TY - JOUR
T1 - Is a social network approach relevant to football results?
AU - Medina, Pablo
AU - Carrasco, Sebastián
AU - Rogan, José
AU - Montes, Felipe
AU - Meisel, Jose D.
AU - Lemoine, Pablo
AU - Lago Peñas, Carlos
AU - Valdivia, Juan Alejandro
N1 - Funding Information:
This work was supported by CONICYT-PCHA/Doctorado Nacional/2016-2116103 (S.C.) and the Fondo Nacional de Investigaciones Científicas y Tecnológicas ( FONDECYT , Chile) under grants Posdoctoral Project 3180315 (PM), 1190662 (JR), 1190703 (JAV), and CEDENNA through “Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia-FB0807” (JR and JAV). JDM was funded by the Research Office at the Universidad de Ibague (project 17-466-INT). FM was funded by the Vicepresidency of Research and Creation of Universidad de los Andes (FAPA grant).
Publisher Copyright:
© 2020 Elsevier Ltd
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/1
Y1 - 2021/1
N2 - We study the relevance of considering social network analysis in determining soccer results. As a benchmark, we start using a simple regression model based on past performance to try to determine the main trends of a soccer match based on probabilities of winning, losing or tying, as home or visiting teams. The success of this simple model, based on historical performance, is improved by the addition of network descriptors of both teams in a game. Therefore, such network measures do offer additional useful information in determining match outcomes. We validate our approach using the data of the Spanish League (La Liga) 2012–2013. We observe that betweenness centrality seems to provide additional relevance information related to the performance of a team during the tournament.
AB - We study the relevance of considering social network analysis in determining soccer results. As a benchmark, we start using a simple regression model based on past performance to try to determine the main trends of a soccer match based on probabilities of winning, losing or tying, as home or visiting teams. The success of this simple model, based on historical performance, is improved by the addition of network descriptors of both teams in a game. Therefore, such network measures do offer additional useful information in determining match outcomes. We validate our approach using the data of the Spanish League (La Liga) 2012–2013. We observe that betweenness centrality seems to provide additional relevance information related to the performance of a team during the tournament.
KW - Complex networks
KW - Football
KW - Probabilistic models
KW - Social network analysis
UR - http://www.scopus.com/inward/record.url?scp=85094907157&partnerID=8YFLogxK
U2 - 10.1016/j.chaos.2020.110369
DO - 10.1016/j.chaos.2020.110369
M3 - Artículo
AN - SCOPUS:85094907157
VL - 142
JO - Chaos, Solitons and Fractals
JF - Chaos, Solitons and Fractals
SN - 0960-0779
M1 - 110369
ER -