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Measuring skill via player dynamics in football dribbling

Although a myriad of studies have been conducted on player behavior in football, in-depth studies with structured theory are rare due to the difficulty in quantifying individual player skills and team strategies. We propose a physics-based mathematical model that describes football players’ movement...

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Autores principales: Brink, Lukas, Ha, Seung Kyun, Snowdon, Jack, Vidal-Codina, Ferran, Rauch, Bobby, Wang, Fan, Wu, David, López-Felip, Maurici A., Clanet, Christophe, Hosoi, Anette E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624867/
https://www.ncbi.nlm.nih.gov/pubmed/37923817
http://dx.doi.org/10.1038/s41598-023-45914-6
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author Brink, Lukas
Ha, Seung Kyun
Snowdon, Jack
Vidal-Codina, Ferran
Rauch, Bobby
Wang, Fan
Wu, David
López-Felip, Maurici A.
Clanet, Christophe
Hosoi, Anette E.
author_facet Brink, Lukas
Ha, Seung Kyun
Snowdon, Jack
Vidal-Codina, Ferran
Rauch, Bobby
Wang, Fan
Wu, David
López-Felip, Maurici A.
Clanet, Christophe
Hosoi, Anette E.
author_sort Brink, Lukas
collection PubMed
description Although a myriad of studies have been conducted on player behavior in football, in-depth studies with structured theory are rare due to the difficulty in quantifying individual player skills and team strategies. We propose a physics-based mathematical model that describes football players’ movements during dribbling situations, parameterized by the attacker aggressiveness, the defender hesitance and the top speed of both players. These player- and situation-specific parameters are extracted by fitting the model to real player trajectories from Major League Soccer games, and enable the quantification of player dribbling attributes and decisions beyond classical statistics. We show that the model captures the essential dribbling dynamics, and analyze how differences between parameters in varying game situations provide valuable insights into players’ behavior. Lastly, we quantitatively study how changes in the player’s parameters impact dribbling performance, enabling the model to provide scientific guidance to player training, scouting and game strategy development.
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spelling pubmed-106248672023-11-05 Measuring skill via player dynamics in football dribbling Brink, Lukas Ha, Seung Kyun Snowdon, Jack Vidal-Codina, Ferran Rauch, Bobby Wang, Fan Wu, David López-Felip, Maurici A. Clanet, Christophe Hosoi, Anette E. Sci Rep Article Although a myriad of studies have been conducted on player behavior in football, in-depth studies with structured theory are rare due to the difficulty in quantifying individual player skills and team strategies. We propose a physics-based mathematical model that describes football players’ movements during dribbling situations, parameterized by the attacker aggressiveness, the defender hesitance and the top speed of both players. These player- and situation-specific parameters are extracted by fitting the model to real player trajectories from Major League Soccer games, and enable the quantification of player dribbling attributes and decisions beyond classical statistics. We show that the model captures the essential dribbling dynamics, and analyze how differences between parameters in varying game situations provide valuable insights into players’ behavior. Lastly, we quantitatively study how changes in the player’s parameters impact dribbling performance, enabling the model to provide scientific guidance to player training, scouting and game strategy development. Nature Publishing Group UK 2023-11-03 /pmc/articles/PMC10624867/ /pubmed/37923817 http://dx.doi.org/10.1038/s41598-023-45914-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Brink, Lukas
Ha, Seung Kyun
Snowdon, Jack
Vidal-Codina, Ferran
Rauch, Bobby
Wang, Fan
Wu, David
López-Felip, Maurici A.
Clanet, Christophe
Hosoi, Anette E.
Measuring skill via player dynamics in football dribbling
title Measuring skill via player dynamics in football dribbling
title_full Measuring skill via player dynamics in football dribbling
title_fullStr Measuring skill via player dynamics in football dribbling
title_full_unstemmed Measuring skill via player dynamics in football dribbling
title_short Measuring skill via player dynamics in football dribbling
title_sort measuring skill via player dynamics in football dribbling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624867/
https://www.ncbi.nlm.nih.gov/pubmed/37923817
http://dx.doi.org/10.1038/s41598-023-45914-6
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