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Related Experiment Video

Updated: Jun 13, 2026

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
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Published on: August 16, 2020

Can Locomotor Performance Predict the Final Result of a Football Match? A Machine Learning Approach.

Julen Castellano1, Aitor Pinedo-Jauregi1,2, Roberto Lopez Del Campo3

  • 1GIKAFIT Research Group, Department of Physical Education and Sport, Faculty of Education and Sport, University of the Basque Country (UPV/EHU), 01007 Vitoria-Gasteiz, Spain.

Sensors (Basel, Switzerland)
|June 12, 2026
PubMed
Summary

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This summary is machine-generated.

Predicting soccer match outcomes is possible using player movement data. High-intensity activity during the defensive phase, specifically out-of-possession, is the key predictor of winning.

Area of Science:

  • Sports Science
  • Performance Analysis
  • Football Analytics

Background:

  • Understanding factors influencing football match outcomes is crucial for performance optimization.
  • Locomotor performance data offers objective insights into player and team dynamics during matches.

Purpose of the Study:

  • To predict Spanish professional football (LaLiga and LaLiga2) match outcomes using locomotor-related data.
  • To identify key locomotor variables that determine match success.

Main Methods:

  • Utilized locomotor data (total distance, high-speed running) across different game phases from two LaLiga seasons.
  • Employed LASSO-regularized logistic regression to predict win/loss outcomes.
  • Evaluated model performance using accuracy, precision, recall, F1-scores, and AUC-ROC.
Keywords:
machine learningmatch performancesoccertime-motion

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Main Results:

  • The LASSO model achieved 76.8% predictive accuracy with an F1-score of 0.77 and AUC of 0.85.
  • Key predictors of victory included total distance (TD) during specific game moments and high-speed running (HSR) during possession and out-of-possession phases.
  • High-intensity activity out-of-possession (defensive phase) was the primary determinant of match success.

Conclusions:

  • Locomotor variables can accurately predict football match outcomes.
  • High-intensity activity during the defensive phase is a critical factor for achieving victory.
  • Further research into the defensive phase's impact on match success is warranted.