iSports: A web-oriented expert system for talent identification in soccer

Nowadays soccer is the most practiced sport in the world and moves a multimillionaire market. Therefore, a club that is able to recruit and develop talented players to theirs fullest potential has a lot of advantages and economic benefits. However, in most clubs the players are selected through scouts and coaches recommendation, with predictive success based mostly on intuition than other objective criteria. In addition, it is known that talent development and identification is a multifactorial process involving many characteristics. To this end, this paper proposes the creation of performance indicators based on multivariate statistical analysis. Usual principal components and factor analysis are performed to construct physical, technical and general score and copula modeling is proposed to create the consistency index, which generalizes the Z score method. With these indicators, a web-oriented expert system for analyzing sport data in real time via R software is proposed as a powerful tool for talent identification in soccer. This system, the so called iSports, allows the monitoring and continuous comparison of athletes in a simple and efficient way, taking into account essentials aspects, as well as identifying candidate talented that have above the average performance, that is, who stand out from the studied population of soccer players. In order to promote and popularize the access of information and the statistical science applied in the sports context, the iSports system can be used in any training center of the country, impacting the increase of knowledge of the athletes in training phase at any school, city or region. © 2015 Elsevier Ltd. All rights reserved.