Predictive factors of the attack efficacy: the case of the Brazilian women’s Volleyball League champion team

Abstract

The aim was to identify the predictive factors of the attack efficacy of the Brazilian women’s League Champion team according to the level of performance of the opposing team.The sample was composed of the observation of 1137 attacks in 21 games of the 2015-2016 Brazilian women’s Volleyball League champion team. The results were significant to identify the predictive factors of the attack efficacy against high (.2=110.562; .<0.00001), intermediate (.2=64.134; .<0.00001) and low (.2=62.137; .<0.00001) performance opponents. Thus, it is concluded that when playing against high- performance teams, powerful attack for position 6 and second attack tempo increase the chances of attack point; powerful attacks for position 1 and 5 reduce the chances of game continuation; and powerful attack for position 6 increases the chances of blocking. In addition, in games against intermediate-performance teams, reception that allows organized attack without all attack options reduces the chances of attack point and game continuation, while the reception effect did not seem to be a predictive factor of the attack efficacy in games against high- and low-performance opponents and, finally, in games against low-performance teams, powerful attack for position 1 reduces the chances of game continuation and attack blocking.

Sequence and efficacy of game complexes in high-level women’s volleyball: A novel perspective through Social Network Analysis

“…39 Furthermore, with the insertion attack efficacy in each game complex, positive associations of KI, KII, KIII(1), KIII(2), KV(1) and KV(2) with point (E2), show the importance of adopting some risk in the serve and minimising errors in attack. 14,21,40,41 Using SNA and Eigenvector Centrality, in addition to providing an overview of all game complexes, [14][15][16][17] reinforced the need to investigate less well-studied complexes (i.e. KIII, KIV and KV).…”

“…39 Furthermore, with the insertion attack efficacy in each game complex, positive associations of KI, KII, KIII(1), KIII(2), KV(1) and KV(2) with point (E2), show the importance of adopting some risk in the serve and minimising errors in attack. 14,21,40,41…”

Social Network Analysis: Understanding Volleyball Dynamics through Match Opponents

“…Studies on match analysis in sports currently indicate a correlation between performance and game location [11,12], player experience [13,14], type of game played [13,15] game rules [15,16], offensive and defensive phases [4,17], team level [11,18], and other aspects inherent to the game context. Furthermore, it is observed that the analysis of tactical behaviors, for the most part, results from the interpretation of general metrics [19][20][21], examining the team's tactical behaviors that specify success or failure in the match [22][23][24].…”

“…In this context, the analysis of Complex I in volleyball underscores a relationship between reception and subsequent actions, such as the setting effectiveness [3,32], attack tempo [4,31,33], attack effect [10,19,33,34], and blocker number [4,9,33]. Furthermore, several studies indicate an association or prediction [23,24,33,[35][36][37] between the game actions of complex I, highlighting that receptions that allow an organized attack, quick settings, and powerful attacks culminate in attack point [33,[38][39][40].…”