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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Universidade Estadual Paulista
2014
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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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Clemente,Filipe Manuel Couceiro,Micael Santos Martins,Fernando Manuel Lourenço Mendes,Rui Sousa |
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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 |
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Clemente,Filipe Manuel Couceiro,Micael Santos Martins,Fernando Manuel Lourenço Mendes,Rui Sousa |
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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 |
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Using network metrics to investigate football team players' connections: A pilot study |
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Using network metrics to investigate football team players' connections: A pilot study |
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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. |
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Universidade Estadual Paulista |
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2014 |
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http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1980-65742014000300262 |
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