Talent development programmes: a retrospective analysis of the age and support services for talented athletes in 15 nations

ABSTRACT

Research question: Due to increasing competition, national governing bodies (NGBs) are put under pressure to deliver collective success and develop talent programmes for their athletes at an increasingly young age. This paper seeks to make a contribution to the talent development literature from an organisational perspective. It addresses the following research question: How and at what age have athletes received support services as upcoming talent from their sport clubs and NGBs?

Research methods: A total of 2041 elite athletes from 15 nations and 37 different sports were surveyed. Analysis of variance (ANCOVA and MANCOVA) was used to examine the data and identify differences between sports, countries and athletes’ sporting achievement levels.

Results and findings: The data revealed that athletes received club or NGB support at a relatively late age. This differed by gender, by sport and between sports in which athletes specialise at younger or older ages. Athletes with higher achievement levels (e.g. in the world’s top eight) were slightly younger when they received support services compared with lower level athletes (e.g. national level); however, effect sizes are small. Most elite athletes received a variety of support services and only slight differences were found according to athletes’ achievement levels.

Implications: The relevance of these findings relates to the role that sports clubs (can) play in the total development of an athletic career. This paper has practical implications for the management of talent development by NGBs and clubs, national sport associations and for coach education.

KEYWORDS:

• Talent development
• elite sport policies
• athlete development pathways
• sport clubs
• high-performance management

Acknowledgement

The authors would like to thank the dedicated research partners involved in the SPLISS-2.0 study, among others (sorted by country): Hans Westerbeek and Camilla Brockett (Australia, Victoria University); Stephanie De Croock and Jasper Truyens (Belgium (Fla), Vrije Universiteit Brussel) Mathieu Winand (Stirling University) and Thierry Zintz (Belgium (Wal), Université catholique de Louvain); Maria Tereza Silveira Bohme & team (Brazil, University of São Paulo); David Legg & team (Canada, Mount Royal University); Henrik Brandt, Rasmus K. Storm, Lau Tofft and Nynne Mortensen (Denmark, Danish Institute for Sports Studies & University of Southern Denmark); Eerik Hanni (Estonia, National Audit Office of Estonia); Patrick Mignon and Emanuel Lelore (France, Institut National du Sport et de l'Éducation Physique-INSEP); Jari Lämsä, Jarmo Mäkinen and Mikko Kärmeniemi (Finland, KIHU - Research institute for Olympic Sports); Yoshiyuki Mano, Hiroaki Funahashi and team (Japan, Waseda University); Maarten van Bottenburg and Bake Dijk (the Netherlands, Utrecht University); Simon Shibli (Sheffield Hallam University) and Paul Donnelly (Sport Northern Ireland, UK); Pedro Guedes De Carvalho and Rui Canelas (Portugal, Beira Interior University); Anna Vilanova, Eduard Inglés and team (Spain, National Institute of Physical Education of Catalonia, INEFC); Eunha Koh (South Korea, Korea Institute of Sport Science); Hippolyt Kempf, Marco Stopper & Andreas, Christophe Weber (Switzerland, Swiss Federal Institute of Sport Magglingen SFISM). The author would like to thank the policy institutions that funded the national data collection (see De Bosscher et al., 2015, pp. 24–29 for an overview).

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. In the whole SPLISS study, talent identification and development was one of the nine policy areas (Pillar 4) under consideration. This pillar is concerned with the national strategies towards the identification of young talented athletes and how talent development is facilitated in the different nations. It analyses 12 critical success factors, including 169 sub-factors, related to the planning and coordination of talent identification systems, talent development planning, multidimensional support services and dual career support for the combination of elite sport and study. Data collection for this pillar was not only based on surveys with athletes, coaches and performance directors, but also on an inventory completed by the local researchers on each critical success factor, by means of interviews and desk research.

2. Note that differences in the different variables between the top three and the top eight were only small (not significant) and these two were merged in order to compare significant differences with more equal sample sizes.

3. A one-way independent ANOVA revealed significant differences according to the 37 sports disciplines in all three measures: (a) the age that athletes first started their sporting career (F(36,2004)= 35.2, p < 0.001, ω = 0.613), (b) received club support (F(36,2004) = 14.5, p < 0.001, ω = 0.439) and (c) received NGB support (F(36,2004) = 12.1, p < 0.001, ω = 0.405). Note that the overall ANOVA with sport as predictor leads to large effect sizes (above the 0.14 threshold for large effects (Field, 2013)).

4. In addition, endurance, aerobic capacity and muscular-strength abilities are sensitive to training only at older ages as the body and skeleton are not ready to develop these skills (Purcell, 2005; Zahradník & Korvas, 2012).

Additional information

Funding

The coordination of the SPLISS research was funded by the Vrije Universiteit Brussel (Free University of Brussels). SPLISS has largely depended on institutional investments to ensure the national coordination of this large-scale project. The SPLISS consortium partners did not seek any financial contribution from the participating nations as a return for the massive coordinating work. All such costs were met by the Vrije Universiteit Brussel and supported by the consortium members and engaged researchers from the partner countries.