DEVELOPMENT OF PREDICTION MODEL FOR SUPPORT IN DECISION-MAKING PROCESS IN FOOTBALL ACADEMIES – LITERATURE REVIEW

Abstract

Talent development process in football is considered as a process of providing the optimal environment for identifying and realising the maximum ability of young athletes. A multidimensional approach to analysing factors that influence junior to senior transition can produce much better support for coaches and management to distinguish elite and non-elite players. With development of digital technologies and artificial intelligence, more clubs are able to perform detailed analysis of their youth development programme. In this paper, we focus on identfying good practices in connecting digital technologies with talent development process in sports. Based on established methods and techniques used by experts in a field of data mining within sports, we want to select an appropriate methodology and approach in discovering knowledge from the data for the doctoral dissertation. Literature review presents a first step in a hollistic process of identifying key attributes in junior to senior transition. The findings suggest that the comprehensive approach towards analysing data in sports, results in better identification of skills and attributes of young athletes. Consequently, data mining in sports is becoming more and more important in assessing important characteristics on every level within talent development process.