Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/40280
Title: Applying graphs and complex networks to football metric interpretation
Authors: Arriaza Ardiles, Enrique
Martín-González, J.M. 
Zuñiga, M.D.
Sánchez Flores, Javier
De Saa, Y.
García Manso, Juan Manuel 
UNESCO Clasification: 241118 Fisiología del movimiento
Keywords: Betweenness centrality
Closeness centrality
Clustering
Football
Network, et al
Issue Date: 2017
Journal: Human Movement Science 
Abstract: This work presents a methodology for analysing the interactions between players in a football team, from the point of view of graph theory and complex networks. We model the complex network of passing interactions between players of a same team in 32 official matches of the Liga de Fútbol Profesional (Spain), using a passing/reception graph. This methodology allows us to understand the play structure of the team, by analysing the offensive phases of game-play. We utilise two different strategies for characterising the contribution of the players to the team: the clustering coefficient, and centrality metrics (closeness and betweenness). We show the application of this methodology by analyzing the performance of a professional Spanish team according to these metrics and the distribution of passing/reception in the field. Keeping in mind the dynamic nature of collective sports, in the future we will incorporate metrics which allows us to analyse the performance of the team also according to the circumstances of game-play and to different contextual variables such as, the utilisation of the field space, the time, and the ball, according to specific tactical situations.
URI: http://hdl.handle.net/10553/40280
ISSN: 0167-9457
DOI: 10.1016/j.humov.2017.08.022
Source: Human Movement Science [ISSN 0167-9457], v. 57, p. 236-243
Appears in Collections:Artículos
Show full item record

SCOPUSTM   
Citations

7
checked on Apr 11, 2021

WEB OF SCIENCETM
Citations

7
checked on Apr 11, 2021

Page view(s)

32
checked on Apr 17, 2021

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.