Using network metrics to investigate football team players' connections: A pilot study

The aim of this pilot study was propose a set of network methods to measure the specific properties of football teams. These metrics were organized on "meso" and "micro" analysis levels. Five official matches of the same team on the First Portuguese Football League were analyzed. An overall of 577 offensive plays were analyzed from the five matches. From the adjacency matrices developed per each offensive play it were computed the scaled connectivity, the clustering coefficient and the centroid significance and centroid conformity. Results showed that the highest values of scaled connectivity were found in lateral defenders and central and midfielder players and the lowest values were found in the striker and goalkeeper. The highest values of clustering coefficient were generally found in midfielders and forwards. In addition, the centroid results showed that lateral and central defenders tend to be the centroid players in the attacking process. In sum, this study showed that network metrics can be a powerful tool to help coaches to understanding the specific team's properties, thus supporting decision-making and improving sports training based on match analysis.

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Bibliographic Details
Main Authors: Clemente,Filipe Manuel, Couceiro,Micael Santos, Martins,Fernando Manuel Lourenço, Mendes,Rui Sousa
Format: Digital revista
Language:English
Published: Universidade Estadual Paulista 2014
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-65742014000300262
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spelling oai:scielo:S1980-657420140003002622015-10-09Using network metrics to investigate football team players' connections: A pilot studyClemente,Filipe ManuelCouceiro,Micael SantosMartins,Fernando Manuel LourençoMendes,Rui Sousa match analysis football network metrics performance The aim of this pilot study was propose a set of network methods to measure the specific properties of football teams. These metrics were organized on "meso" and "micro" analysis levels. Five official matches of the same team on the First Portuguese Football League were analyzed. An overall of 577 offensive plays were analyzed from the five matches. From the adjacency matrices developed per each offensive play it were computed the scaled connectivity, the clustering coefficient and the centroid significance and centroid conformity. Results showed that the highest values of scaled connectivity were found in lateral defenders and central and midfielder players and the lowest values were found in the striker and goalkeeper. The highest values of clustering coefficient were generally found in midfielders and forwards. In addition, the centroid results showed that lateral and central defenders tend to be the centroid players in the attacking process. In sum, this study showed that network metrics can be a powerful tool to help coaches to understanding the specific team's properties, thus supporting decision-making and improving sports training based on match analysis.info:eu-repo/semantics/openAccessUniversidade Estadual PaulistaMotriz: Revista de Educação Física v.20 n.3 20142014-09-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-65742014000300262en10.1590/S1980-65742014000300004
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country Brasil
countrycode BR
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region America del Sur
libraryname SciELO
language English
format Digital
author Clemente,Filipe Manuel
Couceiro,Micael Santos
Martins,Fernando Manuel Lourenço
Mendes,Rui Sousa
spellingShingle Clemente,Filipe Manuel
Couceiro,Micael Santos
Martins,Fernando Manuel Lourenço
Mendes,Rui Sousa
Using network metrics to investigate football team players' connections: A pilot study
author_facet Clemente,Filipe Manuel
Couceiro,Micael Santos
Martins,Fernando Manuel Lourenço
Mendes,Rui Sousa
author_sort Clemente,Filipe Manuel
title Using network metrics to investigate football team players' connections: A pilot study
title_short Using network metrics to investigate football team players' connections: A pilot study
title_full Using network metrics to investigate football team players' connections: A pilot study
title_fullStr Using network metrics to investigate football team players' connections: A pilot study
title_full_unstemmed Using network metrics to investigate football team players' connections: A pilot study
title_sort using network metrics to investigate football team players' connections: a pilot study
description The aim of this pilot study was propose a set of network methods to measure the specific properties of football teams. These metrics were organized on "meso" and "micro" analysis levels. Five official matches of the same team on the First Portuguese Football League were analyzed. An overall of 577 offensive plays were analyzed from the five matches. From the adjacency matrices developed per each offensive play it were computed the scaled connectivity, the clustering coefficient and the centroid significance and centroid conformity. Results showed that the highest values of scaled connectivity were found in lateral defenders and central and midfielder players and the lowest values were found in the striker and goalkeeper. The highest values of clustering coefficient were generally found in midfielders and forwards. In addition, the centroid results showed that lateral and central defenders tend to be the centroid players in the attacking process. In sum, this study showed that network metrics can be a powerful tool to help coaches to understanding the specific team's properties, thus supporting decision-making and improving sports training based on match analysis.
publisher Universidade Estadual Paulista
publishDate 2014
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-65742014000300262
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AT couceiromicaelsantos usingnetworkmetricstoinvestigatefootballteamplayersconnectionsapilotstudy
AT martinsfernandomanuellourenco usingnetworkmetricstoinvestigatefootballteamplayersconnectionsapilotstudy
AT mendesruisousa usingnetworkmetricstoinvestigatefootballteamplayersconnectionsapilotstudy
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