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Football Match Line-Up Prediction Based on Physiological Variables: A Machine Learning Approach

Alberto Cortez, António Trigo, Nuno Loureiro

2022Computers14 citationsDOIOpen Access PDF

Abstract

One of the great challenges for football coaches is to choose the football line-up that gives more guarantees of success. Even though there are several dimensions to analyse the problem, such as the opposing team characteristics. The objective of this study is to identify, based on the players’ physiological variables collected using Global Positioning Systems (GPS), which players are the most suitable to be part of the starting team/line-up. The work was developed in two stages, first with the choice of the most important variables using the Recursive Feature Elimination algorithm, and then using logistic regression on these chosen variables. The logistic regression resulted in an index, called the line-up preparedness index, for the following player positions: Fullbacks, Central Midfielders and Wingers. For the other players’ positions, the model results were not satisfactory.

Topics & Concepts

FootballLogistic regressionGlobal Positioning SystemComputer scienceLine (geometry)Index (typography)Feature (linguistics)PreparednessVariablesWork (physics)StatisticsMachine learningMathematicsEngineeringGeographyLinguisticsGeometryMechanical engineeringLawArchaeologyWorld Wide WebPhilosophyTelecommunicationsPolitical scienceSports Performance and TrainingSports Analytics and PerformanceSports injuries and prevention
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