Football Movement Profile-Based Creatine-Kinase Prediction Performs Similarly to Global Positioning System-Derived Machine Learning Models in National-Team Soccer Players.

Journal: International journal of sports physiology and performance
PMID: 38917990

Abstract

PURPOSE: The relationship between external load and creatine-kinase (CK) response at the team/position or individual level using Global Positioning Systems (GPS) has been studied. This study aimed to compare GPS-derived and Football Movement Profile (FMP) -derived CK-prediction models for national-team soccer players. The second aim was to compare the performance of general and individualized CK prediction models.

Authors

  • Gabor Schuth
    Department of Sport Medicine and Sport Science, Hungarian Football Federation, Budapest, Hungary.
  • György Szigeti
    Department of Sport Medicine and Sport Science, Hungarian Football Federation, Budapest, Hungary.
  • Gergely Dobreff
    Department of Telecommunications and Media Informatics, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Budapest, Hungary.
  • Alija Pašić
    Department of Telecommunications and Media Informatics, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Budapest, Hungary.
  • Tim Gabbett
    Gabbett Performance Solutions, Brisbane, QLD, Australia.
  • Adam Szilas
    Department of Sport Medicine and Sport Science, Hungarian Football Federation, Budapest, Hungary.
  • Gabor Pavlik
    Department of Health Sciences and Sport Medicine, Hungarian University of Sports Science, Budapest, Hungary.

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