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

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...

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Bibliographic Details
Main Authors: Abdessatar Ati, Patrick Bouchet, Roukaya Ben Jeddou
Format: Article
Language:English
Published: KeAi Communications Co. Ltd. 2024-06-01
Series:Data Science and Management
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2666764923000504
Description
Summary: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.
ISSN:2666-7649