Who are The Prominent Players in the UEFA Champions League? An Approach Based on Network Analysis

Filipe Manuel CLEMENTE, Fernando Manuel Lourenço MARTINS

Abstract


This study aimed to analyze the centrality levels of elite football players. Tactical positions and tactical line-ups were considered factors to be used in analyzing the variance in the prominence of players, measured by social network measures. The best 16 teams from the UEFA Champions league were analyzed during the entire competition. A total of 109 matches were analyzed for this study. Significant statistical differences between positions were found in % indegree (p = 0.001; ES = 0.268, moderate effect), % outdegree (p = 0.001; ES = 0.301, moderate effect) and % betweenness (p = 0.001; ES = 0.114, minimum effect). No statistical differences between tactical line-ups in % outdegree (p = 1.000; ES = 0.001, no effect) or % indegree (p = 1.000; ES = 0.001, no effect) were found. Central midfielders had the greatest values of centrality, thus confirming their importance in the linkage process of the team. Position had great influence on the centrality levels of players.


Keywords


Applied mathematics, graph theory, soccer, football, match analysis

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References


JF Gréhaigne, P Godbout and Z Zerai. How the ‘rapport de forces’ evolves in a football match: The dynamics of collective decisions in a complex system. Rev. Psicol. del Deport. 2011; 20: 747-65.

T McGarry. Soccer as a Dynamical System: Some Theoretical Considerations. In: T Reilly, J Cabri, and D Araújo (eds.). Science and Football V. Routledge, Taylor & Francis Group, London and New York, 2005, p. 570-9.

J Bloomfield, GK Jonsson, K Houlahan and PO Donoghue. Temporal Pattern Analysis and its Applicability in Soccer. In: L Anolli, S Duncan, MS Magnusson and G Riva (eds.). The Hidden Stucture of Interaction: From Neurons to Culture Patterns. IOS Press, Amsterdam, Netherlands, 2005, p. 237-51.

FM Clemente, MS Couceiro, FML Martins and RS Mendes. Using network metrics to investigate football team players’ connections: A pilot study. Motriz 2014; 20: 262-71.

JF Gréhaigne, P Godbout and D Bouthier. The foundations of tactics and strategy in team sports. J. Teach. Phys. Educ. 1999; 18, 159-74.

IT Costa, J Garganta, PJ Greco, I Mesquita and A Seabra. Influence of relative age effects and quality of tactical behaviour in the performance of youth football players. Int. J. Perform. Anal. Sport 2010; 10, 82-97.

JF Gréhaigne, D Bouthier and B David. Dynamic-system analysis of opponent relationship in collective actions in football. J. Sport. Sci. 1997; 15, 137-49.

D Lusher, G Robins and P Kremer. The application of social network analysis to team sports. Meas. Phys. Educ. Exerc. Sci. 2010; 14, 211-24.

TU Grund. Network structure and team performance: The case of English Premier League soccer teams. Soc. Network. 2012; 34, 682-90.

J Bourbousson, G Poizat, J Saury and C Seve. Team coordination in basketball: Description of the cognitive connections among teammates. J. Appl. Sport Psychol. 2010; 22, 150-66.

M Hughes and M Franks. Notational Analysis of Sport. Routledge, London, UK, 2004.

R Duarte, D Araújo, V Correia and K Davids. Sports teams as superorganisms: Implications of sociobiological models of behaviour for research and practice in team sports performance analysis. Sport. Med. 2012; 42, 633-42.

B Travassos, K Davids, D Araújo and PT Esteves. Performance analysis in team sports: Advances from an Ecological Dynamics approach. Int. J. Perform. Anal. Sport 2013; 13, 83-95.

H Sarmento, R Marcelino, MT Anguera, J Campaniço, N Matos and JC Leitão. Match analysis in football: A systematic review. J. Sport. Sci. 2014; 32, 1831-43.

D Memmert and J Perl. Game creativity analysis using neural networks. J. Sport. Sci. 2009; 27, 139-49.

FM Clemente, FML Martins and RS Mendes. Social Network Analysis Applied to Team Sports Analysis. Springer International Publishing, Netherlands, 2016.

FM Clemente, FML Martins, DP Wong, D Kalamaras and RS Mendes. Midfielder as the prominent participant in the building attack: A network analysis of national teams in FIFA World Cup 2014. Int. J. Perform. Anal. Sport 2015; 15, 704-22.

J Duch, JS Waitzman and LA Amaral. Quantifying the performance of individual players in a team activity. PLoS One 2010; 5, e10937.

JL Peña and H Touchette. A Network Theory Analysis of Football Strategies. In: C Clanet (ed.). Sports Physics. Paris, France, 2012, p. 517-28.

S González-Víllora, J Serra-Olivares, JC Pastor-Vicedo and I Teoldo. Review of the tactical evaluation tools for youth players, assessing the tactics in team sports: football. Springerplus 2015; 4, 663.

S Wasserman and J Glaskiewicz. Advances in Social Network Analysis: Research in the Social and Behavioral. SAGE Publications, California, USA, 1994.

P Malta and B Travassos. Characterization of the defense-attack transition of a soccer team. Motricidade 2014; 10, 27-37.

Y Yamamoto and K Yokoyama. Common and unique network dynamics in football games. PLoS One 2011; 6, e29638.

FM Clemente, FML Martins, D Kalamaras, DP Wong and RS Mendes. General network analysis of national soccer teams in FIFA World Cup 2014. Int. J. Perform. Anal. Sport 2015; 15, 80-96.

G Robinson and P O’Donoghue. A weighted kappa statistic for reliability testing in performance analysis of sport. Int. J. Perform. Anal. Sport 2007; 7, 12-9.

V Di Salvo, R Baron, H Tschan, FJC Montero, N Bachl and F Pigozzi. Performance characteristics according to playing position in elite soccer. Int. J. Sport. Med. 2007; 28, 222-7.

D Kalamaras. Social Networks Visualizer (SocNetV): Social Network Analysis and Visualization Software, Available at: http://socnetv.sourceforge.net, accessed December 2016.

T Opsahl, F Agneessens and J Skvoretz. Node centrality in weighted networks: Generalizing degree and shortest paths. Soc. Network. 2010; 32, 245-51.

M Rubinov and O Sporns. Complex network measures of brain connectivity: Uses and interpretations. Neuroimage 2010; 52, 1059-69.

CJ Ferguson. An effect size primer: A guide for clinicians and researchers. Prof. Psychol. Res. Pract. 2009; 40, 532-8.

C Cotta, AM Mora, JJ Merelo and C Merelo-Molina. A network analysis of the 2010 FIFA world cup champion team play. J. Syst. Sci. Complex. 2013; 26, 21-42.

T Reilly and V Thomas. A motion analysis of work-rate in different positional roles in professional football match-play. J. Hum. Mov. Stud. 1976; 2, 87-97.

FM Clemente, FML Martins and RS Mendes. Analysis of scored and conceded goals by a football team throughout a season: A network analysis. Kinesiology 2016; 48, 103-14.

S González-Víllora, JC Pastor-Vicedo and D Cordente. Relative age effect in UEFA Championship soccer players. J. Hum. Kinet. 2015; 47, 248.


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