Is a social network approach relevant to football results?

Medina, Pablo; Carrasco, Sebastián; Rogan, José; Montes, Felipe; Meisel, José D.; Lemoine, Pablo; Lago‐Peñas, Carlos; Valdivia, J. A.

doi:10.1016/j.chaos.2020.110369

Cited by 15 publications

(10 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on the results of this study, the mathematical models which assumed the highest degree of importance were Network Density; Network Heterogeneity and Reciprocity. These data are in line with Medina et al [5], which upon analyzing the Social Network Approach to verify if this model was truly useful in terms of methodology to determine the statistical role of the passing network in the performance of a team in a soccer match, concluded that some network measures could cover relevant information about player performance indicators. Our results follow the same idea as Dhand et al [6] when they verified that the personal social network mapping, or egocentric network analysis, is a useful proxy for multiple factors.…”

Section: Discussionsupporting

confidence: 85%

“…In this case, a human network or a superorganism like a football team, is, in most cases, composed by vertexes (also designated as nodes), in which they are represented by the number of players on the team [2][3][4]. Furthermore, Medina et al [5], upon analyzing the usefulness of the social network approach in terms of a methodology to determine the statistical role of the passing network in the performance of a team in a soccer match, questioned the following "Is a social network approach relevant to football results?" The authors concluded that some network measures could cover relevant information about player performance describers, such as betweenness centrality, connectivity, among others.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Social Network Analysis: Mathematical Models for Understanding Professional Football in Game Critical Moments—An Exploratory Study

et al. 2022

View full text Add to dashboard Cite

Considering the Social Network Analysis approach and based on the creation of mathematical models, the aim of this study is to analyze the players’ interactions of professional football teams in critical moments of the game. The sample consists in the analysis of a 2019/2020 season UEFA Champions League match. The mathematical models adopted in the analysis of the players (micro analysis) and the game (macro analysis) were obtained through the uPATO software. The results of the networks indicated a performance pattern trend more robust in terms of the mathematical model: Network Density. As far as it concerned, we found that the Centroid Players had a decisive role in the level of connectivity and interaction of the team. Regarding the main critical moments of the game, the results showed that these were preceded by periods of great instability, obtaining a differentiated performance in the following mathematical models: Centrality, Degree Centrality, Closeness Centrality, and Degree Prestige. We concluded that the networks approach, in concomitance with the dynamic properties of mathematical models, and the critical moments of the game, can help coaches to better evaluate the level of interaction and connectivity of their players toward the actions imposed by opponents.

show abstract

Section: Discussionsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Social Network Analysis: Mathematical Models for Understanding Professional Football in Game Critical Moments—An Exploratory Study

et al. 2022

View full text Add to dashboard Cite

show abstract

“…position. 22 In our work we only found correlations for some of the network metrics for some of the leagues and it could be suggested that a combination of network metrics could give a better indication of the relationship between success and teamwork. Another explanation could be that ladder position is influenced by external factors that differ between teams and seasons such as personnel, systems, tactical approaches and the ability of a team to execute these.…”

Section: Discussionmentioning

confidence: 60%

“…Besides the difference in teamwork between winning and losing teams found in previous men's research 12,21,22 it could be suggested that teams playing in a league cooperate in a different way than teams playing a tournament like a confederation or world cup. National teams often only come together for the specific tournament and might have limited time beforehand to train as a group compared to a club team playing together for a full season.…”

Section: Introductionmentioning

confidence: 93%

Teamwork and performance in professional women's football: A network-based analysis

Jong

Gastin

Bruce

et al. 2022

International Journal of Sports Science & Coaching

View full text Add to dashboard Cite

Analysis of the underlying tactics and teamwork in women's football is rare and it is unknown how professional women's teams cooperate to be successful. The aim of this study was to investigate teamwork using network analysis while comparing match-outcome, match-type, ladder halves and tournament phases, to determine whether teamwork is related to success. Ball transfer data in 694 matches from the 2015, 2016 and 2017/18 Football Association Women's Super League (FA WSL) seasons; 2016–2018 National Women's Football League (NWSL) seasons; 2013 and 2017 European Cups; and 2011 and 2013 World Cups were analysed. The network metrics: edge density, transitivity, mean distance, out degree centrality, closeness centrality, betweenness centrality and eigenvector centrality were calculated. Success was categorised in match outcomes, ladder halves, tournament phases and ladder positions. It was found that successful professional women's football teams are highly connected (p = 0.006), and the distribution of ball possession is centralised (p = 0.001). There is a tendency for key players to send out a high number of passes, but there is no dependency on these key players for the total ball flow within a team, which is a characteristic that may be unique to women's football. Differences in teamwork exist between single matches and full seasons or tournaments, with successful teams having more effective ball movement and successful passes over the course of a season or tournament (p < 0.001). Moreover, successful league teams have more players with connecting roles than tournament teams and match tactics should be adapted to this.

show abstract

“…Finally, Medina et al [23] presented a method combining a simple regression model and complex network features to assess the probability of teams to win/loss/tie matches when playing home or away. They showed that the addition of both approaches could offer useful information in determining matches outcomes.…”

mentioning

confidence: 99%