The Application of Machine Learning on the Injury Prediction of Soccer Players

Abstract

Soccer player lives with a high risk of injury since soccer is one of the sports activities with relatively high injury incidence compared with many other sports. Injuries can be a huge influence not only player’s career and financial situation but also it is the reason for soccer changing the coach’s game tactics as well as for directors of clubs have to find a new player. In order to reduce the risk of getting injured by predicting the probability of soccer players’ injuries for the new season, we conduct research in this paper. In this paper, we propose parameters that are connected each other and we collected using a non- technical way while most of the recent research provides technical ways such as GPS tracking technology or wearing devices. Moreover, we provide the accuracy of injury prediction and estimation of recovery time by using supervised classification machine learning models. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).