CARDIFF METROPOLITAN UNIVERSITY

CARDIFF SCHOOL OF SPORT

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Name: James Taverner Programme: SPE

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SSP6050 Independent 19th March 1 week 2nd Apriil 2pm Project

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Deputy Dean Signature Please ensure that you attach a copy of this extension form to your submitted assignment(s) by the new submission dates quoted. Failure to do so will result in a maximum mark of 40%. Cardiff School of Sport DISSERTATION ASSESSMENT PROFORMA: Empirical 1

Student name: Student ID: James Taverner St2002354

SPE Programme:

Dissertation title: A Quantified Process of Comparing Spin Bowlers Performances in Contrasting Locations. Supervisor: Ray Ponting

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Title and Abstract (5%)

Title to include: A concise indication of the research question/problem. Abstract to include: A concise summary of the empirical study undertaken.

Introduction and literature review (25%)

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1 This form should be used for both quantitative and qualitative dissertations. The descriptors associated with both quantitative and qualitative dissertations should be referred to by both students and markers. Results and Analysis (15%) 2

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Discussion and Conclusions (30%) 2

To include: collation of information and ideas and evaluation of those ideas relative to the extant literature/concept/theory and research question/problem; adoption of a personal position on the study by linking and combining different elements of the data reported; discussion of the real-life impact of your research findings for coaches and/or practitioners (i.e. practical implications); discussion of the limitations and a critical reflection of the approach/process adopted; and indication of potential improvements and future developments building on the study; and a conclusion which summarises the relationship between the research question and the major findings.

Presentation (10%)

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CARDIFF METROPOLITAN UNIVERSITY Prifysgol Fetropolitan Caerdydd

CARDIFF SCHOOL OF SPORT

DEGREE OF BACHELOR OF SCIENCE (HONOURS)

SPORT AND PHYSICAL EDUCATION

2014-5

A Quantified Process of Comparing Spin Bowlers Performances in Contrasting Locations.

(Performance Analysis)

James Taverner

St20023954

A Quantified Process of Comparing Spin Bowlers Performances in Contrasting Locations.

Cardiff Metropolitan University Prifysgol Fetropolitan Caerdydd

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Table of Contents Chapter 1 ...... 1 Introduction ...... 1 1.0 Introduction ...... 2 1.1 Background ...... 2 1.2 The Evolution of T20 Cricket ...... 2 1.3 Research in Cricket ...... 3 1.4 Rationale for Research Question ...... 3 1.5 Research Question ...... 4 1.6 Null Hypotheses ...... 4 1.7 Limitations ...... 5 1.8 Delimitations ...... 5 1.9Glossary of Terms ...... 5 Chapter 2 ...... 7 Literature Review ...... 7 2.1 Notational Analysis ...... 8 2.2 Research in Cricket ...... 8 2.3 Performance Analysis in Cricket ...... 9 Chapter 3 ...... 15 Methods ...... 15 3.1 Introduction ...... 15 3.2 Equipment Used ...... 16 3.3 Pilot Studies ...... 16 3.3.1 Pilot 1...... 16 3.3.2 Pilot 2...... 16 3.4 Operational Definitions ...... 17 3.4.1 Delivery Line ...... 17 3.4.2 Delivery Length ...... 17 3.4.3 Delivery Outcome ...... 18 3.4.4 Type of Bowler ...... 19 3.4.5 Type of batsman ...... 19 3.5 Data Collection Procedure ...... 20 3.6 Reliability Study ...... 21 3.7 Data Analysis ...... 22 Chapter 4 ...... 25 Results ...... 25 4.1 Introduction ...... 25 4.2 Line of Delivery ...... 26 4.3 Length of Delivery ...... 27 4.4 Percentage of Runs Conceded ...... 28 4.5 Economy Rate ...... 29 4.6 Wickets Taken ...... 30 4.7 Dot Ball Percentage ...... 31 4.8 Types of Bowler...... 31 4.9 Strike Rate ...... 32 4.10 Percentage of Runs Conceded in Boundaries ...... 33 Chapter 5 ...... 34 Discussion ...... 34 5.1 Line and Length ...... 35 5.1.1 Length ...... 35 5.1.2 Line ...... 36 5.2 Dot Ball Percentage ...... 37 5.3 Percentage of Runs Conceded in Boundaries ...... 38 5.4 Economy Rate ...... 38 5.5 Strike Rate ...... 39 Chapter 6 ...... 42 Conclusion ...... 42 6.1 Summary of findings ...... 43 6.2 Practical Implications ...... 43 6.3 Future Recommendations ...... 44 References ...... 46 Appendix A – Example of initial spreadsheet…………………………………………... 50 Appendix B – Example of ball-by-ball commentary used………………...... 52 Appendix C – Kappa table………………………………………………………………...54 Appendix D – Kappa table………………………………………………………………... 56 Appendix E – Kappa table………………………………………………………………… 58 Appendix F - Kappa table………………………………………………………………… 60 Appendix G – Line and Length spreadsheet…………………………………………… 62 LIST OF TABLES Table No. Title Page No.

Table 1. Glossary of Terms 5

Table 2. Tournaments that have been analysed in previous 9

studies

Table 3. Outcomes of delivery definitions 18

Table 4. Types of spin bowlers 18

Table 5. Types of Batsman 19

Table 6. Definition for Delivery angle 19

Table 7. Kappa Values (Altman 1991) 21

Table 8. Means, Standard Deviations and P Values for all 25

variables across both locations.

Table 9. Kappa results table for length of delivery inter-reliability 55

Table 10. Kappa results table for length of delivery intra-reliability 57

Table 11. Kappa results table for line of delivery inter-reliability 59

Table 12. Kappa results table for line of delivery intra-reliability 61

LIST OF FIGURES

Figure No. Title Page No.

Figure 1. Spreadsheet example 16

Figure 2. Results for line of delivery 26

Figure 3. Results for length of delivery 27

Figure 4. Results for percentage of runs conceded 28

Figures 5. Results for economy rate 29

Figures 6 Results for wickets taken 29

Figures 7. Results for dot ball percentage 30

Figures 8 Results for types of bowlers 31

Figures 9 Results for bowlers’ strike rates 32

Figures 10 Results for percentage of runs conceded in 32

boundaries

Acknowledgments

I would like to thank Ray Ponting for his continued support and guidance through the dissertation procedure.

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Abstract

The aim of this study was to develop the understanding of spin bowlers performances in T20 cricket for different locations. 35 T20 games were accumulated from two separate T20 World Cups held in Bangladesh and the West Indies. A Mann-Whitney U test was conducted on the data to find significant differences between variables for locations. The test revealed very few significant differences between variables, but a full length (p = 0.018) and fours conceded (p = 0.003) were found to be significant (p < 0.05). Although a full length was found to be significant, it was the least effective length in terms of taking wickets. In addition, there was minimal difference found between the percentage of full and good length deliveries bowled across both locations. Percentage of runs conceded in boundaries was found to be of higher percentage per game in Bangladesh (9.1%) than in the West Indies (5.7%). Which contradicted previous research. Moreover, economy rate and strike rate differed minimally in both locations. But surprising, right arm leg spin bowlers were found to be the most economical bowlers. On the whole, these findings indicate that spin bowlers should aim to bowl a good length to take wickets and restrict runs, and effects on spin bowlers performances in different location are minimal.

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Chapter 1

Introduction

63

1.0 Introduction 1.1 Background Cricket is a team based game consisting of two teams made up of 11 players each. It can be played across 3 different formats at international level: Twenty20 (T20), One Day Internationals (ODI) and multiday tests. Multiday cricket at international level, best known as test cricket or five day matches, differs from domestic levels which are only played over 4 consecutive days. The game of cricket is split into two halves, one side bats first and, attempts to score as many runs as possible within the allocated over depending on which format they’re playing, while the opposing team bowls, striving to dismiss all the batsmen whilst simultaneously restricting runs. In the most recently developed form of cricket, T20, both teams face 20 six-ball overs, during the first six of these overs only 2 fielders are allowed to be outside the 30 yard circle (inner ring). Once the first six overs have been bowled, the fielding team only have to have four fielders inside the inner ring, not including the wicket- keeper or the bowler. This shortest format of the game requires all players to be accurate and precise when performing any skill as the margin for error decreases compared to either of the longer formats (Douglas and Tam 2010).

1.2 The Evolution of T20 Cricket

The English domestic T20 competition launched in 2003, it was the first of its kind, and sparked an evolution in cricket. Soon after, many other countries invented their own domestic T20 tournament (West Indies, India and Australia). Petersen et al., (2008a) and Mani (2009) suggested that the popularity of T20 was rising dramatically, due to the large financial investment being seen in the domestic competitions around the world. The subsequent rise in popularity has generated larger attendances to T20 matches than One day matches in South Africa and Australia (Douglas and Tam 2010; Kitchen 2008). The Indian Premier League (IPL) became the most popular competition as it attracted some of the worlds’ greatest players through potentially high wages and an auction house where players were bought by the eight franchise teams and is now a global phenomenon. In 2008 the IPL was born and since then has become the world’s richest T20 competition (Gupta 2011). Upon the conclusion of the competition’s first year, The Board of Control for Cricket in India (BCCI) had made 1.75 billion USD which therefore provided huge income for players’ salaries, rivalling the NBA as the highest paying league (Mitra

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2010). As a result of the players’ wages rocketing above any contract from their respected national or county/state team, players began to focus more on playing and performing well in the T20 format in the hope of being bought in the IPL auction by a franchise team. Lasith Malinga, the Sri Lankan bowler, has even gone as far as to retire from test cricket to focus specifically on his T20 career playing around the world in the various competitions. Invasive has been placed on the shoulders of the team management and coaches within the franchise teams, due to the money invested, to implement successful strategies and selecting the correct players to win matches (Petersen et al. 2008a).

1.3 Research in Cricket Cricket as a whole has been slow to react to technology advances in regards to performance analysis, compared to rugby or football (Moore 2012). Research related to cricket has mainly been within the field of Biomechanics focusing on fast bowling, and occasionally spin bowlers actions ( Bartlett et al., 1996; Elliot 2000; Glazier and Wheat 2013), physiological aspects required for the sport (Noakes and Durandt 2000) and psychology in cricket, (Bawden and Maynard 2001; Bull et al. 2005). However within the last decade studies have been conducted in the field of performance analysis (Clarke 1988; Preston and Thomas 2000). The research these authors have conducted focuses on the technical and tactical aspects for bowling and batting within ODI competitions. On the other hand research has been conducted to identify key performance indicators for both batsmen and bowlers (Petersen et al., 2008a; Petersen et al., 2008b; Nadjan 2014 et al.; Moore et al. 2012). Limited research has been conducted in T20 cricket, especially regarding the effects different bowlers have in the varied conditions encountered in the sub- continent (India; Pakistan; Sri Lanka) and non-sub-continent (Australia; England; South Africa) environments.

1.4 Rationale for Research Question T20 cricket has changed the two phases of the game, batting and bowling. Individual batsmen are inventing new strategies and adapting their technique to deal with the demand of T20 matches in particular, developing new skills and stroke play to limit bowlers’ effectiveness (Holmes and Talbot 2011). Bowlers are yet to show any adaption in their game (Justham et al. 2008), therefore T20 cricket remains a batsmen friendly game along with rules which benefit batsmen for example: small

3 playing area, allowing for high percentage of boundaries scored, and limiting the number of fielders allowed outside the inner ring. With that in mind, Najdan et al. (2014) suggested that performance analysis could play a greater role in the adaption of bowlers within the T20 format as, with the changes batsmen have made, bowlers would benefit from analysing batsmen’s techniques and focusing on which of their deliveries restricts batsmen’s scoring opportunities and has the best chance of taking wickets, which is identified as a key performance indicator for winning teams (Petersen et al. 2008a; Petersen et al. 2008b; Douglas and Tam 2010; Moore et al. 2012).

Very few studies found by the author have focused specifically on a type of bowler, and their effectiveness in different playing conditions. Wales Cricket Board (2009) stated that sub-continent pitches favour spin bowling due to them being dryer and therefore being prone to be slower and spin a greater amount than non-sub- continent wickets including: (England and West indies). This would seem to be backed up by Najdan et al. (2014) study, which focused on the English T20 domestic competition, when spin bowling overs were suggested to have a negative effect on the winning outcome. On the other hand, the 2007 T20 World Cup, hosted in South Africa, provided statistics (ESPNcricinfo, 2007) which showed spin bowlers took the highest number of wickets, and the lowest economy per game, which has already been identified as a key performance indicator for winning outcomes. Spin bowlers performances in T20 have yet to be researched in greater depth, even though research studies and statistics contradict each other. Researching spin bowlers performances across two different environments could provide coaches with knowledge of their effectiveness, and therefore could affect team strategies and selection for future matches.

1.5 Research Question Are spin bowlers performances affected by the location in T20 cricket

1.6 Null Hypotheses

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H1 – There are no significant differences between line and lengths bowled and locations in T20 cricket

H2 – There are no significant differences between percentages of runs conceded and locations in T20 cricket

H3 – There are no significant differences between strike rate and locations in T20 cricket

H4 – There are no significant differences between percentages of runs conceded in boundaries and location in T20 cricket

H5 – There are no significant differences between dot balls bowled and location in T20 cricket

H6 – There are no significant differences between wickets taken and location in T20 cricket

H7 – There are no significant differences between economy rate and location in T20 cricket However, Woolmer and Noakes (2008) stated that Asian conditions give a greater advantage to spin bowlers due to the preparation of the pitches, generating a larger degree of turn. In comparison to West Indian conditions which suit pace bowling because of harder, bouncier pitches prepared (Woolmer and Noakes 2008). With this said, spin bowlers performances may benefit in certain conditions.

1.7 Limitations  Matches proposed cancelled or shortened due to weather conditions.  Unable to obtain the footage for the 2010 ICC T20 World Cup in time for the data collection process.

1.8 Delimitations  The international matches used featured male participants, therefore these results cannot be applied to female cricket or any other level of cricket.

1.9Glossary of Terms Table 1 Glossary of Terms Over Six consecutive legal balls bowled by a single bowler from one end of the pitch to the batsmen Boundary This can be either a 4 or 6 struck by the batsmen. Attack bowlers Their main aim is to take wickets but on the other hand could

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leak a large number of runs. Defensive Bowlers of this nature aim to contain the batting sides scoring bowlers rate and focus less on wickets. Dot ball A delivery faced by a batsman from which no run was scored Inner ‘Circle’ A 30 yard ring where only 2 fielders are allowed outside it in the first 6 overs, and a minimum of 4 fielders have to be inside it after the completion of first 6 overs. Spin Comprised of all the various types of spin bowlers Day First innings of a Day/Night T20 Night Second innings of a Day/Night T20 Soft, damp A pitch which has been subject to heavy rain and has not wicket received much preparation, with little bounce and slow pace (Hinchliffe 2009a) Hard, fast A pitch which has been dried out due to little rain, generates wicket extra pace and bounce, mainly found in Australia, South Africa (Hinchliffe 2009a). Super 10s Two groups of five teams playing in round robin style tournaments to generate the four semi-finalists by taking the top two teams from each group. Super 8s Exactly the same format as the Super 10s system but only contains 4 teams per group. Still the same outcome producing the 4 semi-finalists. Northern Cricketing nations represented in the ICC T20 World Cups Hemisphere include; West Indies, England, Ireland and Netherlands

Southern Cricket related nations include; South Africa, Australia, New Hemisphere Zealand and Zimbabwe

Asia Associated countries include; India, Sri Lanka, Pakistan and Bangladesh. Economy rate The average number of runs conceded by a bowler per over. Wicket A batsmen being dismissed. Strike rate The average number of deliveries it takes to for a bowler to

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dismiss a batsmen. Average This is calculated by taking the number of runs conceded by a bowler divided by the number of wickets the bowler has taken.

Chapter 2 Literature Review

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2.0 Literature Review

2.1 Notational Analysis Match analysis on a whole can be used as guidance to the coaching process. Observing and collecting suitable information which will contribute to the evaluation of performance, linking to developments of tactical and technical aspects of performance (Franks et al. 1983). Before technology was available in cricket, the scorebook was used as a basic hand notation system. To this date the scorebook is still being used alongside technology that emerged to aid coaches in producing training programmes and team selection.

2.2 Research in Cricket Research conducted within the last decade has focused on the physiological demands associated with batsmen, bowlers and fielders. Two systems were used in the studies, time-motion analysis (Duffield and Drinkwater 2008; Rudkin and O’Donoghue 2008), and global positioning system (GPS), (Petersen et al., 2009; Petersen et al., 2010).

Rudkin and O’Donoghue (2008) observed 27 first class cricketers in the field, entering data into a laptop real-time. Running velocities had been calculated using timing gates in a controlled environment to combine with the data collected on the field. On the other hand Petersen et al. (2009) conducted a study of four T20 matches collecting GPS data from 18 players, which was designed to quantify the player’s movement demands and gauge the amount of physical preparation and recovery needed for T20 matches. Results determined the most physically demanding discipline within cricket was fast bowling as it had the highest levels of high-intensity work, coupled with the least rest period (Petersen et al. 2009). However Rudkin and O’Donoghue (2008) found that T20 fielders travelled more than double the distance per hour compared to the fielders in multiday matches. In conclusion Petersen et al. (2009) concluded that coaches should understand that the

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3 different formats have different physical demands and tailor their training to reflect this.

2.3 Performance Analysis in Cricket Cricket has been said to be predominately focused around statistics which can influence coaches’ strategies towards different matches (Petersen et al. 2008b). Previous performance analysis studies in Cricket have aimed to identify whether bowlers should try to take wickets more than restricting runs, batting tempo and skill execution and these areas affect the match outcome (Petersen et al. 2008b). Also the author struggled to find studies focused on bowling strategies, compared to batting strategies (Clarke 1988; Preston and Thomas 2000). De Silva and Swartz (1997) was one of the first few studies which focused on the coin toss and home field advantage. They concluded that the winning of the toss gave no competitive advantage and secondly, teams playing at home had a greater probability of winning the match. Match location effects were supported by Morley and Thomas (2004) provided backing in regards to match location effects. They analysed home field advantage, match importance and team quality. Their analysis showed that winning the toss gave the home team a greater advantage.

Table 2. Tournaments that have been analysed in previous studies

Tournament Location 2010 English Domestic T20 League* England 2008 Indian Premier League (IPL)* India 2009 ICC World T20 England 2007 ICC World T20 South Africa 2013 Indian Premier League India 2013 Champions Trophy England 2012 ICC World T20 Sri Lanka 2007 ICC Cricket World Cup West Indies * Tournament used more than once

Studies which focused on bowling specifically, Justham et al. (2008) compared bowling tactics of 3 right arm bowlers: medium pace, fast pace and an off-spin participating in all three forms of cricket. Justham et al. (2008) found that spin bowlers bowled a full length throughout all three formats, whereas fast bowlers and

9 medium pace bowlers tended to bowl a shorter length in test matches and then bowl a fuller length in T20. The small number of bowlers used given that various bowlers have different tactics, and for example, the different locations, pitch conditions and opposition can have an effect on the bowlers’ tactics which impact the length they’ll be trying to bowl. Also this study showed no correlation between the bowling lengths bowled to key performance indicators such as, wicket-taking and economy rate (Petersen et al. 2008a).

Moore et al. (2012) built on the research conducted by Justman et al. (2008). They analysed the various types of bowling as well as the specific bowling delivery. This provided information regarding which type of delivery took most wickets and which bowler is most effective in T20. The addition of in depth performance indicators allowed for extensive feedback to the coaches after games rather than basic performance indicators; wickets taken, spin overs bowled and scoring rate identified by (Petersen et al., 2008a; Douglas and Tam, 2010).

Moore et al. (2012) used a T-test and effect sizes to analyse data from the 2010 English domestic T20 tournament, unlike previous research had been conducted using the Indian Premier League or World Cup Competitions in sub-continent conditions. The different playing conditions did not affect the performance of spin bowlers, because their effect on winning and losing was trivial. Therefore an assumption could be made that conditions do not affect the performance of spin bowlers. The number of matches used was considered a limitation by Najdan, Robins and Glazier (2014). Moore et al. (2012) also acknowledged that the low sample size could limit validity of the data.

Since the CBR equation was developed by Lemmer (2002), researchers have found it to be a popular equation within analysis (Sankaran 2012). However, Saika and Bhattacharjee (2012) emphasised limitations when the metric is used. Saika and Bhattacharjee (2012) discovered that CBR failed to take into consideration the number of games bowlers have played, and also presented differing results to expectations of experts. Furthermore Saita and Bhattacharjee (2012) acknowledged these limitations and created a new metric called Linear Bowling Performance Measure. But Sankaran (2012) criticised this metric, stating that it also failed to include important bowling performance attributes that are relevant to the T20 format;

10 percentage of dot balls bowled (PDB) and percentage of runs conceded in boundaries (PBS).

Sankaran (2012) investigated the relationship between the cost of players in the IPL auction and players performance. Sankaran (2012) developed a new performance metrics (PDB) to calculate dot ball percentage within cricket analysis. Sankaran (2012) stated that using this metric is particularly beneficial in judging bowlers performances in T20 tournaments, as it’s difficult to bowl dot balls, compared to in the test match format. Moreover, PRB is identified to be an important metric to consider when T20 cricket is analysed, since the T20 format is focused mainly on scoring runs as quickly as possible, bowlers tend to concede a larger proportion of runs in boundaries and therefore is essential to analyse across different locations (Sankaran 2012). Also cluster analysis was used to classify groups of data into different clusters. In this case, Sankaran (2012) used 4 different clusters; inexpensive underperformers, expensive good performers, moderately expensive poor performers and highly expensive star performers. Spin bowlers were found to be mostly grouped in the final cluster, and justified their dominance in Indian conditions which are identical to Bangladesh conditions.

Lemmer (2008) used the equation to calculate the combined bowling rate (CBR) using four main aspects of bowling: overs bowled, runs conceded, balls bowled and wicket taken based on data from T20 World Cup (held in South Africa). This was ‘CBR’ = 3R/(W* + O + W*×R/B) where B represents the number of balls bowled, R stands for runs conceded, O is the number of overs bowled, and W* stands for the importance of wicket taken in relation to batting position. Although employing a calculation which takes into consideration importance of batsmen dismissed provides varied data and ranks bowlers differently to previous studies, the situation in a game may require the bowler to take wickets at the end of the innings of a lower order batsmen to win, if successful the bowler would not be ranked as highly as a bowler who took one wicket in the match of a top order batsmen. Lemmer (2008) acknowledged that Basevi and Binoy (2007) developed a formula, Calc = R2/(W×B) which can also be written as Calc = A×E/6, where A is the bowlers average and E is the bowlers economy rate. However Lemmer (2008) dismissed this equation as it

11 required bowlers to deliver 200 balls which is unlikely to be met in T20 cricket as a bowler can only bowl a maximum of 4 overs (24 balls min) per game.

PJ Van Staden (2008) conducted a study which attempted to compare bowlers, batsmen and all-rounders in the IPL using a graphical display. The author identified that minimal analysis had been conducted on T20 cricket due to its short lifespan as a format of cricket so far. Previous to PJ Van Staden, the method used was first presented by Kimber and Hansford (1993) solely to compare batsmen. PJ Van Staden (2008) used three common metrics, bowlers average, economy rate and strike rate. Bowlers from the tournament were only taken into consideration for analysis if they had bowled a minimum of 100 balls. Therefore only 16 bowlers were displayed in the graph. Moreover, some players overlapped each other; therefore a further table would need to be designed to allow interpretation of the data. It would be difficult to quantify the performance of spin bowlers using this methodology as not all bowlers are included in the analysis.

Researchers have attempted to create a method which ranked bowlers highest to lowest using different variables. In this case, Manage et al. (2013) devised a method to quantify the performance of the bowlers in Sri Lanka using these variables; wickets, average, strike rate and economy. The authors highlighted that the variables chosen were the most specific to a bowlers performance. They also used the First Principal Component (FPC) that correlated the 4 different variables for each bowler and generated a variance and points system for which the bowlers were ranked on. The authors found that 4 spin bowlers were included in the FPC top 10 rankings.In comparison to Lemmer (2008) who found only 3 spin bowlers in the top 10, in South Africa, but used a different equation (CBR). Comparing spin bowlers performances for different locations could influence team selections. Also, not every spin bowler is included in the analysis for these results. A bowlers had to make specific requirements to be considered for the analysis.

Petersen et al. (2008a) analysis was conducted on the 2008 Indian Premier League (IPL). The analysis used magnitude-based inferences (Batterham & Hopkins, 2006) to identify the importance of batting and bowling variables to winning and losing teams. These included: more runs coming from boundaries, bowling more spin overs 12 and taking more wickets. The effect size statistic (Hopkins, 2004) was used as it determined the significance of the different variables for winning and losing teams and comparing variables.

Analysis showed during the middle 8 overs of the innings, employing more defensive bowlers such as spin or medium paced bowlers would contain the batsmen scoring rate.

Petersen et al. (2008b) also used magnitude based differences when they analysed 47 ODI games from both the Round Robin and Supers 8 stages of the 2007 ICC Cricket World Cup (held in the West Indies) specifically focusing on batting and bowling differences between winning and losing teams. As before in the Petersen et al. (2008a) magnitude-based differences were used in the analysis of the data. They found that the margin between winning and losing was smaller in the Super 8s phase. As in the Petersen et al. (2008a) study, results showed that taking wickets was the highest performance indicator (PI) for success. However the two studies otherwise found wickets had a significant effect for winning teams, but the variable spin overs bowled had negative effect on winning indicating these types of bowlers perform worse on West Indian pitches.

The studies by Petersen et al. (2008a; 2008b) failed to collect data for bowling areas linking to taking wickets and minimising runs. Data of this type could be useful for coaches when, preparing strategies to restrict run scoring and take wickets in early overs, variables that have a significant effect on winning outcomes (Petersen et al. 2008a; 2008b).

Wickramasinghe (2014) used the ‘CBR’ in finding that spin bowlers were more effective than non-spin bowlers throughout the 2013 Champions Trophy. This contradicted Petersen et al. (2008b) who stated that the variable, spin bowling overs had a negative effect on Round Robin stages and a trivial effect in the Super 8 stages. These contrasting results may be due to the ICC introducing various rule changes in October 2007 (The International Cricket Council 2009). These changes included: increasing minimum boundary distance and allowing an extra fielder to be outside the inner ring outside of Powerplays. Therefore Petersen et al. (2008b) analysis that spin bowlers had a negative effect on performance due to the boundary

13 size being smaller is dated because the 2007 ICC World Cup was completed prior to the rule changes. 2.4 Aims of the Study T20 cricket seems to have been neglected within research studies for cricket. However, as it is developing quickly as a format of the game, further research is required. Recent research has focused on one location, whereas it would be useful to compare players performances in two contrasting locations as teams travel regularly to play away from home. Specifically the aim is to analyse spin bowlers performances for different locations, as some conclusions about spin bowlers is dated due to rule changes.

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Chapter 3 Methods

3. Methods

3.1 Introduction This chapter identifies the method employed to collect the data, any problems found in pilot tests and the data analysis process required to answer the research question. Are spin bowlers performances affected by the location in T20 cricket?

The data was collected from 37 T20 matches played during the Super 8s and Super 10s stages of two world cups, which were hosted in different countries. 14 of the games in the 2010 ICC T20 World Cup, held in the West Indies and 23 games from the 2014 ICC T20 World Cup held in Bangladesh were used. Matches that were reduced in length or abandoned due to weather, resulting in them being decided by Duckworth-Lewis method were omitted from analysis (Douglas and Tam; Moore et

15 al., 2012). This removed two games played in the 2014 ICC T20 World Cup meaning, 21 games were finally analysed from the 2014 ICC T20 World Cup.

3.2 Equipment Used  ESPN Cricinfo (See Appendix A for an example ball-by-ball commentary)  Software - Windows XP 2007, Microsoft Excel 2007, Statistical Package of Social Sciences (SPSS)  Printer - HP Deskjet F2200  Laptop

3.3 Pilot Studies Pilot studies were conducted to minimise any problems that the final system would encounter and these were altered before data was collected. Therefore the analyst could collect the data with greater efficiency. These pilot studies are discussed below.

3.3.1 Pilot 1 Firstly data was collected, using the ball-by-ball commentary from ESPN Cricinfo, from a single T20 match in the 2014 ICC World Cup (Match 13 India v Pakistan) using a hand notation system. Following the collection of data from the specific match, data was to have been moved from the hand notation sheet into a Microsoft Excel spreadsheet. However, the pilot study identified that using the hand notation sheet prior to inputting the data into an electronic spreadsheet would have been time consuming due to the amount of raw data gathered. The operator also found the hand notation system to be tedious suggesting that errors were made due to lack of concentration.

3.3.2 Pilot 2 Second pilot study was conducted to test a Microsoft Excel spreadsheet designed to allow direct entry of data. The same ball-by-ball commentary was followed to obtain data. It was found that the spreadsheet allowed for length and line of delivery and

16 outcome of delivery to entered more quickly, therefore raw data was produced faster. After the pilot study, it was determined that alterations had to be made to the spreadsheet (see Appendix B for example of initial spreadsheet). Firstly the spreadsheet failed to allow entry of whether the batsmen was right handed or left handed. Also a column needed to be inserted to state whether the spin bowler was delivering the ball from ‘over’ or ‘around’ the wicket. The bowling team may decide to change tactics or line of delivery therefore the extra column was included. Finally the outcome column in the initial spreadsheet was removed and replaced with three separate coloumn; runs, dot balls and wickets. This decision was made to make analysis in SPSS. Following these changes being made, the spreadsheet met all the purposes of the study, collecting the data effectively and efficiently. A ‘X’ symbol was entered in the cell in the relevant cell for length of delivery, and the line which that delivery was travelling on. Figure 1 provides an example of the spreadsheet template used to collect data from all the games.

Figure 1 spreadsheet example

3.4 Operational Definitions 3.4.1 Delivery Line Woolmer and Noakes (2008) described the line of delivery as being the direction the ball is travelling on release by the bowler. As this study focused solely on spin bowlers, who have the ability to move the ball of the pitch, the line was noted based on where the batsman made contact with the ball instead of noting where the ball pitched on the wicket. The three different types of line are defined below.

Definitions for line of delivery are follows:

 Off – A ball that the batsmen made contact with on or outside off stump  Middle – A ball that the batsmen made contact with between off and leg stump  Leg – A delivery that the batsmen made contact with on or outside leg stump

3.4.2 Delivery Length The length of delivery is normally referred to as where the ball lands on the pitch in relation to a ‘general’ stance taken by the opposing batsman (Woolmer and Noakes, 2008). Spin bowlers are prone to batsmen using their feet to come down the pitch and successfully play a shot to deviating deliveries in T20 cricket to force spin

17 bowlers into changing line and lengths (Petersen et al. 2008a). Noting the length of the ball will not be influenced by a batsmen’s movements. The length of delivery will not change if the batsman backs away using the depth of their crease, changing a good length ball, in their typical stance, to a shorter delivery.

The operational definitions below for length of delivery are in accordance with those defined by Lewis (1995) on a 22 yard (20.12cm) length pitch:  Short – a delivery pitched more than 8 metres away from the batsman’s middle stump  Good – a delivery that landed 6 to 8 metres away from the batsman’s middle stump  Full – a delivery that landed between 2 to 6 metres from the batsman’s middle stump  Yorker – a delivery pitched 2 metres from the batsman’s middle stump  Full toss - a delivery which doesn’t bounce at all before reaching the batsman.

3.4.3 Delivery Outcome Trevillion and Holder’s (2009) provided definitions of outcomes of delivery were used (see Table 3). Also within data collection specific symbols were used to recognise each of the outcomes (shown in Table 3 alongside the definitions).

Table 3. Outcomes of delivery definitions (Trevillion and Holder 2009)

Outcome Symbol Definition Dot ball ‘0’ A delivery which a batsman scores 0 runs off A run is scored when the two batsman run to each other’s end without being run out. The amount of time Run ‘1,2,3,4’ they run leading to the number inputted. The commentary mentioned how many runs were scored at the end of each delivery.

A ball which crosses the boundary after bouncing at Boundary ‘4, 6’ least once (4), a ball does has not touched the ground before crossing the boundary (6). Wicket ‘W’ The umpire gives the batsmen out.

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3.4.4 Type of Bowler The types of bowlers vary from fast bowlers to slow bowlers. Table 4 shows the definitions for types of spin bowlers only, as the study focused on the performances by spin bowlers. If the author was unsure about what type of bowler a player was, then ESPN cricinfo was used as it provided player information.

Table 4. Types of spin bowlers Type of Bowler Abbreviation Definition Left Arm Orthodox LAS Slow left arm bowlers turn the ball away from a right handed batsman. Right Arm Off - Spin RAO Right arm off spinners turn the ball in to a right handed batsman. Right Arm Leg – Spin RAL Right arm leg spinners turn the ball away from a right handed batsman. Left Arm Chinaman LAC Left arm chinaman bowlers turn the ball into a right handed batsman.

3.4.5 Type of batsman The two batsman styles are described with abbreviations in Table 5. Player information on ESPN cricinfo showed the author whether the batsmen were right handed or left handed if the author was unsure.

Table 5. Types of Batsman Abbreviations Description

RH Right handed batsman

LH Left handed batsman

3.4.6 Delivery angle A bowler can choose to deliver the ball from over or around the wicket, as long as the umpire is told before the bowler’s run-up begins. Table 6 lists the definitions and abbreviations for both over and around the wicket.

Table 6. Delivery angle Angle of delivery Definition

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(Abbreviations) Around the wicket (a) During his/her bowling action the right arm bowler passed the stumps on the right hand side. Vice versa for a left arm bowler. Over the wicket (o) During his/her bowling action the right arm bowler passed the stumps on the left hand side. Vice versa for a left arm bowler.

3.5 Data Collection Procedure

Before data collection began, these specific match details were entered into the spreadsheet:

 Match No. in the tournament  Teams  Innings No.  Match over No.  Bowler over No.

Secondly these details were entered into the spreadsheet for each delivery:

 Type of Bowler  Batsman style  Delivery angle

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 Bowlers over No.  Delivery (line and length)  Delivery outcome

To start the data collection, the specific game is located on (ESPNCricinfo) and ball- by-ball commentary is clicked and left open to refer back to for each of the spin bowlers deliveries. Once an over was found to be bowled by a spinner, the match over number was entered into the spreadsheet, followed by the bowler’s over number. Then ball-by-ball the line and length was entered into the spreadsheet using the symbol ‘X’ in the specific cell. Followed by the outcome of that delivery. Once the over had been completed, ball-by-ball commentary was referred back to double check that all data inputted was correct, as well as the amount of balls bowled. Also scorecards were referred to relate to bowlers figures to make sure the amount of runs and wickets are correct for each spin bowler who has bowled at least one over.

3.6 Reliability Study An inter - and intra - observer reliability test was conducted using two full matches from the 2014 T20 WC: (Match 18 – New Zealand v South Africa and the final – India v Sri Lanka). Intra – observer reliability was conducted, followed 7 days later by another observer to calculate inter – observer reliability. One final observation was made for intra observer reliability by the initial observer to compare for intra – observer reliability using Kappa statistical test. Comparisons were made between observer 1 and observer 2 for inter - reliability. Altman (1991) interpreted kappa values, as given in Table 7. Results of the Kappa reliability test for length of delivery showed in Appendix C and D. Line of delivery was also tested for reliability using Kappa given in Appendix E and F. Both of the areas tested reveal a high kappa value above 0.90 which is interpreted by Altman (1991) as very good agreement. Further variables were tested, wickets, runs, outcomes, batsman type and bowler type that had perfect Kappa reliability. Further variables, (wickets, runs, dot balls, delivery angle, batsmen type and bowler type) were tested for reliability and showed a perfect kappa score (1.0).

Table 7. Kappa Values (Altman 1991)

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Strength of agreement Kappa values Very good Over 0.8 Good Between 0.8 –0.6 Moderate Between 0.6 –0.4 Fair Between 0.4 –0.2 Poor Below 0.2

As an extra reliability test, two full games, (the finals from both tournaments) were chosen to be watched on television using a DVD disc to ensure that the comments being written on the ball-by-ball commentary corresponded with the events happening in the match. The author recognised that when the commentary on ESPNcricinfo stated that the delivery was of a good length, the video footage agreed with that statement as the delivery had pitched in between 6 and 8 metres away from the stumps, which was defined as a good length delivery. This also applied to line of delivery, as the video footage matched up with the commentary and the operational definitions in place.

3.7 Data Analysis Before data analysis was conducted LAC bowlers were discarded from the study due to only bowling three overs in one location. Once the data collection process had been completed, the following metrics were used.

Bowling Economy Rate (BER) – A bowler’s economy rate is the average number of runs conceded per over. The formula below is used to calculate it, using ‘x’ as 6, as it’s typically the number of balls in an over.

Number of runs BER = x* Number of balls

Bowling Strike Rate (BSR) – This metric is represented by the number of balls bowled divided by the number of wickets taken. Below shows the formula.

Number of balls BSR = Number of wickets

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Percentage of Runs Conceded in Boundaries (PBS) – A new metric which the author has yet find in previous cricket analysis. Defined as the percentage of runs conceded in boundaries. Shown below is the formula used, where ‘x’ is 100.

Number of runs conceded in boundaries PBS = x* Number of runs

Percentage of Dot Balls Bowled (PDB) – Defined by the number of dot balls bowled divided by the number of balls bowled. In the formula below, ‘x’ is 100.

Number of dot balls bowled PDB = x* Number of balls bowled

Before raw data was transferred into SPSS, line and length raw data was split into two columns headed ‘length’ and ‘line’. Each line and length variable was associated with a number, because SPSS can only work in numbers and allowed data to be correctly formatted. Prior to a Mann-Whitney U test being carried out, percentages per game was worked out for all variables being tested. The Mann-Whitney U test was used to analyse the data and aimed to show whether any variable were significantly different.

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24

Chapter 4 Results

4.0 Results 4.1 Introduction The results chapter aimed to give a brief overview of the various findings. Below, table 8 shows the variables tested across both locations. Furthermore, the values shows in table 8 are per game. So for example, the percentage of dot balls per game in Bangladesh (34.10% ± 17.90), whereas in the West Indies the dot ball percentage was (30.6% ± 9.40) per game. Table 8 also shows the percentage of LAS employed per game in Bangladesh (22.48% ± 21.00), compared to in the West Indies where

25 the percentage grew per game (32.53% ± 16.12). Table 8 also shows the P Value for each variable, highlighting whether there is a significant different (p < 0.05). Two variables were found to have a significant difference, 4s conceded (p = 0.003), and full length (p = 0.018).

Table 8 Means, Standard Deviations and P Values for all variables across both locations.

Variable Bangladesh West Indies Mean ± SD Mean ± SD P Value Dot Balls Bowled 34.10% ±17.90 30.6% ± 9.40 0.800 Wickets 4.86 ± 3.05 4.4 ± 2.23 0.568 Runs Conceded - 1 41.14% ± 18.62 41.93% ± 9.22 0.874 Runs Conceded – 2 5.29% ± 2.90 6.87% ± 2.77 0.160 Runs Conceded – 3 0.48% ± 0.60 0.33% ± 0.62 0.465 Runs Conceded – 4* 8.38% ± 3.68 5% ± 2 0.003 Runs Conceded – 5 0.05% ± 0.22 0.07% ± 0.26 0.924 Runs Conceded – 6 4.29% ± 2.88 5.73% ± 4.25 0.465 Line of Delivery – Off 45.24%± 19.06 44.33% ± 12.97 0.849 Line of Delivery – Middle 38.71% ± 17.10 38% ± 8.08 0.899 Line of Delivery – Leg 14.43% ± 6.77 13.47% ± 8.19 0.465 Length of Delivery –Full toss 1.43% ± 1.21 0.73% ± 0.96 0.083 Length of Delivery – Yorker 0.24% ± 0.44 0.33% ± 0.72 0.975 Length of Delivery – Full* 25.24% ± 10.69 16.87% ± 5.58 0.018 Length of Delivery – Good 48.91% ± 24.01 58.2% ± 16.45 0.180 Length of Delivery - Short 22.38% ± 13.56 19.47% ± 6.77 0.776 Bowler Type – LAS 22.48% ± 21.00 32.53% ± 16.12 0.077 Bowler Type – RAO 63.14% ± 21.15 60.13% ± 17.76 0.727 Bowler Type – RAL 26.90% ± 19.43 17.4% ± 15.27 0.133 Delivery Angle – Over 50.05% ± 26.16 51.67% ± 17.89 0.776 Delivery Angle - Around 45.62% ± 21.82 43.27% ± 21.24 0.505 Percentage of Boundaries 50.61% ± 10.96 47.41% ± 9.87 0.265 Strike Rate 17.95% ± 14.06 31.30% ± 29.96 0.127 *Variable with a significant difference (p < 0.05)

4.2 Line of Delivery The results for percentage of line bowled are shown in figure 2 above contrasting the two locations. A leg line delivery featured less in both locations. Spin bowlers favoured delivering the ball both on and off and middle line in both locations as percentages show only 1% difference. No significant difference was found between line of delivery and location.

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70

60

50

40

30

20

Percentage per game (%) game per Percentage 10

0 Off Middle Leg Line of Delivery

West Indies Bangladesh

Figure 2. The line of delivery between the two locations, West Indies (red) and Bangladesh (green) presented as a percentage per game.

4.3 Length of Delivery Figure 3 displays the percentages of length bowled. The most common length of delivery bowled for both locations was a good length, while yorkers and full tosses occurred infrequently. In the West Indies spin bowlers bowled a good length more often, but failed to be significant (p < 0.05). But bowling a full length was shown to be significant (p = 0.018) for both locations.

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90

80

West Indies Bangladesh

70

60

50

40

30 Percentagepergame (%)

20

10

0 Full toss Yorker Full Good Short Length of Delivery

Figure 3. The length of delivery between the two locations, West Indies (red) and Bangladesh (green) presented as a percentage per game.

4.4 Percentage of Runs Conceded In both locations, figure 4 shows that ones were scored more than any other run value. Threes and fives were scored infrequently. However, only scoring fours was found to be significantly different (p = 0.003).

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70

60

50 West Indies Bangladesh

40

30 Percentage per game (%) game per Percentage 20

10

0 0 1 2 3 4 5 6 Run Values

Figure 4. The percentage of runs conceded per game broken down by run values in both locations, West Indies (red) and Bangladesh (green).

4.5 Economy Rate Figure 5 gives the economy rates for spin bowler types for both locations. LAC were omitted from the graph as to few overs were bowled in Bangladesh. LAS achieved a lower economy rate in Bangladesh, whereas RAO economy rates increased higher. LAS were consistent over both locations.

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8.0

7.8

7.6

7.4 7.2 7.0 Bangladesh West Indies 6.8 6.6 Average economy rate rate economy Average 6.4 Figu 6.2 re 5. LAS RAO RAL The Type of Bowler aver age economy rate per tournament in both locations, West Indies (red) and Bangladesh (green).

4.6 Wickets Taken Figure 6 shows that in Bangladesh, spin bowlers marginally took more wickets on average per game, compared to in the West Indies. However no significant different was found (p < 0.05)

8 7.5

7

6.5 6

5.5 5

Wickets taken Wickets 4.5

4 3.5 3 West Indies Bangladesh Location Figu re 6. The average number of wickets taken in both locations, West Indies (red) and Bangladesh (green) per game.

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4.7 Dot Ball Percentage The results for dot ball percentage are given in figure 7. Results show that LAS had the biggest difference with 41% of balls being dot balls in Bangladesh, compared to 33% in West Indies. Nevertheless no significant difference was found (p < 0.05).

50.00

45.00 WEST INDIES BANGLADESH

40.00

35.00

30.00 Percentage of dot balls bowled per game (%) game per bowled balls dot of Percentage

25.00 LAS RAO RAL Type of Bowlers

Figure 7. The overall dot ball percentage for the types of spin bowlers

4.8 Types of Bowler RAO were clearly shown to bowl the most deliveries in figure 8, averaging over 60 balls per game for both locations. Nonetheless, no significant difference was found for all three types of bowlers (p < 0.05).

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90

West Indies 80

70 Bangladesh

60

50

40 Number of balls bowed per game per bowed balls of Number

30

20

10

0 LAS RAO RAL Types of Bowlers

Figure 8. The average number of balls bowled by the types of bowlers in both locations, West Indies (red) and Bangladesh (green).

4.9 Strike Rate Figure 9 shows that both LAS and RAL achieved a lower average strike rate per tournament in Bangladesh, compared to in the West Indies. Another key point is that RAL strike rate was the lowest in both Bangladesh 18% and West Indies 10%. Nevertheless, no significant difference was found (p < 0.05).

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35.00

30.00

25.00 WEST INDIES BANGLADESH 20.00

15.00

Average strike rate rate strike Average 10.00

5.00

0.00 LAS RAO RAL Type of Bowlers

Figure 9. The bowlers average strike rate in both location by bowler type

4.10 Percentage of Runs Conceded in Boundaries Figure 10 gives the percentage of runs conceded in boundaries for both locations. In Bangladesh, over 50% of runs conceded by bowlers were in boundaries. Whereas in the West Indies, less than 50% were boundaries,

65

60

55

50 boundaries (%) boundaries

45 Percentage of runs conceded in in conceded runs of Percentage

40 Bangladesh West Indies Location

Figure 10. The percentage of runs conceded in boundaries for both locations, West Indies (red) and Bangladesh (green).

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Chapter 5 Discussion

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5.0 Discussion

5.1 Line and Length

5.1.1 Length Spin bowlers appeared to adjust their line and length according to the location. A full length was found to have a significant difference (p = 0.0.18) in Bangladesh. The percentage of deliveries pitching on a full length in Bangladesh (25.7%) compared to a lower percentage (17.6%) in the West Indies. A rationale for the higher percentage of fuller deliveries could be due to the lack pace and bounce in Asian pitches, which make shorter deliveries easier for batsmen to score off (Woolmer and Noakes 2008). The increase of fuller deliveries in Bangladesh may also be down to teams strategies. In Bangladesh, two teams in particular (India and Pakistan) opted to use a spin bowler in the latter overs. Najdan et al. (2014) and Moore et al. (2012) identified that last 5 overs as being targeted by batsmen, and suggested that bowlers should aim to bowl a fuller length as it restricts the batsmens leverage under the ball.

Due to the highest percentage of deliveries being bowled on a good length (West Indies: 60.9% and Bangladesh: 49.7%), it can be suggested a good length delivery is the favoured length for a spin bowler. These results match the conclusion made by Najdan et al. (2014) and Moore et al. (2012) who stated that, bowlers should aim to ball a good length the majority of the time in England.

Both a full and good length were recognised by Najdan et al., (2014) in their discussion as the two lengths a bowler should aim for when trying to restrict runs and also take wickets. Woolmer and Noakes (2008) stated that spin bowlers aimed to bowl a fuller length to allow flight and guile to lure the batsmen out of their crease, especially if the pitch is unresponsive. English conditions were comparable to those in the West Indies, due to the pace in the pitches and favoured pace bowling rather than spinners (Woolmer and Noakes 2008).

However, it is worth noting across both Bangladesh and the West Indies, there was minimal differences between the accumulated percentages of both a good and full length delivery (West Indies: 78.5% and Bangladesh: 75.8%). Which therefore agreed with H1.

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In both locations, a yorker length delivery was bowled less frequently than any other length, Bangladesh (0.2%) and West Indies (0.3%). This may have been due to spin bowlers being utilised in the middle overs, rather than the last 6 overs where batsmen are looking to be more aggressive (Najdan et al., 2014). However due to teams in Bangladesh bowling a spinner in the latter over, it could be suggested that it was poor execution of the yorker rather than a fuller length was intended to be bowled.

Najdan et al., (2014) also suggested that a short length delivery was the least effective length for taking wickets in English conditions. However, the current results disagree with Najdan et al. (2014) as in both the West Indies, which has similar conditions to England, and Bangladesh a full length was the least effective length for taking wickets (Refer to Appendix G for analysis of all lines and lengths bowled). The percentage of short deliveries was higher in Bangladesh (22.7%) than in the West Indies (20.4%), but not significantly so. The batsmen may choose to advance down the wicket to negotiate any chance of turn on a dry pitch. This is because a dry pitch gives more assistance to a spin bowler compared to bouncier, grassier wickets (Woolmer and Noakes 2008).

5.1.2 Line There was no significant difference found between locations for the lines of delivery bowled. An off line was the most consistent line of delivery (Bangladesh: 46% and the West Indies: 46%). This corresponded with Moore et al. (2012) who found bowlers preferred to deliver the ball on an off line compared to middle and leg. The current study found that, In the West Indies bowling an off line took marginally more wickets, which agrees with Moore et al., (2012), but bowling a middle line had a lower strike rate suggesting that more wickets would be taken bowling a middle line per game (see Appendix G for strike rates of all lines and lengths). Moreover in Bangladesh, an off line was the most effective line to take the most wickets as well as, accumulating the lowest strike rate.

Moore et al., (2012) stated that a larger percentage of boundaries were scored when the ball was bowled on an off line, but this was due to the ball pitching on a short length which is easier for the batsmen to score runs, whereas the wicket taking deliveries on an off line were bowled on a good length. Which is what Najdan et al.

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(2014) suggested bowlers should aim to pitch the on a good length to achieve wickets.

Even though in Bangladesh, deliveries were bowled on a leg line only 1% more than in the West Indies. There was a clear strategy employed by RAO bowlers to bowl around the wicket to RH’s as (51.7%) of RAO bowlers delivered the ball around the wicket, compared to in the West Indies (26.7%). This agrees with Najdan et al., (2014) who found the same strategy was employed in English conditions, as they suggested that the strategy was used to create the angle of a left arm bowler coming over the wicket to a right handed batsmen. This tactic can be both a positive and a negative as it can restrict runs, due to cramping the batsmen for room or, can concede more wides which gives an extra ball and run to the batting team.

5.2 Dot Ball Percentage Dot ball percentage were not significantly different between locations. Even though no significant difference was found, LAS and RAO (41.6% and 37.0%) accumulated a higher dot ball percentage than in the West Indies (33.2% and 35.0%). These results would seem to back up Woolmer and Noakes (2008) who suggested that sub-continent conditions favoured spin bowlers. Only RAL had a higher PDB in the West Indies (36.3%) compared to their performances in Bangladesh (33.6%).

Douglas and Tam (2010) and Petersen et al. (2008b) found that dot balls bowled had a moderate effect size on winning outcomes. Also Petersen et al. (2008b) found that batsmen’s run rate was one of the top 3 for KPI’s. Therefore spin bowlers who have a higher PDB are more likely to be selected. These results therefore support Petersen’s et al. (2008b) statement that spin bowlers generally found it harder to reduce the batting teams run rate in the West Indies than in Asian conditions. However, contradicting Petersen et al. (2008b) RAL, who predominately are attacking bowlers aiming to take wickets, achieved a higher PDB than any other type of spin bowler in the West Indies suggesting that spin bowlers are able to contain a batting team’s run rate. Furthermore this disagrees with Petersen et al. (2008b) who suggested that teams should employ defensive spin bowlers in the middle overs to restrict run. Najdan et al. (2014) suggested that bowling dot balls would affect the batsmen’s run rate in a negative matter.

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5.3 Percentage of Runs Conceded in Boundaries There was no significant difference found for percentage of runs conceded in boundaries (PRB) per game. However, analysis conducted on PRB uncovered percentages which contradicted previous literature. Petersen et al. (2008a) stated that spin bowlers conceded more boundaries in the West Indies than in other locations due to the smaller grounds and fast bowling friendly conditions. The currents results showed that spin bowlers PRB was lower in the West Indies (48%) compared to in Bangladesh (52%). Moreover, suggesting that spin bowlers PRB is not affected by the location.

However, it could be speculated that the higher PRB was due to lower quality spinners performing in the tournament, as ‘part time’ bowlers were utilised more by team captains as pitches in Bangladesh favoured spin bowling (Petersen et al., 2008a). The West Indies employed 1 specialist spin bowler when they played at home, whereas when they played in Bangladesh they chose 2 specialist spinners and a part time spinner. A part time bowler is usually used as a last resort strategy if a batting team’s run rate is high to try and take a wicket.

In the West Indies, spin bowlers conceded a higher percentage of sixes than in Bangladesh. Suggesting that part of Petersen et al’s. (2008a) statement is accurate that a higher percentage of sixes are conceded on the smaller grounds. The percentage of fours conceded was significantly (p = 0.003) higher in Bangladesh (9.1%) than in the West Indies (5.7%) which lead to the overall higher PRB in Bangladesh.

5.4 Economy Rate Economy rate is highly regarded by both coaches and players as being an important statistic which all players must strive to improve (Najdan, 2011). Davis and Collins described T20 as ‘frenetic’ with the fast paced nature putting pressure on a batsmen to have a high scoring rate. Restricting a batsmen’s scoring rate has been known to contribute to taking wickets later in the same over or following overs (Petersen et al. 2008b). Woolmer and Noakes (2008) suggested that bowlers are either used to take wickets or restrict runs depending on their skill set. Petersen et al., (2008b) stated that spin bowlers should attempt to restrict runs as they operate mostly in the middle overs.

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In the West Indies, RAO bowlers were found to have the lowest economy rate (6.8), but marginally had the highest economy rate (7.3) in Bangladesh (excluding LAC bowlers who only bowled 3 overs in one location). On the other hand, RAL bowlers were found to be the most consistent bowlers in terms of economy rate, successfully achieving the lowest overall economy rate in Bangladesh (7.0) runs per over and (6.9) in the West Indies . Woolmer and Noakes (2008) emphasised that the RAL’s role in a team was to take wickets rather than containing runs, due to their variations and ability to spin the ball a larger degree than other types of bowlers. These results agree with Lemmer (2008) who found RAL to had the lowest economy rate (6.6) in the 2007 T20 World Cup in South Africa, which has similar conditions to the West Indies. In comparison to Manage et al. (2013) who analysed both spin and pace bowling in the 2012 T20 World Cup in Sri Lanka, and discovered that RAL achieved the 2nd lowest economy rate (6.47) behind LAS bowlers (5.48). This agreed with the current findings that LAS also achieved the lowest economy rate in Bangladesh (7.3).

On the other hand, RAO bowlers economy rates differed to those found in Lemmer (2008) and Manage et al. (2013). In South Africa Lemmer (2008) found that RAO had an economy rate (8.2) substantially higher than in West Indies (6.9). The pitch conditions for both these locations are categorised by Woolmer and Noakes (2008) as being similar due to fast bowling friendly advantages. However a reason why these results could contradict each other may be due to the different altitude levels in South Africa. Haake and Choppin (2010) suggested that every 1000 metres rise in altitude decreased atmospheric pressure, thus the density of the is 11% less in Johannesburg (South Africa) than in the West Indies. Therefore, as the air has lower density, the ball will travel further (Haake and Choppin 2010).

5.5 Strike Rate There was no significant difference found for strike rate per game for location, the strike rate achieved, for both locations in this study suggested how effective the bowlers performed. As it’s indicated by Petersen et al. (2008a) and Petersen et al. (2008) as being a KPI for bowlers. Furthermore, not only did RAL bowlers achieve the lowest economy rate in Bangladesh (7.0), RAL accumulated strike rate for both

39 locations was the lowest recorded (Bangladesh 17.7 and the West Indies (9.6). As mentioned before, Woolmer and Noakes (2008) stated that a RAL’s role in a team is to take wickets, these results support that statement. Figure 8 showed that RAL were employed the least in the West Indies but marginally used more in Bangladesh where they were used more than LAS. Captains can be reluctant to bowl RAL in a tight game, as RAL are prone to conceding a higher number of runs due to their attacking nature (Woolmer and Noakes 2008).

Even though no significant difference was found between strike rate and location, the bowlers strike rate in the West Indies (31.3% ± 30) was considerably higher than in Bangladesh (17.9% ± 14.1). Moreover from these results it can be suggested that due to the bouncier and grassier nature of the pitches in the West Indies (Woolmer and Noakes 2008), spin bowlers are at a disadvantage compared to in Bangladesh where the pitches are dustier and softer, offering greater help to the spin bowler.

In comparison to results from studies by Lemmer (2008) and Manage et al. (2013), RAL differed substantially achieving the lowest strike rate in Bangladesh (17.7), but in Sri Lanka (Manage et al. 2013), their strike rate (23.5) was higher than in the locations studied by Lemmer (2008), and the current study. However, Lemmer’s (2008) study in South Africa provided results (21 and 15.3) which were similar to those found in the current study for West Indies for both RAL and RAO bowlers (20.7 and 17.7), suggesting that spin bowlers perform similarly in conditions more suited to pace bowling. RAO strike rate per game in Bangladesh (26.0) was dissimilar to that found in Sri Lanka (16.3). Which is surprising given the similarities of the pitch conditions. However, seven out of ten teams who participated in Bangladesh adopted a strategy of bowling the first over of the innings with a spin bowler. The strategy was implemented to contain runs as opening batsmen are used to facing pace bowling in the early overs. Petersen et al. (2008b) explained that spin bowlers take the majority of their wickets after the first 6 overs when the fielding restrictions have been completed. But strike rate per game (17.9%) in Bangladesh would suggest the use of a spin bowler in the early overs does not decrease the chance of taking a wicket.

LAS strike rate (19.8) was lower in Bangladesh, even though they were utilised more in the West Indies (23.6). Najdan et al. (2014) suggested that teams should employ a

40 greater number of left arm bowlers because the angle of delivery and spin direction is similar to that of RAL bowlers who have been described as wicket taking bowlers (Woolmer and Noakes 2008). At the conclusion of both tournaments, LAS bowled 3.1 overs per match in Bangladesh compared to 4.6 overs per match in the West Indies. These results may be due to teams changing selection because of uncontrollable factors: players retiring or being injured prior to the tournament.

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Chapter 6 Conclusion

42

6.0 Conclusion

6.1 Summary of findings In conclusion, minor significant differences were found between locations: fours conceded (p = 0.003) and full length deliveries (p = 0.018). However no significant differences were found for KPIs identified in previous research. Bowlers in Bangladesh were found to have taken a higher number of wickets per game (Bangladesh: 4.9 and West Indies: 4.4), but conceded a higher percentage of boundaries (Bangladesh: 48.3% and West Indies: 52.6%). The higher PRB in Bangladesh contradicted previous research by Petersen et al. (2008a) who stated that in the West Indies spin bowlers conceded a higher percentage of runs in boundaries due to the small grounds, pace bowling friendly conditions.

Bowling a full length was the least effective wicket taking length which disagreed with Najdan et al. (2014) who found that bowling a full length gave a greater success of taking wickets in English conditions which, as Woolmer and Noakes (2008) alluded to as being similar to those found in the West Indies. Also the line of delivery was found to be relatively consistent over both locations.

Literature suggested that RAL conceded a higher percentage of runs than the other types of spin bowlers, due to their attacking nature and role in the team to focus on wickets. However, the current study showed that RAL bowlers were the most consistent in term of economy rate for both locations.

Even though strike rate was not found to be significantly different, the results showed strike rates per game in the West Indies to be higher, suggesting that spin bowlers find it harder to take wickets in those conditions compared to in Bangladesh, where conditions are friendly towards spin bowling.

6.2 Practical Implications From this exploration into whether location effected spin bowlers performance it is recommended that:  Spin bowlers should aim to bowl a good length for the majority of the time in all locations, as it has wicket taking potential and contains the scoring rate.  RAL should be utilised more by teams, as shown they have wicket taking ability and can contain runs.

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6.3 Future Recommendations

 A study should be conducted to analyse spin bowlers performances in different stages of the game across different locations to see whether their effectiveness varies.  A study should be conducted which focuses on batting styles against spin bowlers in different locations to see if the location changes batsmen’s strategy.  A study analysing location effects on spin bowlers performances in ODI cricket to discover whether having more allocated overs changes the performance.  The same methodology should be applied to compare pace bowling and spin bowling performances to winning and losing teams in different locations.  A study which compares teams performances that use 2 quality spinners against teams that use 1 in terms of winning and losing.

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References

45

References

Altman, D.G. (1991). Practical Statistics for Medical Research. London: Chapman & Hall.

Bartlett, R.M., Stockill, N.P., Elliott, B.C. and Burnett, A.F. (1996). The biomechanics of fast

bowling in men’s cricket: a review. Journal of Sports Sciences, 14 (5), 403-424.

Batterham, A. & Hopkins, W.G. (2006). ‘Making meaningful inferences about magnitudes’. International Journal of Sports Physiology and Performance, 1(1), 50-57.

Bawden, M. and Maynard, I. (2001). Towards an understanding of the personal experience of the “yips” in cricketers. Journal of Sports Sciences, 19 (12), 937-953.

Bull, S., Shambrook, C., James, W. and Brooks, J. (2005). Towards an understanding of mental toughness in elite english cricketers. Journal of Applied Sport Psychology, 17 (3), 209-227.

BaseviI, T. & Binoy, G. (2007). The world’s best Twenty20 players [http://contentrsa.

cricinfo.com/columns/content/story/311962.html]. Accessed on January 2015.

Clarke, S.R. (1988). ‘Dynamic programming in one-day cricket – optimal scoring

Rates’. The Journal of the Operational Research Society, 39(4), 331-337.

De Silva, B. M., & Swartz, T. B. (1997). ‘Winning the coin toss and the home team

advantage in one-day international cricket matches’. New Zealand Statistician,

32, 16-22.

Douglas, J.M., & Tam, N. (2010). ‘Analysis of team performances at the ICC world

Twenty20 cup 2009’. International Journal of Performance Analysis in Sport, 10(1),

pp. 45-53.

46

Duffield, R., & Drinkwater, E.J. (2008). ‘Time-motion analysis of test and one-day international cricket centuries’. Journal of Sports Sciences, 26(5), 457-464.

Elliott, B.C. (2000). Back injuries and the fast bowler in cricket. Journal of Sports Sciences, 18 (12), 983-991.

Glazier, P.S. and Wheat, J.S. (2014). An integrated approach to the biomechanics and motor control of cricket fast bowling techniques. Sports Medicine, 44, 25-36.

Gupta, A. (2011). The IPL and the Indian domination of global cricket. Sport in Society: Cultures, Commerce, Media, Politics. 14 (10), P1316-1325.

Haake, S., Choppin, S. (2010) 'The altitude factor', New Scientist, 206(2763), pp. 35-37.

Holmes, M, Talbot, D (2011). Twenty20 Cricket: How to Play, Coach and Win. London: Bloomsbury Publishing. pp. 1-5.

Hopkins, W.G. (2004). ‘How to interpret changes in an athletic performance test’. Sportscience, 8, 1-7. Hughes, M. & Bell, K. (1998). ‘Performance profiling in cricket’, cited in Notational

Analysis of Sport (edited by M. Hughes and F. Tavares), pp. 176-183. Porto: Faculty

of Sport Sciences, University of Porto, Portugal. Journal of Sports Sciences, 19, 107- 115.

ICC cricket rule changes - free hit or no free hit (2007) Available at: http://www.sheetudeep.com/blog/sports/icc-cricket-rule-changes-free-hit-for-no- ball/#.VP8gHfmsVIE (Accessed: 22 November 2014).

ICC World Twenty20, 2007/08 /Records (2007) Available at:http://stats.espncricinfo.com/twenty20wc/engine/records/bowling/best_career_eco nomy_rate.html?id=3115;type=tournament (Accessed: 10 October 2014).

Justham, L.M., West, A.A., & Cork, A.E.J. (2008). ‘An analysis of the differences in

bowling technique for elite players during international matches’. In F.K. Fuss, A.

Subic & S. Ujihashi (Eds.), The impact of technology in sport II (pp. 331-336).

London, United Kingdom: Taylor and Francis.

Kimber, A. C. and Hansford, A. R., A statistical analysis of batting in cricket.

47

Journal of the Royal Statistical Society: Series A (Statistics in Society), 1993, 156(3), 443–455.

Kitchen, P. (2008). Twenty20 and English Domestic Cricket. International Cases in the Business of Sport. London: Elsevier.

Lemmer, H.H. (2002). The combined bowling rate as a measure of bowling performance in cricket. South African Journal for Research in Sport, Physical Education and Recreation, 24(2): pp. 37-44. Lemmer, H.H. (2008). ‘An analysis of players’ performances in the first cricket

twenty20 world cup series’. South African Journal for Research Sport, Physical

Education and Recreation, 30(2), 71-77.

Lewis, T. (1995). MCC masterclass: the new MCC coaching book. London: Weidenfeld & Nicolson.

Manage, A.B., Scariano, S.M., Hallum, C.R. (2013) 'Performance Analysis of T20-World Cup Cricket 2012', Sri Lankan Journal of Applied Statistics, 14(1), pp. 1-12.

Mani, E. (2009). A strong sport growing stronger: a perspective on the growth, development and future of international cricket. Sport in Society, 12, pp. 681-693.

Mitra, S. (2010). The IPL: India’s foray into world sports business. Sport in Society, 13, 1314–1333.

Morley, B., & Thomas, D. (2004). ‘An investigation of home advantage and other

factors affecting outcomes in English one-day cricket matches’. Journal of Sports

Sciences, 23(3), 261-268.

Moore, A., Turner, D.J., & Johnstone, J.A. (2012). ‘A preliminary analysis of team

performance in English first-class twenty-twenty (T20) cricket’. International Journal of Performance Analysis in Sport, 12, 188-207.

Najdan, M.J., Robins, M.T., Glazier, P.S. (2014) 'Determinants of success in English domestic Twenty20 cricket', International Journal of Performance Analysis in Sport, 14(1), pp. 276-295.

48

Noakes, T.D. and Durandt, J.J. (2000). Physiological requirements of cricket. Journal of Sports Sciences, 18 (12), 919-929.

Petersen, C., Pyne, D.B., Portus, M.R., & Dawson, B. (2008a). ‘Analysis of Twenty/20 cricket performance during the 2008 Indian Premier League.’. International Journal of Performance Analysis in Sport, 8(3), pp. 63-69 Petersen, C., Pyne D.B., Portus, M.R., Cordy, J. & Dawson, B. (2008b). ‘Analysis of performance at the 2007 Cricket World Cup’. International Journal of Performance Analysis in Sport, 8(1), pp. 1-8. Petersen, C., Pyne, D.B., Portus, M.R., & Dawson, B. (2009). ‘Quantifying positional

movement patterns in twenty20 cricket’. International Journal of Performance Analysis of Sport, 9, 165-170.

Petersen, C., Pyne, D., Portus, M., & Kellett, A. (2010). ‘Movement patterns in cricket

vary by both position and game format’. Journal of Sports Sciences, 28(1), 45-52.

Preston, I. & Thomas, J. (2000). ‘Batting strategy in limited overs cricket’. The Statistician, 49, 95-106 Rudkin, S.T., & O’Donoghue, P.G. (2008). ‘Time-motion analysis of first-class cricket

Fielding’. Journal of Science and Medicine in Sport, 11, 604-607.

Saikia, H. and Bhattacharjee, D. (2012). A Fairer Metric for the Performance Measurement of Bowlers in Cricket. Gurukul Business Review, 8, pp. 1-5.

Sankaran, S. (2012) 'Comparing Pay versus Performance of IPL Bowlers: An application of Cluster Analysis', International Journal of Performance Analysis in Sport , 14(1), pp. 174-187.

Staden, P. J. (2009). Comparison of cricketers’ bowling and batting performances using graphical displays. Current Science, 96, pp. 764-766. Trevillion, P. & Holder, J. (2009).You are the Umpire. The ultimate guide to the laws of cricket. London: Observer.

Tucker, W. (2005). Game location effects in professional soccer: a case study. International Journal of Performance Analysis in Sport, 5 (2), 23-35.

Wales Cricket Board (2009). Cricket. 5th ed. London: A&C black publishers LTD. 10-12.

49

Wickramasinghe, R.P. (2014) 'Bowlers’ performances in 2013 Champions Trophy', Annals of Applied Sport Science, 2(1), pp. 1-10

Woolmer, B., & Noakes, T. (2008). Bob Woolmer’s Art and Science of Cricket. London: New Holland Publishers Ltd.

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Appendix A Example of Initial Spreadsheet

51

52

Appendix B Example of Ball-by-ball Commentary Used

53

54

Appendix C Kappa Table

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Table 9. Kappa results table for length of delivery inter-reliability

Full toss Yorker Full Good Short Total

Full toss 5 5 Yorker 0 1 1 Full 62 62

Good 1 71 1 73 Short 1 31 32 Total 5 0 64 72 32 173

P0 0.976879

PC 0.343246

Kappa 0.964794

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Appendix D Kappa Table

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Table 10. Kappa results table for length of delivery intra-reliability

Full toss Yorker Full Good Short Total Full toss 5 5

Yorker 0 1 1 Full 59 2 61 Good 4 69 2 75

Short 1 30 31 Total 5 0 64 72 32 173

P0 0.942197

PC 0.344849

Kappa 0.911771

Appendix E

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Kappa Table

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Table 11. Kappa results table for line of delivery inter-reliability

Off Middle Leg Total

Off 85 3 88

Middle 1 53 3 57

Leg 2 26 28

Total 86 58 29 173

P0 0.947977

PC 0.390457

Kappa 0.914652

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Appendix F Kappa Table

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Table 12. Kappa results table for line of delivery inter-reliability

Off Middle Leg Total

Off 84 1 85

Middle 2 55 57

Leg 2 29 31

Total 86 58 29 173

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P0 0.971098

PC 0.384744

Kappa 0.953025

Appendix G Line and Length Spreadsheet

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