Using network metrics to investigate football team players' connections: A pilot study
| Main Author: | |
|---|---|
| Publication Date: | 2014 |
| Other Authors: | , , |
| Format: | Article |
| Language: | eng |
| Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Download full: | https://hdl.handle.net/10316/109510 https://doi.org/10.1590/S1980-65742014000300004 |
Summary: | 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. |
| id |
RCAP_de56db4490ca71b43b7dd063f2141d5b |
|---|---|
| oai_identifier_str |
oai:estudogeral.uc.pt:10316/109510 |
| network_acronym_str |
RCAP |
| network_name_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| repository_id_str |
https://opendoar.ac.uk/repository/7160 |
| spelling |
Using network metrics to investigate football team players' connections: A pilot studymatch analysisfootballnetworkmetricsperformanceanálise de jogofutebolnetworkmétricasrendimentoanálisis del juegofútbolredmétricasrendimientoThe 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.Resumo—“Avaliando as conexões entre jogadores de futebol utilizando métricas de network: Um estudo piloto.” O presente estudo piloto teve como objetivo do piloto propor um conjunto de métodos de network para avaliar as propriedades de equipes de futebol. Essas métricas foram organizadas em função dos níveis de análise “meso” e “micro.” Foram analisados cinco jogos oficiais da mesma equipa participante na Primeira Liga Profissional de Futebol Português. Um conjunto de 577 jogadas atacantes foram analisadas ao longo desses cinco jogos. As interações entre companheiros de equipa foram recolhidas e processadas seguindo os níveis de análise anteriormente referidos. Os resultados evidenciaram que os maiores valores de escala de conetividade foram encontrados nos defensores laterais e zagueiros, bem como, nos meio-campistas e os menores valores encontraram-se no atacante e goleiro. Os maiores valores de coeficiente de agrupamento foram geralmente encontrados nos meio-campistas e atacantes. No caso dos resultados relativos ao centroid verificou-se que os defensores laterais e zagueiros tendem a ser os jogadores centroids no processo atacante. Em resumo, este estudo destacou que as métricas de network podem ser um instrumento poderoso para auxiliar os treinadores a compreenderem as propriedades específicas das equipes, suportando a tomada de decisão e melhorando o treinamento tendo como base a análise de jogo.Resumen—“La evaluación de las conexiones entre los jugadores de fútbol utilizando métricas de red: un estudio piloto.” El objetivo de este estudio piloto fue el de proponer un conjunto de métodos para evaluar las propiedades de la red los equipos de fútbol. Estas métricas se organizaron de acuerdo con el nivel de análisis “meso” y “micro.” Se analizaron cinco partidos oficiales en el mismo equipo que participan en la Liga Premier de Fútbol Profesional de Portugal. Se analizó una serie de 577 atacantes mueve en estos cinco partidos. Las interacciones entre los compañeros de equipo fueron recolectados y procesados siguiendo los niveles de análisis mencionados. Los resultados mostraron que los valores más altos de conectividad de la escala se encuentran en los defensores laterales y centrales, así como los mediocampistas centrales y los valores más bajos se encontraron en-punta delantera y el portero. Los valores más altos del coeficiente de agrupamiento se encuentran generalmente en el medio y los atacantes. En los resultados para el jugador centroid, se encontró que los defensores laterales y centrales tienden a ser actores centrales en el proceso de ataque. En resumen, este estudio pone de relieve que las métricas de la red puede ser una herramienta poderosa para ayudar a los entrenadores a comprender las propiedades específicas de los equipos, el apoyo a la toma de decisiones y la mejora de lo entrenamiento basada en el análisis del juego.Universidade Estadual Paulista (UNESP)2014info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://hdl.handle.net/10316/109510https://hdl.handle.net/10316/109510https://doi.org/10.1590/S1980-65742014000300004eng1980-6574Clemente, Filipe M.Couceiro, Micael SantosMartins, Fernando Manuel LourençoMendes, Rui Sousainfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2023-10-18T10:06:12Zoai:estudogeral.uc.pt:10316/109510Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T06:01:10.111025Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
Using network metrics to investigate football team players' connections: A pilot study |
| title |
Using network metrics to investigate football team players' connections: A pilot study |
| spellingShingle |
Using network metrics to investigate football team players' connections: A pilot study Clemente, Filipe M. match analysis football network metrics performance análise de jogo futebol network métricas rendimento análisis del juego fútbol red métricas rendimiento |
| 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 |
| author |
Clemente, Filipe M. |
| author_facet |
Clemente, Filipe M. Couceiro, Micael Santos Martins, Fernando Manuel Lourenço Mendes, Rui Sousa |
| author_role |
author |
| author2 |
Couceiro, Micael Santos Martins, Fernando Manuel Lourenço Mendes, Rui Sousa |
| author2_role |
author author author |
| dc.contributor.author.fl_str_mv |
Clemente, Filipe M. Couceiro, Micael Santos Martins, Fernando Manuel Lourenço Mendes, Rui Sousa |
| dc.subject.por.fl_str_mv |
match analysis football network metrics performance análise de jogo futebol network métricas rendimento análisis del juego fútbol red métricas rendimiento |
| topic |
match analysis football network metrics performance análise de jogo futebol network métricas rendimento análisis del juego fútbol red métricas rendimiento |
| 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. |
| publishDate |
2014 |
| dc.date.none.fl_str_mv |
2014 |
| dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10316/109510 https://hdl.handle.net/10316/109510 https://doi.org/10.1590/S1980-65742014000300004 |
| url |
https://hdl.handle.net/10316/109510 https://doi.org/10.1590/S1980-65742014000300004 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
1980-6574 |
| dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
| eu_rights_str_mv |
openAccess |
| dc.publisher.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
| publisher.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
| dc.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
| instname_str |
FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
| instacron_str |
RCAAP |
| institution |
RCAAP |
| reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| collection |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| repository.name.fl_str_mv |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
| repository.mail.fl_str_mv |
info@rcaap.pt |
| _version_ |
1833602549433761792 |