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Abstract Details

Abstract Title

Isports: A Web-Oriented Expert System for Talent Identification in Soccer

Abstract Theme

Technology in sports

Type Presentation

Oral presentation

Abstract Authors

Francisco Louzada - University of São Paulo (Statistics) - BR
Presenter Alexandre Cristovão Maiorano - Federal University of São Carlos (Statistics) - BR
Anderson Ara - University of São Paulo (Statistics) - BR

Presentation Details

Room: Marte        Date: 2 September        Time: 10:20:00        Presenter: Alexandre Maiorano

Abstract Resume

Background: 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. In the most clubs, new 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.

Methods: This work proposes the creation of performance indicators based on multivariate statistical analysis using field tests that reflect the physical and technical aptitude of an
athlete. Technical ability are measured by Mor and Christian pass test, 5 cones dribbling test and a kick after pass test and the physical capacity are evaluated by 1000 meters on a track test, cyclic
speed of 20 meters test and the anaerobic power test (RAST). 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.

Results: 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.

Conclusions: 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, increasing significantly the knowledge of the athletes in training phase at any school, city or region. Since the system is available on a cloud structure, it is not necessary
to install it on local use, requiring only a connection to the Internet indicating that iSports can be used in large scale and accessed from different locations and different type of devices. To the
best of our knowledge, this is the first we based system that aims at the discovery, identification and development of talents in soccer.

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