Identifying Talent Paula Jardine CSC- Calgary Talent Identification and Systems Integration Manager He/She’s a natural • Gifted & Talented • Wasted talent • “God-given gifts” • Parable of the Talents (Matthew 25: 14-30) Jonah Ziff The Champion Model • Assumes an underlying genetic basis to performance • Identify attributes associated with Champions in a given sport and test for those that are untrainable – e.g. you can’t train them tall • Systematic screening of children and adolescents using tests of anthropometrical and physiological attributes in order to identify those with potential for success in a designated sport • Previous involvement in the sport is not a pre-requisite for identification (otherwise not T-id – Talent Selection) Talent Selection in the GDR • “The effectiveness of sport selection in the GDR does not result from possession of a set of infallible (prognostic) indicators but from an extended process of conducting measurements and observations at subsequent stages of sports training. These measurements conducted over several years reveal the direction and pace of an individual’s development. As a consequence the adjustments are made regarding the most suitable sport and training methods.” Dr Henryk Sozanski 1977 GDR Talent Selection System Early selection for Preliminary screening gymnastics, diving, 250,000 children tested twice annually By 1973 funding for the figure skating training centres = 16 million marks / yr Basic Preparation Training between 50,000 – 70,000 selected to train regularly Talent Selection Phase I During the 1980s at the 9,000 training centers (500-700 in each) a total of 89,440 Children selected for sport (age 10, 11, 12 – 270 training hours per year) schools at age 12 and 13 via athletes testing participated in the GDR sports Talent Selection Phase II system Build Up Training Streaming towards speed, 25 sports schools power or endurance – In total between 10,000 athletes redirection to other sports 30-40,000 (age 13, 14, 15 – training hours 550, 650, 750) athletes attended sport schools Talent Selection Phase III Connecting Training Late selection / Specialization phase specialisation Assignment to specialist sport (age 16, 17, 18 - 8,000 in Jr national programs) The Australian Legacy • One off testing for ‘untrainable’ attributes or those thought to have high heritability (e.g. VO2max) • Gagné’s Differentiated Model of Giftedness and Talent asserts that the origins of talent begin with innate natural gifts or abilities that are transformed into expert performances via learning and practising throughout development. • One cannot be talented without first being gifted • 10% of population have spontaneously occurring gifts • DMGT model also says that the easier or faster the learning process, the greater the natural abilities Continuum of Sports Demands Nature (Genetics) Swimming, Cycling, Rowing, Canoeing, Athletics, Triathlon, Speed Skating, x-country skiing Demand: cyclical, repetitive: physical / Gymnastics, Boxing, Judo physiological Demand: Individual sports: Racket Sports Physical / physiological / skill (Badminton, Tennis, Squash) Team ball sports Demand: Physical, physiological, skill and decision making Shooting, Archery Demand: skill Nurture (Environment) Adapted from Farrow British Cycling Olympic Academy • Started in 2004 – initial intake 6 athletes including Ed Clancy and Mark Cavendish • 2005 – Geraint Thomas, Andy Tennant, Ben Swift, Lizzie Armistead • Other successful products include: Jason Kenny, Dani King, Laura Trott, Emma Trott, Jess Varnish, Peter Kenaugh, and others • Now take 25 athletes per year British Cycling Olympic Academy Cavendish on the Academy “It was nice after 15 months,” Cavendish recalls. “I didn’t go on the road or track to the junior worlds and then there were a couple of people in the Academy, including Rod Ellingworth, who saw something I had. “That was what the Academy was about, it was more than lab tests and a physical thing. It was racing, it was learning to be a bike rider, that’s what he saw and it turned me from that into a world champion within 15 months. That was the process it was, it wasn’t just getting stronger it was learning everything about bike racing and living as a bike rider.” Evidence Based Talent Identification Tests must be highly diagnostic to improve selection decisions T-ID focused here: Tests of athletic performance that provide indicators of general fitness and trainability by selecting those with the highest levels of fitness in tested movements Athletes fast – tracked into high performance environments Gagné / Gulbin and the 10 year rule Table 2. Rate of development of high performance athletes, including ‘quick’ and ‘slow’ developers. Start => Start => Junior national level => Senior national level Junior national level Senior national level (n=256) (n=382) (n=179) Number of years Mean (SD) 7.5 (4.1) 5.7 (3.2) 2.7 (2.1) Quick; Slow; Quick; Slow; Quick; Slow; ≤ 4 years ≥ 10 years (n=78) ≤ 3 years ≥ 8 years ≤ 1 years (n=64) ≥ 4 years (n=61) (n=72) (n=113) (n=117) Type of sport: % Individual 69% 44% ** 58% 28% *** 56% 51% (vs.team) Age when began main sport 17.1 (4.5) 7.9 (2.5)*** 13.6 (3.1) 7.2 (1.6)*** 11.7 (3.3) 9.8 (3.1)** Number of sports before starting with 3.3 (1.6) 0.9 (1.3)*** 3.1 (1.9) 0.8 (1.3)*** 2.2 (1.7) 1.5 (1.5)** main sport Number of sports after starting main 0.2 (0.5) 2.4 (1.8)*** 0.4 (0.8) 2.1 (1.7)*** 0.9 (1.5) 1.6 (1.6)* sport Significant differences: * p<.05; ** p<.01; *** p<.001. “It can be concluded that the ‘10-year rule’ is not applicable to sports development. 69% of novice athletes develop into senior elite representatives in <10 years. Furthermore, it is possible to transfer previous sporting experiences at a late age in order to make a quick transition to elite level” Oldenziel, Gagne, Gulbin (2002) Nagorni 1978 • Diversified development: vast majority of best Soviet athletes had a strong multi-lateral foundation • Started to practice sport at 7-8 years • Specialised programmes began at age 15 -17 • Best performances came after 5 – 8 years of specialisation • Athletes who specialised younger – best performances at jr age level • Most top class Soviet international athletes were never jr champions or held a jr national record Jennifer Suhr In 2006 won her first World Athletics Finals medal (bronze) (Training age 2) Her season’s best jump in 2006 was 93% of World Record PB set in 2008 was 98% of World Record (Training age 4) Won silver medal in Beijing (TA 4) and gold medal in London (TA 8) College all-star basketball player, NY state high school pentathlon champion Factors effecting athlete development • Core Knowledge --The more you know the more readily you can learn ( Bompa 1994, Matveyev 1981) • An athlete who is pre-elite in one sport has a higher probability of becoming an elite athlete in another • “There is no question that early specialisation, especially before puberty, has little benefit for later success” Magill (1988) • Expert performance in sports where peak performance occurs after the age of 20 has been achieved with 3,000 to 4,000 hours of specific training (Cote, Baker, Abernethy) • The number of hours of deliberate practice needed to acquire expertise is inversely related to the number of other sport activities undertaken during the sampling years prior to specialisation (M=3,939 hours) (Abernethy et al 2003) Kim Crow • Jr International hurdler – silver at World Youth Championships in 2001 • Finished 2nd behind 2x world champion Jana Pitman in 400mh at Australian National Championships • Started rowing erg as part of rehab programme in 2004 • Switched to rowing in 2005 at the Melbourne University (age 20) • Coaches used to have her row in the bow seat of the men’s 8 at Melbourne Uni • 2006 – World Championship Bronze medal, women’s 8 • 2007 – 4th World Championships 2- • 2008 – 10th Olympic Games • London 2012 – Silver medal – 2x • London 2012 – bronze medal 1x Practice histories of elite players sampling specialising investing (Côté) (Bompa) initiation athletic formation specialisation high performance The Operating System Rate of Improvement • Experimental studies in the USSR in the 1970s found little predictive value on the basis of a single series of tests • highlighted the importance of the rate of improvement • Youngsters who made fast progress during the first 18 months of training were most successful later. • Athletes, whose initial performance levels were only average but who improved at a rapid rate, often passed those with excellent initial levels. • It is generally considered that the improvement rate in speed and power events is good when it reaches 10.5 to 12.5% at the end of 18 months. Long Track Speed Skating - Rate of Improvement 1000m seasons bests by age 68 70 72 WR 74 R² = 0.8261 Nesbitt Schussler 76 Remple time in seconds Poly. (Nesbitt) 78 80 82 age 18 19 20 21 22 23 24 25 26 27 Nesbitt – 1.5 years from specialisation to National team selection / Season’s best at age 20 was 97% of World Record time 3 years to first Olympic medal / 8 years to World Record Talent ID – What can you do? So what can you do? • Late specialisation / Early diversification • Performance across a number of different sports • Testing - Top performances on tests of physical abilities are more correlative than causative and can be misleading • General preparation: improve movement patterns to reduce injury risk & enhance long term ability to acquire advanced skills - this requires a focus on individual needs not on short term performance gains • Rate of improvement • Quick developers need suitably challenging training An East Bloc view on talent • “It is a popularly held belief that genetic or geographic origin brings with it athletic advantage. This belief sees nature as more important than nurture in determining performance potential.” … “To acknowledge the dominance of athletes on genetic and geographic grounds a priori and to take it for granted, is a non- scientific and counter-productive point of view.