首页|Using multi-criteria decision-making and machine learning for football player selection and performance prediction:a systematic review
Using multi-criteria decision-making and machine learning for football player selection and performance prediction:a systematic review
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
万方数据
Evaluating and selecting players to suit football clubs and decision-makers(coaches,managers,technical,and medical staff)is a difficult process from a managerial-financial and sporting perspective.Football is a highly competitive sport where sponsors and fans are attracted by success.The most successful players,based on their characteristics(criteria and sub-criteria),can influence the outcome of a football game at any given time.Consequently,the D-day of selection should employ a more appropriate approach to human resource manage-ment.To effectively address this issue,a detailed study and analysis of the available literature are needed to assist practitioners and professionals in making decisions about football player selection and hiring.Peer-reviewed journals were selected for collecting published papers between 2018 and 2023.A total of 66 relevant articles(journal articles,conference articles,book sections,and review articles)were selected for evaluation and analysis.The purpose of the study is to present a systematic literature review(SLR)on how to solve this problem and organize the published research papers that answer our four research questions.
Multi-criteria decision-makingMachine learningFootball player selectionManagerial-financial and sporting performance
Abdessatar Ati、Patrick Bouchet、Roukaya Ben Jeddou
展开 >
Faculty of Legal,Economic,and Management Sciences,University of Jendouba,Jendouba,8189,Tunisie
University of Bourgogne Franche-Comte',Université de Bourgogne,Dijon,21078,France
NETL
NSTL
万方数据
