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Predicting Physiological Variables of Players that Make a Winning Football Team: A Machine Learning Approach

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Computational Science and Its Applications – ICCSA 2021 (ICCSA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12951))

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Abstract

As football gained popularity and importance in the modern world, it been under greater scrutiny, so the industry must have better control of the training sessions, and most importantly, the football games and their outcomes. With the purpose of identify the physiological variables of the players that most contribute to winning a football match, a study based on machine learning algorithms was conducted on a dataset of the players GPS positions during the football matches of a team from the 2nd division of the Portuguese championship. The findings reveal that the most important players’ physiological variables for predicting a win are Player Load /min, Distance m/min, Distance 0.3 m/s, Acceleration 0.2 m/s with an accuracy of 79%, using the XGBoost algorithm.

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Author information

Authors and Affiliations

  1. Coimbra Business School Research Centre | ISCAC, Polytechnic of Coimbra, Coimbra, Portugal

    Alberto Cortez & António Trigo

  2. Sport Sciences School of Rio Maior, 2040-413, Rio Maior, Portugal

    Nuno Loureiro

  3. Life Quality Research Centre (CIEQV), Polytechnic Institute of Santarem, Santarem, Portugal

    Nuno Loureiro

Authors
  1. Alberto Cortez
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  2. António Trigo
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  3. Nuno Loureiro
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Corresponding author

Correspondence to Alberto Cortez .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Monash University, Clayton, VIC, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

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Cortez, A., Trigo, A., Loureiro, N. (2021). Predicting Physiological Variables of Players that Make a Winning Football Team: A Machine Learning Approach. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12951. Springer, Cham. https://doi.org/10.1007/978-3-030-86970-0_1

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  • DOI: https://doi.org/10.1007/978-3-030-86970-0_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-86969-4

  • Online ISBN: 978-3-030-86970-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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