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The Dirty League: English Premier League Provides Higher Incentives for Fouling as Compared to Other European Soccer Leagues

Fouling in soccer has been studied from an ethical standpoint as a measure of aggression. However, there is limited research related to fouling for performance. The present study investigated fouling as a factor influencing performance in European soccer leagues. Out of possession fouls (FPGNorm), y...

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Autores principales: Phatak, Ashwin A., Rein, Robert, Memmert, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sciendo 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8607766/
https://www.ncbi.nlm.nih.gov/pubmed/34868434
http://dx.doi.org/10.2478/hukin-2021-0095
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author Phatak, Ashwin A.
Rein, Robert
Memmert, Daniel
author_facet Phatak, Ashwin A.
Rein, Robert
Memmert, Daniel
author_sort Phatak, Ashwin A.
collection PubMed
description Fouling in soccer has been studied from an ethical standpoint as a measure of aggression. However, there is limited research related to fouling for performance. The present study investigated fouling as a factor influencing performance in European soccer leagues. Out of possession fouls (FPGNorm), yellow cards (YCFNorm), and their ratio (YCPFPG) were used as predictors of points (Pts) and goals conceded (GA) at the end of the season using three separate linear regression models. Furthermore, 5-fold cross-validation was used to measure out sample reliability. All the models significantly predicted GA and Pts (p < 0.001). Models predicting GA showed higher reliability than models predicting points. Cross validation (CV) results suggested that FPGNorm and YCPFPG models showed a small standard deviation (SD) in the R(2) results whereas the results from YCFNorm were not reliable to high SD in the 5-fold CV results. In summary, FPGNorm and YCPFPG seem to predict success (low GA and high Pts) across European soccer leagues, with EPL showing the maximum effect. The findings of the current study and the methodology can be applied to an actual game analysis by coaches in multiple invasion sports. Normalizing for out of possession time is a crucial step for the time spent in particular phases of play, which has not been done in previous research while analyzing ‘key performance indices’ (KPIs). Normalization can successfully introduce domain-specific knowledge into predictors, which can be used in complex algorithms improving predictions and investigation of underlying mechanisms.
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spelling pubmed-86077662021-12-02 The Dirty League: English Premier League Provides Higher Incentives for Fouling as Compared to Other European Soccer Leagues Phatak, Ashwin A. Rein, Robert Memmert, Daniel J Hum Kinet Section III - Sports Training Fouling in soccer has been studied from an ethical standpoint as a measure of aggression. However, there is limited research related to fouling for performance. The present study investigated fouling as a factor influencing performance in European soccer leagues. Out of possession fouls (FPGNorm), yellow cards (YCFNorm), and their ratio (YCPFPG) were used as predictors of points (Pts) and goals conceded (GA) at the end of the season using three separate linear regression models. Furthermore, 5-fold cross-validation was used to measure out sample reliability. All the models significantly predicted GA and Pts (p < 0.001). Models predicting GA showed higher reliability than models predicting points. Cross validation (CV) results suggested that FPGNorm and YCPFPG models showed a small standard deviation (SD) in the R(2) results whereas the results from YCFNorm were not reliable to high SD in the 5-fold CV results. In summary, FPGNorm and YCPFPG seem to predict success (low GA and high Pts) across European soccer leagues, with EPL showing the maximum effect. The findings of the current study and the methodology can be applied to an actual game analysis by coaches in multiple invasion sports. Normalizing for out of possession time is a crucial step for the time spent in particular phases of play, which has not been done in previous research while analyzing ‘key performance indices’ (KPIs). Normalization can successfully introduce domain-specific knowledge into predictors, which can be used in complex algorithms improving predictions and investigation of underlying mechanisms. Sciendo 2021-10-31 /pmc/articles/PMC8607766/ /pubmed/34868434 http://dx.doi.org/10.2478/hukin-2021-0095 Text en © 2021 Ashwin A. Phatak, Robert Rein, Daniel Memmer, published by Sciendo https://creativecommons.org/licenses/by-nc-nd/3.0/This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
spellingShingle Section III - Sports Training
Phatak, Ashwin A.
Rein, Robert
Memmert, Daniel
The Dirty League: English Premier League Provides Higher Incentives for Fouling as Compared to Other European Soccer Leagues
title The Dirty League: English Premier League Provides Higher Incentives for Fouling as Compared to Other European Soccer Leagues
title_full The Dirty League: English Premier League Provides Higher Incentives for Fouling as Compared to Other European Soccer Leagues
title_fullStr The Dirty League: English Premier League Provides Higher Incentives for Fouling as Compared to Other European Soccer Leagues
title_full_unstemmed The Dirty League: English Premier League Provides Higher Incentives for Fouling as Compared to Other European Soccer Leagues
title_short The Dirty League: English Premier League Provides Higher Incentives for Fouling as Compared to Other European Soccer Leagues
title_sort dirty league: english premier league provides higher incentives for fouling as compared to other european soccer leagues
topic Section III - Sports Training
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8607766/
https://www.ncbi.nlm.nih.gov/pubmed/34868434
http://dx.doi.org/10.2478/hukin-2021-0095
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