Inter-team variability in game play under critical game scenarios: a study in high-level men's volleyball using social network analysis

被引:0
|
作者
Martins, Joao Bernardo [1 ]
Afonso, Jose [1 ]
Mendes, Ademilson [1 ]
Santos, Leticia [1 ]
Mesquita, Isabel [1 ]
机构
[1] Univ Porto, Porto, Portugal
关键词
performance analysis; match analysis; team sports; game patterns; TECHNICAL ACTIONS; ENTROPY MEASURES; MATCH ANALYSIS; PERFORMANCE; FOOTBALL; ATTACK; REGULARITY; EFFICACY; LEAGUE;
D O I
暂无
中图分类号
F [经济];
学科分类号
02 ;
摘要
Critical scenarios are highly relevant to match analysis because they contribute to a better understanding of performance and provide essential information about team evolution. The goal of this study was to investigate inter-team variability in high-level men's volleyball during critical game scenarios (i.e., non-ideal setting conditions). Ten matches of the Men's 2019 Volleyball Nations League Finals (Russia, USA, Poland, Brazil, Iran, France) were analyzed (n = 649 plays). Six independent Eigenvector Centrality networks were created (632 nodes; 3507 edges) using Social Network Analysis. When playing under critical scenarios the top two ranked teams differed in side-out attack. Specifically, the USA presented quick attacks, mainly in zone 4, using both the strong attack and exploration of the block. Conversely, Russia presented a game with high attack tempos and strong attacks. The USA and Russia also differed from Poland and Brazil in their approach to the game, the latter two teams using a varied attack (between strong, exploited, and directed attacks). After one error in attack, most teams presented a game style characterized by strong attacks, although Russia played using exploration of the block. The study shows teams competing at the same competitive level have differences in game patterns. The variability in approaches to the attack in critical scenarios (e.g., under non-ideal setting conditions and/or after consecutive attack errors) revealed that teams find different solutions for similar problems. Findings imply that match analysis should focus on exploring inter-team differences in gameplay while being cautious when interpreting aggregate data.
引用
收藏
页码:1095 / 1105
页数:11
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