Using multi-criteria decision-making and machine learning for football player selection and performance prediction:a systematic review  

作　　者：Abdessatar Ati Patrick Bouchet Roukaya Ben Jeddou 

机构地区：[1]Faculty of Legal,Economic,and Management Sciences,University of Jendouba,Jendouba,8189,Tunisie [2]University of Bourgogne Franche-Comte’,Universitéde Bourgogne,Dijon,21078,France

出　　处：《Data Science and Management》2024年第2期79-88,共10页数据科学与管理（英文）

摘　　要：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 management. 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.

关 键 词：Multi-criteria decision-making Machine learning Football player selection Managerial-financial and sporting performance 

分 类 号：G84[文化科学—体育训练]