Title |
Expert Performance in Sport and the Dynamics of Talent Development
|
---|---|
Published in |
Sports Medicine, October 2012
|
DOI | 10.2165/11319430-000000000-00000 |
Pubmed ID | |
Authors |
Elissa Phillips, Keith Davids, Ian Renshaw, Marc Portus |
Abstract |
Research on expertise, talent identification and development has tended to be mono-disciplinary, typically adopting genocentric or environmentalist positions, with an overriding focus on operational issues. In this paper, the validity of dualist positions on sport expertise is evaluated. It is argued that, to advance understanding of expertise and talent development, a shift towards a multidisciplinary and integrative science focus is necessary, along with the development of a comprehensive multidisciplinary theoretical rationale. Here we elucidate dynamical systems theory as a multidisciplinary theoretical rationale for capturing how multiple interacting constraints can shape the development of expert performers. This approach suggests that talent development programmes should eschew the notion of common optimal performance models, emphasize the individual nature of pathways to expertise, and identify the range of interacting constraints that impinge on performance potential of individual athletes, rather than evaluating current performance on physical tests referenced to group norms. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 20% |
United States | 2 | 13% |
Canada | 1 | 7% |
Australia | 1 | 7% |
South Africa | 1 | 7% |
Unknown | 7 | 47% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 9 | 60% |
Scientists | 5 | 33% |
Practitioners (doctors, other healthcare professionals) | 1 | 7% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | <1% |
Canada | 3 | <1% |
Belgium | 2 | <1% |
United States | 2 | <1% |
Portugal | 2 | <1% |
Brazil | 1 | <1% |
South Africa | 1 | <1% |
Norway | 1 | <1% |
New Zealand | 1 | <1% |
Other | 6 | 1% |
Unknown | 517 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 113 | 21% |
Student > Ph. D. Student | 106 | 20% |
Student > Bachelor | 67 | 12% |
Researcher | 41 | 8% |
Lecturer | 30 | 6% |
Other | 112 | 21% |
Unknown | 70 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Sports and Recreations | 316 | 59% |
Psychology | 49 | 9% |
Social Sciences | 32 | 6% |
Medicine and Dentistry | 17 | 3% |
Agricultural and Biological Sciences | 9 | 2% |
Other | 39 | 7% |
Unknown | 77 | 14% |