Networks as a novel tool for studying team ball sports as complex social systems

Passos, Pedro; Davids, Keith; Araújo, Duarte; Paz, Nij; Minguens, J.; Mendes, J. F. F.

doi:10.1016/j.jsams.2010.10.459

Cited by 179 publications

(181 citation statements)

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“…A player has to act in order to perceive a teammate's behaviours, as well as those of a defender and the opposition (Passos et al, 2011). Interactions among players originate in coadaptive behaviours, where players adjust their behaviours relative to the perceived actions of neighbouring players in order to achieve performance goals (Fajen, Riley, & Turvey, 2009).…”

Section: Volume 9 | Issue 2 | 2014 | 658mentioning

confidence: 99%

“…The competency network is based on each player's recognized strengths and weaknesses with reference to the practice of the sport, and also in relation to the group's dynamism (Gréhaigne et al, 2005). Therefore, team function performance in sports is assured by a complex network of interpersonal relationships among players (Passos et al, 2011); as such, the competency network is more of a dynamic concept than a static one (Gréhaigne, Godbout, & Bouthier, 1999). Any network analysis needs to consider the regular and variable interactions between players.…”

Section: Networkmentioning

confidence: 99%

“…teammates), as well as their own contribution to successful and unsuccessful collective performance (Bourbousson, Poizat, Saury, & Seve, 2010). In their study, Passos et al (2011) built an adjacency matrix for each unit attack, and found that two linkage levels were established: i) identification when a player passed the ball to a teammate; or ii) identification when players changed their position in the performance area due to a teammate's displacement. In terms of the usefulness of this method, the results suggest that the networking method provides an interesting tool to qualitatively describe the interactions that occur between team players in water polo games (Passos et al, 2011).…”

Section: Networkmentioning

confidence: 99%

See 2 more Smart Citations

A systemic overview of football game: The principles behind the game — ; ; Mendes, Rui Sousa; Figueiredo, António José

Clemente

Martins

Mendes

et al. 2014

jhse

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Clemente, M.F., Lourenço Martins, F.M., Sousa Mendes, R., & Figueiredo, A.J. (2014). A systemic overview of football game: The principles behind the game. J. Hum. Sport Exerc., 9(2), pp.656-667. The football game is a specific system constituted by many players' interactions. The specific nature of such sport must be properly analyzed and discussed in sport community in order to understand the principles that rules the system organization. As a team sport with specific properties it is truly important to discuss how players' interactions from the dynamic nature of game. Therefore, the aim of this study is to classify the football game as a team sport and to discuss their specific dynamic that determines the emergence of a tactical behavior and a strategic definition. Such discussion can be important to determine the specific pedagogical and didactical contents to teach at youth football training and even in Physical Education classes.

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Section: Volume 9 | Issue 2 | 2014 | 658mentioning

confidence: 99%

Section: Networkmentioning

confidence: 99%

Section: Networkmentioning

confidence: 99%

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A systemic overview of football game: The principles behind the game — ; ; Mendes, Rui Sousa; Figueiredo, António José

Clemente

Martins

Mendes

et al. 2014

jhse

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“…This matrix represents the numeric relationship (arrows) between teammates connections (nodes) ). The linkage indicator it was the pass between two players (Cotta et al, 2013;Passos et al, 2011). Each unit of attack (passing sequence) resulted in an adjacency matrix.…”

Section: Network Analysismentioning

confidence: 99%

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2015

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Abstract:The aim of this study was to verify the prominence levels of rink-hockey players in different competitive levels. For that reason, it was analysed the variance of network centrality metrics between competitive levels and tactical positions. Fifty-four rink-hockey players from five different levels (U12, U14, U16, U18 and Elite) were analysed during three official matches. The results did not found statistical differences in centrality levels of players between competitive levels (p-value = 1.00; partial eta square = 0.001; very small effect size). Nevertheless, tactical position (p-value = 0.001; partial eta square = 0.534; moderate effect size) had significant main effects on the centrality metrics. In this study it was found that defender and forward are the positions that most receive balls from the teammates. In other hand, the forward is the position that most passes performed until the U16 and in older levels the defender assumes the centrality in passes performed.

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“…However, this method does not make use of intrinsic knowledge of the procedures that lead to the results used in the analysis (Lees, 2002). Recently, intelligent systems have been developed to reach a deeper understanding of team behaviors, i.e., collective tactical behavior (Passos et al, 2011;Frencken et al, 2011). Through automatic tracking of player movements, it is possible to identify with reasonable accuracy the players' positions on the field.…”

Section: Introduction 123456mentioning

confidence: 99%

Intelligent systems for analyzing soccer games: The weighted centroid

Clemente¹,

Couceiro²,

Martins³

et al. 2014

ing.inv.

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New, intelligent systems have been developed recently to improve the quality of match analysis. These systems analyze the tactical behavior of the teams. However, the existing methods leave room for improvement. Thus, the main goal of this study is to refine the team centroid metric by considering all of the players on the team and the ball position. Furthermore, this study analyzes the relationship between the centroids of the two opposing teams. One 11-on-11 soccer match was analyzed to test the new centroid algorithm. The results provided strong evidence of the positive relation between the centroids of the two teams over time in the ‫-ݔ‬axis ‫ݎ(‬ ௦ = 0.781) and the ‫-ݕ‬axis ‫ݎ(‬ ௦ = 0.707). This study confirmed the results of previous studies that analyzed the relationship between team centroids. Furthermore, it was possible to prove the effectiveness of the new tactical metric and its relevance for adding information during a match.Keywords: Match Analysis, Soccer, Tactics, Collective Behavior, Centroid. RESUMENNuevos sistemas inteligentes se han desarrollado recientemente, con el fin de mejorar la calidad de análisis del partido. Estos sistemas basan su análisis en el comportamiento táctico de los equipos, sin embargo, todos los métodos innovadores necesitan algunos cambios para aumentar su potencial en las implicaciones prácticas. Por lo tanto, el objetivo principal de este trabajo es proponer una actualización del centroide y métrica del equipo, teniendo en cuenta a todos los jugadores del equipo y también la posición de la bola, además, tiene como objetivo analizar la relación entre los centroides de los equipos oponentes. Un partido de fútbol 11, fue analizado con el fin de aplicar el nuevo algoritmo del centroide; los principales resultados mostraron una fuerte evidencia de la relación positiva entre centroides en el eje x ‫ݎ(‬ ௦ = 0.781) y el eje y ‫ݎ(‬ ௦ = 0.707). Este estudio, confirma trabajos previos que analizaron la relación positiva y fuerte entre equipos centroides. Además, fue posible demostrar la pertinencia de la nueva actualización de métrica táctica y su importancia para el aumento de la información en las aplicaciones prácticas durante el partido.Palabras clave: análisis del partido de fútbol, táctica, comportamiento colectivo y Centroide.

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Networks as a novel tool for studying team ball sports as complex social systems

Cited by 179 publications

References 9 publications

A systemic overview of football game: The principles behind the game — ; ; Mendes, Rui Sousa; Figueiredo, António José

A systemic overview of football game: The principles behind the game — ; ; Mendes, Rui Sousa; Figueiredo, António José

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Intelligent systems for analyzing soccer games: The weighted centroid

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