most notable change occurred between the 1993-95 and 1997-99 Periods, with an I8.9Yo increase in ball in play time in rugby union. This was predominantly due to a change in kicking strategy, that is, between these two Periods there were significant decreases in the frequencies of all kicks; in particular kicks out of play (-5|%)(Table 5.7). This reduction is more pronounced when one considers this variable normalized to ball in play time, with a touch kick (on average) being made every 46 s in 1993-95 compared to every 111 s in the 1997-99 Period (Table 5.8). This change possibly reflects law changes at the lineout in the professional Periods; allowing players to be initially 'supported' and 165 in later years 'lifted'. As a consequence, the lineout became less contested. This view was purported by Thomas and Williams (2001), who reported that Wales contested only 5 out of a possible 137 lineouts in 1999-2000. Williams, Hughes et al. (2005, p. 8) suggested that lineouts Laws introduced in 2000 and 200I were designed to 'speed the game up and improve continuity and competition'. Speciflrcally, these stopped the 'huddle' occurring before the lineout, howeveç subjective assessment of recent games (2006) has seen the re-emergence of this tactic, most notably by England. Accordingly, the law changes at the lineout appeared to have an immediate effect, Williams, Hughes et al. (2005) reporting ball in play time increased from34.3Yo in 1999 to 35.9Yoin2002. These compare favourably to the results of the present study (31.9% in 1997-99 and35.0Yo in 2000-02). In addition to the Law amendments, the increase in ball in play time was likely to be a reflection of the changes in player fitness across the four Periods. Duthie et al. (2003, p.973) suggested that the move to professional rugby has 'elicited rapid changes in the fitness profile of elite players'. In contrast, in the pre-professional Era Coaches and players were ostensibly 'amateur', with Hands (19SS) referring to thejob ofcoaching England as a'hobby'; all three coaches in 1988 (Cookg Elliot and Uttley) having full-time work outside of rugby. In rugby league the l0.7Vo reduction in ball in play time across the four Periods was predominantly due to the large reduction between the 7997-99 and2000-02 Periods (Table 5.2). The most likely explanation for this effect is the introduction of the 40-20 rule in 1999. This rule gives the 'head and feed' at the scrum when a player kicks the ball from inside his own 40-m line to touch (not on the full) inside his opponent's 20-m line; a rule which seemingly encourages kicking the ball out of play. However, the data from the present study revealed that the frequency of kicks out of play between these Periods fell by 77.60/o (Table 5.7). The likely explanation of this effect is much simpler- the change in timing method from using 'extra-time' to the stop clock method and the introduction of an external time-keeper. In rugby union it has been shown that even top International referees make very large errors in time-keeping. Carter and Potter (2001a) cited the examples of Steve Lander playing nearly two minutes of injury time, but still calling no side 10 s short of the regulation 80 minutes of play, having played only 37 min 35 s in the first half. Similarly, George Gadjovich ignored 2 minutes of extra time in the New Zealand versus Japan game, perhaps out of sympatþ for the Japanese points against tally in this record New Zealand score (Carter & Potter, 2001). The same circumstance is likely in rugby league, In 2001, a further amendment was made to the rules of the game making the sound of the hooter the definitive signal for the end of the game; taking away the decision from the referee, who previously could allow play to continue beyond the full time hooter. 166 5.4.2 Ruck time Mean ruck times were found to be less in rugby union than in rugby league in all four Periods (Figure 5.2), reflecting the faster ball re-cycling in the union Code. In rugby union mean times in the 1988-92 Period were found to be significantly lower than in all other Periods (Table 5.l), particularly the 1993-95 Period (20.4% increase in mean ruck times on the previous Period) (Table 5.2). In subsequent Periods, perhaps due to the introduction of the 'use it or lose it' law in the maul in 1992-93, the ruck became more dominant. This change at the breakdown is highlighted by the 41.4o/o increase in ruck frequency and ll.6Yo decreases in maul frequency across the 1988-92 and 1993-95 Periods (Table 5.7) In the post-1988-92 Periods it appears more common practice for teams under pressure to attempt to slow the ball at the ruck to ensure greater control. Consequently, in these Periods the mean times are greater due to this style of play, a problem confirmed by later law changes at the ruck (Figure 1.1) According to Williams, Thomas et al. Q005) the change in the Laws governing the ruck introduced by the IRB in 1999, which were designed to prevent slowing down the quick recycling of the ball, should have resulted in faster ruck ball. However, the result from the present study suggest that ball recycling speed was not increased (mean ruck times being 3.1 s in both Periods spanning 1999) (Table 5.1). One might also expect a decrease in ruck time in the post-2000 Period, with the amendment to Laws governing the 'squeeze ball' at the ruck (Laws 14.1 and 15.6 d). This law change which required players to present the ball immediately, again did not result in changes in ball recycling time. Hence, two laws implemented in an attempt to speed up the ruck appears to have no impact on this aspect of the game. The importance of controlling the 'play the ball' time in rugby league cannot be understated. A discussion between the then BBC commentary team of Ray French, Jonathan Davies and Joe Lydon at the 1998 Challenge Cup Final provides some insight into the aspect of the game. Ray French quoting John Kear stated "Ifyou can stretch the time ofthe 'play the ball' from three seconds to four seconds you can get your men back in defence." Joe Lydon continued "Just one second difference might be three steps in defence as you are going backwards to set your line." Jonathan Davies concluded "That little second extra gives you a couple of yards to organise your defence". Clearly, the 'play the ball' time was, and still is perceived as crucial to both offence and defence. In rugby league, the mean ruck times were much greater in the 1988-92 Periods compared to all other Periods (Figure 5.2), with the g¡eatest change occurring between 1988-92 and 1993-95 Periods (18.6% reduction) (Table 5.2). This change was probably due to the introduction of the 10-m rule in 1992-93.Pnor to this rule change, defence lines were required to retreat only frve metres from the ruck. Hence, defences 767 were usually well organised and quick to form, and as such there was no real advantage to the attacking team attempting to 'play the ball' quickly. In a basic coaching textbook of the time @amford, 1989) the coverage of the 'play the ball' prior to 1993 was merely technical; no mention is made of any tactics at the 'play the ball'. However, in later texts (Kear, 1996; Smith, 2002) statements were made regarding the tactical importance of this aspect of the game. Kear (1996, p.64) stated "Players must realise that a ball which is brought slowly back into play allows the defence time to retreat the required distance and re-group". He added "A fast 'play the ball' is likely to catch the defence out of position and moving backwards". Hence, the introduction of defences having to retreat l0 m had two basic effects that enhanced the importance of the 'play the ball'. Firstly, defences took longer to retreat and reform, giving the offence an oppofunity to attack a disorganised defence, if they were able to re-cycle the ball quickly. The second important factor was the space between the teams. The increased separation enabled a more direct attack from the ruck by the dummy- half, or from other players playing close to the ruck. In the subsequent Periods mean ruck times continued to fall, with teams attempting to increase the speed of the 'play the ball'. However, between 1997-99 and 2000-02 the trend was reversed; mean ruck times increased (Table 5.1). The results from the present study on defence actions may shed light on this change. In Ihe 7997-99 Period 47.3Yo of all tackles were completed by a lone tackler, whereas in 2000-02 this reduced to 40.5o/o, indicating an increase in double and mob tackles (Table 5.9). Hence, with more players in the tackle the resultant 'play the ball' was slowed. This is complicated as it can be an advantage to both offences and defences. From an oflence viewpoint, attracting more players to the tackle creates space if an offload can be completed. Additionally, teams may have adopted the Australian strategy which was identified by Clarke (as cited in O'Hare, 1995). This strategy involved the attacker attempting to remain on his feet, thus attracting more defenders into the tackle. He would then immediately fall to the ground, play the ball quickly. This enabled other attackers to exploit the space creaTed. Clarke (as cited in O'Hare, 1995) noted that Australian attackers remained on their feet for (on average) 0.63 s longer than British attackers. In recent times, in the British game, a similar strategJ has evolved, whereby attacking players drive low into the defender and immediately fall to ground (very similar to an illegal voluntary tackle), enabling a quick 'play the ball' and subsequent attack against a retreating defence. From a defence viewpoint, increasing the number of players in the tackle means the 'play the ball' is slowed since each tackler is given time to move off the tackled player. A further tactic employed in more recent times is turning the tackled player onto his back (know as the 'turtle'), turning him to face his own team, or attempting to fall underneath the tackled player. Again this provides the defence with a small 168 amount of extra time to reform, since it takes the tackled player longer to get into the correct position to 'play the ball'. According to Smith (2002), players must practice all tackle techniques and try to come up with 'other quirky little ideas' (p.5), aimed at controlling the ruck area. In 2001, the rules governing the 'play the ball' were made stricter; to prevent defences interfering and slowing the'play the ball'. The results of this study, however, indicate this rule change had little impact, since mean ruck times actually increased (non-signifïcantly) between 1997-99 and 2000-02. One limitatíon of the current study was the analysis of the ruck time being taken from tackle completion only and not including the timing of initial contact to tackle completion. It is therefore recommended that future researchers examine the time from initial contact to the time of tackle completion, as well as the time of the subsequent of the 'play the ball', since this will give a better indication of the speed of play and the tactics employed at the ruck area. The growing dominance of the ruck in rugby union is highlighted by the increases in the percentage of total time engaged in this breakdown activity. The increase in the total time players are engaged in the ruck greatly outstrþs the concomitant increases in 'ball in play' time. In the 2000-02 Period more than 25o/o of the ball in play time v/as taken up with ruck activity. Whilst this appears a large proportion of the total game time, it is notably less than the 3L5%o in rugby league for the same Period. The total ruck time percentage in rugby league football was relatively stable across the four Periods, with only the 37.6yo in 1988-92 being significantly greater than all other Periods. The large reduction in total ruck time between 1988-92 and 1993- 95 reflects the decrease in mean ruck time due to tle implementation of the l0-m offside rule. 5.4.3 Activity time Mean activity times were found to be very similar in both Codes across the four Periods, with significant Code main effects only identified in the 1988-92 Period. This differencÆ was due to a significantly higher mean activity time in rugby union in this Period compared to all other Periods (Table 5.1). One explanation of this effect is the inclusion of maul time in the timing of activity. The frequency of the maul was gteater in this Period than all other Periods, reducing by lI.6% between 1988-92 and 1993-95 (Table 5.7). This reduction is very similar to the reduction in mean activity time (9.6%) between the same Periods, indicating that the change in playing pattem regarding the breakdown had a significant effect on the mean activity time. In addition, the reduction in mean activity time across the four Periods may also be a reflection of a faster game and a game played closer to the breakdown in that the reduction in mean activity time reflected the move away from the more maul-dominated game towards a faster ruck-style game. 169 In rugby league, no significant Period main effects for mean activity time were identified, indicating the relative stability of this variable across the four Periods. This stability in mean activity time is reflective of the more predictable playing pattern in this Code of rugby. However, the change in mean activity time between 1988-92 and 1993-95 is worthy of note. The mean increase of 0.4 s across these Periods is less than would be expected, since after 1993 the 10-m offside was expected to be advantageous to the attacking side, giving them more time and space to exploit. This non-significant change in activity time, therefore may indicate a change in playing strategy. This was twofold. Firstly, in offence, teams attacked closer to the advantage line, a fact highlighted by Anderson (2002a), who stated that since the introduction of the lO-m rule his teams attempt to create space by earning it þlaying a flat line offence) rather than getting back behind the advantage line (running from deep). Prior to this rule change teams attacked from deeper rather than employ a flat line attack (Anderson, 2002a). Secondly, to reduce the space between the teams, defences adopted a more attacking approact¡ moving more quickly into the tackle. Bayliss (2002) suggested that it is essential to limit the time and space of the opposition thus reducing their attacking options. Smith (2002) similarly suggested the role of the marker is fundamental in moving to make the tackle on the advantage line, and turning the player onto his baclq in an attempt to slow the subsequent 'play the ball'. Considering these tactical changes in offence and defence, the small increase in mean activity time across these Periods is less perplexing. For total activity time a convergence of the Code was identified across the four Periods (Figure 5.5). The convergence of this variable across the Periods was predominantly due to increases in total activity time in rugby union, increasing (on average) I 1.3% between each ofthe Periods 1993-95 and 1997-99, and 1997-99 and 2000-02 (Table 5.2). These increases match closely to the increases in the frequencies of activity/phases (Table 5.7), indicating the increases in this time va¡iable were a result of mean activity frequency increases across these Periods. 5.4.4 Set possession time The significant (but reducing) Code difference in set possession times across the Eras and Periods v/as not surprising. These changes were predominantly due to increases in set possession time in rugby union, rather than decreases in rugby league (Figure 5 6) The stability of set possession time in rugby league reflects the finite number of possessions per set, compared to the less constrained number possible in rugby union. In rugby union the significant difference identifìed in mean set possession between the Eras indicates clearly that in the professional Era teams were able to maintain possession longer in each phase of play than r70 in the pre-professional Era. Further analysis of this variable indicated that teams in the professional Era were in activity for approximately 48Yo longer between game stoppages (recovery periods) compared to teams in the pre-professional Era. Period analysis of this time variable highlighted an upward trend in mean set possession time from 1988-92 to 2000-02, the most notable and significant difference being between the Periods 1993-5 and 1997-99; a35.4Yo increase (Table 5.2). The results of the passing analysis in this study (Table 5.5) indicated the game is becoming less open, being played closer to the breakdown situation. As a consequence, possession rather than territorial advantage has become more important to teams in the professional Periods. The increases in ruck frequency and concomitant reduction in maul frequency are also indicative of the greater emphasis on possession. This relationship between the game being played close to the ruck and possession was identified by McKenzie e/ al. (1989), who reported that possession retention showed an inverse relationship with distance from the previous breakdown. Hence, in this style of play, it would be expected that mean activity times would be reduced and the frequency of individual activities would increase between these Periods; facts established in the present study. Interestingly, Corris Thomas's (IRB Centre, IJWIC) analysis of the 2005 Autumn internationals showed that open play passes are becoming less frequent, agun indicating a less open game style (personal communication 12m December, 2005). With the increases in set possession time across the Periods in rugby uniorl the implications for the physiological game demands must be considered. It is probable that the anaerobic demands of the game have increased due to the increases in the frequency of ruck engagements and contact situations (tackles). As a consequence, it would be expected that blood lactate levels would be elevated, particularly in forwards, who have been shown by Deutsch et ø1. (1998) to have lactate levels of 6.6 mmolll compared to 5.1 mmol/L in backs. The increases in set possession time and continuous ball in play time (reported earlier) indicate the need for increased periods of recovery so that blood lactates can be metabolised and ATP-PC stores replenished. Insufiïcient recovery will result in impaired performance which is likely to be more apparent in the latter stages ofthe game, due to elevated blood lactates and incomplete restoration ofphospho-creatine stores. Such changes in blood lactates in forwards ìvere reported by Mclean (1992), who measured higher lactate concentrations after 30 minutes of play compared to 15 minutes of play. These values and the post- game concentrations ranging from 5.8-9.8 mmol/L were recorded in games where the mean ruclc/maul frequency was 73, a count consistent with the combined value of 71 in 1988-92 found in the present study (Table 5.6), but notably less than 127 and 154 for the Periods 1997-99 and 2000-02, respectively. The implications are clear; without suffrcient recovery periods, players' - particularly forwards - performances may be affected. The results from the current study suggest that strategies are already being employed to 171 facilitate increased periods of recovery. Whilst ruck frequencies have increased across the four Periods by 41.4yo,74.4Yo and 27.9% the forwards increases in ruck activity are only 36.1yo,9.7Yo and 9.7Yo respectively. Over the same Periods the backs ruck activity has increased by 240Yo, l53Yo and l05o/o, respectively @aves, 2006). Whilst these values appear extreme, this is due to the relative low frequency of ruck engagements by backs in the pre-professional Periods. However, this provides an illustration that the workload at the breakdown (ruck/maul) is being more evenly shared thus enabling greater recovery time for players in professional rugby. The sharing of workload is more obvious in rugby league; props and second row players in particular are regularly interchanged. This is imperative as these players predominantly work carrying the ball in the 'hit up', ancl often have the highest tackle counts (Gabbett, 2005). The rotation of players away from the contact situation is also easier in the league Code, due to the ruck being non-contested. It is therefore more likely that player workloads are more evenly distributed. Meir et al. (1993) suggested that rugby league is a more interval-like activity, with 5 s bursts of intense activity followed by 30 s of recovery for forwards and 40 seconds for backs. Hence for forwards, the replenishment of the ATP-PC system is unlikely to be complete before the next bout ofexercise. Glaister (2005) suggested that recovery from 5 - 6 s sprint bursts is impaired if there is insuffrcient recovery time to remove accumulated lactates and inorganic phosphates and re- synthesise ATP. The performance during subsequent bouts of intense exercise are therefore likely to be compromised, hence, there is a need for regular player interchanges. At Australian amateur and junior levels such interchanges are unlimited; however, in professional rugby leagr.re football only 12 interchanges per game are permitted. The introduction of the 'zero tackle' law in summer rugby league has placed greater emphasis on the backs to carry the ball into the tackle (Gissane et al,, 1998). This law allows the first tackle from a kick - often received by wings or full backs - to not be counted as the first tackle, effectively allowing an extra tackle per set. Interestingly, this has had little impact on the set possession time in rugby league, although a,3.7Vo decrease was observed in the change to summer rugby (Table 5.2). Between the previous Periods a small (4AW increase in set possession time was identified, which may be due to the introduction of the l0-m rule in 1992-93. This change from the defence having to retreat l0 m rather than 5 m at the ruck resulted in an increase in distance travelled by players and an increase in high intensity activity by forwards, indicating this rule change placed greater stress on players, particularly forwards (Meir, Colla et ø1., 2001). Moreover, they suggested that the reduction in work: rest ratios was due to this rule change and added that this did not mean an increased demand on aerobic mechanism, but a need for greater and more frequent recovery periods. 172 5.4.5 Continuous possession time Significant continuous possession time Code main effects were established in all four Periods, with continuous possession time greater in rugby league than rugby union (Figure 5.7). These greater times in the league Code are indicative of the less contested breakdown situations compared to rugby unìor¡ and the rules governing possession in rugby league (six tackles). As a consequence, the continuous possession times in rugby league are more stable across the four Periods than in rugby union, with the only discrepancy noted in the 1997-99 Period, when times fell from 55 s to 47 s (Table 5.1). In the subsequent Period times again rose to 56 s. This reduction in continuous possession time after the introduction of summer rugby league, is possibly due to the physiological considerations mentioned previously, but may also reflect a speeding up of the game; teams completing sets more quickly. The results of the set possession analysis support this. However, the reduction in set possession times across these Periods was very small (3.7%). The subsequent rise in continuous possession time may also be due to the introduction of the 40-20 rule; successful teams being rewarded with possession from an accurate touch kick. Whilst kicks out of play across these Periods decreased and the relative frequency of 4O-20 kicks were low, they must have impacted on the overall mean scores for this time variable. In rugby union, significant Era main effects were observed for this variable, with times greater in the professional Era compared to the pre-professional Era. Continuous possession time also increased across the four Periods, with the most notable and significant difference between 1993-95 and 1997-99, representing a 51.4% increase (Table 5.2). This change was slightly more than the change reported for set possession time, however, the percentage change in the continuous possession time has been inflated due to the small reduction observed between 1988-92 and 1993-95. This was probably due to the instigation ofthe 'use it or lose it' law in the maul; possession being handed over to the opposition if the ball is not playable when the maul stops. The increase in this time variable between 1997-99 and 20OO-02, whilst also closely matching the set possession time, may have been influenced by a change in contesting the lineout, and amendments to the 'use it or lose it' law allowing teams an extra five seconds to re-start a ceased maul before being penalised. 5.4.6 Continuous ball in play time The differences observed across the four Periods reflect a convergence of Codes with respect to this time variable. Whilst there were reductions in times in rugby league (-9.8% across the four Periods), the 773 convergence is predominantly due to the increases in continuous ball in play time occurring in rugby union (+93.9% across the four Periods) (Table 5.2). This trend in rugby union incorporated a more pronounced increase between the Periods spanning the introduction of professional rugby (1993-95 and 1997-99) and was mirrored by the greatest decrease in times in rugby league across the same two Periods (Table 5.2) In rugby league, the change to the summer rugby playing season would appear to have promoted a more open/running game, however, the reduction in continuous ball in play time across these Periods reflected an increase in the frequency of stoppages in the game. Whilst this was mainly due to the increase (26.1%) in kicks out ofplay across the Periods, it could also be a consequence ofincreased fatigue due to playing in a warmer and more humid climate. In rugby union the continuous ball in play time increased across the four Periods, with the most notable change being between the Periods 1993 -95 and 1997 -99 . TLrs 49 .3Yo increase in continuous ball in play time (Table 5.2) conelated strongly with the 5L.0Yo decrease in the frequency of kicks out of play reported in this study (Table 5.7), indicating the change in kicking strategy across these Period was fundamental to the increase in continuous ball in play time. 5.4.7 Total ball carries The frequency of ball carries in rugby league was found to be greater than in rugby union in both Eras and all four Periods. The relative change in this variable indicated that the Codes were converging over these Periods @igure 5.9). Analysis of the percentage change in each of the Codes across the Periods indicated that the increase in rugby union (+52.20% between 1988-92 and 2000-02) was more responsible for the apparent convergence than the small (+4.1%) change in rugby league (Table 5.4). Analysis of this variable relative to time indicated that in all Periods the frequency of ball carries per minute tvas greater in the rugby union than in rugby league, although the relative difference between the Codes across the Periods was found to be stable. This suggests thatthe apparent convergence ofthis variable was facilitated predominantly by the increased ball in play time in rugby union across the Periods. This is illustrated by the signifïcant increase in total ball carries in rugby union between the Eras (+38.1%) closely matching the similar increase in ball in play time (+27 .8%), and the increase across the four Periods (+52.2%) matching closely the increase in ball in play time over the same time (+44.7%)(Tables 5.2 & 5.4) Hencg whilst the increases in frequencies are strongly related to the ball in play times, these increases in ball carries cannot be accounted for merely by the changes in ball in play times alone. In the professional Era, it appears that the quicker game is reflected by the greater frequency of ball carries per unit possession time 174 (11.9 compared to 11.3 per min) (Table 5.5). However, the results of the time variable analysis (Table 5.1) indicated that the mean ball recycling times were consistent across the Eras (3.08 s compared to 3.10 s). Hence, the increased ball carries per minute were not facilitated by a faster ruck ball. This is somewhat misleading though, since the Period analysis for mean ruck time does indicate a faster ruck in the professional Periods compared to 1993-95. A reduction in mean activity across the Periods was also revealed. These changes suggest the ball was re-cycled slightly quicker at the ruck, and the time between rucks was reduced, both contributing to more ball carries per unit time. The increase in the frequency of ball carries between the 1988-92 and 1993-95 Periods may be due to the introduction of the'use it or lose it' law at the maul in 1992-93. According to Hughes and Clarke (1994, p.180), this was to 'make the game more attractive' and seemingly had the desired effect; the increase of ball caruies indicating a more open game, with the increase in ball in play time across these Periods being +18.9% (Table 5.2). Hence, some of the increase in the frequency of ball carries must be related to the concurrent increases in ball in play time. If the 'use it or lose it' law change was successful, there would be fewer stoppages at the breakdown, which would result in an increase in the mean set possession time. The results of the time variable analysis revealed increases in mean set possession time across all four Periods, with the most notable increase (+35.4%) occurring between 1988-92 and 1993-95 (Table 5.2). As such the law change appears to have had a marked effect on the game playing pattern, contributing to the increase in frequency ofball carries. In rugby league the change in this variable was less apparent. The stability of the median frequency and frequency per unit time for ball carries across the four Periods was revealed by the non-significant Era difference and Period main effect being identified for either of these variables. In addition, there was no obvious change in the trend ofthe data across the fourPeriods, indicating that the ball carries in rugby league were unaffected by the change in game rules (offside rule in 1993; 4O-20 rule in 1999) or the change in playing season. 5.4.8 Passing Analysis of the relative changes in rugby union and rugby league revealed a convergence of the Codes in all passing variables across the Eras and all four Periods. Further analysis showed that the convergence was mainly due to the increases in frequencies in the rugby union variables rather than large reductions in variable frequencies in rugby league, with the most notable convergences being in the median frequency of 175 total passes per game (Figure 5.1l), the median frequency of passes from dummy/scrum half position (Figure 5. l3) and the median frequency of passes in open play (Figure 5. 1 5). In rugby union in the 1988-92 Period the mean total game pass frequency of 209 was far greater than the L27 rcported by Hughes and Clark (1994), the 167 identifïed by Potter and Carter (2001b) for Rugby World Cup @WC) 1987, and the 170 reported for the same tournament in 1991. The frequency in this Period more closely matched the game pass frequency observed by Potter and Carter (2001b) for games involving World Cup winners (223 passes). The only direct comparison for Five Nations Rugby is Carter's (1997) analysis of this tournament, in which a frequency of 166 passes was reported. In the 1993-95 Period, the frequencies identified in the present study (215) also exceed those from those previously reported by Potter (1997) and Potter and Carter (2001, a" b). Potter (1997) reported the frequencies in both 1993 and 1994 5N rugby did not exceed 162 passes, much less than found in the present study. The frequencies for this variable were also considerably higher than those presented by Potter and Carter (2001a, b) for RWC full tournament (179) and games involving the tournament winner (174). These frequency differences were possibly due to inconsistencies in the use of operational definitions for this variable. That is, in none of the previous studies was it made transparent whether the pass from the dummy or scrum half position was included in the count. It is likely that they were not. If such data are excluded from the pass calculations for the present study, Period counts become similar, with mean frequencies of 155 and 152 forthe 1988-92 and 1993-95 Periods, respectively, In the professional Periods in rugby union the median total game pass frequencies continued to increase steadily, the frequency for 2000-02 being significantly higher than both the pre-professional Periods (Table 5,3), Significant differences were also noted for passes from the dummy/scrum half position between the 2000-02 Period and both pre-professional Periods. The analyses of these variables per unit time indicated no significant Era difference or Period main effect for total passes per game (Figure 5.12) or for passes in open play (Figure 5.16). This indicates that the increased ball in play time was responsible for the increases in these frequencies across the Era and Periods. However, for the frequency of passes from the dummy half position per unit time the difference indicated that increases in ball in play time could not be solely responsible for these frequency increases. Two other factors need to be considered:- the change due to a tactical decision by coaches to play a more open game, and law changes at this time which may have significantly impacted on the playing pattern after 1999. The latter seems likely. In 1999, the IRB introduced a law to prevent defending players slowing down or preventing release of the ball at the ruck and maul. According to Williams et al., (2003) this resulted in an increase in the frequency of breakdowns and improved continuity. Hence, the likelihood is that pass frequencies increased, particularly passes from the 176 dummy/scrum half positiorq a fact confirmed by the results of the pass analyses in the present study (Table s3) The increase in the pass frequency from the dummy/scrum half position across all Periods was greater than the changes in open play pass frequency. This indicates that far from being a more open passing game, the game has actually become one that was played more close to the contact situation. This was highlighted by Thomas (2001), who reported only 8% of aøivity cycles contained more than four passes and 52% of activity cycles were made up of only one pass (presumably a dummy/scrum half pass). In the professional Era, therefore, whilst there were significantly more total passes in the game, this was mainly due to increases in ball in play time and specific law changes resulting in an increased frequency of rucks. This 'safer' style of play is also reflected in the decreased offload frequency observed between the Periods in the professional Era (Table 5.3), indicating a greater emphasis on ball retention, rather than the adoption ofa higher risk approach to offence. If ball retention became the primary aim of teams in the professional Era then the game played close to the ruck is the most appropriate option, a fact reported by McKenzie et aI. (1989), who suggested that ball retention is improved when close (< 5 m) to the original contact position and deteriorates as a function of distance from the origin of play. More recent analysis by Smyth et al. (1998) supported this view, indicating that successful teams maintained possession when the ball was closer to the previous contact position. For all pass variables in rugby league no significant Period main effect or Era difference was identified. The small percentage changes in all pass variables between the Periods appear to be in line with changes in both activity time and percentage ball in play time. These fìndings suggest that the introduction of the l0-m offside rule in 1992-93 and the change from a winter season to summer playing season rugby in 1996 had little impact on this aspect of the game. The only notable change in this Code of rugby was the run to pass ratio from the dummy half positior¡ with a trend away from the run towards the pass being noted. This was most notable between the 1988-92 and 1993-95 Periods, perhaps due to the 10-m offside rule change noted above. This rule change meant that teams on offence had more space to exploit at each play the ball and hence, could adopt a more expansive/wider game, rather than playing close to the ruck. It has been suggested that the conversion ofhalfbacks to hookers to exploit the increased space was a direct result ofthis 1992-93 rule change (O'Connor, 1997).It would therefore have been expected that the rule change would result in an increase in the frequency of dummy half runs, a fact not supported by the findings of this study. The signifìcant difference found in the frequency of dummy/scrum half passes per unit time across 1988-92 and 1993-95 reflected an increase in the intensity of the game, particularly at the 'play the ball'. The evolving role of the hooker from a traditional forward player to 'distributor' (Meir, Newton et a1.,2001) may have 177 been fundamental to this change occurring. More recently Gabbett (2005) indicated that 'hookers and half- backs' are now categorised as one of four sub-groups related to positional similarities, indicating the major change in this role in the fully professional game. 5.4.9 Ball carries into contact In the professional Era and Periods the differences in the median frequency of ball carries into contact between the Codes was reduced markedly, indicating a converging of the Codes (Figure 5.19). The percentage change across the four Periods indicated the convergence was mainly a result of increases in rugby union rather than decreases in rugby league, ostensibly due to a large increase across the 1993-95 and 2000-02 Periods (Table 5.4). Since a significant Code difference in frequency per unit time was also established across these Periods, the increase in the frequency of ball carries into contact cannot be fully explained by the increased ball in play time aoross the Periods. Whilst the frequency of ball carries also rose across these Periods, this was not as great as the increase in ball carries into contact. The contact to carry ratio analysis in rugby union showed a l4.4Yo increase (Table 5.4), indicating that teams in the 7997-99 Period were directing more possession into the contact situation, one ball carry into contact (on average) every 11.3 s in 1993-95 compared to one every 9.5 s in 1997-99 being an able illustration (Table 5.5). The change in offence strategy by teams in the 1997-99 Period was accompanied by a large increase (+44.2%) in the ball being 'popped' (immediately released upwards on contact with the ground) to any supporting player (Table 5.4). This style of play puts great emphasis on support runners arriving at the breakdown quickly. According to Smyth et al. (1998), the quicker the arrival of support, the faster the ball can be released from contact, thus giving the defence less time to organise. The'popped' ball (a fast release of the ball) is different to the offload (where the ball is directed towards a specific player during the tackle), and is a higher risk strategy, reliant on good support play. This faster style of game was directed through the middle of the ruck, rather than the more heavily defended fringes. This high risk strategy was, however, short-lived, with the frequencies of both offloads and popped passes per minute decreasing in the 2000-02 Period (Table 5.3). This can be partly explained considering Lydon's (2001. p.10) opinion that the stratery at this time was to take the ball into contact and then go to ground to a generally uncontested mini-ruck. Hence, whilst the offence strategy in 1997-99 was better at disrupting the defence (in terms of forcing missed tackles) (Table 5.3), the higher risk approach appears not to have been universally adopted. In rugby league, the frequency of ball carries into contact was found to be stable across the four Periods (Table 5.3), with a small increase noted in the 1997-99 Period. This represented (on average) 12-13 contacts 178 in offence per playing position per game. When added to the frequency of defence contacts per position (12- 14) observed in the present study (Table 5.3) the total 'physical confrontations' (24-27) was found to be slightly less than reported by Larder (1938), who noted total confrontations in professional rugby league ranging from 36-55 for forwards and 19-29 for backs. More recently, Gissane et al. (2001\ suggested the mean number of collisions per player in rugby league was (on average) 41. However, the tackle counts in the present study were based on actual completed tackles and not individual player contacts, hence this score takes no account ofadditional contacts due to multiple (double and mob) tackles. Ifall tacklers are credited with the tackle in multiple tackles, the mean defence con-frontation frequency increases to approximately 500 in all Periods, or approximately 800 player collisions per game, representing a mean of 3l per player, which is still much less than reported by Gissane et al. Q00l) The small increase in the frequency of contacts per unit time observed in the 1997-99 Period cannot be fully explained by the change in ball in play time, since the frequency of contacts per minute also increased across these Periods, 6.4 per minute in 1993-95 compared to 6.9 per minute in 1997-99. The decrease in mean ruck time (indicating faster ball re-cycling at the play the ball) across these Periods from 3.71 s to 3.28 s and the concomitant decrease in mean activity time from 5.92 s to 5.58 s across the 1993-93 and 1997-99 Periods clearly resulted in more collisions per unit time. 5.4.10 Tackle attempts Although significant Code differences \¡/ere identified for tackle attempts in both Eras and all four Periods, the convergence of the Codes was apparent (Figure 5.21), Whilst the tackle attempts remained higher in rugby league than rugby union, the difference between the Codes reduced across the Periods, predominantly due to an increased ball in play time in rugby union. However, when the data were normalised to the respective ball in play times, the tackles attempts per minute were still higher in rugby league than rugby union in both Eras and all four Periods. In rugby union the frequency of tackle attempts increased across the Periods, whilst the frequencies in rugby league remained relatively stable. The relatively low pre-professional Era and Period frequencies identified for rugby union were inconsistent with the findings of Du Toit (1989), who reported a mean frequency of only 35 tackles per game in1987. Similarly, the 59 tackles reported by Hughes and Clarke (1994) in their analysis of the l99l Rugby World Cup is less than half that found in the 1988-92 Period of the present study (123 tackles). It is diflicult to asceftain the reasons for such large differences; however, it is important to note that the values reported for other variables in Hughes and Clarke's (1994) study also differ 179 greatly from those found in the present study and Potter and Carter's (1997b) 1991 Rugby World Cup analysis. Hence, this may be partly explained by the poor reliability of previous analyses and/or the representativeness of the matches selected in all of these analyses (sampling enor). The largest increase in tackle attempts and successful tackles occured between the 1993-95 and 7997-99 Periods (Table 5.4). This increase was much gfeater than can be explained by the increases in activity time and ball in play time across these Periods, illustrated by the tackle attempts per unit time increasing between these Periods (Table 5.5). Whilst these time increases may be in some part responsible for the change in the tackle frequencies, there are other confounding factors that must also be considered, for example the changes in laws in the set pieces (lineout and scrum) across these Periods may partly account for such changes. The revised law at the scrum meant that back row forwards had to remain bound until the scnrm was over. This created more space and enabled attacks closer to the set piece, exploiting the smaller inside backs, erstwhile more protected by the back row forwards. The changes to the lineout laws allowing 'supported' jumpers almost guaranteed possession since there was a reduction in fully-contested lineouts (}Iand 2002; Martin, Thomas et al., 200I), and according to Sommerville (1997, p.8) allowed 20 m of space from quick tap ball. Such laws discouraged the slower maul-dominated play and resulted in a faster rucking style of play. The reductions in mean time engaged at the ruck and mean time in activity, allied to the increases in ruck frequency (75%) and the large reduction in kicking away possession identified in this study, all suggest a move towards a more possession-dominated game, played close to the breakdown. In rugby league, the tackle frequency and the tackles completed per unit time were found to be relatively stable across the Eras and four Periods. The main changes were found to be the decrease in median tackle frequency between 1997-99 and2000-02 (Figure 5.21) and the increase in tackles per minute across the 1988-92 and 1993-95 Periods (Figure 5.22). The increase in tackles per unit time was much greater than the 2.4Yo increase in tackle frequency indicating the change could not be solely explained by changes in ball in play time. These Periods span the introduction of probably the most discussed rule change in rugby league, both in academic research and amongst elite coaches; the 10-m rule. Farar (2002) suggested that the introduction of this rule, contrary to the aim of opening up the game lilas more advantageous to defences, whilst Fagan (2005) believed the contrary, the rule allowing the dummy half an easy 10 metres. The results of the time analyses in this study showed that the view of Fanar Q002) was ostensibly correct, since the mean time in activity did not increase significantly after 1993, despite the increase in team separation from 5 m to l0 m. However, one cannot understate the role of the dummy half run in starting 'a roll' (Smith, 2002); a dummy run followed by a quick 'play the ball' that can upset the defence, hence the easy l0 metres is not just aboutterritorial advantage, it is about starting the roll and making the defences retreat. 180 The results of this study indicate the rule change (10-m offside) had an effect on making the game more intense (more collisions per unit time) in the 1993-95 Period. The increase of a tackle every 8.5 s to one every 7.8 s is a notable change, however, it is more remarkable when considering that the 10-m rule change effectively put teams further apart at the 'play the ball'. Hence, it would have been expected that this separation would have decreased the tackles per minute in 1993-95. There are a number of factors which combined appear to have impacted on this increased game intensity, resulting in less time between collisions. In the September 1983 the Rugby Football League (RFL) as a response to the defeats by the touring Australians, and recognition of the increasing gap between the British and Australian sides lifted the transfer ban. This according to Collins (2000) resulted in an influx of Australian and New Zealand players. The magnitude of this 'deluge' of Southern hemisphere players was highlighted by Halifax signing thirteen Australians in one season, and fielded ten of them in a match against Leeds, who in the same game incidentally, also fielding five Australians. Perhaps more influential though was the similar movement of coaches from the Southern hemisphere, most significantly perhaps, Graham Lowes and John Monie, who were responsible for developing the dominant Wigan side of the 80s and early 90s. These coaches brought a different style of play, imitating the more confrontational style previously observed only in Australian touring sides. This was highlighted by Clarke (as cited in O'Hare, 1995) who assessed the impact of the 7992 Australian tourists, and sought to identify why they were so successful. The fundamental difference between Great Britain and Australia, according to Clarke (as cited in O'Hare, 1995) was in the collision and subsequent 'play the ball'. The Australian players attacked from a deeper position, gaining more speed and momentum before the collision. This sprint into contact (30% of the time for Australians compared to 5%o for British players) resulted in (on average) an extra 0.44 m gained per tackle (although how this level of accuracy in measurement was achieved was not reported, and should therefore be viewed with some caution). He also reported that the Australian defenders were more likely to move into the tackle rather than tackle stand still. This more successful 'attacking' defence style was to become more pronounced after the introduction of the l0-m rule the following year. In play under the 10-m rule it became necessary for teams to reduce the space, time and options of the attack (Bayliss, 2002). Hence, defences were forced to move up into the tackle more quickly. In addition, to exploit the new space, teams in offence adopted a more flat line attack, rather than running from deep behind the advantage line. Anderson (2002a) suggested that this flat line of running in attack enabled teams to force the defence to stand still in the tackle. As a consequence both offences and defences attempted to reduce the space between the teams, resulting in the reduction in mean times between collisions after the mle change. 181 With the influx of Southern hemisphere coaches introduced the more 'attacking' defence, and offences employing flatter attack lines, it is not surprising that the tackles per unit time reported in this study increased despite the rule change increasing the separation of the teams. Thus, combining the rule change with legislative changes allowing an influx of players and coaches from the Southern hemisphere possibly resulted in a more intense game, illustrated by the change in tackles per unit time in this study. In the professional Periods, the frequency of tackles per minute did not change notably from that in the 1993-95 Period. However, assessing these data in isolation can be misleading as they do not effectively illustrate the fine balance between the control of the ruck and the attacking offence and defence lines. The tackles per unit time are a reflection ofthe speed ofthe play the ball and the distance between offence and defence. Hence, a quick play the ball may result in more tackles per minute. However, this can be offset by a slow attacking defence, or offences attacking from more depth. Mulholland (as cited in Hunt, 2002. p. 8) suggested that in the professional game the 10 m separation is now 'more like seven or eight', therefore one would expect more collisions per minute, however this does not account for the ongoing battle for control at the ruck. Since the introduction of the 10-m rule, the 'play the ball' has become the most important aspect of the game, Farrar (2002) highlightedthe importance of this part of the game suggesting that in offence it is vital to secure quick 'play the ball' and in defence prevent the opposition from doing so. Smith (2002, p. 5) made stronger comments, suggesting that whilst it may only take a few seconds, it is "a big part of the sport. .. and that is why people say winning the ruck or winning the game on the ground is important". Sharp Q002) added that defending against players playing close to the line is simple, players merely have to control the speed of the 'play the ball'. Hence, in orderto control the game and defend effectively against the flat line attack, teams in the professional Periods adopted strategies to slow the 'play the ball' (refer to section 5.4.2). 5.4.11 Tackle type In rugby union the introduction of rugby league coaches (Phil Larder, David Ellis, Clive Griffrths and Joe Lydon to name a few) to the union game after 1996, and the return of previous rugby union 'converts', for example, Jonathan Davies, Scott Gibbs, Martin Offiah and Alan Tait in the Period immediately after the introduction of professional rugby union may also have had an effect. The use of rugby league coaches as specialist defence coordinators had a marked impact on the union game. The more compact defence close to the ruck using markers and the umbrella style defence forced attacks more close to the breakdown. Defences defended tenitory rather than challenge for the ball, particularly at the ruck. This change in defence strategy is clearly evident from the results of the tackle analysis (Table 5.3). Whilst tackle frequencies increased in the 182 professional Era, the principal significant difference between the Eras was the increase in double tackle frequencies and the decrease in mob tackles. The double tackle is more apparent in a defence that seeks to defend close to the breakdowq preventing the ball from being passed to wide positions where the defence is less dense. It is also an effective strategy in preventing the ofiload. The reduction of mob tackles is also a strategy of a more disciplined system, preventing too many players being committed to the tackle. On the surface, it appears that this more structured and disciplined defence was not successful in that there was a large (non-significant) increase in missed tackles between the L993-95 and 1997-99 Periods (Table 5.3). Howeveq this change was much less than the change in total tackle frequency indicated by the missed tackles expressed as a percentage of total tackles falling across these Periods (Figure 5.27), reflecling a more efficient defence system. Between the subsequent Periods it was apparent that mob tackles increased much more than single and double tackles (Table 5.4). This might indicate a change in strategy; however, when one examines the raw data the very low frequencies identified for this variable mean that a small change between Periods is inflated when expressed as a percentage. This highlights the importance of examining both frequencies and percentage changes in variables before inferences are made. In the Australian National Rugby League (NRL), according to Hagan (2002b, cited in www.rll908.corn, accessed 15/2/06), the gang tackle (mob tackle) is now 'back in vogue', a strategy employed to slow the 'play the ball' and provide the team in defence time to re-align. The results ofthe present study suggest that the same strategy has not been employed in Northern hemisphere rugby league football, with mob tackles and mob tackles per unit time found to be stable across the Eras and all four Periods. This difference in tackle strategy between Northern and Southern hemisphere games is probably due to the 'dominant tackle' rule being used in the NRL. The rule (which is not actually a rule stated in the International Rules of the game) means that if a tackled player is moved backwards in the tackle, or importantly, surrenders (attempts to dive to ground) the referee will call a dominant tackle and allow the defending players more time to clear the ruck areq effectively slowing the subsequent'play the ball'. Dalkeith (2006) suggested that coaches can prepare to win the ruck in defence by taking advantage of the dominant tackle rule; sending more players into the tackle and peeling off one at a time. In this way the defence can control the ruch but this can only be achieved if the dominant tackle is called, hence, the need for more players in the tackle to ensure the attacking player is driven backwards. In Super League, no such 'rule' is in place, and as a consequence the use of a mob tackle is less effective in controlling the ruck area. The results ofthe present study suggest that in the professional Era there has been a significant increase in the frequency of double tackles, and the frequency per unit time compared to the pre-professional Era. This 183 increasing trend was also apparent across the four Periods indicating a change in tackle strategy. This was further highlighted by the increases in the relative percentage ofdouble tackles across the Periods 1992-95 to 2000-02 (Table 5.9). In effect, these results suggest thal like the mob tackle in the NRL, the double tackle became more 'in vogue' in an attempt to control the 'play the ball'. The advantage to the defence of having two or more players in the tackle is threefold. Firstly, the additional tackler(s) can create a 'pile' (stack of players) which slows the 'peel' (one player at a time moving offthe pile). Secondly, according to Dalkeith (2006), is the additional tackler(s) role in 'turtling' (turning a player onto his back). These "limit the attacking team's ability for a quick 'play the ball' and a crack at a retreating defence" (Hagan, 20O2b, as cited in www.rll908.com, accessed 1512106). Thirdly, having multiple players in the tackle is an effective strategy in preventing the ofiload and second phase play against more disrupted and disorganised defences. It is clear that the two Codes of rugby are distinct in their tackle type preference, with the single tackle being the tackle of choice in rugby union and the mob and double (multiple) tackle being preferred in rugby league in all Periods (Table 5.9). Hence, while defence systems have changed in rugby union to be more like the systems used in rugby league, the tackle type has changed less. In rugby league the use of multiple tackles is ostensibly employed to slow the 'play the ball' and prevent second phase play, whereas in rugby union this is less effective as the opposition can 'clear out' at the ruck. As a consequence, the single tackle is still preferred in rugby union since it enables fewer players being 'trapped' in the ruck or maul, making more available for defending the subsequent attack. Therefore, whilst there are more double tackles being made in professional rugby union (ostensibly to prevent the offload), there appears to be no Code convergence related to the tackle type preference. 5.4.12 Tackle errors The Code difference in the percentage of missed tackles was relatively stable across the four Periods, being greater in rugby league than rugby unior¡ with the most notable difference being in 1993-95 (Table 5.9). Whilst this large increase may be due to the introduction of the lO-m offside rule in rugby league, in the professional Periods no significant Code differences were identified, with tackle percentage differences in both Codes reducing across the professional Periods. In rugby unior¡ though the decrease in the time between missed tackles across the Periods suggested an increase in tackle errors, it must be considered that this was due to concomitant increases in the frequency and frequency per unit time of tackle attempts. To assess the analyses of this aspect of the game, it is more appropriate to report tackles missed related to tackle attempts (expressed as percentages). The (non- 184 significant) reduction in the percentage of missed tackles across the Periods 1993-95 and 2000-02 may be a reflection of an improvement in defence systems. Eaves (2006) reported that the number of players engaged in rucks and mauls showed a gradual reduction across the same four Periods, hence, there was a gradual increase in the number of players in the defence line, as opposed to being 'tied' into the ruck or maul. In addition, after the introduction of professional rugby in 1996, many specialist coaches (ostensibly defence coaches) from rugby league were employed by rugby union sides. Gallagher (2005) suggested that the change in defence alignments is the most significant change in rugby union since the onset of professionalism. Similarl¡ Lydon (2001, p.ru) highlighted the importance of defence suggesting that "an emphasis on defence has been one of the many positive elements brought to the game [rugby union] with the advent of professionalism". The fact that all Home Nations countries currently employ ex-rugby league coaches - Phil Larder @ngland), Dave Ellis @rance), Mike Ford (Ireland), Clive Griffrths (Wales) and Alan Tait (Scotland) - and the current British Lions defence team (Phil Larder and Mike Ford) are league 'converts' can be no coincidence. These coaches have been responsible for instigating more rugby league- style defences, 'drift or outside in', the 'umbrella' and more recently the 'inside out' defence favoured by coaches like Brendan Venter (Ex-London Irish) and Shaun Edwards (Wasps) (Gallagher, 2005). Whichever defence is employed; the basis of these systems is to move up to the tackle area as a unit to deny the attackers the space and time to make decisions. As a consequence of the more effrcient defences, the missed tackle percentage has gradually declined across the Periods. With the defences now being so well organised and spread across the field -as seen in rugby league- it may not be long before the use of the maul is once again favoured, in an attempt to oreate more attacking space. Indeed, subjective analysis of more recent international rugby games (Six Nations Championships 2006) has shown an increase in mauls and mini-mauls compared to the 2000-02 Period. This has been shown in the mean ruck maul ratio (calculated from the frequency counts) for five randomly selected games being l: 0.14 (range 0.07 - 0.20). In addition, in four of the five games the ratios exceeded the mean ratio for the 2000-02 Period (l: 0.12) (news.bbc.co.uk/sportl/trilrugby_union/internationaVstm, accessed l8/03/06). Whilst some caution should be taken when using such data (no operational defrnitions presented or evidence of reliability analysis undertaken) they do give some indication of the possible changes in the game in the post 2000-02 Period. It is therefore suggested that future research examines the 2003-06 Period in a more systematic manner to ascertain the 'true' changes over this time frame. In rugby league the median frequency of tackle misses and the frequency per unit time were found to be significantly g¡eater in the pre-professional Era than the professional Era. For the tackles per unit time, the Era difference was predominately influenced by the high score recorded in the 1993-95 Period (l.2tacÞJe l8s misses per minute) compared to all other Periods (range 0.7-0.8 missed tackles per minute) (Table 5.5). This was most likely due to the introduction of the lO-m offside rule. The impact of this rule according to Meir, Colla et al. Q00l) was an increase in distance travelled during the game. This extra distance may have had a fatiguing effect, perhaps resulting in more missed tackles in the frnal stages of the game. A further consideration must be that teams needed time to adapt to the rule change and devise defence systems to counteract the advantage seemingly afforded the attacking players. It has been suggested by Williams, Thomas et al. (2005) in their analysis of law changes in rugby union that rule changes tend to have an immediate impact, but their effects seldom last more than 3 years. Hence, it seems feasible that the change noted between 1993-95 and 1997-99 was due to increases in player fitness after the introduction of fuIl-time professional playing status and change to the summer playing season, and teams developing appropriate defence strategies to offset the impact of the l0-m rule change. 5.4.13 Lineouts The mean frequency of lineouts per grìme in the pre-professional E,ra (47) established in the present study (Table 5.6) is consistent with previous research examining game action frequencies in International matches. Mclean (1992) and Treadwell et al. (1991) both reported 41 lineouts in the Five Nations (5N) and New Zealand v British Lions games in 1989-90, respectively. In addition, Potter (1997) reported frequencies in 5N rugby of 40 in 1992, 52 in 1993 and 46 in 1994. This apparent high value for 1993 being strongly influenced by a very high frequency of 61 lineouts in one particular game @ngland versus lreland). This aside, the overall mean (46) is remarkably similar to that identified for pre-professional rugby in the current study. In the professional Era the mean lineout frequency decreased to 31, which is consistent with that reported MartirL Thomas et al. (2001) (27 in both Tri-Nations (3N) and Six Nations (6N) rugby in 2000). Whilst there were no observable differences in lineout frequencies for games across Periods within the same Era, the overall Era difference was highly signifrcant, with fewer lineouts occurring in the professional Era compared with the pre-professional Era. This downward trend in lineout frequency is more striking when one considers the values presented by Hughes and \{illiams (2002), who suggested that in 1977 there were 71 lineouts in the Wales versus Scotland game, compared to only 18 in the 2000 New Zealand Australia encounter. This low lineout frequency for the Southern hemisphere game in 2000 is inconsistent with values found in the present study, with (on average) 32 lineouts in games in the similar Period (2000-02) in the Northern hemisphere (Table 5.6). It must be noted, however, that the data of Hughes and Williams Q002) were based on only one game, and therefore any inferences made with regard to their frndings must be r86 viewed with caution inasmuch as these data were unlikely to have reached stable mean (based on the analyses ofthis variable in the current study). In Northern hemisphere rugby, it appears that whilst lineout frequencies fell between Eras, they are now stabilising in the professional Era, as indicated by non-significant change between the 1997-99 and2000-02 Periods. The initial reduction in such frequencies after the introduction of professional rugby appears to be a refleotion of teams increased reluctance to kick away possession (possession being almost guaranteed at the lineout), a fact identified in the current study. This indicates a possible change, with teams adopting a more possession-dominated game strategy as opposed to a more territorial strategy. This is demonstrated in the analysis of the time variables in this study which showed that in the pre-professional Era each complete sets of play (set possession time) lasted on average (mean) 10.4 s, with a continuous ball in play time of ló.0 s. In the professional Era these values rose signifïcantly to 15.4 s for set possession time and to 22.6 s for continuous ball in play time (Table 5.1). In addition, teams in the professional Era had significantly more activity phases per game Q26) than teams in the pre-professional Era (174), possibly reflecting an increase in ball recycling frequency and maintenance ofpossession (Table 5.6). The reduction in lineout frequency in Periods in the professional Era may in part be due to law changes in the game. For example, in the professional Era the acceptance of supported lineout jumpers @FU Technical Journal Sept. 1995, p. I l) and 'lifting' has meant that teams throwing in were more likely to win possession. That is, subjective analysis ofgames (in the professional Era) indicates that the result ofthis law change has been that opposing teams seemingly opt not to contest the lineout fully (contest for the ball in flight), but prefer to set up a defence alignment to defend the subsequent attack from the set play. This was highlighted by Keith Bonser (RFU Club England Coaching Team), who stated "There are basically two areas where the competition can take place. You can compete in the air or on the floor" (as cited in Hardy 2002, p.7). In the professional game the increase in contesting the lineout 'on the ground' reflects the view ofRichards and Richards (2002, pp. l8l-184) that defence wins games; hence, it is more important to set the line of defence than compete for the ball. As a consequence, the likelihood of teams sacrifìcing competing for the ball in the air in preference to setting a more structured defence system is enhanced. This is a view echoed by Hands (2002) who suggested that the law change regarding 'lifting' resulted in opposition not jumping, but instead defending against any driving lineout. This lack of challenge for the ball at the lineout appears to be more pronounced in Northern hemisphere rugby; Martin, Thomas et al. (2001) reported Six Nations' (6N) teams were less likely to compete (in the air) at the lineout than Southern hemisphere teams. They cited the extreme examples of Wales contesting 20Yo of lineouts compared to 78Yo contested by Australia of in 5N and 3N games, respectively. The results presented by Martin, Thomas et al. (20O1) indicated that uncontested r87 lineouts were prevalent in this period; 44.5% of lineouts being uncontested in 1999-2000 (3N and 6N rugby). The remaining55.5Yo whilst defined as contested may have been'semi-contested'. That is to say, according to Martin, Thomas et ø1. (200I\, a lineout was defìned as being contested if one player from the opposition teams gets his feet offthe ground. This is a very conservative definition, and as a consequenoe probably inflated the frequency of contested lineouts in their study. If an examination of lineouts were undertaken with more specific operational definitions the results are likely to be very different, Hence, whilst there are no data to confirm this, it is appropriate to state that the uncontested or more specifically the semi-contested lineout has emerged during the professional Era. This means that in the professional Era and Periods the advantage of touch kick has become merely territorial, whereas previously it had been for territory and possible possession. Interestingly, in a subjective assessment of more recent games (post-2002), it appears that the fully contested lineout is re-emerging. Perhaps this is a reflection of the findings of Martin, Thomas el ql. (2001) who reported that Australia (the team most frequently contesting lineouts in 199912000) won one in tlree of their opponent's lineouts. Add to this the findings of Jones, Mellalieu and James (2004) who reported that only tries scored and lineouts won on opposition ball were performance indicators for success in rugby union, and it is then perhaps no great surprise that the winners of the 1999 Rugby World Cup were Australia. If one accepts the view of Melville (2000), that analysis of team performance and particular elements of the game are part of the professional game, then the success of Australia in the lineout is not likely to have gone un-noticed by other International teams and coaches, or if it has, one would need to question'why'? 5.4.14 Kicking Analysis of the kicking variables indicate that a convergence of the Codes was apparent between 1988 and 1997; however, in the latter Period (2000-02) both the frequency ofkicks (in and out ofplay) and kicks per unit time indicated a slight Code divergence. Irrespective of the relative trends, the frequency of all kicks was significantly greater in rugby union than rugby league in all Periods, reflecting a greater emphasis on this activity in the union Code. The less frequent use of the kick in all Periods in rugby league is a reflection of the lack of contesting for the ball at the ruck. As a consequence there is less need to kick away possession for tenitorial advantage as is the case in rugby union. In rugby union no significant Era difference was identified for kicks in play; howeveq tlere was a significant difference for kicks out of play (mean:30 in the pre-professional compared to mean: 18 in professional Era). The proportions of kicks in play also increased (52% to 63%o) between Eras, with a low of 188 50Yointhe 1988-92 Period and a high of 65Yo in the Period immediately after the introduction of professional rugby. Comparisons with previous research are diffrcult since most papers fail to identify whether the kicks were in open play or included penalty kicks, free kicks, drop kicks and conversions. For example, the values for total game kicks reported by Potter (1997) and Potter and Carter (2001a) are notably higher than the frequencies reported in the present study, and as such probably include all types ofkick. The values reported in this study more closely match those presented by Marshall and Hughes (2001) in their analysis of women's rugby between 1994 and 2000, in which a significant decrease in the frequency of kicks between these years (76 in 1994 compared to 46 in 2000) was observed. Such a reduction, they suggest, was due to law changes and coaching strategy. Unfortunately, the authors failed to elaborate beyond this basic statement, avoiding any depth ofdiscussion on either specific law changes or coaching strategies. The failure ofthese studies to address the different types of kicks makes inferences on changing game strategies more diffrcult, as the assessment of whether the ball is kicked in or out of play is imperative if playing patterns and strategies are to be clearly identified. In the present study the frequency of kicks out of play was found to be significantly different between the two Periods either side of 1996 (31 in the 1993-95 Period and 15 in the 1997-99 Period) representing a Sl%ó reduction (Table 5.7), In both professional Periods, kicking the ball out ofplay occurred less frequently than in the Periods in the pre-professional Era, indicating a change in kicking strategy. This was highlighted in an examination of lineouts awarded due to touch kicks in opposition to running or being tackled into touch. In the pre-professional Periods the percentage of lineouts resulting from a kick was 62.7% in 1988-92 and 65.5% in 1993-95. However, in the 1997-99 Period, this percentage dropped to 52.2Yo, before re-stabilising in 2000-02 at 63.lYo. A stabilising process similar to that observed by Williams, Thomas et al. (2005) appears to have occurred. Hence, whilst the introduction of professional rugby did have an immediate impact on the tactic of kicking to toucl¡ the effect rilas not long lasting, and possibly reflects the re-emergence of the previously mentioned 'contested' lineout. A fuilher consideration according to Sayers (2005, p.95), is that over the past four years rule changes have reduced the advantages of the throwing team, and hence, the previous resultant possession'certainty' at the lineout is markedly reduced. It is important to note that if one considers the additional 5 min 49 s of ball in play time in the professional Era found in the current study (Table 5.1), the difference in frequencies for these kicks is even more pronounced. Analyses of these variables per unit time revealed the frequencies to be significantly lower in the professional Era compared to the pre-professional Era. In professional rugby union teams were less likely to kick the ball to touch, and kick the ball in play. These results clearly show a change in kicking pattern in professional rugby union football. 189 In rugby league, whilst the total game frequencies for kicks and kicks kept in play remained relatively stable, the frequency of kicks out of play, and the frequency per unit time decreased across the four Periods. The most notable of these changes were the 29Yo decreases in the kick out of play frequencies between the 1988-92 and 1993-95, and 7997-99 and2000-02 Periods (Table 5.7). These changes sppear more pronounced when assessed relative to ball in play time, indicating that these variables were not significantly influenced by any changes in ball in play time, and hence, were a deliberate change in game playing pattern, either due to a change in strategy or resulting from specific rule changes. Iî 1992-93 the l0-m rule was introduced. This had a significant impact on the game. Meir, Colla et al. (2001) reported that under the 5-m rule gaining territorial advantage was more difficult, as a consequence the kick at the end of the tackle count was the usual occuffence, often aimed to touch to force a scnrm. This not only was a good taúical decision in terms of the teritorial advantage, but also it gave the attacking team the opportunity to secure possession; contested scrums being evident during this Period. The introduction of the 10-m rule initially made territorial progression much easier since teams were further apart at the ruck. With tenitorial advancement easier, the use of the kick at the end of the set changed and became a more attacking weapon ('bomb' or attacking cross kicþ, hence an increase in the percentage of ball kicked in play resulted. 5.4.15 Rucks and Mauls In rugby union the analysis of ruck and maul frequencies revealed a change in playing pattern across the four Periods, with teams adopting a more ruck- and less maul-dominated approach in both Periods in the professional Era. This change in approach seemingly pointed to teams' primary focus being on maintaining possession rather than gaining tenitorial advantage. This was highlighted by Treadwell et al. (1991) who suggested that the retention of the ball was much better when contact was followed by a ruck rather than a maul, (ruck ball retention being on average 90Yo, compared to average maul ball retention of 79Yo). ln addition, Sm¡h et al. (1998) reported that there was a negative relationship between ball retention and mean distance from the previous contact. Whilst the present study has revealed that total ruck and maul engagements have increased over the four Periods, and significant differences were identified between all Periods in each different Er4 it is the ruck component of these values that is most notable. Ruck frequencies were found to be higher in the professional Periods than the pre-professional Periods, whilst there was a non- significant decrease in maul frequencies (Table 5.6). Moreover, for ruck frequency, the percentage change dramatically outstripped any change that could be explained by the concomitant increases in ball in play time (Table 5.7). This change was reflected in the significant Period main effect for ruck frequency per unit time; 190 differences being between all Periods in each different Era. As such, this constitutes a definite change in playing pattern, either due to law changes, tactical reasons or other factors. It could be suggested that the introduction of the 'use it or lose it' law in 1992-93, to 'make the game more attractive' (Hughes & Clark, 1994, p.180) was a catalyst for this change in playing pattern. Indeed, the results ofthe present study have shown that the ruck frequencies between 1988-92 and 7997-99 increased. As such, this indicates that the law change may have had an effect. In contrast, Hughes and Clarke (1994\ reported no significant differences in ruck frequencies in the year before or year after the introduction of this law change. However, it must be noted that the data from the present study were derived from a much gfeater time span (Periods up to four years long) than those in Hughes and Clarke (1994). Law changes at the lineout resulted in opposition teams opted not to challenge for the ball in the lineout, but instead set players into defence positions. The same may be true at the ruck. Opposition teams' lack of success in challenging for the ball meant it was futile to compete for the ball in the ruck. Lydon (2001) highlighted this suggesting that a strategy at this time was for players to take the ball into contact and go to ground to an uncontested mini-ruck. This view v/as supported by Eaves (2006) who found that there has been a significant reduction in the number of opposition players engaged in the ruck in the professional Era. Eaves (2006) reported that in the 1988-92 Period 45% of rucks had less than two opposition players competing for the ball, compared to 92o/o in the 2000-02 Period. This change in defending the ruck was possibly a reflection of the more disciplined 'rugby league-style' defence systems instigated by ex- rugby league coaches. Without effective opposition in the ruck teams were able to retain possession more easily. As a consequence, the ruck became a more dominant feature of the game. The opposite was true of the maul, where active opposition meant there was greater potential for turnover ball. It must be noted, however, that subjective analysis of more recent games (post-2002) would suggest an increased use of the maul, perhaps due to the 2001 Law amendment; allowing extra time in a static maul, ostensibly to 'unclutter' the midfield. In rugby league the ruck or 'play the ball' frequency was found to be relatively stable across the Eras and Periods, with no significant Era difference or Period main effect being identified for either of these variables. The frequencies of the'play the ball' (Table 5.1) were all noticeably less than those reported by the only other source to report frequencies for this variable. Larder (1988) suggested that rugby league games consisted of over 300 'play the balls' compared to approximately 260 found in the present study (1988-92 Period), although it is not apparent from where Larder derived this value. The changes in median ruck frequencies over the four Periods indicate that the Codes are converging, predominantly due to increases in ruck frequency in rugby union set against a more consistent profrle in 191 rugby league (Figure 5.33). However, it must be noted that even in the 2000-02 Period the Code difference for ruck frequency ì^ias still very great. 5.4.16 Scrums In rugby union no significant Era difference or Period main effect was established for scrum frequency. It is, however, notable that there was a decrease from 32 in 1988-92 to 25 in2O00-02 (Table 5.6). The frequency of scrums in 1988-92 established by the present study is consistent with previous research in 5N rugby. Mclean, (1992) reported the same number of scrums in his 1989-90 analysis, and Lyons (1991) reporting 33 in the same Period and 34 in 1991. Interestingly, an increase in scrum frequency was noted for the Period immediately after the introduction of professional rugby unioq with 24 in 1993-95 and 30 in 7997-99 (Table 5.6). Again, the 1993-95 value in the present study is similar to those presented by Potter (1997);29 1n 1993 and 24 in 1994. The results of the current study appeæ to indicate that the frequencies of scrums are relatively stable, however, when the frequencies are assessed in relation to the ball in play time, the results are very different. Such analyses revealed a significant Era difference for scrums per unit time, with fewer scrums per minute being observed in the professional Era compared to the pre-professional Era. A significant Period main effect for scrums per unit time was also identified. In the Period 1988-92 there were an average of 1.6 scrums per minute, compared to l.l per minute in 1993-5 and 1997-99, and 0.8 per minute in 2000-02. This highlights the importance of normalising the dat4 since data viewed without reference to total game frequencies can be misleading (tlughes & Bartlett, 2002).In the case of scrum frequencies, the data viewed in isolation would suggest no significant changes across the four Periods; however, in analysing the data per unit time, it is apparent that the scrum frequencies have decreased across Eras and a¡e notably less frequent in the 2000-02 Period than the previous three Periods. This effect could be due to the introduction ofthe 'use it or lose it' law in 1999, which according to Williams (2004, p.520) was implemented to "improve the scrum with regards to reducing the time being used up in scrum reformations and injury, especially at the S-metre scrum". This law penalised teams who did not use the ball quickly; hence, effectively reducing the possibility of the push over try, and as such the reduction in the frequency of scrums in this Period may be due to a reluctance to opt for the scrum at a given penaþ. In rugby league the frequency of scrums (19.4 per game) reported by Larder (1988) was strikingly similar to those observed in the 1988-92 Period of the present study, and was not dissimilar to all other Periods. The only Period where scrum frequencies were noticeably less was the 2000-02 Period, predominantly due to a decrease in the frequency ofkicks out ofplay noted previously. 192 The differences in the scrums in rugby union and rugby league are clear in that in rugby league, this set piece play is seen merely as a restart strategy, although Bayliss (2OO2, p. 12) suggested in his coaching of rugby league scrum opposing teams should, "endeavour to win the ball with a six man push". This tactic, however, is not evident in Northern hemisphere rugby to any extent. Indeed, more space in coaching literature is dedicated to the 'breaking pattern' from the scrum rather than on the scrum itself. By compæison, in rugby union the scrum is heavily contested and is an important weapon in offence, particularly scrums which are close to the opponent's goal line. This is apparent in that the option to scrum at a penalty is often taken. This has two advantages, the possibility of a push-over try and the confinement of the opposing forwards, since in the latter Period the laws prevented back row players from leaving the scrum until the ball is out. This provides the attacking backs with an opportunity to exploit the increased space which is harder to defend. It is therefore perplexing that the option is not taken more, since the modern defence line at the breakdown is so compact and effective. 5.4.17 Set Possessions In rugby union the significant Era difference for set possession frequency (-12.3%) was a reflection of games being more dominated by possession in the professional Era compared to the pre-professional Era (Table 5.7). Moreover, this reduction in set play frequency \ryas more pronounced when assessed relative to ball in play time. The significant Era difference for set possession per unit time represented a 32.2% reduction across the Eras and indicates that the change in frequency of set possession was flindamentally independent of the changes in ball in play time across the Era (Table 5.8). The mean frequency of set possession was found to be relatively stable across the four Periods, and consistent with previous researct¡ with the I27 set possessions in the 1988-92 Period being similar to the I l8 for 5N rugby in 1988, the l2l for 5N rugby in l99l (Treadwell et al. l99l) and the 120 for the 1989-90 5N rugby (Lyons 1991). One anomaly is the 132 set possessions reported by Lyons (1991) for the 1991 5N championships. However, this value was based on one game and hence may not be considered representative, since the data for this variable would likely not stabilise within one game (based on the findings of the present study - refer to chapter 4). The significant difFerence in set possession frequency between the Periods 1993-95 and 1997-99 (-12.7%) was most the most notable change between any of the Periods (Table 5.7). This modest change, however, is slightly misleading, since the analysis of this variable per unit ball in play time indicted a26.6Yo reduction in set possession frequency, illustrating a definite change in playing pattern, with teams maintaining set 193 possession for (on average) 10.4 s in the 1993-95 Period compared to 14.3 s in the 1997-99 Period. This change in playing pattern indicated a reduction in the frequency of turnover ball and an increase in the continuity of play, possibly a reflection of positive increases in player fitness in the professional Periods. This view is supported by Duthie et al. (2003, p.973), who suggested that "increased professionalism in rugby has elicited rapid changes in the frtness profïle of elite playerl'. Thomas (2001) also suggested that there has been a change in the size ofplayers across time, reporting that (on average) the backs in 1999 were two stone heavier than in 7973, one and a half stone heavier than in 1980 and nearly a stone heavier than in 1990. A similar trend was evident in the forwards, with these players being two stone heavier in 2000 than in 1980 and one stone heavier than in 1990. These changes in anthropometry were further supported by Olds (2001, p. 258), who not only suggested that players "have become taller, heavier and more mesomorphic", but these changes "may be five times as great as drifts in the source population". In additior¡ Olds (2001, p. 259) further indicated that these changes, similar to in American football "may be due to increasing professionalism". Moreover, according to the RFU's fitness and conditioning coach Dave Reddin (as cited in Bee, 2005), the strength to weight ratios of players have increased since the introduction of professional playing status, and estimated that this represented a 30Yo increase in strength of the professional player compared to his pre-professional counterpart. Based on his analysis using pressure pads in tackle bags he also suggested that players a¡e faster in the 'modern' game, with the top speed of backs being approximately l0 m/s. In rugby league the frequency of set possession was found to be very stable (75-82 per game) across the four Periods, indicating a more consistent playing pattern over time. One possible explanation is that in rugby league there is less of a contest for the ball, and hence fewer turnovers. This results in a more structured pattern of play, whereas in rugby union the active contest at the set piece and breakdown increases the likelihood of turnovers and errors. 5.4.18 ActivityÆhases In rugby union in the professional Era a significant increase in activity/phase play frequency was identified. That is to say, the ball was recycled more often in games in this Era than in the pre-professional Era. It is tempting to suggest that this indicates a change in the pattern of play; teams in the professional Era recycling the ball more quickly than those in the pre-professional Era, and hence increasing the frequency of this game action. However, more in-depth analysis relating the activity/phase frequency to the ball in play time revealed no significant Era difference, with approximately 8 activity/phase cycles per min in both Eras. 194 The significant Period main effect identified for the activity/phase frequency is likewise not apparent when these data are normalised to ball in play times. The percentage increase in the frequency ofthis variable is very similar to the percentage increase in ball in play time across the four Periods, indicating that the increases in activity/phase frequency were ostensibly due to ball in play time increases across the four Periods. Whilst the changes in activity frequency in rugby leagrle remained relatively constant between 1988 and 2002, it is apparent that there was a slight fall in frequency after the introduction of the lO-m rule in 199213 . This was possibly due to an increase in available space resulting in a concomitant increase in mean activity time, a fact established in the current research (increase of 0.25 s per activity phase) (Table 5.1). In the subsequent Period (1997-99) ruck frequencies slightly increased (beyond that expected by increases in ball in play time), indicating a possible increase in game intensity after the introduction of summer rugby. 5.5 Summary The objective of this study was to construø longitudinal time, offence, defence and game action profiles for rugby union and rugby league in four periods spanning 1988 and 2002 to facilitate an assessment of the impact of key factors on these profiles which may have resulted in a converging of the Codes. Table 5.10 presents a summary of all variables, the factors effecting changes in performance profiles, whether the Codes are converging and the predominant direction ofany convergence. 195 Table 5.10 Summary of game variables, factors influencing change in performance profiles and the predominant direction of any code convergence Veriable Arc Codes Change in Change in Predominant Period ofchange and possible Period ofchange and Convergence becoming rugby union rugby league direction of influencing factors in rugby possible influencing factors of the Codes more across time across time conver€ence union in rugby league by 2000-02 alike? frame frame Mean rucktime Yes Stable Decrease League -Union Decrease 1988-92+1993-95 Yes a lO-m rule Total ruck time Yes Increase Decrease Union + League Increase I 988-92+ 1993-95 Decrease I 988-92+ I 993-95 No a 'Use it or lose it' Law a lO-m n¡le Increase 1993 -95+1997 -99 a Professional playing status Mean activity time Yes Decrease St¿ble Union + League Decrease 1988-92+ 1993-95 Yes (crossover a Use it or lose it' Law in 2000-02) \o League Increase 1993 -9 5 -02 No o\ Total activity time Yes Increase Stable Union - -2000 . Ball in play time changes . Professional playing status Mean set Yes Increase Stable Union * League Increase 1993-95+2000-02 No possession time ¡ Professional playing status o Change in playing pattem - more possession dominated Mean continuous No Increase Fluctuating Increase 1993-95+2000-02 No possession time ¡ Lineout law changes - supported Jumpers ¡ Amendments to maul laws (2001) ¡ Professional playing status ¡ l¡Eoduction of non-injury substitutions Variable Are Codes Change in Change in Predominant Period ofchange and possible Period of change and Convergence becoming rugby union rugby league direction of influencing factors in rugby possible inlluencing factors of the Codes more acr,oss time across time convergence union in rugby league by 2000-02 alike? frame frame Mean continuous Yes Increase Stable Union - League Increass L993 -95 +2000 -02 Decrease 1993 -95 +1997 -99 NO ball in play time a Lineout law changes - supported Change in playing season jumpers Professional playing status trntroduction of non-injury substitutions +2000, Mean total ball Yes Increase Decrease Union * League Ircrease 1993 -9 5 - 1997 -Ð f )ecrease 199 7 -99 -02 No in play time o Lineoutlawchanges a InEoduction of external ¡ Professional playing status time-keepers Median frequency Yes Increase Stable Union - League Decrease I 988-92+ 1993-95 No . Use it or lose it' maul law \o oftotal ball carries \¡ per g¡me ¡ Ball in play time changes Mean frequency of No Stable Stable No ball caries per unit time Median frequency Yes Increase Stable Union -+ League Increase I 993-95+2000-02 No oftot¡l passes per ¡ Ball in play time changes g¡me Median frequency No Stable Stable No oftotal passes per unit time Median frequency Yes Increase Stable Union ---+ League Increase 1993 -95 ---+2000 -A No ofopen play passes (cross-ovø ¡ Law changes preve,nting slowing per g¡me in 2000-02) of the ball at tle ruck ¡ Ball in play time changes Variable Are Codes Change in Change in Predominant Period ofchange and possible Period ofchange and Convergence becoming rugby union rugby league direction of influencing factors in rugby possible influencing factors ofthe Codes more across time across time conver3ence union in rugby league by 2000-02 alike? frame frame Medi¡n frequency No Stable St¡ble No of open play passes per unit time Median frequency Yes Increase Søble Union - League Increase 1997 -9 +2000 -A No of dunmy half ¡ Law changes preventing slowing passes per grme of the ball at the ruck ¡ Ball inplay time changes Median frequency Yes Increasç Stable Union+Loague l¡crease 1997-99-4000-02 Increase 1988 -92- 1997 -99 No of dummy half . Law changes prwenting slowing o lO-m n¡le change passes per unit of the ball at the ruck . Change inplaying season \o oo time Median frequency No Flucürating Decrease Decrease 1988 -92+1997 -Ð Yes ofoffloads per . l0-m rule change game ¡ Cbange inplaying season Medi¡n frequency Yes Stable Decrease League-Union Decrease 1988 -92-1993 -9 5 No ofoffloads per unit a l0-m rule change time Medi¡n frequency Yes lncrease Stable Union - Le¿gue Inorease 1993 -9 5 ---+2000 -02 No ofball c¡rries into . Increase ball in play time contact per game ¡ 'Use it or lose it' maul law Median frequency Yes Increase Stable Union - League Increase 1993 -9 5 ---+ 1997 -99 Yes ofball carries into 'Use it or lose it' maul law contcct per unit time Variable Are Codes Change in Change in Predominant Period ofchange and possible Period ofchange and Convergence of becoming rugby union rugby league direction of influencing factors in rugby possible infl uencing factors the Codes by more alike? across time across time convergence union in rugby league 200042 fr¡me frane Median frequency Yes trncrease Decrease Union-League Increase I 993-95*2000-02 Decrease 1997 -99 +2000-02 No of tackle attempts ¡ Lineout law changes a Decreased ball in play time p€r game o Professional playing status ¡ Scrumlawchanges r Increased ball in play time Median frequency Yes Increase Stable Union ---+ League Decrease I 988-92* 1993-95 No oftotal ball carries ¡ Use it or lose it'maul law per grme r Ball in play úme changes Mean frequency of No Stable Stable No ball caries per unit \o time \o Median frequency Yes I¡crease Stable Union - League Increase 1993-95-2000-02 No oftotal passes per . Ball in play time changes game Median frequency No Stable Stable No oftotal passes per unit time Median frequency Yes Increase Stable Union - tæague lncrease 1993-95-4000-02 No ofopen play passes (cross-over ¡ Law changes preventing slowing per gsme in 2000-02) of the ball at the ruck . Ball in play timo changes Median frequency No Søble Stable No of open play passes per unit time Variable Are Codes Change in Change in Predominant Period ofchange and possible Period ofchange and Convergence of becoming rugby union rugby league direction of influencing factors in rugby possible influencing factors the Codes by more alike? across time across time convergence union in rugby league 20,.m42 frame frame * League Increase 1997 -99 -02 No Median frequency Yes lncrease Stable Union -2000 of dummy half o Law ch¡nges preventing slowing passes per game of the ball at the ruck . Ball in play time changes Median frequency Yes Increase Stable Union r League Increase 1997 -99+20M-02 Increas e 19 88 -92---+ 1997 -99 No of dummy half o Law changes preventing slowing o l0-mrule change passes per unit of the ball at the ruck . Changeinplayingseason time Median frequency No Fluctuating Decrease Decrease 1988-92---+1997 -99 Yes ofoffloads per a 10-m rule change game a Change in playing season N) O O Median frequency Yes Stable Decrease League -Union Decrease I 988-92- I 993-95 No of offloads per unit a lO-m rule change time Median frequency Yes Increase Stable Union + League Increase 1993-95+2000-02 No ofball carries into ¡ Increase ball in play time contact per game . 'Use it or lose it' maul law Median frequency Yes Increase Stable Union - League Increase 1993 -95 +1997 -99 Yes ofball c¡rries into a 'Use it or lose it' maul law contact per unit time Median frequency Yes Increase Decrease Union _+ League Increase 1993-95+2000-02 Decrease 1997 -99+2000-02 No of tackle attempts . Lineout law changes a Decreased ball in play time per game o Professional playing status . Scrumlaw changes ¡ Increased ball in play timo Variable Are Codes Change in Change in Predominant Period of change and possible Period ofchange and Convergence of becoming rugby union rugby league direction of influencing factors in rugby possible influencing factors the Codes by more alike? across time across time convergence union in rugby league 20ím42 frame frame Median frequency Yes Increase Stable Union * League I¡crease I 993-95*2000-02 Increase 1988-92-1993-95 No of tackle attempts o Lineout law changes a 10-m rule change per unit time ¡ Professional playing status . Scrum law changes Median frequency Yes Increase Decrease Bi-directional Increase 1993 -95 -2000-02 Decrease 1988-92+1993-95 Yes of single tackles a Professional playing stahrs a l0-m nrle change p€r game Decrease 1997 -99 +2000-02 No Median frequency No Increase Decrease Increase 1993-95 -1997 -99 ofsingle tackles (diverging) o Professional playing sktus per unit time ¡ 'Use it or lose it' maul law N) Median frequency No Stable Stable No ofdouble tackles per game Median frequency No Increase lncrease Increase 1993-95+2000-02 Increase 19 93 -9 5 +2000 -Q2 No of double tacRes . Professional playing status ¡ lO-mn¡le change per unit time o Law changes preventing slowing ¡ Change in playing season of the ball at the ruck . 'Use it or lose it' maul law Median frequency No Stable lncrease lncrease 1993 -95 -4000 -02 No of mob tackles per (diverging) r lO-mrule change game r Change in playing season Median frequency No Stable Stable No of mob tackles per unit time Vari¿ble Are Codes Change in Change in Predominant Period ofchange and possible Period of change and Convergence of becoming rugby union rugby league direction of influencing factors in rugby possible infl uencing factors the Codes by more alike? across time across time convergence union in rugby league 20iJi.ùo.2 frame frame Median single No Stable Stable No tacHe percentage per game Median double No Stable Stable No tacHe percentage per game Median mob tackle No Stable Sråble No percentage per game Median missed Yes Stable Fluctuating læague - Union I¡crease 1988-92---+ 1993-95 No tacHe percentage o 10-m rulc change ol.J Per game Decrease 1993 -95 ---+ 1997 -99 l\) a Change in playing season Median frequency Yes Decrease Stable Union --+ League Decreasc 1993 -95 --+1997 -99 No oftotal kicks per o Lineoutlawchanges geme ¡ Professional playing status Median frequency Yes Decrease Stable Union - League Decrease 1993 -95 +1997 -99 No oftotal kicls per ¡ Lineout law changes unit time ¡ hofessional playing status Median frequency Yes Decrease Stable Union - League Decroase 1993 -9 5 ---> 1997 -9 No of kicks out ofplay ¡ Lineout law changes per game r Professional playing stahrs Median frequency Yes Decrease Decrease Union-League Decrease 1993 -9 5 -> 1997 -99 No of kicks out ofplay ¡ Lineor¡t law changes per unit time ¡ Professional playing status Variable Are Codes Change in Changein Predominant Period ofchange and possible Period ofchange and Convergence of becoming rugby union rugby league direction of influencing factors in rugby possible infl uencing factors the Codes by more alike? across time across time convergenoe union in rugby league 20,J,ù0.2 fr¡me frame Median frequency Yes Increase Fluctuation Union - League lncÌrease 1988-92 +2000-02 No of rucla per game . Professional playing status o 'Use it or lose it' maul law o Ball in play time changes Median frequency Yes Increase St¿ble Union-LeagUe Increase 1988-9 ---+1997 -Ð No of ruclis per unit o Professional playing status time o 'Use it or lose it' maul law Median frequency No Søble Stable No of scrums per grme l.J O Median frequency Yes Docrease Stable Union-League Decrease I 988-92- 1993-95 No UJ of scrums per unit Decrease 1997 -9 ---+20@-02 tine a Scn¡m law amendments Median frequency No St¿ble Ståble No of set possessions per game Median frequency Yes Decrease St¿ble Union-League Decrease 1993 -95 -+1997 -9 No of set possessions ¡ Professional playing status per unit time o 'IJse it or lose it' maul law Median frequency Yes Increased Stable Union - League Increase 1988-92 --+ 2ffJ,042 No of activity phases a Changes in ball in pþ time per game Variable Are Codes Change in Change in Predonin¡nt Period ofchange and possible Period ofchange and Convergence of becoming rugby union rugby league direction of influencing factors in rugby possible influencing factors the Codes by more alike? across time across time convergence union in rugby league 2DÍ0,LO2 frame frame Median frequency No Stable Stable No of activityphases per unit time N) èo It is apparent that where the Codes are converging it is changes in rugby union rather than in rugby league than are predominantly responsible for this effect. For most offence variables the increases in frequencies are ostensibly due to increases in ball in play time, although some contribution to changes may be ascribed to changes in playing status and specific law changes. For the defence variables the change to professional playing status in 1996 and the concomitant increase in players and coaches moving from rugby league to rugby union appears to have been a major influence in change. However, it must be noted that the change to professional playing status was accompanied by key law changes at the lineout which may also have impacted significantly on the changes in defence shucture. The law changes at the lineout in 1996, the law changes at the scrum in 1999 and law changes in the ruck and maul in 1993, 2000 and 2001 also appear to have impacted, particularly in relation to the changes in game action variables. In rugby league the change to a summer playing season appeared not to have a major impact on changes in the game. This is somewhat perplexing given the plethora of rule changes which accompanied this change in season ofplay (refer to Figure l. l). Additionally, the introduction ofthe 40-20 kick in 1999 also appears to have had a limited impact on changes in the game. The only rule change to have had an effect on game variables in rugby league- particularly those responsible for the converging of the Codes- was the introduction of the 10-m offside rule in 1992-93. The results of this study indicate that the games of rugby union and rugby league are becoming more alike and the changes in both codes a¡e a result of law and rule changes, changes in playing status in rugby union and to a lesser extent the change in playing season in rugby league. Moreover, the changes in rugby union after the introduction ofprofessional playing status may also be attributed in part to the acceptance ofboth rugby league players and coaches to the union game, particularly in the more structured defence systems employed in the professional Era. 20s CHAPTER 6 PERT'ORMANCE INDICATORS 6.1 Introduction 207 6.2 Summary statistics 208 6.3 Statistical analyses 223 6.3.1 Mean total possession time 223 6.3.2 Meart set possession time 224 6.3.3 Mean continuous possession time 225 6.3.4 Mean ruck time 227 6.3.5 Mean percentage'fast' and 'slow' b¡ll 228 6.3.6 Ball carries 231 6.3.7 Passes 233 6.3.8 Turnovers 233 6.3.9 Successful tackles 234 6.3.10 Tackle type 237 6.3.11 Tackle erron¡ 239 6.4 Discussion 240 6.4.1 Mean total possession time 240 6.4.2 Mean set possession tirne 241 6.4.3 Mean continuous possession time 242 6.4.4 Mean ruck time and percentage 'fast' and 'slow' ball 243 6.4.5 Ball carries 246 6.4.6 Passes 247 6.4.7 Turnovers 247 6.4.8 Successful tackles 248 6.4,9 Tackle type 250 6.4.10 Tackle erron¡ 252 6.5 Summary 254 206 6.1 Introduction The identification of key performance indicators in sports is an important aspect of performance analysis. It enables players and coaches to identify and measure factors associated with successful performance. Whilst in rugby union several studies have been published which report on the identification of these performance indicators (Jackson & Hughes, 2001; James et al., 2005; Long & Hughes, 2004; Parsons et a1.,2001; Vivian et a1.,2001) no publications exist in resea¡ch in rugby league which have attempted to identify any performance indicators, There are, however, a number of concerns with current publications in rugby union which have reported performance indicators. Firstly, it has been common practice for researchers to report only raw frequency scores which have not been normalised or non-dimensionalised. That is to say, no account has been taken of the influence of either a team's possession time or frequency of possession. As a consequence the inferences and conclusion which are based on these data are likely to be flawed. To ensure that performance indicators are correctþ identified Hughes and Bartlett (2002) advocated the presentation of both non-dimensionalised data and the processed data or raw frequency scores. Secondly, research addressing performance indicators in rugby football have reported the differences between winning and losing teams which are all based on full game data. By reporting full game data alone, no account is taken ofthe changes in performance during sections ofthe game. That is to say, those indicators which may have been related to success in a section of play may actually be reported as indicators of failure in the full game data. Hence, it is not possible to identify correctly which performance indicators are true measures of successful performance. In order to identifr clearly the performance indicators in both codes of rugby it is important to report not only full game data,but also data which are more reflective of successful sections of play. To this end the objective of this study was to assess changes and factors influencing change in key performance indicators (by game result and successful game quarters) in rugby union and rugby league in four periods spanning 1988 and 2002 to assess the impact of these factors on the common performance indicators which may have resulted in a converging of the Codes. 207 6.2 Summary data The summary data for time performance indicators by Game Result and Game Quarter Outcome for rugby union are presented in Tables 6.I and 6.2, respectively. The time performance indicators for rugby league by Game Result and Game Quarter Outcome are presented in Tables 6.3 and 6.4. Tables 6.5 and 6.6 present summary data for offence and defence performance indicators in rugby union for Game Result and Game Qua¡ter Outcome, respectively. For rugby league the summary data for offence and defence performance indicators by Game Result and game Quarter Outcome are presented in Tables 6.7 and 6.8. 208 6.1 Time performance indicators (s) by Gane Result by Period for rugby union (mean +SD) Winning teams Losing teams 1988-92 199195 tryt-gg 2ün42 Pre. Professional 198&92 199395 1997-99 2lÙlJfù42 Pre Professional professional Era professional Err Era Era Total time 658.6 649.7 78t.4 934.7 654.1 858.0 6t4.4 7t6.7 843.5 907.7 665.5 875.57 in (4e.e) (rr2.3) (r22.) Qrt.4) (82.e) (183.2) (102.0) (81.0) (152. l) (270.7) (102.8) Qt2.0) possession Percentage 51.5 47.7 48.9 52.4 49.6 50.7 48.5 s2.3 51.1 47.6 50.4 49.3 (7.e) time in (2,8) (6.e) (4.e) (r0.3) (5.4) (7.e) (2 8) (6.e) (4.e) (10.3) (5.4) possession Set 10.0 10.1 14.5 16.0 10.0 15.3 r0.l 10.8 14.l 16.3 10.5 t5.2 (1.3) (2.8) (1.4) (2.8) possession (0.4) (l.l) (l.e) Q.3) (0.8) (2.r) (1.5) Q.6) N) \o time Continuous 16.6 14.6 20.9 24.7 15.6 22.8 16.6 l6.l 22.r 22.4 16.3 22.2 (3.1) (4.4) possession (l.e) (3.2) (3.6) (5.6) (2.8) (4.e) (3.6) Q.e) (3.6) (5 s) time Mean ruck 2.7r 3.25 3.03 3. 13 2.98 3.08 2.77 3.30 3.26 3.08 3.04 3.17 (0.46) (0.33) time (0.31) (0.27) (0.16) (0.3) (0.3e) (0.23) (0.23) (0.50) (0.46) (0.12) Percentage 37.6 27.7 25.8 29.4 32.6 27.6 36.9 26.7 24.4 26.0 3 1.8 25.2 (8.5) (10.1) (7.6) (5.4) (10.4) (6.4) 'fast'ball (10.4) (e.s) (7.3) (7.3) (10.8) (7.2) Percentage r6.1 28.3 23.9 22.4 22.2 23.t L9.7 23.8 24.7 20.8 2t.7 22.7 (4.8) (4.7) (7.6) (8.6) (6.1) (6.6) (8,0) (e.4) (4.3) (7.3) 'slowt ball (7.1) Q.3) Table 6.2 Time performance indicators (s) by Game Qtrarter Outcome by Period for rugby union (mean +SD) 'lYinning teams Losing teams 198& 1993-95 1997- 200(). Pre Professional 19E8- 1993-95 L997-99 2ü)0- Pre. Professional 92 99 02 professional Era 92 02 professional Era Er¡ Era Total tine 139.4 159.7 194.4 237.6 148.3 2ts.5 153.9 164.8 r89.2 186,9 t58.7 188. I in (47.7) (34.2\ (s2.s) (78.3) (42.e) (6e.0) (s1.8) (48.2> (s7.e) (63.e) (4e.7) (60.1) possession Percentage 47.7 49.7 50.9 55.7 48.6 53.2 52.3 50.3 49.1 44.3 5r.4 46.8 time in (13.0) (e.l) (12.3 (t3.7) (l 1.3) (13. l) (13.0) (e.1) (12.3) (13.7) (r r.3) (13. l) possession to.2 10.9 t4.5 t4.9 10.5 14.7 N) Set 9.7 11.0 14.5 18.0 10.2 16.2 o possession (1.8) (3.3) Q.7) (s.l) Q.6) (4.4) Q.4) (2.6) (4.4) (4.3) (2.s) (4.3',) time Continuous 15.0 15.3 22.0 27.3 15.2 24.6 t7.5 15.7 2t.3 20.6 16.8 2l.o possession (4.6) (s.2) (6.2) (10.3) (4.8) (8 e) (8.7) (6.2) (8.3) (7.6) (7.6) (7.e) time Mean ruck 2.59 3.12 3.09 3.06 2.82 3.08 2.87 3.27 3.20 3.ls 3.05 3.18 time (0.73) (0.67) (0.36) (0.34) (0.74) (0.3s) (0.74) (0.67) (0.6r) (0.3e) (0.73) (0.s1) Percentage 4t.r 27.2 23.8 27.8 35.0 25.8 29.8 29.4 24.s 24.2 29.6 24.3 'fast'ball Qs.7) (t4.e) (12.0) (11.2) (22.s) (1r.7) (1e.6) (r2.e) (13.3) (1 1.8) (16.6) (r2.s) Percentage I 1.3 26.2 22.5 20.8 17.8 2t.7 22.0 23.1 27.4 21.6 22.5 24.6 'slow'ball (t2.e) (1e.s) (10.4) (e.3) (t7.6) (e.8) (23.4) (13.7) (12.6) (12.5) (1e.3) (r2.7) 6.3 Time performance indicators (s) by Game Result by Period for rugby league (mean +SD) Winning teams Losing teams 198È92 1993-95 1997-99 2000-02 Pre- Professional 1988-92 1993-95 1997- 2000-02 Pre. Professional professional Era 99 professional Era Era Era Total time in 153r.2 7466.6 1461.4 1427.2 1498.9 t444.3 1450.4 1350.8 1384.7 1243.6 1400.8 1314.2 possession Q47.3) (10r.r) (207.7> (rs6.s) (183.3) (176.2) (112.3) (202.3\ (2s2.3) (22s.s\ (r64.s) (23e.7) Percentage 51.6 5t.4 52.4 54.2 5l .5 53.3 48.4 48.6 47.6 45.8 48.5 46.7 time in (s 7) Q.7\ (4 6) (s.7) (4.2) (s 0) (s.7) Q.7) (4.6) (s 7) (4.2\ (s.0) possession Set possession 36.5 40.6 37.9 37.5 38.5 37.7 36.7 35.8 35.2 34.6 36.3 34.9 time (s 2) (3.8) (3.7) (3.3) (4.e) (3.3) (3 3) (2.0) (3.8) (s 8) (2.6) (4 7) N) Continuous 49.8 59.6 5t.2 67.7 54.7 56.4 49.8 54.7 45.8 53.3 52.3 49.6 possession (s.s) (s.2) (5.e) (6.e) (7.z',) (8.2) (7.0) (8.6) (4 0) (12.8) (7.e) (e e) time Mean ruck 4.92 3.89 3.23 365 4.40 3.44 4.24 3.54 3.32 362 3.89 3.47 time (0.51) (0.s6) (0. le) (0.27) (0.74\ (0.32) (0. le) (0.44) (0.26) (0.22) (0.4e) (0.27) Percentage 8.0 27.0 40.8 26.5 17.5 33.6 13.6 34.9 42.0 23.9 24.3 33.0 'fast' ball (2 8) (14.7) (12.3) (e l) (r4.2) (12.7) (4.6) (r4.7) (11.2) (7 0) (1s.2) (13.0) Percentage 44.2 16.9 4.3 14.6 30.5 9.5 23.5 9.4 3.9 12.2 16.5 8.1 'slow'ball (14.e) (ll.s) (3.2) (3 0) (1e.1) (6.1) (4 8) (8.2) (1.7) (3.2> (e.7\ (s.0) Table 6.4 Time performance indicators (s) by Game Qtrarter Outcome by Period for rugby league (mean +SD) Winning teams Losing teams 1988-92 199'95 1997-99 2000-02 Pre Professional 198È92 1993-95 1997-99 2000-02 Pre Professional professional Era professional Era Era Era Total time in 369.6 350.2 363.7 332.0 359.7 349.r 374.7 319.6 324.9 317.0 317.2 321.3 possession (ee o) (60 e) (87.1) (63 o) (81.3) (77.6) (7e.e) (62.6) (74.8) (ee.3) (70.7) (8s.8) Percentage 53.6 51.9 52.7 52.9 52.7 52.8 46.4 47.3 47.3 47.1 46.8 47.2 time in (t2.3\ (7.3) (6.e) (11 2) (10.0) (e.0) (r2.3) (7.6) (6.e) (10.8) (10.1) (8.8) possession 37.9 36.6 36.3 38.0 37.1 36.1 37.2 36.7 N) Set 36.6 39.2 36.7 36.5 (8.0) (s.7) (s.e) (6.e) (6.e) (6 3) (s 8) (s.7) (6.2) (7.t) (s.7) (6.E) N) possession time Continuous 53.5 61.0 51.2 60.0 57.3 55.2 47.9 52.8 46.5 53.0 50.4 49.5 possession (13.6e) (16 0) (10.3) (1e.0) (ts.2) (1s.4) (17.8) (r r.o) (7.3) (t6.2) (14.8) (12.s) time Mean ruck 4.66 3.70 328 3.78 4.t7 3.51 4.44 3.60 3.25 3.62 4.01 3.42 time (0.s0) (0.47) (0.26) (0.36) (0.68) (0.40) (0.s6) (o 54) (0.2e) (0.20) (0.6e) (0.32) Percentage tl,7 29.6 42.8 25.2 20.9 34.7 9.2 33.7 40.7 25.9 2t.8 33.9 'fast'bdl (7.30) (1s.1) (12.3) (11.2) (14.e) (r4.7) (s.2) (18.3) (1s.5) (8.8) (18.3) (t4.7) Percentage 36.9 tl.7 4.7 9.8 24.O 7.0 27.s I1.6 3.7 6.6 19.4 5.1 (16 (4.t) 'slowt ball (r4.3) (il.1) (4.7) (7.e) (17.e) (6.8) (16 6) (12.7) (4.2) (s 0) 6) Table 6.5 Offence and defence performance indictors (mear¡ median Gange)), Game Result by Period for rugby union 'lVinning teams Losing teams 1988-92 199395 1997-99 2000-02 Pre. P¡ofessional 1988-92 1993-95 1997-99 2000-02 Prrc- Profession¡l pnofessional Era professional Er¡ Era Era Carries into 43.2 45.3 70.7 81.5 44.3 76.1 45.5 55.3 70.3 842 50.4 77.3 contact 40.0 45.0 68.0 87.0 43.0 72.0 44.0 58.0 68.5 80.5 52.0 72.5 (34-57) (35-57) (4r-e2) 45-109 (34-s7) (4r-l0e) (33-61) (37-6e) (57-el) (56-125) (33-6e) (56-125) Carries into 3.9 4.2 5.4 5.2 4.I 5.3 4.4 4.6 5.1 5.6 4.5 5.4 contact per 3.9 4.2 5.t 4.9 4.1 4.9 4.3 4.8 5.3 5.5 4.6 5.5 unit time (3.t-4.7) (3.6-5.0) (4.s-6.5) 4 l-6.3) (3.1-5.0) 4 l-6 5) (3.e-5.4) (3.6-5.6) (3.3-6.0) (s 3-6.2) (3.6-5.6) (3 3-62) Passes in open 67.7 52.0 77.7 85.3 59.8 81.5 55.2 80.0 65.2 91.5 67.6 78.3 play 61.s 46.0 84.5 81.0 59.0 84.5 s8.0 75.7 62.5 97.0 62.0 67.0 (48-e6) (3 l-7e) (s2-e6) (4e-l 15) (3 l-e6) (4e-l ls) (37-66) (46-l 15) (s l-88) (54-130) (37-l ls) (s 1-130) N) u) Passes in open 6.2 4.8 6.0 5.5 5.5 5.7 5.4 6.6 4.7 6.0 6.0 5.3 play per unit 6.0 5.2 6.4 5.5 5.2 5.8 5.4 6.3 4.6 6.0 5.7 5.1 time (4.6-8.2) (3.0-6.7) (3.8-7.0) (4.2-7.2) (3 .o-8 2) (3.8-7.2) (4.3-6.2) 4.4-8.9) (3.8-5.8) (4.6-7.2) (4.3-8.e) (3.8-7.2) Pass to contact 1.6 1.2 1.1 1.1 1.4 l.l t.3 1.5 0.9 1.1 1.4 1.0 ratio 1.6 t.I 1.2 t.I 1.4 t.2 1.3 1.5 0.9 T.I 1.4 t.0 (0.8-1.3) (0.8-1.3) (1: ) (1.0-2.4) (0.6-r.8) (0.6-r.s) (0.7-1.3) (0.6-2.4) (0.6-1.5) (0.8-1.6) (0.8-2.3) (0.8-1.2) (0.8-1.6) Offloads 17.5 8.3 18.7 14.3 12.9 16.5 15.3 12.2 13.0 15.0 13.8 14.0 15.5 8.5 18.0 10.5 14,0 I3.5 t5.5 12.0 12.0 16.5 12.0 14.0 (t426) (2-t4) Q-36) (6-36) (2-26) (2-36) (e-2t) (l l-14) (7-2t) (4-2t) (e-21) (4-2t) Offload to 0.4 0.2 0.3 0.2 0.3 0.2 0.3 0.2 0.2 0.2 0.3 0.2 contact ratio 0.4 0.2 0.2 0.t 0.3 0.2 0.4 0.2 0.2 0.2 0.3 0.2 (0.1-0.2) (r: ) (0.3-0.8) (0 0-0.3) (0.1-0.5) (0.1-0.4) (0.0-0.8) (0.1-.05) (0.2-0.5) (0.2-0.3) (0. r-0.2) (0.1-0.2) (0.2-0.5) Turnovers 9.3 7.0 8.2 7.8 8.2 8.0 11.5 9.3 6.8 t0.2 10.4 8.5 8.5 7.0 4.5 8.0 7.5 6.0 I1.0 9.0 5.0 t0.0 r0.5 7.0 (s-17) (2-12) (t-27) (4-12) (2-r7> (r-27) (7-18) (6-13) (3-17) (s-ls) (6-18) (3-t7> Winning teams Losing teams 1988-92 1993-95 1997-99 2000-02 Pre- Profession¡t 19t8-92 1993-95 1997-9 2000-02 Prc- Profession¡l professional Era professional Era Era Er¡ Turnovers per 0.8 0.7 0.6 0.5 0.8 0.6 1.1 0.8 0.5 0.7 1.0 0.6 unit time 0.8 0.8 0.4 0.5 0.8 0.5 I.t 0.7 0.4 0.7 0.9 0.5 (0.5-1.5) (0.2-r.o) (0.0-l.e) (0.2-0.8) (0.2-1.5) (0.0-l.e) (0.7-t.4) (0.s-r.3) (0.2-o.e) (0.3-1.4) (0.5-1.4) (0.2-1.4) Turnover to 5.1 9.4 20.6 12.0 7.3 16.3 4.2 6.4 14.6 9.7 5.3 t2.t contact ratio 5.5 6.0 I3.8 9.3 5.8 10.7 4.5 6.0 12.2 8.5 4.8 10.8 (3.6-t7.6) (3.6-30.3) (1r ) (3.1-7.0) (3 9-28 s) (3.4-67.0) (6.4-27.3) (3. r-28.5) (3.4-67.0) (2.8-s.4) (4.5-8.6) (3.6-30.3) (2.8-8.6) Successful 57.0 60.5 83.3 94.3 58.8 88.8 54.7 44.7 73.3 87.8 49.7 80.6 tackles 56.0 62.5 85.5 93.5 60.0 89.5 53.5 44.0 67.5 88.0 48.0 74.0 (34-81) (48-6e) (60-106) (72-t2s) (34-8 l) (60-125) (44-70) Q7-67) (4r-107) (46-t2e) Q7-70) (4t-r2e) Tackles 5.5 5.1 5.9 6.4 5.3 6.2 5.0 4.t 5.6 5.5 4.5 5.5 \') 4.9 3.8 5.1 5.7 4.4 5.3 N) completed per 5.7 5.2 6.0 6.4 6.3 5 minute (4.r-6.3) (4.7-5.2) (4.8-7.0) (s.s-7.2) (4.1-6.3) (4.8-7.2) (4.3-s.7) (3.3-5.8) (4.s-7.3) (4.2-6.4) (3.3-5.8) 42-7 3) Percentage 68.2 70.8 72.4 656 69.5 69.0 67.7 76.t 69.5 71.8 7r.9 70.6 single tacHes 67.0 70.2 72.0 65.4 69.3 68.7 67.3 75.0 69.7 73.2 71.5 72.9 (s8.8- (63.9-81.s) (68.7-77.4) (s6.9-7s.0) (58.8-81.5) (56.9-8 r.s) (s7.4-77.3) (tr.e-88.e) (6t.0-79.4) (67.3-7s.0) (s7.4-88.e) (61.0-7e.4) 7e.2) Percentage 28.1 25.0 26.5 32.6 26.5 29.6 28.5 2t.6 27.9 25.0 25.0 26.5 double tackles 27.7 26.5 26.i 33. I 26.5 30.7 29.4 21.9 27.4 2s.3 25. I )\7 (r8.8- (18.5-2e.5) (20.2-3r.3) (25.0-38.e) (18.5-38.3) Q0.2-38.9) (18.241.0) (tt.t-2e.7) (r7.7-36.6) (20.8-29.t) (ll.l4l.0) (17.7-36.6 38.3) Percentage 3.7 4.2 1.1 1.8 3.9 t.4 3.8 2.4 2.6 3.2 3.1 2.9 mob t¿ckles 3.9 3.9 0.5 1.2 3.9 0.5 4.1 2.2 2.7 2.6 3.3 2.7 (r.5-s.7) (0.0-9.4) (0.0-3.3) (0.0-4.2) (0.0-e.4) (0.0-3.3) (r.6-5.6 (0.0-5 4) (t.r-4.7) (0.0-8.7) (0.0-5.6) (0.0-8.7) Missed tackles 6.5 6.s 6.5 8.0 6.5 7.3 6.7 4.0 8.7 7.2 5.3 7.9 7.0 5.5 7.0 7.5 6.5 7.0 7.5 4.0 7t 6.0 4.0 6.0 (2-10) (3-13) (2-e) (3-14) (2-t3) Q-t4) (0-14) (3-5) (3-16) (3-t2) (0-14) (3-16) Winningtcams Losing teams 1988-92 199395 1997-99 200i0-O2 Prç Professional 198ùy2 199395 1997-99 20m-02 Pre Professio prufessio Era professio nel Ere nel Era nal Era Percentage ll.9 10.8 7.8 8.5 10.0 7.5 12.3 9.6 13.1 8.0 9.5 9.3 missed tacklg I t.2 9.9 8.5 7.7 10.0 7.1 11.6 8.3 12.8 8.3 8.5 8.4 (3.8- (4.s-20.3') (3.3-10.e) (3.3-15.3) (3.8-20.8) (3.3-r5.3) (0.0-26.0) (6.0-14.8) (3.2-23.s) (5.5- 10.4 (0.G.26.0) (3.2-23.s) l.J (â Table 6.6 Offence and defence performance indicators (mear\ median, (range)) Game Quarter Outcome by Period for rugby union 'lVinning teams Losing teams 198ù92 199395 1997-99 2000-02 Pre Profession 19E8-92 199395 1997-99 2000-02 Pre Professional professional al Era professional Era Era Era Carries into 9.1 10.9 16.4 20.0 9.8 lE.1 10.4 13. I 17.0 16.7 11.6 16.9 contact 9.5 9.5 17.0 19.0 9.5 18.0 r 1.0 12.5 17.0 15.0 T 1.5 16.0 (3-1 l) (6-2r) (5-34) (e-32) Q-21) (5-34) (4-20) (5-20) (7-3 l) (6-30) (4-2o) (6-31) Carries into 4.0 4.0 5.1 5.0 4.0 5.1 4.1 4.8 5.3 5.3 4.4 5.3 contact per 3.7 3.7 4.8 5.1 5- / 4.9 4.2 4.8 4.9 5.2 4.4 5.1 (2.6{.1) (3.8-7.7) (1.96.5) (2.6-8.1) (1,7óÁ) 6-7.3) (3.74.7) (1.74.7) (1.74.7) unit time (1.e6.s) Q.e-s.n Q.6.6.7) {3 Passes in open 15.3 13-6 t7.8 21.4 14.5 19.6 13.1 17.4 17,3 19.7 15.0 18.5 play 14.0 13.5 17.0 21.5 r4.0 18.0 12.0 12.0 18.0 19.5 12.0 18.0 (6-32) (6-22) (4-2e) (s-3Ð (6-32) (4-3Ð (3-2s) (643) (0-2e) (440) Q43) (343) N) Passes in open 6.5 5.2 5.6 5.4 5-9 5.5 5.1 6.0 5,8 6.1 5.5 5.9 Or play per unit 6.3 5.2 5.0 5.8 5.8 5.6 5.0 5.2 5.4 5.9 5.0 5.6 (3 (l 9-9 7) (2.3-8.5) (0.0-16.6) (1.7-8.e) (20-12 0) (1.7-12.0) time 8-9 7) (l e{.2) Q.1-r2.2) Q.2-7.s) 8.1-r2.2) Q0-12.0) Pass to 1.9 1.4 t.2 1.1 1.6 l.l 1.5 t.4 1.2 l.l 1.4 t.2 cont¿ct ratio 1.7 1.3 1.0 I.I 1.7 1.0 1.2 1.3 1.0 L1 1.2 I.I (0.8-3.4) (0.4-2.6) (0.4-2.e) (0.5-1.Ð (0.4-3.4) (0.4-2.e) (0.5-s.0) (0.3-3.0) (0.04.1) (0.3-2.2) (0.3-5.0) (0.34.1) (1: ) Offloads 4.3 2.9 J.5 3.7 3.7 3.5 3.1 2.0 3.9 3.2 2.6 3.5 4.5 2.0 3.0 3.0 3.5 3.0 )t 2.0 3.0 3.0 2.0 3.0 (0-10) (0-7) (0-r3) (0-l 1) (0-10) (0-l 3) (0-8) (0-8) (0-r3) (0-1Ð (0-8) (0-13) Ofrload to 2.4 3.7 5.3 9.2 3.0 6.3 4.0 6.5 6.0 6.0 5.5 6.0 cont¡ct ratio* (1: ) Turnovers 2.1 t.9 1.6 2.0 2.0 1.8 ¿.3 1.8 2,0 1.8 2.1 l.e 2.0 2.0 2.0 2.0 2.0 2.0 3.0 1.5 LO 1.5 2.0 LO (0-s) (0-5) (0-5) (04) (0-5) (0-Ð (0-s) (04) (0-14) (0-s) (0-5) (0-14) Winning teams Losing teams 1988-92 199395 1997-99 2000-02 Pre Profession 1988-92 1993-95 1997-99 2000-02 Pre- Professional professional al Era professional Era Era Era Turnovers 1.0 0.8 0.5 0.5 0.9 0.5 1.0 0.7 0.6 0.6 0.9 0.6 per unit tine 1.0 0.8 0.5 0.5 0.9 0.5 I.I 0.5 0.4 0.6 0.8 0.5 (0.04.4) (0 0-22) (0.0-l.e) (0 0-l 4) (0 0-22) (0 0-l e) (0.0-2.3) (0.0-1.8) (0 0-3 6) (0.0-l s) (0 0-2 3) (0 0-3 6) Turnover to 3.5 7.0 9.0 9.0 40 9.0 i.8 6.5 7.8 55 7.7 contact ratio* (1: ) Successful t2.t I 1.5 19.8 19.0 1 1.8 19.4 12.7 12.9 17.2 2t.4 12.8 19.2 tackles 12.0 10.5 20.0 18.0 11.0 19.0 I 1.5 9.5 18.0 22.0 11.0 18.0 Q-27) (2-2s) (s42) (1G.32) Q-17) (s42) (4-23) Q-28) (4-34) Q-3s) (4-28) (4-35) Tackles 4.6 4.0 6.1 6.2 4.4 6.1 5.5 4.7 5.4 5.5 5.1 5.4 completed per 4.5 4.2 6.5 5.9 4.3 6.0 5.7 4.0 5.1 J.J 4.3 5.4 (1 (3.0-l (2.8-8.7) (2.1-e.e) t-e e) N) minute (2 0-8 6) (1 1.62) (3.0-e.0) (3.2-r1.2) 1-8 6) 1.2) Q.7-8.6) a 5-8 8) Q.7-8.7) Q { Percentage 69.6 74.9 71.8 69.4 '11.9 70.6 68.7 79.4 71.3 6.9 73.4 692 single tackles 7s.0 73.9 74.1 74.3 73.0 74.1 68.6 80.0 70.6 6s.9 7r.7 69.2 (25.0-100) (61.s-100) (44.4-87.s) (47.r-82.4) (2s.0-l00.cD (44.4-87.s) (41.7-100.0) (37.5-100.0) (56.3-8e.Ð (4s.s-92.9) (37.5-100-0) (4s.s-e2 9) Percentage 27.1 21.5 34;7 295 24.6 32.1 276 19.5 31.9 28.6 24.0 30.3 double t¡ckles 21.5 23.3 26.2 25.0 23.1 25.9 27.6 15.2 25.0 31.0 24.3 28.0 (0.0ó2.3) (0.0-38.5) (6.3-76.5) (15.8-52.9) (0.0-62.3) (6.3-76 s) (0.0-58.3) (0.0ó2.5) (10jó6.7) (7.145.5) (0.056.Ð 166 7) Percentage 3.4 3.6 l-7 1.1 3.4 l4 3.1 t.2 1.8 45 26 3.1 mob tackles 1.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.6 00 0.0 (0.0-12,5) (0.0-r2.s) (0.0-9.1) (0.0-10.s) (0 0- t2 5) (0.0-10 5) (0.0-2s.0) (0.0-12.s) (0.0-11.8) (0.0-18.2) (0.0-25.0) (0.0-r8.2) Missed 1.7 1.1 t-6 1.4 l5 1.5 1.1 1.5 1.9 2.0 l3 2.0 tackles 2.0 0.5 1.0 1.0 1.0 1.0 1.0 1.5 2.0 2.0 1.0 2.0 (0-5) (0-5) (0ó) (04) (0-s) (0ó) (0-5) (0-4) (0ó) (0-5) (0-s) (05) Percentage 13.5 7.3 6.8 70 10.8 6.9 8.8 I 1.3 9.7 8.7 9.9 9.2 t7 ) missed tackles 8.9 2.8 3.2 6.6 7.6 5.9 6.8 7.1 7.7 8.0 7.4 (0-50.0) (0-33.0) (0-3 l 3) (0-25.0) (0.0-50.0) (0.0-33.0) (0 042 9) (0.0-25.0) (0.0-33.3) (0.0-20.0) (0.0-25.0) (0 0-25.0) 6.7 Offence and defence performance indictors (mean, median (range), Game Result by Period for rugby league Winning teams Losing teams 198&92 199395 1997-99 2000-02 Pre- Professional 1988-92 1993-95 1997-99 2000-02 Pre Professional professionel Era professional Era Era Era Carries into 129.3 r33.3 145.3 133.0 l3 1.3 139.2 141.5 t34.7 15 1.8 t33;l 1 38.1 142.8 124 13s.5 141.5 133.0 132.0 135.0 140.s 136.0 152.0 129.5 138.0 147.0 cont¿ct (ee-173) (120-181) (r29-r'77) (108-l4e) (ee-181) (108-17Ð (l l9-160) (r08-156) (116-l%) (r08-171) (r08-r60) (108-194) Carries into 5.1 55 6.2 5.4 5.3 5.8 5.8 6.0 6.3 6.7 5.9 6.5 5.8 6.2 6.2 6.0 5.9 6.0 contact per 4.9 5.5 6.2 5.4 J.3 5.7 (4.8-s.6) (5. l-5.8) (5 76 8) (s 1-5 8) (4.8-5.8) (5.16.8) (5 642) (5.3ó 3) (5 9:7 0) (5.6-r 1.0) (s243) (5.6-l1.0) unit time N) Passes in open 72.8 80.0 65.2 6.2 76-4 65.7 76.7 61.8 81.2 63.0 69.3 73.1 66.5 70.5 67.0 play 73-5 80.0 62.s 67.5 74.0 65.5 72.5 65.0 79.5 oo (44-es) (62-102) (37-101) (46-82) (44-t02) (37-l0r) (62-%) (46:74) (s3-13Ð (4s-77) (46-e6) (4s-137) Passes per unit 2.9 J-i 2.8 2.8 3.1 2.8 3.2 2.7 3.4 3.2 3.0 3.3 3.1 2.7 2.9 2.8 3.2 3.2 2.9 3.2 time 2.7 3.2 2.8 2.7 (2.4-3.8) Q343) (l 5-3 e) (1.84.3) (2.34.3) (l 44 (2.84.1) Q.1-3.3) Q747) (1 e43) Q 14 l) (r 94 7) OfrIoads 14.3 14.5 15.5 18.0 14.4 16.8 20.8 t7.3 12.0 11.7 19. l I 1.8 14.5 15.0 16.0 16.5 14.5 16.5 19.5 15,0 13.0 12.0 19.5 12.0 (8-21) (e-20) (e-22) (r3-26) (8-21) (e-26) (r4-29) (6-3 l) (5-1e) (6-18) (6-3 1) (5-le) 0llload to 9.4 9-7 10.5 7.8 0.1 0.1 7.5 10.8 16.3 12.4 0.1 0.t 8.7 8.6 9.0 8.0 0.1 0.1 7.5 9.9 12.8 I 1.3 0.1 0.1 contact ratio (6.1-30.4) Q.9-12,4) (7.1-14.3) (6 0-16 3) (5.4-l1.5) (7. r-14.3) (5.4-16.3) (4.r-1 l.l) (4 4-21.8) (6. l-30.4) (8.5-le.Ð (4.1-21.8) (1: ) Winning teams Losing teams 1988-92 199395 1997-99 2000-02 Pre Professional 19w92 199&95 1997-99 2000-02 Pre' Professional professional Era professional Era Era Er¡ Turnovers 10.5 7.7 I1.0 r0.2 9.1 10.6 tt.2 8.2 10.7 9.5 9.7 t0.l 8.0 8.0 10,0 9.0 8.0 9.s 10.0 8.0 I1.0 8.5 9.0 n.0 (3-re) (s-10) Q-r7) (6-ls) (3-1e) (6-r7) Q-te) (5-r2) (6-15) a-14) (s-le) (6-15) Turnovers per 0.4 0.3 0.5 0.4 0.4 0.4 0.5 0.4 0.4 0.5 0.4 0.5 0.4 0.4 unit time 0.3 0.3 0.4 0.4 0.3 0.4 0.1 0.3 0.4 0.4 (0 14 8) (0 24 5) (0 34 8) (0 24 6) (0 l4 8) (0 24 8) (0-34 7) (0.2{.6) (0 34 6) (0.34.Ð (0.24.D (0 24.6) Tur:novers to 18.1 18.6 14.8 14.2 18.4 14.5 l4.l 17.7 15.6 15.0 15.9 15.3 16.0 17.0 15.2 13.5 t7.I 13.9 14.6 16.4 14.9 15.0 16.0 15.0 ratìo contact (6.342.3) (120-27 2) (9.e-22.0) (6.342.3) (8.2-20.3) (10.e-28.2) (r0.1-25.3) (8.2-28.2) N) (1: Q.8-2r.6) Q.8-22.0) Q.9-20.3) Q-e-2s.3) \o ) Successful t&.2 155.0 156.3 134.5 r59.6 145.4 148.2 149.3 171.0 157.0 148.8 164.0 r62.5 157.0 15 3.5 125.0 162.s r48.5 140.0 150.0 162.0 r56.5 149.0 158.0 tackles (150-17Ð (l ls-18Ð (t25-199) (1 l8-164) (1 l5-r8Ð (l l8-199) (102-1ee) (138-l60) (148-20Ð (t2e-r76) (r02-lee) (rze-zoD Tackles 6.E 6.9 6.8 6.2 6.8 6.7 5.8 6.1 6.5 6.4 5.9 6.8 6.8 6.9 6.4 6.8 6.5 5.5 6.1 6.9 6.6 5.9 6.7 completed per 6.8 (6.6-7.0) (6 5:7 6) (6.0-7.3) (6.0-7.6) (6.5-7.6) (6.0:7.6) (5.36.5) (5.8ó.ó) (6.0-7.3) (6.1-7.6) (5.36.6) (6.0-7.6) minute Percentage 50.9 53.5 45.0 38.2 52.2 4t.6 46.7 44.8 49.2 426 45.8 45.9 45.0 39.0 s0.8 43.4 46.4 44. I 48.6 41.6 44.1 47.0 single tackles 49.8 5s.3 (40.5ó3 0) (40.062.6) (35.0-54.e) Q9.343.3) (40.063.0) Qe.3-63.0) (41.2-s4.6) (40.0-51.o (46.0-52.3) (34.0-51.e) (40.0-54.6) (34.o-52.3) Winning teams Losing teams 198t-92 199395 1997-99 2000-02 Pre' Professional 1988-92 199395 1997-99 2000-02 Pre- Professional professional Era professional Era Era Er¡ Percentage 40.7 39.0 46.4 51.5 39.9 48.7 44.9 46.4 43.7 50.1 45.6 46.9 50.8 38.5 50.0 44.6 46.3 43.1 49.4 45.2 44.3 double tackles 42.0 36.0 45.7 (33-349 r) (30.5-54.5) (38.6-53.3) (48.3-53.Ð (30.5-s4.Ð (38.6-s3.Ð (40.248.7) (41.9-50.6) (41.248.0) (3e.e-se.2) (40.2-50.6) (3e.e-se.2) Percentage 8,3 7.5 8.6 10.7 7.9 9.7 8.4 8.8 7.2 7.4 86 7.3 7.6 9.0 6.8 6.1 8.2 6.6 mob tackles 8.5 7.0 9.5 10.0 7.6 9.5 (3.7-tt 4) (4.1-13.0) (3.2-1t.7) (6.3-17.1) (3.7-13.0) (3 2-17.1) (5.0-14.7) (s.6-11.3) (4.1-1 1.3) (4.7-t2.8) (5.0-14.Ð (4.1-12.8) N) l.J ))) 18.5 27.5 18.3 o Missed tackles 18.2 26.2 17.0 12.7 14.8 23.3 3t:l r8.0 17.0 25.5 16.0 I 1.5 22.0 13.0 26.5 3L5 19.0 15.0 30.0 r5.0 (tt-27) (t2-37) (s-2e) (8-20) (l r-37) (5-le) (t2-33) Q242) (3-30) (12-35) (12-42) (3-35) Percentage 9.9 14.5 9.5 8.5 t2.2 9.0 13.2 17.5 9.1 10.4 15.4 9.7 9.1 8.3 13.0 8.3 14.0 17.2 9.5 9.5 I6.l 9.s missed tackles 9.6 13.9 (6.3-13.8) Q.7-2t.3) (3 e-ls.e) (6.4-11.6) (6.3-23.3) (3.9-15.9) (8.s-16.e) (r2.4-23.3) <2.0-13.2) (6.4-17.2) (8.5-23.3) Q.0-17.2) Table 6.8 Offence and defence performance indicators (-eaq median, (range)), Game Quarter Outcome by Period for rugby league Winning teams Losing teams 198&92 199&95 1997-99 2000-02 P¡e' Profession¡l t9Eù92 199$.95 1997-99 2000-02 P¡e- P¡ofe¡sion¡l profesrional Er¡ professional Er¡ Era Era Carries into 38.1 31.9 40.6 36. I 38.0 38.5 34.8 5t.t 37.8 34.3 36.3 36.2 39.0 38.0 3s.0 39.0 36.s 33.0 36.0 36.0 contact s9.5 37.0 4L0 36.0 (r2-s5) Q743) Q4-s7) Q746) (12.6.3) (24-57) (15-53) (2160) (2r-56) (7-5 l) (rs50) Q-s6) Carries into 6.3 6.5 6.8 6.6 6.4 6.7 6.7 7.2 7.0 6.6 6.9 6.8 6.7 6.8 6.8 6.1 6.8 6.7 contact per 6.1 6.6 7.0 6.3 6.3 6.5 (3.e-8.e) (4.6-10.3) (5 0{ 4) (5 1-r0 o (3 9-10 3) (s.0-r0.6) (4.8{.Ð (3.1-r3.0) (5.7-8.8) (s.r-14.4) (3 l-r3 0) (s. l-14.4) unit time Passes in 20.2 18.1 17.6 15.2 19. l 16.5 15.4 ls.9 17.9 16.2 15.6 l7.t 14.0 20.0 14.0 15.5 16.0 16.s 16.0 16.0 16.0 open play 21.0 18.0 17.0 (2-37) (8-32) (8-28) (4-32) 8-37) (4-32) (1-25) (5-33) (7-3e) (3-30) (l-33) (3-3e) 1..) N) Passes in 3.3 3.0 2.9 2.8 3.2 2.8 2.9 3.0 3.3 3.1 3.0 3.2 3.3 3.0 2.6 2.3 3.1 2.5 3,1 3.0 3.2 3.2 3.0 3.2 open play (1.3-7.5) (ts47) (l.s-5.2) (0 6-s 4) (1.3-7.Ð (0 6-s 4) (0 s-s.2) (1.2-6.3) (l 3-5 7) (1.64.5) (0.56.3) (1.3-5:t) per unit time Offloads 4.9 3-7 3.9 3.9 4.2 3.9 3.1 3.5 2.8 3.5 5.5 3.1 4.0 3.0 3.5 3-0 3.0 4.0 2.5 3.0 3.0 3.0 3.0 3.0 (1-l l) (0-e) 0-7) (0-e) (0-l l) (0-e) (0-8) (0-e) (0-Ð (0-10) (0-e) (0-10) OfÍIoad to 8.9 I 1.7 11.4 13.7 I 1.7 10.7 14.5 16.9 12.3 I t.7 13.3 12.3 contact ratio* (1: ) Turnovers 2.8 1.9 ', ') 2.1 2.3 2.t 1.5 1.9 3.0 2.5 2.1 2.8 3.0 2.0 2.0 2.0 2.0 2.0 2.0 1.0 3.0 2.0 2.0 3.0 (06) (04) (1-5) (14) (06) (l-5) (0-Ð (l-5) (16) (0-5) (0-7) (0ó) Tur:nover 0.5 0.3 0.3 0.4 0.4 0.4 0.4 0.2 0.5 0.5 0.3 0.5 per unit time* Winning teams Losing teams t98t-92 1993-95 1997-99 2000.02 Pe Profe¡¡ion¡l 198&92 199395 1997-99 2000-02 Pr+. Profe¡sion¡l professioual Er¡ profecolonal Ers Era E¡¡ Turnoyer to 12.0 18.3 20.3 17.5 15.5 19.0 15.0 29.0 12.5 13.4 21.0 13.0 contsct ratio* (1¡ ) Successful 39.4 41.8 41.2 36.9 40.6 ?9.2 44.0 46.1 45.6 41.2 45.2 43.6 tackles 37.5 44.0 39.5 36.0 42.0 38.0 43.5 46.0 48.0 42.0 45.0 42.0 (r760) Q7-s2) Q242) (7-5e) (1760) Q42) (10-66) (3351) (286e) Q4-s4) (1066) Q44e) Tackles 7.6 7.8 7.6 7.2 7.7 7.4 7.1 7.9 7.6 7.2 7.5 7.4 completed per 7.7 7.7 7.4 6.9 7.7 /,J 6.8 7.7 7.8 7.1 7.0 7.5 (5.4-r (5.6-l (4.7-e.8) (6.4-8.5) (s.4-11.2) (4.7-e.8) minute (5. r-e.9) (4. t-e.5) (6.3-8.e) (s.2-8.4) (4.1-e.e) 5.2-8.90 1.2) 1.0) Percentage 49.s 49.6 46.3 40.5 49.5 43.7 48.6 48.2 48-9 42.8 48.4 46.0 single tackles 48.9 47.5 45.6 42.5 47.7 45.5 46.t 50.0 50.6 40.4 47.4 50.0 N) (33.3-75.E) Qe.6-71.4) (31.0ó2.5) (14.3-52.3) Qe.6-7s.8) (14.3-62.5) (40.066.Ð (32,r-64.3) (16.2-7t.1) Q6.3J04) Q2.t6.7) (16.2-71.1) l'.) N) Percentage 428 42.6 45.8 50.8 42.7 48.1 43.4 43.t 43.1 49.5 43.2 46.0 double tacHes 43.6 41.9 45.5 50.0 42. I 46.8 44.7 43.6 42.0 46.9 43.6 44.2 Q2.2-ss.9) Q6.243.0) (2s.0-63.3) (27.8-8s.7) Q2.2- 63.e) Qs.0-8s.7) (30.7-58.3) Q3.840.7) Qe.0-70.3) Q9.o-73.7) Q3.86.7) Q9.0-73.7) Percentage 7.7 7.8 7,9 8.7 7.7 8.3 80 8.8 8.0 7.8 8.4 7.9 77 mob tackles 6.3 7.5 6.3 7.7 6.5 63 7.9 7.9 6,3 7.4 7.6 (0.0-2r.2) (0.0-15.2) (0.0-16 3) (00-222) (0.0¿1.2) (0.0-22.2) (0 0-2 e) (0.0-21.e) (0.0-22.0) (0 0-32 4) (0.0-21.e) (0.0-32.4) Missed tackles 4.1 6.3 3.4 3.6 {t 3.5 6.0 8.7 5.2 4.6 7.4 4.9 4.0 7.0 3.0 4.0 5.0 3.0 5.5 8.0 5-5 5.0 7.0 5.0 (l-8) Q-l1) (0-8) (0-8) (l 1) (0-8) (0-14) (3-tÐ (0-12) (l-12) (0-1Ð (0-12) Percentage 9.9 14.s 9.5 8.5 12.2 9.0 11.2 15.7 10.1 9.3 13.5 9.7 missed tackles 9.6 13.9 9.1 8.3 12.0 8.7 10.8 15.4 9.7 8.5 13.0 9.2 (6.3-13.8) Q.7-23.3) (3.e-15.e) (6.4-11.6) (6.0-23.3) (6.0-23.3) (0.0-20.6) Q.7-22.7) (0.0-22.5) (2.6-18.E) (0.0-22;t) (0.0-22.s) 6.3 Statistical Analyses 6.3.1 Mean total possession time Rugby Uníon In neither Era nor any of the four Periods were significant Game Result differences identified for total possession time (Table 6.1). In addition, no significant Game Quarter Outcome difference was identified in either Era, however, a significant (t = 2.25, P < 0.03) difference was identified in the 2000-02 Period, with teams winning Game Quarters maintaining possession for 55.7%o of the time (Table 6.2), representing 5l s more possession time per quarter than teams losing Game Quarters (Figure 6.1). ¡* 350 300 ar) 2s0 o trf 200 -' - J' - Garne Quater Winner É 150 -----r- Grne Quarter loser ocl À= 100 50 0 t988-92 1993-95 1997-99 2000-02 Period Figure 6.1 Mean + SD total possession time per quarter in rugby union by Game Quarter Outcome. * significant Game Quarter Outcome difference P < 0.003. Rugbl League No sþnificant possession time Game Result difference was identified in either Era or any of the four Periods, however, it is notable that the possession percentage was greater for winning teams than for losing teams in all four Periods (Table 6.3). This was most apparent in the 2000-02Period, with winning teams maintaining possession for 183 s more than losing teams. A significant (t = 2.83, P < 0.005) Game Quarter Outcome difference was identified in the pre-professional Era" teams winning Game Quarters maintaining possession for 43 s more per quarter than teams losing Game Quarters (Table 6.4). No significant Game Quarter 223 Outcome difference was identified in any of the four Periods, howeveq in all Periods teams losing Game Quarters had less possession time than teams winning Game Quarters (Table 6.4). ó.3.2 Mean set possession time Rugby Uníon In no Era or any of the four Periods was a significant mean set possession time Game Result difference identifìed. In addition, no signiflrcant Era Game Quarter Outcome difference was noted, however, in the professional Era teams winning Game Quarters had higher mean set possession times (16.2 s) than teams losing Game Quarters (14.7 Ð. This difference was due to a significant (t:2.12, P < 0.04) Game Quarter Outcome difference in the 2000-02 Period, with teams winning Game Quarters maintaining possession for longer (18.0 s) than teams losing Game Quarters (1a.9 s) @igure 6.2). * 25 ã20 I €) Ë t) - - -o.'' Gane Quarter Winner ã10 ------¡- Game Quarter Loser à5-€) 0 1988-92 t993-95 1997-99 2000-02 Peúod Figure 6.2 Mean + SD set possession time per quarter for rugby union by Game Quarter Outcome. * significant Game Quarter Outcome difference P < 0.04. Rugby League No signifrcant set possession time Game Result difference was identified in either Er4 however, a significant (t:2.75, P < 0.02) difference was noted for the 1993-95 Period, winning teams having longer duration of set possession time than losing teams (Figure 6.3). In no other Period were significant time differences identified, but it is notable than in both professional Periods winning teams had higher possession times than losing teams (Table 6.3). No signifrcant Game Quarter Outcome difference was identified in either Era or any ofthe four Periods (Table 6.4). 224 rl. 50 I @40 Ë30 -'-j--GameWinner ã20 -¡-Ganel¡ser eÀ10 0 1988-92 1993-9s 1997-99 2000-02 Period Figure 6.3 Mean + SD set possession time per game for rugby league by Game Result. * significant Game Result difference P < 0.02. 6.3.3 Mean continuous possession time Rugby Unìon In rugby union no significant mean continuous possession time Game Result difference was identified in either Era or any of the four Periods, neither were signifìcant Game Quarter Outcome differences noted in either Era. However, mean continuous possession times were (on average) notably higher for teams winning Game Quarters (24.6 s) than losing Game Quarters (21.0 Ð in the professional Era (Table 6.2). This difference was predominantly due to the significant (Z: - 2.10, P < 0.04) difference identified in the 2000-02 Period, with teams winning Game Quarters having gteater continuous possession times than teams losing Game Quarters @þre 6.4). 225 35 ¡f .-. 30 ízsçn I .Ë 20 - - -<} - - Gmre QuarterWinner ã15 ---r- Gune Quarter Loser =u10 Å5llr 0 1988-92 1993-95 1997-99 2000-02 Period Figure 6.4 Mean + SD continuous possession time per quarter for rugby union by Game Quarter Outcome. * signifïcant Game Quarter Outcome difference P < 0.04. Rugby League No significant Game Result difference was identified for continuous possession time in either Era; however, times were greater for winning teams than losing teams in the professional Era (Table 6.3). Similarly, no significant Game Result differences were noted in any Period, howeveq in all post-1988-92 Periods continuous possession times for winning teams ïvere notably greater than for losing teams (Table 6.3). A significant (Z: - 2.55, P < 0.01) Game Quarter Outcome difference was identified in the pre-professional Erq with teams winning Game Quarters having longer continuous possession time (57.3 s) than teams losing Game Quarters (50.4 s) (Table 6.4). similar, but non-significant difference was noted in the professional ^ Er4 with the teams winning Game Quarters also having longer continuous possession (55.2 Ð than teams losing Game Quarters (a9 5 s). \{hilst a significant (Z: - 7.98, P < 0.05) Game Quarter Outcome difference was only identified in 1988-92, teams winning Game Quarters had notably greater continuous possession times than teams losing Game Quarters in both 1993-95 and 2000-02 (Figure 6.5). 226 80 ¡t I Ëuo I I - - -j - - ;40 Gane QuaterWinner GI -----r- Gane Quarter loser À820 0 1988-92 1993-95 1997-99 2000-02 Period Figure 6.5 Median (Inter-quartile range) continuous possession time per quarter for rugby league by Game Result. * significant Game Quarter Outcome difference P < 0.05. 6.3.4 Mean ruck time Ragby Uníon No significant Game Result difference was identified in either Era or any of the four Periods, nor u/as a significant Game Quarter Outcome difference noted in either Era or any Period. However, in both Eras means ruck times were lower for winning te¿ms and teams winning Game Quarters than losing teams and teams losing Game Quarters. In additiorL mean ruck times were lower for teams winning Game Quarters than teams losing Game Quarters in all Periods @igure 6.6). 5 art 4 o E J - " e-'- Gune QuarterWinner -----r- Gane loser 2 I Quarter cË €) il à t 0 1988-92 r993-9s 1997-99 2000-02 Period Figure 6.6 Mean + SD ruck time per quarter for rugby union by Game Quarter Outcome. 227 Rugby Leøgue No significant mean ruck time Game Result difference was identified in either Era, however, times were notably greater for winning teams (4.40 s) than losing teams (3.89 s) in the pre-professional Era (Table 6.3). A significant (t:3.07, P < 0.01) Game Result difference was noted in the 1988-92Period, with winning teams having longer duration mean ruck times (3.89 s) than losing teams (3.5a s) (Table 6.3). In no other Period were Game Result differences identified as significant. No significant Game Quarter Outcome difference was noted in either Era or any Period, however, in both Eras and all Periods teams winning Game Qua¡ters had slightly longer duration mean ruck times than teams losing Game Quarters (Figure 6.7). 6 5 çr) e) 4 É -' - j - - Gane Quarter Winner J Ë ---+- Game Quarter loser 6 6¡ 2 tst à I 0 1988-92 1993-95 1997-99 2000-02 Period Figure 6.7 Mean + SD ruck time per quarter for rugby league by Game Quarter Outcome. 6.3.5 Mean percentnge'fast' and 'slow' ball Rugby Uníon No significant Game Result differences were identified for the percentage 'slow' or percentage 'fast' ball in either Era or any Period. In all Periods, however, winning teams had slightly higher percentage 'fast' ball than losing teams (Table 6.1). No significant Game Quarter outcome was identifìed in either Era or any Period, however, in the pre-professional Era teams winning Game Quarters had notably higher 'fast' ball percentage (35 0%') than teams losing Game Quarters (29.6%) and lower percentage 'slow' ball (17.8%) than teams losing Game Quafters (22.5þ - a trend not evident in the professional Era. These differences were predominantly due to Game Quarter Outcome differences noted in the 1988-92 Period, with teams winning Game Quarters having much higher percentage 'fast' ball (4L1%) than teams losing Game Quarters 89.8%), and lower percentage 'slow' ball (11.3%) than teams losing Game Quarters (22.0%)(Figure 6.8). 228 80 6l o) =ÊàD 60 *-Garne QuarterWinner .ÉË 40 +- Gære Quarter loser 8äÉh àll 20 0 1988-92 1993-95 1997-99 2000-02 Period Figure 6.8 Mean + SD percentage 'fast' ball, per quarter in rugby union by Game Quarter Outcome. Rugby League A significant (Z: - 2.02, P < 0.05 ) Game Result difference was identified for percentage 'slov/' ball in the pre.professional Er4 with winning teams having a higher percentage than losing teams (Table 6.3). In addition, winning teams were found to have less (non-significant) percentage 'fast' ball (17 .5%) than losing teams Q,4.3%o). Significant differences were also identified for both 'fast' (Z: - 2.24, P < 0.03) and 'slow' ball (Z: - 2.56, P < 0.009) percentage in the 1988-92 Period (Figure 6.9 and 6.l0). 60 Ë.,50 - - -?'- Gane Winner E &'+o !r6?o -----r- Gane l¡ser -ê) ¡1. €Eroí) E10 t' 0 1988-92 1993-95 1997-99 2000-02 Period Figure 6.9 Median (Inter-quartile range) percentage 'fast' ball, per game in rugby league by Game Result. * significant Game Result difference P < 0.03. 229 60 {. ¡í)=cl 50 76t 40 I ---r}-- GaneWinner eõ 30 Åe) ----+- Game l¡ser .EqlEl t¡r 20 6) I À- 10 0 1988-92 try3-9s 1997-99 2000-02 Period Figure 6.10 Median Qnter-quartile range) percentage'slow' ball, per game in rugby league by Game Result. * significant Game Result difference P < 0.009. No significant Game Quarter Outcome differences for either the percentage 'slou¡' or 'fast' ball were identified in either Era, however, median 'slow' ball percentage was noted as significantly (Z = - 2.06, P < 0.04) higher for teams winning Game Quarters than losing Game Quarters in the 1988-92 Period (Figure 6.1 1). 50 ¡f =ro)d 40 -oE I 30 - - -r> - - Gãne Quarter Winner -v, õ -----¡- Gane Loser .EeËP 20 Quarter grO lii à l0 0 1988-v2 193-9s r9E7-9 20W-02 Period Figure ó.11 Median (Inter-quartile range) percentage 'slow' ball, per quarter in rugby league by Game * Quarter Outcome. significant Game Quarter Outcome difference P < 0,04. 230 6.3.6 Ball carries Rugby Uníon No significant Game Result difference was identified for either the frequency of ball carries into contact, or the frequency per unit time, in either Era or any of the four Periods (Table 6 5). In addition, no significant Game Quarter Outcome difference was noted for either the frequency or frequency per unit time in any Era or Period, however, it is notable that in all Periods teams winning Game Quarters had fewer carries into contact per unit time than teams losing Game Quarters (Table 6.6). This was most notable was in the 1993-95 Period, with teams winning Game Quarters (on average) carrying the ball into contact 4.0 times per min compared to teams losing Game Quarters carrying the ball into contact 4.8 times per min (Table 6.6). In neither Era, nor any Period were significant Game Result differences identified for the frequency of offloads or the offload to contact ratio. However, a significant (Z: - 2.39, P < 0.02) offload to contact ratio Game Quarter Outcome difference was noted in the pre-professional Era, teams winning Game Quarters having significantly lower ratios than teams losing Game Quarters (Table 6.6). In the professional Era ratios were similar (approx. l: 6.0) for teams winning and losing Game Quarters. No significant Game Quarter Outcome difference was identifïed for either ofiload frequency or offload to contact ratios in any Period; however, it was notable that the offload to contact ratio increased across the four Periods for teams winning Game Quarters, whilst in teams losing Game Quarters the ratio remained relatively stable across the same time frame (Table 6.6). Rugby League No significant Game Result difference for the median frequency of carries into contact was identified in any Era, however, a significant (Z : - 3.41, P < 0.0005) difference was noted for median contacts per unit time in the pre-professional Era (Table 6.7), with winning teams taking the ball into contact fewer times (5.3 per min) than losing teams (5.9 per min) A similar non-significant difference was identified in the professional Era, winning teams making fewer contact carries (5.8 per min) than losing teams (6.5 per min). No significant Game Result difference was identified for the median frequency of carries in any Period. However, significant Game Result differences were identified for carries into contact per unit time in 1988- 92(Z: -2.72,P< 0.004); 1993-95 (Z: -2.08,P< 0.04) and 2000-02 (Z: -2.40, P <0.02) with winning teams in all Periods carrying the ball into contact fewer times per minute than losing teams (Figure 6.12). No significant Game Quarter Outcome difference for the median frequency of carries into contact or frequency per unit time was identified in either Era, or any of the four Periods. 231 !ß 8 c,) t ¡1. E6 + c gF4 t - - -<}'- GameWinner ==¡-Gâme Loser .Eå àE2 0 1988-92 1993-9s t997-99 2000-02 Period Figure 6.12 Median (inter-quartile range) carries into contact per minute for rugby league by Period by Game Result. * significant Game Result difference P < 0.04). Significant Game Result differences were identifìed for the median frequency of offloads (Z : - 2.08, P < 0.04) and the offload to contact ratio (Z: - 2.37, P < 0.02) in the professional Era, winning teams offloading less and having lower ratios than losing teams (Table 6.7). In the 2000-02 Period only were significant Game Result differences identiflred for median offload frequency (Z: - 2.26, P < 0.03) (Figure 6.13) and median offload to contact ratio (Z: - 2.40, P < 0.02) with winning teams having lower ratios than losing teams in all Periods except 1988-92 (Figure 6.14). In neither Era nor any Period were Game Quarter Outcome differences identified for either the frequency or the ratio, however, it is notable that in all Periods the offload frequencies were higher in teams winning Game Quarters than teams losing Game Quarters. It was also noted that ratios in all Periods were lower in teams winning Game Quarters than teams losing Game Quarters (Table ó.8). 25 r¡ 320 E I i Sts GameWinner å "'? " ----¡- Garne loser .E 10 Åes 0 1988-92 1993-95 1997-99 2000-02 Period Figure 6.13 Median (inter-quartile range) frequencies of offloads per game in rugby league by Period by Game Result. * significant Game Result difference P < 0.03). 232 20 >. 1g gt4Ët6 rt ù10îtz - - -.}'- GameWinner É8 I -----r- Gmre loser g4=ó Il À2 0 1988-92 t993-9s t997-99 2000-02 Period Figure 6.14 Median (inter-quartile range) offload to contact ratio per game in rugby league by Period by Game Result. * signifïcant Game Result difference P <0.02). 6.3.7 Passes Ragby Union In neither Era nor any of the four Periods were significant Game Result difference noted for the frequency of open play passes, the frequency per unit time, or the contact to pass ratio (Table 6.5). Moreover, in neither Era nor any Period were significant Game Quarter Outcome differences identified for any of the pass variables. Rugby League In neither Era nor any of the four Periods were signifïcant Game Rezult differences identified for the frequency of open play passes or the contact to pass ratio. In addition, in neither Era nor any Period were significant Game Quarter Outcome differences noted for either the frequency or ratio. 6.3.8 Turnovers Rugby Uníon In neither Era nor any Period were significant Game Result differences identified for turnover frequency, turnovers per unit time or the turnover to contact ratio, yet, in all Periods except 1993-95 it was noted that winning teams had fewer turnovers, and higher turnover to contact ratios than losing teams (Table 6.5). No 233 Game Quarter Outcome differences were identified for any of the turnover variables in either Era or any of the Periods, nor ìüere any trends across time noted for these data. Rugby League No significant Game Result differences were identified in either Era or any of the four Periods for turnovers, tumovers per unit time or the turnover to contact ratio, nor were significant Game Quarter Outcome differences noted for the frequency of tumovers in either Era or any Period. However, inthe 1997-99 Period significant Game Quarter Outcome turnover per unit time differences (Z: - 2.30, P < 0.02) (Table 6.8) and turnover to contact ralio (Z: - 1.95, P < 0.05) were identified. In this Period teams winning Game Quarters had 0.3 turnovers per min and compared to 0.5 per min for teams losing Game Quarters. Teams winning Game Quarters also had higher turnover to contact ratios (one turnover every 20.3 contacts) than teams losing Game Quarters (one turnover every 12.5 contacts) (Table 6.8). 6.3.9 Successful tackles Rugby Union No significant Game Result difference was identified for the frequency of successful tackles or the tackle frequency per unit time (opposition time in possession) in either Era. In additioq no significant Game Result difference was noted for the frequency of tackles in any Period. However, it is notable that winning teams completed more tackles than losing teams in all Periods @igure 6.15). Whilst no significant Game Rezult difference was identified for total tackles per unit time, a notable trend was identified, with winning teams making more tackles per unit time than losing teams in all four Periods (Figure 6.16). No significant Game Quarter Outcome differences in the median frequency of tackles or frequency of tackles per unit time were identiñed in any Period. 234 120 cJ 1 00 É (l) I 5 80 t-€) ---¡-- Gane'W-rnner c¡.¡ 60 ,I. -----r-Game Loser cll E 40 c) Àl. 20 0 1988-92 1993-95 1997-99 2000-02 Period Figure 6.15 Median (inter-quartile range) frequency of successful tackles per game in rugby union by Game Result by Period. t0 c) É 8 q) I (¿Ë5.= 6 --'?--GaneWirmer qi¡¡rH I t ----f-Game Loser gl¡Ég ¡li 4 Ë c) 2 Àli 0 1988-92 t993-95 1997-99 2000-02 Period Figure 6.16 Median (inter-quartile range) frequency of successful tackles per minute per game in rugby union by Game Result by Period. Raghy League In the pre-professional Era no Game Result difference was identified for the median frequency of tackles, however, a significant (Z: - 4.04, P < 0.0005) difference was noted when related to opposition possession time, with more tackles per unit time being completed by winning teams than losing teams (Table 6.7). In the professional Era a significant Game Result difference was also identified for total tackles (Z : - 2.14, P < 0.003) with winning teams making fewer tackles than losing teams (Table 6.7). However, when related to possession time, no significant Game Result difference was noted. In the pre-professional Era a significant (Z 235 : - 2.10, P < 0.04) total tackle frequency Game Quarter Outcome was identified, with teams winning Game Quarters making fewer tackles than teams losing Game Quarters (Table 6.8). In the professional Era no significant tackle frequency Game Quarter Outcome difference was identified. Nor was a significant tackle per unit time difference noted in either Era. In the 2000-02 Period only was a significant (Z: - 2.09, P < 0.04) Game Result difference identified, with teams winning games making fewer tackles than losing teams, yet, it is notable that in the previous Period a large difference in the total t¿ckle frequency was also identified, with winning teams (on average) making 125 tackles compared to 157 tackles made by losing teams (Figure 6.17). For the tackle frequency per unit time, no significant Game Result differences were noted in either of the professional Periods, however, significant differences were identified in both 1988-92 (Z: - 2.88, P < 0.04) and 1993-95 (Z: - 2.72, P < 0.004), with winning teams in both Periods making more tackles per unit time than losing teams @igure 6.18). No significant Game Quarter Outcome differences were noted for tackle frequency or tackles per unit time in any of the four Periods (Table 6.8). 2s0 >ì I 200 ¡f (¡) 6) 150 -'-Ì'- ù GmeWinner 1 Gane Loser ql 100 --r- 6) a= 50 0 1988-92 1993-9s 1997-99 2000-02 Period Figure 6.17 Median Qnter-quartile range) frequency of successful tackles in rugby league per game by Game Result by Period. * sþnificant Game Result differenceP < 0,04. 236 1 0 ¡1. C¿ *. É 8 €) 5.=AÅ 5il otr 6 " -?'- GrneWinner -¡r H El 9 -----tsGfrneLossr Cl¡ ¡li 4 lllo 2 À 0 1988-92 1993-95 1997-99 2000-02 Period Figure 6. 18 Median Qnter-quartile range) frequency of successful tackles per min in rugby league per game by Game Result by Period. * significant Game Result difference P < 0.04. 6.3.10 TacHe type Rugby Uníon In neither Era were signifrcant Game Result differences identified for single, double or mob tackle percentages, though, in the professional Era it is notable that whilst the single tackle percentages were similar for winning and losing teams, the distribution of the multiple tackles was differenq losing teams using more mob tackles and fewer double tackle than winning teams (Table 6.5). No Game Quarter Outcome difference was noted for any of the tackle variable percentages in either Era. However, similar to the Game Result trend, teams losing Game Quarters relied more heavily on the use of the mob tackle than teams winning Game Quarters (Table 6.6) in the professional Era. In the 2000-02 Period only was a significant Game Result difference identified for any of the tackle variable percentages, with the median single tackle percentage being significantly (Z: - 2.07, P < 0.04) less for winning teams than for losing teams (Figure 6.19). A significant (Z: - 2,33, P < 0.01) difference was also noted for the double tackle percentage, with the use of double tackles more evident in winning teams than losing teams (Figure 6.20).In addition, a significant (Z: - 2.37, P < 0.04) Game Quarter Outcome difference was identified for the percentage of mob tackles per game in the 2000-02 Period, with teams winning Game Quarters making more mob tackles than teams losing Game Quarters (Table 6.8) 237 1 00 (¡) ¡lr bo s80Ê (l) t --'.-" GaneWinner €)960 È -----r- Gane I¡ser 6É40 õ20 à!l 0 1988-92 1993-95 1997-99 2000-02 Period Figure 6.l9 Median (Inter-quartile range) percentage of single tackles per game in rugby union by Game Result by Period. * significant Game Result difference P < 0.04), ,f. 40 o èo cl I Ë30(¡) .L (J L ---<}-- GaneWinner 3. 20 ----+- Gane I¡ser Ë cl 810 ÅH 0 1988-92 1993-9s 1997-99 2000-02 Períod Figure 6.20 Median (Inter-quartile range) percentage of double tackles per game in rugby union by Game Result by Period. * significant Game Result difference P < 0.001). Rugby League Significant Game Result differences were identified for the percentage of single tackles in both the pre- professionalEra(Z:-1.99,P<0.05)andprofessionalEra(Z=-7.91,P<0.05).Inthepre-professionalEra the single tackle percentage was greater for winning teams than for losing teams, whereas in the professional Era the trend was reversed, with winning teams having a lower single tackle percentage than losing teams (Table 6.7). No significant Game Result difference was identified for any of the tackle percentage variables in any Period; however, non-significant differences were noted for single tackle and double tackle percentages in the 1993-95 Period; winning teams using the single tackle more and double tackle less than 238 losing teams (Table 6.7). No signifrcant Game Quarter Outcome difference was identified in any of the four Periods, nor were any notable trends in the data noted. 6.3.11 Tackle errors Rugby Uníon In neither Era nor any of the four Periods were significant Game Result differences identified for either the missed tackle frequency or the missed tackle percentage. Moreover, no significant Era or Period Game Quarter Outcome differences identified. Ragby League In rugby league in neither Era nor any of the four Periods was a Game Result difference identified for missed tackle frequency or missed tackle percentage. However, in all Periods winning teams \ilere found to make fewer tackle errors than losing teams (Table 6.7). In the pre-professional Era significant Game Quarter Outcome differences were identified for the frequenoy (Z: - 2.49, P < 0.01) and percentage of missed tackles (Z: - 2.1O, P < 0.04), with teams winning Game Quarters missing fewer tackles than teams losing Game Quarters (Table 6.8). In the professional Era no Game Quarter Outcome differences were identified, however, it is notable that frequencies and percentages were higher in teams losing Game Quarters than teams winning Game Quarters. In the 1988-92 Period a significant (Z: - 1.96,P < 0.05) Game Quarter Outcome difference was identified for the frequency of missed tackles, with teams winning Game Quarters missing fewer tackles per quarter than teams losing Game Quarters (Figure 6.21). No significant Game Quarter Outcome difference was noted for the percentage of tackles missed in any other Period; however, in all Periods both the frequencies and percentages were less for teams winning Game Quarters than teams losing Game Quarters (Table 6.8). 239 I 2 O I 0 t( (¡) 8 (l) - - -ù - - Gane Quarter Winner ù 6 É I ---¡- Gane Quarter loser ql 4 c) t Àll 2 I I 0 1988-92 1993-9s 1997-99 2000-02 Period Figure 6.21 Median (Inter-quartile range) frequencies of missed tackles per game in rugby league by Game * Quarter Outcome by Period. significant Game Quarter Outcome difference P < 0.05. 6.4 Discussion 6.4.1 Mean total possession time The results of the time analyses indicate that in rugby union possession time was not a performance indicator for success in either Era or any Period. These findings though are inconsistent with those reported by Jones, Mellalieu and James (2004), who argued that winning teams (in domestic rugby, 2001-02) had significantly less possession time than losing teams. However, the times they presented were very low (8 min 38 s for winning teams and 8 min 58 s for losing teams), representing a (median) game total of under 17 minutes of ball in play time. As such, these findings should be viewed with cautioq since the authors failed to discuss the signifìcant difference they identified, or explain why the ball in play times were so low compared to previous research . It must also be considered that the use of full game dat¿ alone to identify performance indicators can be misleading in that a team's performance may change according to the stage of the game. In the present study the assessment of time data by successful (winning) and unsuccessful (losing) Game Quarters was also adopted. The results of this analysis revealed (in the professional Periods) a positive relationship (significant in the 2000-02 Period) between successful Game Quarters and possession time, indicating possession time was a more important indicator of success in the professional Periods than in the pre-professional Periods. This is a reflection of two important changes in playing pattern across time; the 240 change in the contest for the ball, and a change from a territorial-dominated game strategy to a more possession-dominated game strategy. This is illustrated by the significant reduction in kicking away possession in professional rugby compared to pre-professional rugby. This was possibly due to changes in the lineout laws (support and lifting) which resulted in a change in the lineout pattern, with teams not contesting the ball in the air, but instead setting up a defence line in an attempt to combat the subsequent attacking play (refer to section 5.4.14). In addition, the reduction in maul frequency across time (refer to section 5.4-15) and the lack of ball won 'against the head' at the scrum in professional rugby indicates that there has been a reduction in the contest for possession across time. This view is supported by James et al. (2005) who reported maul and ruck successes on opposition ball being 0% and 3.9Yo, respectively. As such, possession turnover is more likely to be related to errors in contact. It is therefore probable that the increased possession time in the professional Periods was a reflection of better contact skills and ball retention by successful teams than unsuccessful teams, a fact outlined by Jones, Mellalieu and James (2005), who reported winning teams secured more turnover ball than losing teams. In rugby league, possession time appears to be a more notable performance indicator than in rugby union. In all Periods possession time was found to be greater for winning teams than losing teams, and for teams winning Game Quarters than losing Game Quarters, albeit non-significantly. This indicates that successful teams either maintain set possession for longer (complete more phases and have less turnovers) or maintain continuþ of play (offload more) andl/or are able to maintain longer continuous possession time by forcing opposition errors. The results of offence performance indicator analysis (Table 6.7) are inconclusive regarding the frequency of turnovers and offloads; however, both set possession time and continuous possession time were found to be higher in successful teams than unsuccessful teams in all post-1988-92 Periods. 6.4.2 Mean set possession time In rugby union, mean set possession time was found to be similar in all Periods irrespective of Game Result (win or lose). However, a significant difference in Game Quarter Outcome was identified in 2000-02, with teams winning Game Quarters maintaining set possession for longer than teams losing Game Quarters (Figure 6.2). This highlights the importance of possession maintenance in the professional game and indicates that continuity of phases is fundamental to successful performance. In addition, since according to Sayers and rüashington-King (2005) the maintenance of forward momentum, avoidance of contact and angle 241 of run were all indictors of successful ball canies, it is possible that the running pattern of players (particularly contact avoidance) was a factor in maintaining possession, which may be reflected in the different possession times for successful and unsuccessful teams. However, it must be noted that these authors failed to present any evidence regarding the reliability oftheir data (refer to section 2.5) and as such their results must be viewed with some caution. In rugby league, winning teams were found to have higher (non-significant) set possession times than losing teams in all post-1988-92 Periods (Figure ó.3). The difference in times cannot be fully explained by offence actions (oflloads, open play passes etc.) since the results of the offence performance indicator analysis did not reveal notable or signifïcant differences between winning and losing teams (Table 6.7). Similarly, the frequency of missed tackles cannot explain this difference, although the analysis of defence performance indicators revealed notable differences in the frequency of tackles per unit time. In all Periods, that winning teams made more tackles per minute is indicative of a more 'attacking' style defence. Foulkes (2002, p.18) highlighted the importance of defending "aggressively and pro-actively". Murray Q002, p.l}) likewise indicated that aggressive defence is vital in making teams "earn every inch of the ground". This is achieved, according to Sharp (2002), by increasing the pace ofthe defence line and being more aggressive in the tackle. Attacking defence is, however, heavily reliant on slowing the 'play the ball', thus enabling the defence to retreat, re-organise and attack the offence line. From quicker 'play the ball' the defence has less time and therefore cannot re-engage as quickly with the opposition. As Anderson Q002a, p.2l) outlined, the aim in offence is to get the defence standing still. In contrast, in attack he advocated "going at them (defence) before they come at you". This more 'attacking' style of defence may go some way to explain greater possession time of successful than unsuccessful teams, with organised defences closing down space and therefore forcing the offence into shorter individual phases ofplay. 6.4.3 Mean continuous possession time In rugby union, continuous possession was not identified as a performance indicator (based on Game Result) in either Era or any Period. However, in the 2000-02 Period a significant Game Quarter Outcome difference \Mas noted, with successful teams having significantly greater continuous possession than unsuccessful teams @igure 6.4). This indicates that in the 'modern' game, having a series of possessions is more likely to result in a successful performance outcome. That is to say, that at the end of a set possession (indicated by a stoppage in play) teams are more likely to be successful if they commence the next phase of play in possession, either by turnover at the set piece or by being more dominant at the breakdown, thus securing any 242 subsequent scrum feed. This more dominant approach (forward momentum) has been shown to be an indicator of successful ball ca¡ries (Sayer & Washington-King, 2005), and since the team going forward (advancing over the gain line) when a ball becomes unplayable receives the put in at the scrurr\ these patterns in running identified by these researchers warrant further research. It must, however, be noted that the difference in continuous possession time may also be a reflection of higher penalty counts by unsuccessful tean¡ although this is contrary to the view of James et al. (2005), who reported winning teams had a higher penalty conceded percentage than losing teams, albeit this difference being non-significant. In rugby league, winning teams were found to have higher continuous possession times than unsuccessful teams in all Periods except 1997-99, with the difference in Game Result being revealed as significant in the 1988-92 Period (Figure 6.5). This can be partly explained by winning teams also having higher set possession times, although the difference between winning teams and losing teams for continuous possession was greater than the difference for set possession. As such, it appears that winning teams had better continuity of possession than losing teams. Similar to rugby union, this may be a reflection of the difference in penaþ counts, or more specific to rugby league (in the professional Era) the use of the 40-20 kick. In additio4 the use of the attacking 'bomb' or forcing the goal line drop out are both tactics employed by teams at the end of a set. Anderson Q0O2b\ suggested that at the end of a set an offence kick rather than defence kick should be the aim. Unfortunately, these aspects of the game were not assessed in the present study; however, it is recommended that future research examines these end of set actions in relation to successful and unsuccessful performance. 6.4.4Mean ruck time and percentage 'fast' and 'slow' ball In rugby unio4 whilst no significant Game Result or Game Quarter Outcome difference was identified in either Era or any of the four Periods, it is notable that winning teams and teams winning Game Quarters had lower mean ruck times than losing teams and teams losing Game Quarters (Tables 6.1 &,6.2). However, this result does not establish whether successful teams are proficient at securing 'quick' ball, or slowing opposition ruck ball, or both. Whichever the situation though, the control and speed of ruck ball, similar to the 'play the ball' in rugby league, is a fundamental aspect of the game, and seemingly more important in the professional Periods. In the professional game, it is a constant battle between defence players attempting to slow the ruck and offence players trying to secure 'quick' ball. The importance of this has been highlighted by Ireland Coach Eddie O'Sullivan (as cited in Schwarz, 2004) who suggested that if a ruck is slow it has no value. In the 243 offence situation fast ruck ball has a number of advantages to the attacking side. In the contemporary game the laws state that the defending players must enter the contact situation 'through the gate', that is to say through an imaginary opening behind the ruck or maul. Hence, from quick ruck ball a player from the dummy half position or playing first receiver can more easily break the gain line. This means the defending players have further to travel to re-engage the opposition, not being able to enter from the side of the ruck or maul. In addition, a series of quick ruck ball can result in a defence line having to retreat. This gives the attacking team (particularly the backs) space to attack, and importantly against a defence which is constantly reforming, and therefore, potentially less organised than if the ball from the ruck is slow. From a defence standpoint, slowing the ruck ball is imperative as this gives defences time to re-organise. O'Connell (2004, p.4) suggested that 'poachers' (players slowing the ruck ball) are the biggest problem with the modern game. He added that the running game is dependent on the quick recycle of the ball, and hence the challenge for offences at the ruck is to reduce the effectiveness of the 'poacher'. Many offence strategies to promote 'quick' ball at the ruck have been developed, for example, the 'squeeze ball' (where the tackled player lies over the ball with his head facing the opposition- a strategy now outlawed), and the 'two man drop' (where two offence players intentionally drop to ground in the tackle). Both ofthese benefit the attacking side by increasing the distance between the ball and the 'poacher'. Australian George Smith (a renowned 'poacher') (as cited in O'Connell, 2004, p.5) remarked that whilst poaching over one player is easy, it is more difficult over two. O'Connell (2004, p.5) even suggested that the poacher reaching over two bodies actually "leaves himself open to legitimate and fair damage, particularly around the rib area". The same battle for control at the ruck or 'play the ball' is equally, if not more evident in rugby league. The winning of the ruck or winning 'on the ground' is seen as being perhaps the most important part of the game. Smith (2002, p.5) suggested that whilst the 'play the ball' may only take a few seconds "winning this part of the game can make a difference in the end result". This is not wholly supported by the findings of the present study, since no significant differences were identifted between winning and losing teams in the professional Periods (Tables 6.3 &, 6.4). Hov,iever, similar to in rugby union there is a constant battle for quick ball in offence and slowing the ball in defence. Sharp (2002) highlighted the importance of controlling the ruck area, stating that defending against the flat line offence is all about controlling the speed ofthe'play the ball', which is achieved by being dominant in the tackle (forcing the ball carrier backwards). Fanar (2002, p.4) summed up the situatior¡ stating that his team (St. George Illawana) now have better training drills and techniques to "make players play the ball quicker when you have got the ball or force the opposition to play the ball slowly when you haven't got the ball". 244 The results of the present study revealed a significant Game Result difference for 'play the ball' time in 1988-92, and a notable difference in the pre-professional Era only, in both cases winning teams having slower 'play the balls' than losing teams. However, this is more likely to be due to a team's individual style of play as in all games in the pre-professional Era the winning team was the same team (ltrigan). The results of the Game Quarter Outcome analysis revealed that in all Periods, teams winning Game Quarters also had slower (non-significant) 'play the balls' than teams losing Game Quarters, although the time difference was less than when the data were assessed by Game Result. Whilst a similar trend was observed for the percentage of 'slow' and 'fast' ball, it is evident that there was a large increase in 'fast' ball and decrease in 'slow' ball between 1988-92 and 1993-95, indicated by data assessed by both Game Result and Game Quarter Outc.ome. This is illustrative of the impact of the 10-m rule change in 1992-93. According to Farrar Q002) there is now more impofiance placed on 'play the ball' due to rule changes in the game. Smith (2002) concurred, adding that it is the 10-m rule that has been most influential on the 'play the ball'. In the professional Era the differences between successful and unsuccessful teams (measured by Game Result and Game Quarter Outcome) for the percentage 'fast' and 'slow' ball was reduced markedly, with teams winning games having higher 'fast' ball percentages in 2000-02 and teams winning Game Quarters with higher percentages in 1997-99 (Tables 63 e. 6.4). This indicates the importance of the 'play the ball' in the professional Era. Hence, whilst the results of this study are inconclusive in identifuing the 'play the ball' time as a performance indicator, this is easily explained. The study was designed to assess mean ruck times (by Game Result and Game Quarter Outcome), however, incorrectly it was assumed that teams would seek to 'play the ball' quickly in all attacks. This was not the case. Smith (2002) suggested that teams sometimes intentionally 'play the ball' slowly, particularly in their own 'zone'. In addition, he indicated that in attempting quicker 'play the ball' there is an increased risk oferrors and turnover ball, concluding that often ordinary speed 'play the ball' is suffrcient, and perhaps the need for fast ball is over-emphasised. A further issue with the present study is that the 'play the ball' time was recorded as the time from tackle completion to the ball being back in play. This does not account for the time between contact and tackle completion. This is important as teams are reforming defence during this 'contact' time. It is evident from the initial results of the time performance indicator analysis that further research is warranted. Particular emphasis should be placed on assessment of the mean contact time (contact to tackle) and ruck time, and their relationship to perturbations and post-ruck action for successful and unsuccessful teams. In addition, the analysis of full game and successful Game Quarter data is advocated, taking account not only of field position, but also the ongoing game statuVscore. 24s 6.4.5 Ball carries In rugby union the analysis of the fuIl game data indicated that there were no significant differences between winning and losing teams (Game Results) in any Era or Period for either the frequency or frequency per unit time of carries into contact or offloads. However, the analysis of successful and unsuccessful game quarters (Game Quarter Outcome) indicated that in all Periods teams winning Game Quarters made fewer carries into contact per unit time than teams losing Game Quarters (Table 6.6). In addition, it was noted that across the Periods in teams winning Game Quarters the offload to contact ratio increased, whilst in teams losing Game Quarters the ratios remained relatively stable, an indication that successful teams were more adept at avoiding contact, but when taking contact were less likely to play the higher risk strategy of offloading. This particular style of play became more apparent in the professional Periods, with teams seeking possession maintenance rather than risking losing possession. In contrast, unsuccessful teams were more likely to carry the ball into contact and attempted to play a higher risk style of rugby. This style of play (use of the offload), whilst seemingly unsuccessful in Northern hemisphere rugby has been reported by Jones, Mellalieu, James and Moise Q004> as resulting in consistently larger breaches of the gain line in Southern hemisphere rugby, and was particularly successful when forwards rather than the backs used the offload. As such, it appears that teams in the Northern hemisphere need to explore more fully the use of the offload in the contact situation as a principle offence strategy. In rugby league the main difference between winners and losers, and teams winning and losing Game Quarters was also identifïed as the use of the offload. In both Eras and all Periods winning teams and teams winning Game Quarters had higher oflload frequencies and lower offload to contact ratios than their less successful counterparts, with the exception of the 1988-92 Period (Table 6.7 & 6.8). The Game Result difference was found to be significant in the 2000-02 Period (Figure 6.13) and reflected the increased use of the offload to initiate second-phase play. According to Hagan (2002a, p. 12) this is the most diffrcult thing to defend against, and further suggested that "when you're tired the first thing that suffers is that you don't wrap up the football". Similar to a quick 'play the ball' the successful offload enables offences to attack less organised or disrupted defences. Moreover, Smith (2002) suggested that if players adopt a more traditional grip on the ball, this facilitates the use of playing the ball one handed, which aids the offload. Hence, whilst the offload is a relatively high risk strategy, it was found to be a notable performance indicator in professional rugby football, ostensibly due to the diffrculties associated with defending against this type of offence action. 246 ó.4.6 Passes No Game Result or Game Quarter Outcome differences were identified in either rugby union or rugby league for any of the pass variables. Since no defìnite conclusions can be made regarding the relationship between passing and successful performance, it is suggested that future research in rugby union should focus on identifring the area of attack related to oflence perturbations in relation to freld position and game statuVscore. 6.4.7 Turnovers In all Periods in rugby union winning teams had fewer tumovers than losing teams, and smaller tumover to contact ratios (Table 6.5), which indicate that wining teams were more skilful in retaining possession in the contact situation. This is consistent with the findings of Jones, Mellalieu and James (2004), who reported that in domestic rugby (2002-03) winning teams had a higher percentage of turnover ball and made fewer errors than losing teams, although these researchers only present frequencies (non-normalised) for the total error count. As such, it is not clear whether these differences were due to differences in playing performance or merely reflecting differences in possession frequency or time. A similar trend for turnover to contact ratios was identified in the professional Period in rugby league. In additioq in these Periods winning teams had fewer turnovers per minute than losing teams. According to Bayliss Q002\ the rate of tumovers is strongly related to strong aggressive tackling and applied pressure, Moreover, Smith (2002) inferred that errors (and turnovers) can result when teams attempt to 'play the ball' too quickly. Interestingly, the results of the time performance indicator analysis in this study appear to support this, in that in all Periods except 2000-02,losing teams had a higher percentage of 'fast' ball. Smith (2002) also suggested that not enough time is spent on young players developing handling skills, and this probably contributes to handling errors when using the 'spiral' or 'torpedo' pass which requires a different type of grip, and is often overused. He added that because these passes require a'wind-up', if one hand is removed or taken away, the ball will be dropped. In contrast, with the more traditional type of pass, the ball is easily carried in one hand, hence, handling errors and turnovers are less likely. However, since the focus of this study was the examination ofcontact turnovers and not open playing handling errors, it appears than the differences between winning and losing teams was probably a reflection of more effective tackling - targeting the ball - by winning teams and/or a greater frequency of errors related to the offload in losing teams. In addition, the flatter style of attack - which has become more prevalent in the professional game - 247 forces players to play closer to the opposition. Sharp (2002) suggested that this style ofplay is effective, but fraught with risk, With less time to make decisions, the likelihood of errors being forced prior to or in contact are increased. 6.4.8 Successful tackles In rugby union the use of assessing full game data to identify defence performance indicators appears limited, in that no significant Game Result differences were identified for total tackle frequencies in any Era or Period. The result of the Game Quarter analysis revealed teams winning Game Quarters made signifïcantly fewer tackles than teams losing Game Quarters in 2000-02. However, this effect was found to be due to, or corresponding to successful teams having a greater share of possession, indicated by the non-significant Game Quarter Outcome difference for tackle frequency per unit time. Whilst the in-depth analyses of total tackle frequencies in rugby union were found not to be a significant performance indicator, the same was not true in rugby league. In rugby league it has been a common theme amongst elite coaches to discuss the merits of winning the ruck @ayliss,2002), or winning on the ground (Anderson 2002a, Smith, 2002). These refer to the same aspect of play; dominating the ruck or the 'play the ball'. According to Bayliss (2002, p.l}) the aim of the defence is to 'limit the time and space, and therefore the options of the attacking team'. The use of an 'attacking' defence line which is well organised is fundamental to this strategy. Hence, good defence consist of two vital components, moving quickly into the tackle (reducing activity time) and slowing the 'play the ball' (increasing ruck time). The results of the present study have highlighted that winning teams in the pre- professional Era made more tackles per unit time (6.8 per min) than losing teams (5.9 per min) indicating successful teams used a more attacking defence line, and tackled closer to the opposition advantage line. In- depth analyses of the defence strategy showed that winning teams in this Era did not slow the opposition 'play the ball' more than losing teams (winning teams mean ruck time : 4.4 s, losing teams 3.9 s), but did reduce the opposition's mean activity time (winning teams : 5.9 s, losing teams 5.5 s) (Table 6.3). As a consequence, it is apparent that winning teams made more tackles and more tackles per unit time than losing teams in this Era by utilising a more attacking defence line, rather than focussing on slowing the 'play the ball'. In the professional Era the differences between winning and losing teams and teams winning and losing Game Quarters were found to be negligible. The introduction of more fully professional teams seemingly reduced the difference between success and failure. Further analyses showed that in the professional Periods 248 the margins between success and failure had narrowed when compared to the pre-professional Periods. The change in the offside rule in 1992-93 yielded a grcater importance being placed on 'winning the ground game'. In the professional Periods the development of 'slide', 'drift' and 'umbrella' defence systems meant defences were more organised, and according to Farrar (2002>, were assisted by the lO-m rule. He suggested that contrary to the rule being advantageous to offences, the extra distance allowed defences more time to re- organised before engagement, unlike when the 5-m rule was in place. These defences, however, are only effective if defending players can firstly slow the 'play the ball'. The various strategies of doing this have been discussed previously (refer to section 5.4.2), and reflect the battle for control of the ruch which appears to now favour the defence, since whilst the 'play the ball' rules discourages holding down the tackler, it is a subjective call by the referee and hence, prone to error and dispute. The consequence of this is that the difference between winning and losing teams is less apparent in the professional Periods than the pre- professional Periods. The most notable difference between winning and losing teams can be seen in the 1988-92 Period, winning teams making more tackles per minute (6.8) than losing teams (5.8). The analysis of time variables (Table 6.3) showed that mean ruck times were greater for winning teams, indicating that the slowing of the ruck was either less effective for the losing teams, or not considered an important aspect of the defence. The latter is likely to be the case, as the 5-m offside rule in this Period meant a quick 'play the ball' was less of an advantage, defending teams only having to retreat five metres. As Smith Q002) indicated, whilst the quick 'play the ball' can catch the defence offguard, it can also be a disadvantage in that in rushing to play the ball effors are more likely to be made. He posed the question, "Would you rather retain possession with ordinary 'play the ball' or give up possession and have fast 'play the ball'?" In terms of using the 'attacking' defence, losing teams were shown to have less mean activity time; however, this difference was (on average) only 0.25 s. One possible explanation for this is that in an attempt to negate the attacking offence line, losing teams adopted a deeper attacking line, giving them more time to make decisions in offence. Whilst this may be an option, it would have been at the loss of tenitory. Alternatively, it may be to do with the strategy in the collision and the winning teams playing and coaching personnel. According to Collins (2000) between 1984 and 1995, a total of 747 þrusiralians played in First Grade English rugby league, with many more New Zealanders following suit. Many coaches \¡iere also imported from the Southern hemisphere, their arrival being a direct result of the recognition of Australia's dominance after the 1984 test series. The Australian game, according to Clarke (as cited in O'Hare, 1995) was successful due to the strategy of running from greater depth, sprinting for (on average) 2.77 s pnor to the collisior¡ compared to the British 249 players sprinting for (on average) 1.69 s before collision. This meant the Australian players were more difficult to stop, moving nearly half a metre further in the collision and remaining on their feet for 0.63 s longer than the British players. It is possible that these strategies were subsequently implemented by Australian and New Zealand coaches and players in the English domestic game. Unfortunately, the small difference in activity time reported in this study between winning and losing teams did not account for the total collision time. It is therefore diffìcult to ascertain the true difference in the defence strategy of successful and unsuccessful teams. In order to identify whether these defence and time variables are performance indicators for success, it is suggested that the time of the collision is more carefully assessed in future research. 6.4.9 Tackle type In rugby union in the pre-professional Era, no Game Rezult or Game Quarter Outcome differences were identified for either the percentage single, double or mob tackles. However, in the professional Era and most notably the 2000-02 Period, winning teams were found to make more double and less single tackles than losing teams. In addition, it was identified that teams winning Game Quarters made fewer mob tackles. This indicates that similar to rugby league the double tackle is a more effective defence strategy, as this prevents the offload in the contact situation, hence, providing more time to re-organise the line of defence. According to Fullerton (2002) the use of the single tackle aimed around the legs is no longer an appropriate type of tackle in rugby league. The same appears to be true in rugby union. It is no coincidence that since the introduction of professional rugby union, and the use of rugby league defence coaches, the tackle type preference in rugby union has changed towards a greater use of the double tackle. The fact that unsuccessful teams have lower double tackle percentages signifïes that they rely more heavily on single and mob tackles, which can have negative consequences for the defence. Firstly, the single tackle which is aimed low on the body of the ball carrier is ineffective in preventing the offload and may result in the subsequent phase play being against a less organised defence. Secondly, whilst the use of the mob tackle is effective in 'locking up' the ball, the use of three or more players at the point of contact means these players are likely to be tied into the resulting ruck or maul. Consequently, if the offence can secure 'quick' ruck ball there is an increased likelihood ofan overload ofoffence players in the subsequent open play action. Hence, the use ofthe double tackle is the most appropriate tackle type in reducing the opporhrnities for the opposition to secure disruptive second phase possession and open play player overloads. 250 In rugby league in the pre-professional Era winning teams used the single tackle significantly more often (522%) than losing teams (45.8%). This difference in the tackle type was most notable in the 1993-95 Period, with winning teams using single tackles 53.5Yo of the time compared to 44.8Yo for losing teams, hence, losing teams v/ere seemingly forced into making more double and mob tackles. This can be explained in relation to the findings of Clarke reported by O'Hare (1995), who suggested that the Australian side were successful against Great Britain in the 1992 Ashes series because they began running from further back, and built up more speed prior to the contact. This meant it took the British defenders longer to stop them, allowing the Australians (on average) an additional half metre per collision. In addition, the Australian players remained on their feet for longer drawing in extra defending players, before falling to the ground, quickly playing the ball and exploiting the space created in the British defence. In the seasons after this tour (1993-95) it appears that successful (winning) teams may have adopted this approacl¡ forcing the opposition into making more multiple player tackles, and attempting a quicker 'play the ball'. This increase in ruck speed has been established in the present study, reflecting that this particular strategy was evident in both winning and losing teams. In addition, the rule change in 1992-93 (10-m offside) increased the space between the teams at the 'play the ball', meaning a quick 'play the ball' was more advantageous to the offence compared to when playing under the 5-m rule. The increased opportunity to run from the dummy half position to gain territorial advantage forced the 'play the ball' marker and second marker into more double tackles, hence, teams that were playing the ball quickly, and forcing multiple player tackles were more successful. It must also be noted that in the previous Period the second marker (who must be behind the marker) was actually a dummy half, who was there to secure the ball should it be raked by the marker (Fagan, 2005). The change in the rule preventing the marker attempting to kick at the ball at the 'play the ball' effectively made the defending dummy half redundant. As a consequence, the primary job of the second marker in the professional Periods ì/vas as a defender, often being first into the tackle and defending against the dummy run. In the professional Era winning teams made fewer single tackles (41.6%) than losing teams (45.9þ reflecting the change in defence strategy in professional rugby reported previously, The slowing of the'play the ball' (by having more players in the tackle, thus enabling the re-formation of the defence line) became more prevalent over time. In the 2000-02 Period it is notable that more than 60Yo of all tackles made by winning teams were multiple player tackles. Acoording to Anderson (2002a) the combination (double tackle) is now the most important type of tackle in rugby league. With regard to the defending at the ruck Fagan (2005) suggested that rule changes should be made so that markers do not have to stand 'square' to the 'play the ball'. This would mean a defence line could be formed 2sl closer to the ruck, and hence there would be no need to slow the 'play the ball'. He further argued that this would force offences to move the ball wider, which would result in the reduction in the frequency of 'hit ups'. The change in tackling type across the Periods not only reflects imitation of the more successful Australian side and the change due to law changes, but also reflects a change in relation to offence tactics. The increase in multiple tackles across the Periods mirrors closely the change in offload frequency established in the present study. In the pre-professional Periods winning teams used fewer oflloads than losing teams (Table 6.7). In the professional Periods this trend was reversed. It is probable that the double and mob tackle increased in these Periods in an attempt to reduce the offload frequency and subsequent second phase play against a disrupted defence. 6.4.10 Tackle errors In rugby union in the professional Era no significant or notable Game Result differences were identified for either missed tackle frequency or frequency per unit time. However, there were notable Game Quarter Outcome differences for the frequency and percentage missed tackles, with winning teams making fewer than losing teams in both Periods, with the percentage of missed tackle by winning teams in 2000-02 greater than for losing teams. In contrast, Jones, Mellalieu and James (2005) reported unsuccessful tackles for winning teams being lower (10.7%) than for losing teams (11.7%); however, these differences, similar to those found in the present study, are very small and as such cannot be considered signifìcant performance indicators. In this Code of rugby, it appears that tackle eûors are equally evident in both winning and losing teams and teams winning and losing Game Quarters. In contrast in rugby league, tackle errors were fewer (albeit not significant) for wining teams than losing teams in all four Periods. The frequencies of these tackle errors for both winning and losing teams were relatively stable across time, with the exception of the signiftcant Game Quarter Outcome identified in the 1993-95 Period. This anomaly was possibly due to the introduction of the lO-m offside rule in 1992-93. Masters (1994) suggested that this rule favoured more talented players and those who did not have a full-time job outside of rugby, and therefore effectively widened the gap between full-time professional clubs and those not fully professional. However, the findings of the present study identified that the introduction of this rule in the Northern hemisphere had a similar impact on both winning and losing teams, evidenced by the stability of the winning to losing miss tackle frequency ratios across these Periods (1: 1.28 in 1988-92, 1: l.2l in 1993-95). Similar ratios were also observed when the frequencies were expressed as percentages of 2s2 missed tackles (l: 1.35 in 1988-92, l: l.2l in 1993-95). Further analyses of these data by Game Quarter, however, indicated that the view of Masters (1994) may be corect. In the 1988-92 Period, the frequency of missed tackles across the Quarters ranged from 4,0-5.3 for winning teams and 4.2-6.5 for losing teams. In the subsequent Period winning teams made between 4.5 - 7.3 tackle errors per Quarter compared to 6.7 - 10.2 for losing teams. It appears that the 10-m offside rule change had a marked effect on both winning and losing teams, but was more beneficial to full-time professional teams, who were better conditioned to play the full 80 minutes. Losing sides, with more part-time players were possibly less able to compete effectively in the later stages of the game. In the Period (1997-99) immediately after the introduction of summer rugby (and ostensibly full time professional players) the frequency and percentage ratios for tackle errors decreased to l: 1.06 and l: 0.96 respectively, indicating that the change in the playing season had reduced the difference between winning and losing teams. It could be suggested that the move to full-time playing status for all Super League teams marked a change in player fitness, resulting in a reduction in missed tackles. The change to full-time professional playing status meant coaches could devote more time to the tactical and technical aspects of play, and player conditioning. In addition, an examination of rule changes at the scrum in rugby union (Williams, 2004) indicated that law changes may have had an immediate impact, but three years after the amendment this impact appeared to level out. Hence, the effects of the change in the 10-m offside rule in 1992-93 may have 'levelled out' by 1996. In the 2000-02 Period the frequency of missed tackles for losing teams (18.5) and winning teams (12.7) was much lower than reported by O'Connor (2003), who assessed performance indicators in professional Australian National Rugby League (NRL). Her analysis focussed on the differences between teams reaching the final series and those who failed to qualify. O'Connor (2003) reported that missed tackle frequencies were significantly different between these groups of teams (qualifiers :27.3, non-qualifiers:30.5). However, these were deemed to be non-significant in a later publication (O'Connor, 2004). A further problem with the results reported by O'Connor (2003,2004) is that the data were not normalised, hence no account is made of the influence of possession andlor possession time on these data. In the present study, the normalised data (percentage) revealed non-significant differences between winning and losing teams in this Period (winners :8.S%o,losers 10.4% tackle errors). The differences between winning and losing teams were apparent in all Periods; however, it must be noted that these findings may have been influenced by the playing patterns of the individual teams. In the pre- professional Era, all the games analysed in the present study involved Wigan, hencg due to their dominance in the late 1980s and early 1990s, the results may be skewed. In an attempt to overcome this problem, a further analysis of the data was undertaken, assessing the performance indicators by success in individual 2s3 game quarters (Game Quarter Outcome). Interestingly, the win to lose game ratios for the percentage and frequency of missed tackles v'/ere very simila¡ to the winning/losing Game Quarter ratios in the Periods in the pre-professional Era, however, were notably different in Periods in the Professional Era. The most notable of these differences was in the 1997-99 Period, with the winning/losing game ratios (frequency l: 1.06, percentage 1: 0.96) being much less than Game Quarter Outcome ratios (frequency l: 1.53, percentage l: 1.43) indicating that using full game data may mask differences either due to a team's playing pattern or the effect of periods of poor play (in winning teams) and good play in (losing teams). The importance of using successful Game Quarters rather than full game data is that it provides a truer reflection of how teams are successful, rather than how a team's play fluctuates during the full game, thus enabling coaches to identi$r true performance indicators for success. 6.5 Summary The objective of this study was to assess changes and factors influencing change in key performance indicators (by game result and successful game quarters) in rugby union and rugby league in four periods spanning 1988 and 2002 to establish whether the two codes of rugby football were becoming more similar with regard to factors associated with successful performance. Whilst it is apparent that in both rugby union and rugby league factors such as rule/law changes, changes in playing status and changes in playing season may have resulted in changes in playing patterns and, hence, performance indicators, it is notable that Game Result or Game Quarter Outcome differences were not significant for any performance indicator in both codes of rugby in the same Period (Table 6.9). 2s4 Table 6.9 Summary of performance indicators þy Game Result (GR) and Game Quarter Outcome (GQO) by Code by Period 1988-92 1993-95 1997-99 2000-o2 Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Union League Union League Union League Union I*ague Mean total x x x x x x GR x possession time Mean set x x x GR x x GQO x possession time Mean continuous x GR x x x x GQO x possession time Mean ruck time x x x x x x x x Percentage 'fast' x GR x x x x X x ball Percentage 'slow' x GR x x x x x x ball GQO Median ball x x x x x x x x carries into contact Medianball x GR x GR x x x GR carries into contact per unit time Median offloads x x x x x x X GR Median offloads x x x x x x x x per unit time Median offload to x x x x x x x GR contact ratio Median open play x x x x x x x x passes Open play passes x x x x x x x x per unit time Pass to contact x x x x x x x x ratio Median turnover x x x x x x x x frequency 255 1988-92 1993-95 1997-99 2000-02 Rugby Rugby Rugby Rugby Rugby Rugby Rugby Rugby Union League Union League Union League Union League Median tumovers x x x x x GQO x x per unit time Median turnover x x x x x GQO x x to contact ratio Median total x x x x x x x x tackle frequency Median total x GR x GR x x x x tackles per unit time Median miss x GQO x xxxx x tackle frequency Percentage of x x x xxxx x missed tackles Percentage of x x x XXXGR x single tackles Percentage of xxxxxxGR x double tackles Percentage of mob xxxxxxx x tackles tilhilst it has been established that the codes of rugby are becoming more alike with regard to common time, offence, defence and game action va¡iables (Chapter 5), the same is not true of the time, offence and defence performance indicators examined in the current study. Hence, it may be suggested that rugby union and rugby league are becoming similar games with regard to the content of the games, but not in terms of what constitutes suocessful team performance. 256 CHAPTER 7 ST]MII{ARY AI\D CONCLUSIONS 7.1 'The convergence of the I\waint 258 7.1.t Reliability 2s8 7.1.2 Time 259 7.1.3 Offence 261 7,1.4 Defence 262 7.r.5 G¡me Actions 264 7.2 F¡ctors influencing convergence 265 7.3 Perfomance analysis recearch - the wider context 270 7.4 General conclusions 273 7.5 Future research and recommendation¡ 274 2s7 7.1 óThe convergence of the Twain' 7.1.1 Reliability The reliability analysis undertaken in this study represents the most thorough investigation ever undertaken in research in notational analysis of rugby football. It dealt not only with frequencies, but also the problems of variable and player identification and the errors associated with inputting data. In addition, each variable was examined individually so that the problems in the systems could be more easily identified. Moreover, the use of scatter plots was found to be extremely useful in identifying such errors and data outliers. Unlike much previous research, this study used a sequential data gathering system and as such all the reliability assessments were based on raw sequential data rather than processed data. The more usual approach adopted in previous studies (addressing the reliability of the whole system and using processed data) can result in the true level of agreement between observations being hidderL yielding elevated agreement levels, that subsequently undermine the validity of their findings. The reliability analyses presented in this study indicate that the hand notation systems used were valid. Howeveq even using slow motion, frame-by-frame analysis, forward and back tracking, and secondary player identification characteristics, it must be noted that intra-observer error levels for certain variables was still high e 5%) In particular, identifying players in congested areas of play, distinguishing between types of tackle, and recording the frequencies ofplayers in the ruck and maul situation ìilere prone to poor percentage agreement. In addition, having recognised that inputting errors had occurred (and are always likely) this was resolved by adopting a double-entry system that highlighted the errors surprisingly quickly. None ofthese issues have not been reported in previous studies and therefore cast further doubt on the validity of their findings. It is accepted that the systems utilised in this study are not perfect; however, they have been most rigorously tested, much more than in previous investigations. It is therefore suggested that the analyses presented in this study are a truer representation of rugby union and rugby league football than has previously been achieved. The systems though could be improved, Whilst using computer notational analysis may not improve the reliability of the system, advances in technology may. The use of a transmitter position measurement system (Holzer et al., 2003) which tracks players to within 3 cm may alleviate the problems in both identifying players and in tracking players' arrival at the breakdown. However, the expense of such technology does preclude its use by many analysts, whereas using hand notation is relatively inexpensive, if 2s8 extremely time consuming. The hand notation systems developed for this study are easy to use and importantly, produce valid results. It is therefore recommended that further analysis be undertaken to assess the inter-observer level of agreement of these systems, and identify whether they could be used in the wider context by analysts in both rugby union, rugby league and other teams sports. 7.1.2 Time Whilst ball in play times and percentages remain higher in rugby league than rugby union in all Periods, it is notable that the times in rugby league fell over the four Periods, whereas they increased in rugby union. For mean ruck times, the profìles were found to be converging between the 1988-92 and 1993-95 Periods, after which little change was noted in either Code, with times being remarkably similar in the professional Era and Periods. For mean time in activity the decreases over the four Periods in rugby union and the relative stability in rugby league resulted in a convergence of these profiles, In fact the activity time in rugby union was higher than in rugby league in the 2000-02 Period, a change from the previous three Periods. One of the most notable changes in the time analysis was the large increase in set possession time in rugby union over the four Periods. Most significant was the large increase between 1993-95 and 1997-99, which was much greater than the increases in the previous or subsequent Periods, suggesting that changes to the game between these Periods had a major impact on this time element. In addition, the same trend in the data was noted for continuous possession time and continuous ball in play time. In rugby league a slight downward trend was evident for both set possession time and continuous ball in play time over the same Periods. However, for continuous possession time the general upward trend in the data profile was intemrpted by a marked downturn across the Periods 1993-95 and 1997-99, suggesting that changes in the game at this time had a notable impact on this time variable. In general, it must be noted that for all time variables the changes across time are greater in rugby union than rugby league, indicating that changes in this Code (be they rule changes, tactical changes by coaches, or the impact of professional playing status) had a more marked influence than any concomitant changes in rugby league. In addition, the percentage changes in the time variables across time indicate that the most marked changes in rugby union were evident in the Periods spanning the introduction of professional playing status, whereas, the change to summer playing season appears to have had less impact in rugby league. Moreover, the changes particularly related to the important ruck ('play the ball') area.were more apparent across 1988-92 and 1993-95 suggesting the main rule change (10-m offside rule) at this time had a greater influence on time variable game changes in this Code of rugby. 2s9 The most notable time performance indicators in rugby union were set possession and continuous possession time, with teams winning Game Quarters having gteater times than teams losing Game Quarters. However, this was only identified in the professional Era, ostensibly mediated by the 2000-02 Period data, suggesting that possession maintenance became more important at this time. In rugby league, teams winning Game Quarters had higher set possession and continuous possession times than teams losing Game Quarters in both Eras and all post-1988-92 Periods. In addition, in this Code teams winning Game Quarters had greater total possession time than teams losing Game Quarters, in all Periods. In rugby union, winning teams and teams winning Game Quarters had faster ruck ball than losing teams and teams losing Game Quarters in both Eras and all Periods (except 2000-02), although these differences were found to be not significant. In rugby league, winning teams playing in the pre-professional Era had slower 'play the balls' than losing teams, mainly due to the large difference noted between winning and losing teams in 1988-92, This was reflected in losing teams having a lower percentage of 'slow ball' in the pre-professional Era and 1988-92 Period. In addition, teams winning Game Quarters in 1988-92 had signifïcantly higher 'slow ball' percent¿ges than teams losing Game Quarters, In subsequent Periods, the differences between successful and unsuccessful teams were less pronounced, and 'play the ball' times reduced for both winning and losing teams indicating that after 1988-92, the control of the ruck area became more significant in this Code. The time variable analyses presented in this study represent the most extensive assessment of time variables in either rugby union or rugby league conducted to date. Accordingly, it has been possible to map the changes in these variables and performance indicators over time and hence, to provide the first complete, valid longitudinal profile for each Code, Moreover, it has been identihed that the changes in both Codes in possession time, set possession time and continuous possession time in particular have resulted in the Codes of rugby becoming more alike, particularly since the introduction in professional playing status in rugby union. Further, given that in both Codes the control ofthe ruck area, and set and continuous possession have been identifïed as indicators of successful performance, it seems plausible that coaches could develop specific training programmes to meet the time demands of both games, and, perhaps this may act as a first stage in the development of the single code game. Hov,'ever, it must be noted that in rugby league the possession times are still significantly greater than in rugby union in all Periods. Whilst this time analysis was extensive, it is suggested that a more thorough assessment of time variables be undertaken. In particular, the contact area needs to be examined further, to identify the full contact time in addition to the ruck timg since the control of the ruck area commences with the initial contact and not at the tackle completion, as was assumed in the present study. In addition, it is suggested that the ruck and contact 260 time performance indicators are mapped to subsequent game actions and possible perturbations in play, so that the impact of these aspects of the game can be identified. Moreover, such analyses must be undertaken with due regard to the area of the pitch, since the playing patterns, and hence time variables and performance indicators are likely to change according to the relative position of play, a fact not controlled for in the present study. 7.1.3 Offence Whilst a convergence of the Codes is apparent for total ball carries, predominantly due to an increase in frequency observed in rugby union, the analyses of these data normalised to time indicate that any changes were ostensibly due to changes in ball in play time. The union to league ratios for all passes (total passes, dummy half passes, passes in open play and offloads) were smaller in the professional Era than the pre-professional Era, with total pass, dummy half pass and open play pass ratios also falling across the four Periods. These changes across time were mainly due to increases in the frequencies of these variables in rugby union, in contrast to the relative stability in rugby league. Particularly of note was the large increase in offload frequency between the Period 7993-95 and 1997-99, which was in opposition to the more general decrease in frequency in rugby union. The lack of change across time in the total passes, open play passes and offloads per unit time, in both Codes indicates the changes observed in the frequencies were mainly due to changes in 'ball in play' time. However, the increase in dummy half passes per unit time in rugby union indicated that 'ball in play' time could not be considered solely responsible for the increase in these data. The change across time for the frequency oftotal carries into contact, and the contact and tackle variables indicated a convergence. A similar trend was noted for these variables per unit time, with the most sizeable increases in rugby union being noted between the Periods 1993-95 and 1997-99. Increases (albeit smaller than in rugby union) were also identifìed in rugby league across the Periods 1988-92 and 1997-99, with higher normalised frequencies in this Code than rugby union in all Periods. In rugby unior¡ no differences between successful and unsuccessful performance were identified for the frequencies or frequencies normalised to time for total ball carries into contac! or offloads, However, teams winning Game Quarters were found to have lower offloads per contact than teams losing Game Quarters in the pre-professional Era. Additionally, whilst no differences were identified between successful and unsuccessful teams in any Periods, it is notable that the offload to contact ratio for teams winning Game Quarters increased across the Periods whereas this didn't occur in teams losing Game Quarters. 261 In rugby league, in both Eras and all Periods (except 1997-99) winning teams were found to carry the ball into contact per minute less than losing teams, although this was not signihcant in the professional Era. Winning teams also used the ofiload less often and had lower offload to contact ratios than losing teams. Interestingly, when examined by successful Game Quarter the frequency of offloads was higher in teams winning Game Quarters than teams losing Game Quarters. In both Eras and all four Periods it was identified that winning teams had lower run to pass ratios than losing teams, indicating that winning teams utilised the run from the dummy half position more than losing teams. The same trend was also noted for teams winning and losing Game Quarters. In addition, teams winning Game Quarters in the professional Periods only had higher turnover to contact ratios than teams losing Games Quarters. Whilst the Codes are seen to be converging in terms of the offence variables, the changes were predominantly mediated by the increase in ball in play time in rugby union, indicating that law changes and the change to professional playing status did not impact notably on ball carrying and passing. These findings highlight the importance of normalising data in order to assess the impact of any intervention. In addition, the relative stability of the offence variables in rugby league indicated that rule changes and the change to the summer player season also did not impact noticeably. However, it remains that in the professional Era there was an increase in offence actions compared to the pre-professional Era, and hence the games of rugby appear to be becoming more similar. Few offence performance indicators for success were identifÌed in either Code of rugby. Only in rugby league was it apparent that offloads were used more by successfiil teams than unsuccessful teams, although this only surfaced when the data were examined by successful Game Quarter, and illustrates the importance of analysing successful periods of play as opposed to the full game, since teams are likely to change their playing pattern in relation to the score and available playing time. It is therefore suggested that future researchers adopt this approach when attempting to identi$ performance indicators. 7.1.4 Defence The relative change in tackle attempts across the four Periods indicate that the Codes are converging, mediated predominantly by an increase in frequency and frequency per minute in rugby union rather than in rugby league (in which there is stability). Similar trends were also identifìed in the analyses of single and double tackles; however, it is notable that there was a large decrease in single tackles in rugby league between 1997-99 and 2000-02, reflecting the increasing preference for multiple (double and mob) tackles in 262 this Code, whereas the most used tackle type in rugby union remained the single tackle. In both rugby union and rugby league a decrease in missed tackle percentage \ryas noted across the Periods 1993-95 and 2000-02, reflecting a reduction in tackle errors in the professional Era and Periods. In rugby union, tackle frequency (either raw or per unit time) was not identified as being different for winning or losing teams in any pre-professional or professional Period. However, when tackles were examined by successful Game Quarters, successful teams (those winning Game Quarters) in the 2000-02 Period were found to make fewer tackles than unsuccessful teams, although this appears to be a reflection of differences in possession time, since no tackle per unit time difference was apparent. Regarding the tackle type, few differences were noted between winning and losing teams, and teams winning and losing Game Quarters. Only in the 2000-02 Period was a difference in tackle type percentage identified, with winning teams having a lower single tackle percentage and a higher double tackle percentage than losing teams. It was also notable that losing teams in the professional Era relied more heavily on the mob tackle than the winning teams. Similarly, in the 2000-02 Period, teams winning Game Quarters utilised the mob tackle significantly less than teams losing Game Quarters. In rugby league, winning teams were found to (on average) make mo¡e tackles than losing teams in the pre- professional Era, although, this was reversed in the professional Era. Interestingly, when tackle frequencies were examined in relation to successful Game Quarters, successful teams made fewer tackles than unzuccessful teams in all Periods, yet in the professional Periods no differences were identified when these data and Game Result data were normalised to time, indicating that in the professional game successful performance \ryas not related to tackle frequency. Similar to rugby union, few differences were noted between successful and unsuccessful performance (examined by either Game Result or Game Quarter Outcome) for tackle type. A change was, however, apparent across the Eras with winning teams having higher single tackle percentages in the pre-professional Era, and lower single tackle percentages in the professional Era than losing teams. The convergence ofthe Codes was very apparent regarding the defence variables, with total tackles, single tackle and double tackle frequencies becoming more similar. The increases in these variables in rugby union were most notable in the Periods spanning the introduction of professional rugby, indicating that in defence the change in playing status appeared to have an effect. This is not unsurprising given the Code diflirsion of rugby league defence coaches to rugby union at this time and the instigation of more structured defence systems. The preference for tackle type remained very diflerent between the Codes across time, with the single tackle being more predominant in rugby union and the double tackle being the preferred type in rugby league. 263 However, in both Codes the increasing trend in the double tackle was evident across time. Interestingly, in the 2000-02 Period only did successful teams make fewer single tackles and more double tackles than unsuccessful teams, indicating the change in indicators over time and the importance of double tackles in rugby union in the 'modern' game. Similady, tackle preference changed across the Eras in rugby league, with winning teams making more multiple tackles than losing teams in the 'modern' game. The implications for coaches are clear; the games must be closely examined over time to identifr changes in va¡iables and performance indicators. Without such continued analyses, in developing specific training schedules coaches can only rely on previous research (which may not be valid) and their own subjective analyses. rWhilst the tackle preference remains different in the different Codes, the use of multiple tackles has increased over time and as such the emphasis on this tackle would be the focus of any single Code game. It must be noted, however, that there were diftìculties in tackle type identificatior¡ hence, the results presented may be prone to some level of error. The present study did not address the effectiveness of the tackle, particularly in relation to the time in contact, and the ground conceded in the tackle relative to the gain line. It is therefore recommended that these elements should be the focus of future research in both Codes of rugby. 7.1.5 Game Actions A convergence ofthe Codes across the four Periods was apparent for the frequency per unit time for kicks out ofplay, predominantly due to a large decrease over the Periods spanning the introduction ofprofessional playing status. Conversely, in rugby league the frequency of kicks out of play per minute was found to be stable across time, although it is notable that fewer kicks to touch were made in the professional Era than the pre-professional Era. These changes reflect a reduction in the use ofthe kick (especially out ofplay) in both Codes of rugby after 1996. The increase in ruck frequency over the four Periods in rugby union was found to be in contrast to the stability of the profïle in rugby league. Such changes were found not to be mediated by increases in ball in play time in rugby union, since the frequency of rucks per unit time presented a similar increasing profile across time. As such, both the frequencies and time normalised frequencies for both Codes were seen to be converging. In addition, in rugby union a decrease in the frequency of mauls over time was noted, reflecting a more ruck-dominated game in the professional Periods and Era. Whilst the scrum frequencies in rugby union were found to be relatively stable across time, a different profile emerged when these data were normalised to ball in play time, with the frequencies per minute, noril seen to be reducing over time. Agairì, the changes over time in rugby league were less apparent, suggesting 264 that any Code convergence for this variable was ostensibly mediated by changes in the union game rather than the league game. A convergence of the Codes was also identified for phase/activity frequency, which, similar to other game variables, was due to changes in rugby union rather than rugby leagtre (although, such changes were predominantly a reflection of the increases in ball in play time across the four Periods). Conversely, the declining trend for set possession frequency was mirrored by the trend in these data when expressed per unit time, indicating an increase in mean set possession duration, and reflecting an improvement in ball retention in the professional Periods and Era. A further notable trend in rugby union was the reduction in lineout frequency and frequency normalised to time across the four Periods, which, as with the kicking profiles, indicates a major change in the professional game; the ball being kept in play for longer than in the pre-professional game. The reduction of set pieces in rugby union over time, namely the lineout and the scrur\ has resulted in a reduction in competition for the ball, which immediately makes the game more similar to rugby league, where any competition for the ball has almost been totally removed. Additionally, in both Codes the frequency of kicks out of play has decreased in the professional Period resulting in increased ball in play times. The most notable change in rugby union though was the large increase in the frequency of rucks, with a concomitant reduction in mauls, particularly evident in the Periods spanning the introduction of professional playing status. Clea¡ly the reduction of 'typical' rugby union game elements has made the Codes more similar and would make the development of the single Code game simpler. 7.2 Í'actors influencing convergence The converging of the Codes is predominantly due to changes in rugby union. For the time variables several factors, including law changes, changes to ball in play time and the change to professional playing status may have all influenced the convergence @igure 7.1). ft must also be noted, however, that rule changes and the change to a summer player season in rugby league are also influential factors in the convergence of some of the time variables. For offence and defence variables the law changes to the set pieces in 1996 and 1999, the ruck in 1999, a¡d the change to professional playing status in rugby union are the most probable contributory factors in the 26s convergence of the Codes (Figure 7.2).Inrugby league the introdustion of the lO-m offside rule in 1993 and to a lessor extent the change ofplaying season are both factors influencing the Code convergence. For game aotion variables the predominant factors resulting in the Codes converging were law changes at the set pieoes in 1996 and 1999, law changes at the maul in 1993, the ohange to professional playing status and the increases in ball in play time across the four Periods (Fþre 7.3). 266 Rugby League Rugby Union Mean ruck time Introduction of the lGm offside rule in Mean total Introduction 1993 ruck time of the 6Use it or lose itt maul law in Mean activity 1993 time Introduction of Mean total professional activity time playing status in 1996 fncreased ball Mean set in play time possession time Introduction Mean of non-injury Change of continuous substitutions playing season possession tine inl997 in 1996 Changes to Introduction Mean ball in lineout laws in ofexternal play time 1996 time-keeper in 2001 Figure 7. I Integrated model of factor influencing convergence in time variables 267 Rugby League Rugby Union Introduction Median frequency of the'Use it ofbatl carries per or lose itt game maul law in 1993 Median frequency ofopen play passes per game Amendments or ruck laws Median frequency in 1999 of total game passes per game Introduction Median frequency Increased ball of the lGm of dummy half in play time offside rule in I passes per game 1993 t\ and per unit tÍme nt rl) t\\ Median frequency tl of olÍloads per unit time I Change to \ Change of lineout laws in playing season Median frequency 1996 in 1996 of ball carries into contact per game \ \ and per unit time Change to frequency scrum laws in \ Median of total game 1999 tackles per game \ and per unit time Introduction Median frequency of tackles per of single professional game playing status in 1996 Percentage of missed tackles per game Figure 7.2Integrated model of factor influencing convergence ìn offence and defence variables. 268 Rugby League Rugby Union Median frequency of total kicks per game and Change to per unit time lineout laws in 1996 Median frequency of Introduction kicls out of play per of game and per unit time professional playing status in 1996 Medi¡n frequency of rucks per game and per 'nit time fntroduction of the 'Use it or lose itt maul law in Median frequency of 1993 scrruns per unit time Increased ball in play time Median frequency of set possessions per unit time Change to scrum laws in 1999 Median frequency of activity phases per g¡me Figure 7.2kúegrated model of factor influencing convergence in game action variables. 269 7.3 Performance analysis research - the wider context In scientific research, the use of'controls' is essential in experimental designs to establish whether changes due to interventions are truly due to that intervention rather than due to, or affected by other confounding factors. In performance analysis research, the examination of interventions, for example rule changes are common themes in many sports. Unfortunately, in this type of research the use of controls is not possible, however, alternative methods must be employed in an attempt to 'control' for any confounding variables. To this end, the use of longitudinal mapping of key variables is suggested, since this provides the researcher with a'map' of variable changes over time in which to contextualise any observed changes. The results of the analyses in the present study have clearly shown that trends in the data can easily be presented, in either graph form or by identifying the percentage change from Period to Period. The visual presentations are particularly useful ifthe data are presented as a line graph. The use ofpercentage change to identify trends in data is also suggested, since this gives a quantifiable change and hence, some indication is made regarding the size of the effect. Whilst it is accepted that these trends do not represent true'controls' it is posited that they at least enable the researcher to discuss any performance changes in relation to ongoing changes in the sport in question. However, in the absence of alternative approaches, it is suggested that for all sports researchers undertake longitudinal analyses to establish the nature oftrends in key variables and performance indicators. The analyses of the data presented in this thesis have provided a'map' of key time and tactical/technical variables, performance indicators and performance profiles in both rugby league and rugby union, which future researchers can use to contextualise their findings. It is accepted that there are some concerns with these analyses since the Periods examined span several years, and as such did not account for changes within the Periods. It is therefore suggested that future resea¡ch examines the changes in va¡iables in shorter Periods to provide a more in-depth 'map' of variable changes across time. It could be argued that the common practice of comparing research findings to previous research provides context. This practice, whilst appropriate, is dependent onthe results of previous research being valid. The review ofliterature presented in this thesis has shown that in performance analysis research scant regard has been given to the in-depth analysis of the reliability of systems. Those which do address reliability either use inappropriate statistical techniques, assess the total system reliability rather than by individual variables, use processed rather than raw data, and use data that have not retained their sequentiality. As a consequence, the 270 results of these studies must be viewed with caution, since the reliability and hence the validity of their analyses is in doubt. A further consideration in addressing the reliability of systems which has been identified in this thesis is the diffrculty in identifoing players. Traditionally in team sports, player identification is via a shirt number, however, in fast moving games, where play is often congested, this method of identification can contain low levels of reliability. This particular aspect of reliability analysis in performance analysis research has yet to be fully addressed. In both Codes of rugby the use of secondary identification characteristics was found to increase the reliability of player analyses, although in the professional Era the use of squad numbers (unrelated to position of play) and players playing multiple positions in rugby league made consistent identifìcation almost impossible. In additio4 the increased use of substitutions in both Codes also hindered identifications. The fact that previous research has failed to address this concern must also cast doubt on their findings, since even using slow motion and freeze frame, forward and back tracking and secondary identification characteristics, in only three out of twelve games in rugby league in the professional Era was it possible to identify players suffrciently to produce a player profile. Further to this, it was identified that in congested a¡eas of the game in rugby union (rucks, mauls etc.) very low level of intra-observer agreements resulted. Previous researchers often quote reliability percentages, but these are usually concerned with the reliability of recording frequencies of actions, not in identifying the player. If future studies in sports aim to present performance profrles for players, it is essential that this aspect of the reliability analysis is fully addressed. More generally, the reliability assessments undertaken in this thesis have demonstrated the depth to which such analyses are necessary if the frndings are to be deemed reliable and hence, valid. It is strongly recommended that researchers in sports performance give due regard to these two fundamental concepts of the measurement process. In addition to the in-depth analysis of the reliability of notation systems, it is also recommended that future researchers examine their data to ascertain how many games need to be analysed to reach a normative profile. In previous research, as with reliability analysis, it has been the 'exception rather than the rule' which prevails in this regard. Ofthose researches that have reported normative profiles, few have recognised that the shapes of these profiles are dependent on the order in which the data are input into the computer. The results ofthe profile analyses reported in this thesis have clearly established that unless double line profiles are used, incorrect conclusions can be made with reference to when the profile stabilises. The fact that previous research has omitted to analyse data in this manner, or not at all, means that it is not possible to state unequivocally that the results presented are representative ofthe 'population' as a whole. Hence, this threat of sampling error may cast doubt on the validity of their results and the conclusions derived from these data. 271 Whilst it has been previously reported that incorrect statistical procedures have been adopted in research in notational analysis, a more recent review ofpublished papers has found that researchers are now examining thei¡ data using more appropriate tests. A clear outline has been presented in this thesis which demonstrates the correct procedure for analysing data. Whilst it is important that frequency data are examined using non- parametric tests, higher level time data may be examined using appropriate parametric tests, although this is contingent on the data not violating the assumptions necessary for using such tests (normality of data distribution and homogeneity of variance). Where any of these assumptions are violated a decision can be made (based on the skewness of the data) whether to adopt a parametric test transform the datq use a non- parametric equivalent test or present descriptive data alone. For factorial designs, the additional problem of sphericity (homogeneity of covariance) must also be considered, main effects must be examined using appropriate post-hoc procedures and where multiple pair-wise comparison are necessary, adjustments @onferroni or other) made to the alpha value to protect against the increased risk of a Type I error. In more recent publications, researchers who employ non-parametric analyses have correctly reported the median score rather than the mean. However, there are two issues to consider. Firstly, the mean is a more widely used 'average' measure, and hence researchers who present medians must consider the intended audience (often coaches) and whether or not it will fully understand this central tendency measure. Secondly, using the median score makes comparisons to previous studies (who present the mean) more diffrcult. Hence, a more appropriate approach may be to report both the mean and the median scores, so that both the 'lay' audience and the 'academic' audience are both catered for. The results presented in this thesis demonstrate that, in most cases, there are only small differences between the median and mean scores. Only where there are outliers in the daø set do the mean and median deviate notably, hence, as long as researchers are aware of the effect ofthese outliers on their datq the continued use ofthe mean to describe the 'average' ofthe data is deemed appropriate. In many sports, resea¡chers attempt to identifu performance indicators for successful performance. In doing so, it is important that the data are presented both in raw and non-dimensional form in order to normalise the data in reference to possession frequency or time. The results of this study have shown that the analysis of performance indicators by Game Result may hide actual differences between successful and unsuccessful performance. An alternative method is recommended, whereby performance indicators are examined in relation to successful sections of play, in the case of this study Game Quarters. This provides a better indication of successful performance, which is not 'masked' by winning teams adopting a 'play safe' strategy, or losing teams 'throwing caution to the wind' in an attempt to score. Hence, it is suggested that performance indicators are clearly identified and more thoroughly examined in future research. 272 7.4 Geneml conclusions This study is the first to provide an extensive and, importantly, valid longitudinal mapping of the main elements of play in both rugby union and rugby league football. This notwithstanding, the careful attention paid to the measurement reliability process highlighted that in empirical studies of this kind there exists a considerable challenge for the researcher in the fundamental identification of players and certain game actions. In addition, it became transparent that the process of data inputting is potentially a major source of error, which, if not addressed, may undermine the validity of subsequent analyses and the inferences that follow. The comprehensive analyses reported in this thesis, which included a new method of assessing performance indicators for successful performance (analysing data by successful Game Quarters, as opposed to the more traditional Game Result approach), have led to the conclusion that the introduction of professional playing status (rugby union), the summer playing season (rugby league), and specific law changes have had a marked impact on important aspects of play, which strongly suggest that the two forms of rugby are more becoming similar in terms of game content, but not in terms of what constitutes successful performance. The consequences of such changes were (in general) more pronounced in rugby union than in rugby league, and were reflected ostensibly by an increase in ball in play time across the time frame of the study. In contrast, the game of rugby league was found to be more stable across time, with only minor consequences being identifìed. In effect, this study has demonstrated that between 1988 and 2002, the games of rugby were converging. Whether such harmonisation has continued to the present day is unknown, but further analysis is undoubtedly possible and should be encouraged. The case for the development of a single Code of rugby has now been made. 273 7.5 X'uture research rnd recommendations It is reoommended that future research continues to map both games of rugby, and includes the identification of both key variables and performance indicators in relation to pitch position. Further, performance indicators common to both rugby Codes should be identified and analysed, particularly in relation to successful Game Quarters. In addition, more extensive player profiles should be constructed in order to identify player and positional similarities between the Codes. Finally, it is strongly recommended that players, coaches and administrators in both Codes meet to discuss the possibility of developing a single game of rugby, which would aid the development of junior players for both Codes, and may be mutually beneficial in the continued development of rugby league and rugby union in the Northern hemisphere. 274 REFERENCES Ali, A. and Fanally, M. (1991). A computer-video aided time motion analysis technique for match analysis. Journal of Sports Medicine and Pþsical Fitness, 31, 82-88. Anderson, C. (2002a), Coach Talk. Rugby League Coaching Mamtalt RLCM coaching books, 2l-23. Andersoq D. (2002b). Coach Talk. Rugby League Coaching Manuals,RLCM coaching books, l5-16. Armstrong, C.W. and Hoffman, S. J. (1979). Effects of teaching experience, knowledge of performance outcome on performance effor identification . Reseqrch Quørterly, 50(3),318-327 . Atkinson, G. and Nevill, A. (1998). Statistical methods for assessing measurement enor (reliability) in variables relevant to sports medicine. Sports Medicine,26,217-238. Baker, D. and Nance, S. (1999). The relation between running speed and measures of strength and power in professional rugby league players. Journal of Strength and Conditioning Research,13,230-235. Bamford, M. (1989). Rugby Leagae: The Skills of the Game. Wiltshire: The Crowood Press. Bangsbo, J., Norregaard, L. and Thorso, F. (1991). Activity profile of competition soccer. Cqnodiqn Journal of Sports Science, 16(2), 1 10-1 16. Bard, C. and Fleury, M. (1976). Analysis of visual search activìty during sport problem situations. Journal of Humqn Movement Studie s, 3, 21 4-222. Bard, C., Fleury, M. and Carriere, L. (1980). Analysis of gymnastic judges' visual search. Research Quarterly, 51, 267 -273 . Barrett, N. (1996). @d.). Ihe Daily Telegraph Chronicle of Rugby. London: Guinness Publishing, London. Bartlett, R. (2001). Performance analysis: can bringing together biomechanics and notational analysis benefit coaches? International Journal of Performance Arnlysis in Sporl, l(7),122-126. Bayliss, G. (2002) Defence. Rugby League Coaching Manuals, Book 26. RLCM coaching books, 10-14 Beck, C. and O'Donoghue. P. (2004). Time-motion analysis of inter-varsity rugby league competition. In P O'Donoghue and M. Hughes @ds.) Performønce Analysis of Sport lry. (150-155). Cardiff: CPA IJWIC. Bee, P. (2005,20 March), The impact of professionalism in rugby. Guardiannewspaper. Bills, P. (2006, l0 March). IRB plans to 'revolutionise' rules of rugby. Independent ne\vryaper. Bird, Y. N., Waller, A. E., Marshall, S. W., Alsop, J. C., Chalmers, D. J. and Gerrard, D. F. (1998). The New Zealand Injury and Performance Project: V. Epidemiology of a season of rugby injury. British Journal of Sporls Medicine, 32, 319-325. Bland, J. M. and Altman, D. G. (1986). Statistical methods for assessing agreement between two methods of clinical measurement . The lancet, 8(1 ), 307-3 10. Boddington, M. and Lambert, M. (2004). Quantitative and qualitative evaluation of scoring oppornrnities by South Africa in the World Cup Rugby 2003. International Journal of Performance Analysis in Sport, 4(2),32-55 . Carroll, W. R. and Bandura, A. (1982). The role of visual monitoring in observational learning of action patterns: Making the unobservable observable. Journol of Motor Behavior, T4(2), 153-167. Carter, A. (1997). Time and motion analysis and heart rate monitoring of back row forward in first class rugby union football. In M. D. Hughes @d.) Noîational Analysis of Sport I &.11. (145-160). Cardiff: cPA, trwlc. 275 Carter, A. and Potter, G (2001a). The 1995 Rugby World Cup Finals: Where does all the time go? In M. D Hughes (Ed.) Notational Analysis of Sport I & II. Q20-223). Cardiff: CPA UWIC. Carter, A. and Potter, G. (2001b) The 1995 Rugby World Cup Finals: 187 tries. In M. D. Hughes @d.) Notationol Analysß of Sport I & I. (224-229). Cardiff: CPA UWIC. Chen, A. andZhu, W. (2001), Revisiting the assumptions for inferential statistical analyses: A conceptual goide. Quest, 53, 478-439. Church, S. and Hughes, M. (1986). Patterns of play in Association Football - A computerised analysis. Communiôalion to First l(orld Congress of Science and Football, Liverpool, 1lû'17ú April. Collins. T. (2000). From Bondi to Batley; Australians in English Rugby League. Sporting Traditions,16(2). Croucher, J. S. (1997). The use of notational analysis in determining optimal strategies in sport. In M. D. Hughes (Ed.) Notational Analysis of Sport I & IL (3 - 20). Cardiff: CPAs UWIC. Dalkeith, O. (2006, 15 February). The ruck is the centre of the universe. Rugby League Coaching Manual Newslelter. Daniel, R. and Hughes, M. (2001). Playing patterns of elite and non-elite volleyball. In M. Hughes and I. M. Franks, @ds.)pøss.com. (337-343). Cardiff: CPA LIWIC. Deutsch, M. U,, Kearney, G. A. and Rehrer, N. J. (2002). A comparison of competition work rates in elite club and Super 12 rugby. In W. Spinks, T. Reilly and A. Murphy (Eds.) .Sciet ce and Football IV (l 60- I 66). Cambridge University Press. Deutsch, M. U., Maw, G. J., Jenkins, D. and Reaburn, P. (1998). Hearl rates, blood lactate, and kinematic data of elite under 19 (Colt$ match play. Journal of Sports Sciences,16, 567-570. Docherty, D., Wenger, H. A. and Neary P. (1988). Time-motion analysis related to the physiological demands of rugby. Journol of Humqn Movement Studies, 14,269-277. Downey, J. C. (1973). The Singles Game.London: E.P. Publications. Dunning, E. and Sheard, K. (2005). Barbarians, Gentlemen and Pløyers: A Sociological Study Of The Development Of Rugby Football.London: Frank Cass & Co. Duthie, G., þne, D. and Hooper, S. (2003). Applied physiology and game analysis in rugby union. Sports Medicine, 33(13), 973-997. Duthie, G., Pyne, D. and Hooper, S. (2005). Time motion analysis of 2001 and2002 super 12 rugby. Journal of Sporß Sciences, 23 (5), 523 -53O. Eaves, S. J. (2006). The changing ruck and maul in rugby union 1988-2002. In M. Hughes and H. Dancs (Eds.). Perþrmance Analysis of Sport WI. Elliot, M. (2002). Coach Talk. Rugby League CuchingManralq RLCM coaching books, 19-20. Evangelos, T., Alexandros, K. and Nikolaos, A. (2005). Analysis of fast breaks in basketball. Internstionol Journal of Performance Analysis in Sport, 5(2),17-22. Farrar, (2002). Coach Talk. Rugby League Coaching Manøals, RLCM coaching books, 2-4. ^. Field, A. (2000). Discovering Statistics Using SPSSfor úTindows London: Sage Publications. Field, A. (2005). Discovering Statistics using SPSS (2'd Edition). London: Sage Publications. Foulkes, S. (2002). Rugby Leagae Coaching Maruals, Book 2. Coachtalk, RLCM coaching books, 17-18. Franks, I. M. (1993). The effects of experience on the detection and location of performance differences in a gymnastic technique. Research Quørterlyfor Exercise ønd Sport,64Q),227-233. 276 Franks, I. M. (2004). The need for feedback. In M. Hughes and I. M. Franks @ds.) Notational Analysis of Sport 2ñ Edition. (3-16). London: Routledge. Franks, I. M. and Miller, G. (1986). Eyewitness testimony in sport. Journal of Sport Behaviour, 9,3945 . Franks, I. M. and Miller, G. (1991). Training coaches to observe and remember. Journol of Sports Sciences, 9,285-297. Franks, I. M. and More, K. G. (2001) Analysis of coaching behaviours: A review. In M. Hughes (Ed ) Notational Arnlysis of Sport IIL (2I-42). Cardiff: CPAs UWIC. Franks, I. M., Goodman, D. and Miller, G. (1983). Analysis of performance: Qualitative or quantitative. SPORTS, March. Franks, I, M., Wilson, G. E. and Goodman, D. (1987). Analysing a team sport with the aid of computers. Canadiqn Journal of Sports Sciences, l2(2), 120-126. Fullerton, C. QO02\ Qualities required by the junior player. Rugby League Coaching Mønuals,26,24-25. Gabbett, T.I. (2002).Influence of physiological characteristics on selection in a semi-professional first grade rugby league team: a case study. Journal of Sports Sciences, 20, 399-405. Gabbett, T. J. (2005). Science of rugby league football: A review. Journal of Sports Sciences, 23(9),961-976. Gallagher, M. (2005). The Outside In Defensive Strategy (A personal view). Retrieved 12 February 20O6 fr om www.rugbycanada. aclcontent fileVOutsidelnDefence 05.pdf. GarganIa, J. and Gonclaves, C. (1997). Comparison offsuccessful attacking play in male and female Portuguese national soccer teams. In M. Hughes (Ed.) Notational Analysis of Sport III. (79-84). Ca¡diff:CPA UWIC. Garraway, W, M, Lee, A. J., Hutton, S. J., Russell, E. B. A, W. and Macleod, J. (2000). Impact of professionalism on injuries in rugby union. Brilish Journol of Sports Medicine, 34,348-35 I Gerisch, G. and Reichelt, M. (1993). Computer and video-aided analysis of football games. In T. Reilly, J Clarys and A. Stibbe @ds.) Science andFootboll n. 067 -173). London: E & F. N. Spon. Giles, D. C. (2002). Advanced Reseørch in Psycholog,t East Susses: Routledge. Gissane, C., Jennings, D., White, J. and Cumine, A. (1998). Injury in summer rugby league football: The experiences of one club. British Journal of Sports Medicine, 32(2), 149-152. Gissane, C., Jennings, D., Ker, K. and White, J.A. (2002). A pooled data analysis of injury incidence in rugby league football. Sports Medicine, 32(3), 2ll-216. Gissane, C., Jennings, D., Kerr, K. and White, J. (2003). Injury rates in rugby league football: Impact of change in playing season. Americøn Journal of Sports Medicine, 31, 954-958. Gissane, C., White, J., Kerr, K. and Jennings, D. (2001). Physical collisions in professional super league: The demands of different positions. Cleve land Medical Journal, 4, 137 -146. Grehaigne, J.-F., Bouthier, D. and David, B (1997). Soccer: the players' action zone in a team. In M. D. Hughes (Ed.) Notational Analysis of Sport I e II. Q7-38). Cardiff: CPA IJWIC. Hagan, M. Q002a\ Coach Talk. Rugby League Coaching Mamrals,2,15-16. Hagan, M. (2002b, 3 October). How Roosters have changes the game. Daily Telegraph. Retrieved 15 February 2006 from www.rl1908.com. Hands, D. (1988, l5 January). New model army to face the French. The Times. Hands, D. (2002,22 November). Lineout thieves stealing a march on opponents'ball The Times. Hardy, S. (2002). The line-out strategy and tactics, part II. The RF.U. Technical Journal, Autumn. 277 Hayrinerl M., Hoivala, T. and Blomqvist, M. (2004). Differences between winning and losing teams in men's European top-level volleyball. In P. O'Donoghue and M. Hughes @ds.) Performance Analysis of Sport W. (194-t99). Cardiff: CpA5 IIWIC. Herbert, P. and Tong R. J. (1997). A comparison of the positional demands ofwingers and back row forwards using movement analysis and heart rate telemetry. In M. D. Hughes @d.) Notatiorwl Analysis of Sport I & II. (69-72). Cardiff: CPA UWIC. Holzer, C., Hartmann, fJ., Beetz, M. and Von der Grun, T. (2003). M¿tch analysis by transmitter position measurement. In Book of Abstracts, Science and Football 51h World Congress,l l-15 Ap;il, 2003. Hopkins, W. G. (2000). Measures of reliability in sports medicine and science. Sports Medicine, 30(7), l-15. Howe, P. D. (2004). Sports, Professiornlism and Pain: Ethnographies of Injury and Risk. London: Routledge. Howell, D. C. (1997). StatisticalMethodsfor Psychologt.Belmont, CA:Duxbury. Hughes, M. (1988) Computerised notation analysis in field games. Ergonomics,3l(l l), l5ï5-t592. Hughes, M. (2004). Notational analysis - a mathematical perspective. Internqtional Journal of Performance Analysß in Sport, 4(2),97-139. Hughes, M. D, and Bartlett, R. M. (2002), The use of performance indicators in performance analysis. Journal of Sports Sciences, 20, 7 39-7 54. Hughes, M. and Churchill, S. (2005). Attacking profiles of successful and unsuccessful teams in Copa America 2001. In T. Reilly, J. Cabri and D. tuaujo (Eds.). Science and Footbalt V. (219-224). London: Routledge. Hughes, M. and Clarke, A. (1994). Computerised notational analysis of the effects of the law changes upon patterns of play of international teams in rugby union. Journal of Sports Sciences, 12Q), l8l. Hughes, M. and Franks, I. (1997). Notational Anaþsis of Sport,London: E & F. N. Spon. Hughes, M., andFranks,I @ds.) (2001). pctss.com, Cardiff: CpA UWIC. Hughes, M. and Franks, I. M. (2004). Notational Analysis of Sport (2nd ed.). London: Routledge. Hughes, M. and Jones, R. (2005). Patterns of play of successful and unsuccessful teams in men's seven-a- side rugby union. In T. Reill¡ J. Cabri and D. Araujo @ds.) Science qnd Football I/. (247-252). London: Routledge. Hughes, M and Knight, P. (1995). Playing patterns of elite squash players, using English and point per rally scoring. In T. Reilly, M. Hughes and A. Lees (Eds.) Science and Racket Sports. (257-259). London: E & F.N Spon. Hughes, M. and Sykes, I. (1994). Computerised notational analysis of the effects of the law changes in soccer upon patterns ofplay. Journal of Sports Sciences, 12(l), 180. Hughes, M. and White, P. (1997). An analysis of forward play in the men's Rugby Union World Cup, 1991. In M. D. Hughes (Ed.). (183-192). NotationalAnaþsis of Sport I & il. Carditr: CPA' UWIC. Hughes, M. D. and Williams, D. (1988). The development and application of computerized Rugby Union notation system. Journal of Sports Sciences, 6,254-255. Hughes, M. and Williams, J. (2002). Using analysis to examine rule changes and game structures in team sports. Retrieved 12 February 200ó from www.uksi.com. Hughes, M., Cooper, S-M. and Nevill, A. (2002). Analysis procedures for non-parametric data from performance analysis. Internslional Journal of Performance Analysis in Sport, 2(l),6-20. 278 Hughes, M., Evans, S. and Wells J. (2001). Establishing normative profiles in performance analysis. International Journal of Performance Analysis in Sport, l(l), L-26. Hughes, M. Kitchen, S. and Horabin, A. (1997). An analysis of women's international rugby union. In M. D. Hughes (Ed.). ( I 25- I 3 4). Notati onal Analysi s of Sport I & il. Carditr. CpA UWIC. Hughes, M., Langridge, C. and Dawkin, N. (2001) Perturbations leading to shooting in soccer. In M. Hughes (Ed.).(108-l 16). Notational Analysis of Sport III. Cardiff: Cp{ UWIC. Hunt, S. (2002). The role of the assistant coach. Rugby League Coaching Manuals, Book 26. RLCM coaching books, 7-9. Imwold, C. H. and Hoffinar¡ S. J. (1983). Visual recognition of a gymnastics skill by experienced and inexperienced instructors. Reseorch Quørterlyfor Exercise and Sport, 54, 149-154. Jackson, N. and Hughes, M. (2001). Patterns of play of successful and unsuccessful teams in elite rilomen's rugby union. In M. Hughes and L M. Franks @ds.)pass.com. (ttI-7tï). Cardiff: CpAs UWIC. James, N., Garnish, M. and Hughes, G. (2004). Predicting possession strategies for an international rugby team during the 2003 Rugby World Cup final. (unknown). James, N., Mellalieu, S. D. and Jones, N. M. P. (2005). The development of position-specific performance indicators in professional rugby union. Journol of Sports Sciences, 23, 63-72. Jones, N. M. P., Mellalieu, S. D. and James, N. (2004). Team performance indicators as a function of winning and losing in rugby union. Internatiornl Journal of Performance Analysis in Sport, 4(l), 6t-7t. Jones, N. M. P., Mellalieu, S. D. and James, N. and Moise, L (2004). Contact area playing styles of northern and southern hemisphere international rugby union teams. In P. O'Donoghue and M. Hughes Q0O4) @ds.) Performance Analysis of Sport W. (114-119), Cardiff: CPA IIWIC. Kear, J. (1996). Skills Developmentfor Rugby League. Herts: Queen Anne Press. Laird, P. and Lorimer, R. (2004). An examination of try scoring in rugby union: a review of international rugby statistics. Internationol Journal of Performance Analysis in Sport, 4(l),72-80. Lamb, K,L., Eaves, S. J. and Hartshorn, J. E. O. (2004). The effects of experiential anchoring on the reproducibility ofexercise regulation in adolescent children. Journal ofsports Sciences,22,l5g- tó5. Larder, P (1988) Rugby League Coaching Marual. London: Kingswood Press. Larson, O., Zoglowek, H. and Rafoss, K. (2001). Al analysis of team performance for the Norwegian women soccer team in the Olympics in Atlanta 1996. In M. Hughes, (Ed.) Notational Analysis of Sport III (171-18s). Cardiff: CPA UWIC. Ledger, J. (2006, I I February). Bulls chase six of the best. Yorkshire Post Today [Electronic version] Lieberman, D. G., Katz, L., Hughes, M. D., Bartlett, R. M., McClements, J. and Franks, L M. (2002). Advances in application of information technology to sports performance. Journal of Sporß Sciences,20,755-769. Liddle, S. D. and Murphy, M. H. (2001). A comparison of the physiological demands of singles and doubles badminton among elite players. In M. Hughes, (Ed.) Notational Analysß of Sport III. Q55-265). Cardiff:CPA UWIC. Long, R. and Hughes, M. (2004). Performance profiles of back row forwards in elite men's rugby union, before and after the introduction of professionalism. In P. O'Donoghue and M. Hughes (Eds.) Perþrmance Analysis of Sport W. (I30-l4l). Cardiff: CPA! UWIC. Lydon, J. (2001). Major considerations in back line attack. Ihe RFU Teclmical Jourual, Spring 9-15. Lyons, K. (1991). Notational Analysis: A case study of rugby union. Liverpool Polytechnic, 1912/1991 279 Nevill A. M., Atkinson G., Hughes M. D. and Cooper S-M. (2002). Statistical methods for analysing discrete and categorical data recorded in performance analysis. Journøl of Sports Sciences,20(10), 829 - 844. Nicholas, C. W. (1997). Anthropometric and physiological characteristics of rugby union football players. Sp or ts Medi cine, 23 (6), 37 5 -3 96. Noakes, T. and Jakoet, I. (1995). Spinal cord injuries in rugby union players. Brilish Medical Journol,310, 1345-r346. O'Connell, B (2004) Reply to Schwarz, R. The RFU Technicql JournqL Winter, 4-6. O'Connor, D. (1996). Physiological characteristics of professional rugby league players. Strength and C ordi ti oni ng C oach, 4(l), 2l -26. O' Connor, D. (1997). Fitness profiles in professional Rugby League players. In T. Reilly, J. Bangsbo and M. Hughes @ds.) Football qnd Science III. (11-15). London: E & F.N. Spon. O'Connor, D. (2003). The relationship between performance of professional rugby league teams and game statistics. In Book of Abstracts, Science and Football 5ü World Congress, Portugal, 11-15 April 2003. O'Connor, D. (2004). The relationship between performance of professional rugby league teams and game statistics. Journal of Sports Sciences, 22(6), 5I3. O'Donoghue, P. (2005). Normative profiles of sports performance. Intennlional Journal of Performance Analysis in Sport, 5(1), 104-1 19. O'Donoghue, P. and King S. (2005). Activity profile of men's Gaelic football. In T. Reilly, J. Cabri and D. fuaujo (Eds ). Science ond Foolball I/. (206-210). London: Routledge. O'Harg M. (1995). In a league of their own. New Scientist,30 Sept., 30-35. Olds, T. (2001). The evolution of physique in male rugby union players in the twentieth century. Journal of Sports Sciences, 19, 253 -262. Ortega. E., Sainz de Baranda, P. and Palao, J. M. (2005). Differences between winning and losing teams in basketball games in formation years (14-16 years old). In P. O'Donoghue and M. Hughes (Eds.) Performance Anølysis of Sport W. (156-167). Cardiff: CPA UWIC. Palao, J. M., Santos, J. A. and y Ureña, A. (2005). Effect of team level on skill performance in volleyball. International Journal of Perþrmance Analysis in Sport, 4(2), 50-60. Pa¡sons, 4., Mullen, R. and Hughes, M (2001). Performance profiles of male rugby union players. In M. Hughes and I. M. Franks (Eds.)pass.com (129-137). Cardiff: CPA UWIC. Pearson, A. (2001). Penetrating the flat line defence the SAQ way. Ihe RFU Teclmical Journal, Summer, 18- 19. Potter, G. (1997) A case study of England's performance in the five nations championship over a three year period (1992-1994).In M. D. Hughes (Ed.) Notational Analysis of Sport I & IL (193-202). Cardiff: cPA UWIC. Potter, G. and Carter, A. (2001a). The four year cycle: A comparison of the l99l and 1995 rugby world cup finals. In M. Hughes@d.) Notational Analysis of Sport IIL. (216-219). Cardiff: CPA! UWIC, Potter, G. and Carter, A (2001b). The 1995 rugby world cup finals. From whistle to whistle: A comprehensive breakdown of the total game contents. In M. Hughes @d.) Notational Analysis of Sport III. Q09-215)'. Cardiff: CPA! UWIC. Pritchard, S., Hughes, M. and Evans, S. (2001). Rule changes in elite badminton. In M. Hughes and L M. Franks, @ds.) (2001). passcom. (213-222). Cardiff: CPA UWIC. 281 Rader, B. G. (2002). Bqseball: A History of America's Gqme. Urbana and Chicago: University of Illinois Press. Reep, C. and Benjamin, B. (1968). Skill and chance in association football. Joumol of Royal Statistical Society, Series d 131, 581-585. Reilly, T. and Thomas, V. (1976). A motion analysis of work rate in different positional roles in professional football match play. Journql of Human Movement Studies,2,87-97 . Richards, H. and Richards, D. (2002).In B. Hale and D. Collins (Eds.) Tough Rugby. (181-184). Leeds Human Kinetic. Sasaki, J. et ql. (2005). Defence performance analysis of rugby union: the turnover-play structure. In T Reilly, J. Cabri and D. fuaujo @ds.) ,Science qnd FootbaU V. (243-246). London: Routledge. Sayers, M. (2005). A three-dimensional analysis of lineout throwing in rugby union. In T. Reilly, J. Cabri and D. Araujo @ds.),Science and Football V. (95-102). London: Routledge. Sayers, M. G. L. and Washington-King, J. (2005). Characteristics of effective ball carries in Super 12 rugby Internolionol Journql of Performance Analysis in Sport, 5(3), 92-106. Schwarz, R. (2004). The Two-Man Drop. Ihe R.F.U. Technical Joumal.Winter,l-3, Seward, H. (2002). Sports medicine changes the rules. In W. Spinks, T. Reilly and A. Murphy @ds) Science and Football IV. Q03-206). Cambridge University Press. Sharp, P. (2002). Rugby League Coaching Manuals, Book 2. Coach talh RLCM coaching books. Shultz, B. B. and Sands, W. A (1995). Understanding measì¡rement concepts and statistical procedures. In P. J. Maud and C. Foster (eds.) Physiological Assessment of Human Fitness. (257-287). Leeds: Human Kinetics. Simmons, R. W, and King, H. A. (1994). Expertise in the observation and subjective analysis of motor performance: A review of empirical research. Journal of Human Movement Studies. 27, 49-74. Skrinar, G. S. and Hoffinan, S. J. (1979). Effect of outcome on analytic ability of golf teachers. Perceptual and Motor Ski lls, 48, 7 03 -7 08. Smith, T. (2002). Coach Talk. Rugby League Coaching Mamtals, RLCM coaching books. Smitll T., Hammond, J. and Gilleard, W. (2005). The use of performance analysis technology to monitor the coaching environment in soccer. Internationql Journal of Performance Analysis in Sport,5(3), 126- 138 . Smythe, G., O'Donoghue, P. G. and Wallace, E. S. (1998). Notational analysis of contact situations in rugby union. In M. Hughes and F. Tavares, F. @ds.) Notational Anaþsis of Sport IV. (156-164). Cardiff: cPA UWIC. Somerville, D (1997). The Encyclopedia of Rugby Union. London: Aurum Press. StanhopgJ. andHughes,M.D. (1997). Ananalysisofscoringinthe l99l RugbyUnionWorldCupformen. In M. D. Hughes (Ed.) Notationøl Analysis of Sport I & II. (167-176). Cardiff: CPA UWIC. Tabachniclq B. G. and Fidell, L. S. (2001). UsingMultivariate Statistics (+1h Ednion). Bostoq MA: Allyn and Bacon. Taylor, J. B., James, N. and Mellalieu, S. D. (2005) Notational analysis of corner kicks in English Premiership League soccer. In T. Reilly, J. Cabri and D. Araujo @ds.) Science and Football V Q25 -23 O). London : Routledge. Thomas, C. (2001). The numbers game. The RFU Technicol Journal, Spring, 28-33. Thomas, C. (2004). Patterns of play in elite women's rugby union. Journal of Sports Sciences, 22(6), 519 282 Treadwell, P. J. (1988). Computer-aided match analysis of selected ball games (soccer and rugby union). In T. Reilly, A. Lees, K. Davids and W. Murphy @ds.) Science and Footboll. (282-287). London: E. & F. N. Spon. Treadwell, P., Lyons, K. and Potter, G. (1991). The predictive potential of match analysis systems for rugby union football: An outline review of the function of sports notation. Centrefor Notational Analysis in Sport, CardiffInstiute of H.8., Cardiff. Vincent, W. J. (1999). Stqtistics in Kinesiologt( 2ù edition). Champaigr¡ IL., Human Kinetics. Vivian, R., Mullen, R. and Hughes, M. (2001). Performance profìles and League, European Cup and International levels of male rugby union players, with special reference to flankers, no. 8 and no.9 In M. Hughes and I. M. Franks @ds.)pass.com. (137-146) Cardiff: CPA' UWIC. Wells, G. L. and Leippe, M (1981). How do triers of fact infer the accuracy of eyewitness identifications? Using memory for peripheral detail can be misleading. Journal of Applied Psychologt,66,682-687 Williams, J. (1999). Crickct ønd England: A Cultural and Social History of the Inter-war Years. London: Frank Cass Publishers. Williams, J. Q004). The effect of the wheeled scrum law in rugby union. Journal of Sports Sciences,22(6), 520. tililliams, J., Hughes, M. and O'Donoghue, P. (2005). The effect of rule changes on match and ball in play time in rugby union. Internationql Journal of Performance Analysis in Sport,5(3), 1-11, Williams, J., Thomas, C., Brown, R. and Jones, N. (2003). The effect of changing the law at the breakdown in rugby union in 1999. 8th Annual Congress ofECSS. Salzburg. Williams, J., Thomas, C., Browr¡ R., and Jones, N. (2005). The effect of the wheeled scrum law in rugby union, in T. Reilly, J. Cabri and D. Araujo @ds.) Science and Footbqll V. (262 - 267). London: E. & F. N. Spon. Winter, E. M., Eston, R. G. and Lamb, K. L. (2001). Statistical analyses in the physiology of exercise and kinanthropom etry . Journa I of Sports S c ience s, 19, 7 6l -7 7 5 . Withers, R. T., Maricic, 2., Wasilewski, S. and Kelly, L. (1982). Match analyses of Australian professional soccer players. Journal of Human Movement Studies, S, 158-176. Yiannakos,4., Sileloglou, P., Gerodimos, V., Triantafillou, P., Armatas, V., Kellis, S. (2005) Analysis and comparison of fast break in top level handball matches. Intemational Journal of Perþrmance Analysis in Sport, 5(3), 62-72. 283