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Complexity
Volume 2018, Article ID 9280154, 13 pages
https://doi.org/10.1155/2018/9280154
Research Article

The Development of Talent in Sports: A Dynamic Network Approach

Department of Psychology, University of Groningen, 9712 TS Groningen, Netherlands

Correspondence should be addressed to Ruud J. R. Den Hartigh; ln.gur@hgitrah.ned.r.j

Received 1 March 2018; Accepted 8 July 2018; Published 29 August 2018

Academic Editor: Jordi Duch

Copyright © 2018 Ruud J. R. Den Hartigh et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Understanding the development of talent has been a major challenge across the arts, education, and particularly sports. Here, we show that a dynamic network model predicts typical individual developmental patterns, which for a few athletes result in exceptional achievements. We first validated the model on individual trajectories of famous athletes (Roger Federer, Serena Williams, Sidney Crosby, and Lionel Messi). Second, we fitted the model on athletic achievements across sports, geographical scale, and gender. We show that the model provides good predictions for the distributions of grand slam victories in tennis (male players, ; female players, ), major wins in golf (male players, ; female players, ), and goals scored in the NHL (ice hockey, ) and in FC Barcelona (soccer, ). The dynamic network model offers a new avenue toward understanding talent development in sports and other achievement domains.