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A deeper understanding of the factors behind performance and their interactions is essential to promote better training practices. Notwithstanding, the focus often relies on the outcomes of players' actions (e.g., effi cacy rates), whereas the nature and variations of particular classes of actions remain largely unexplored. Our purpose was to conduct a systemic analysis of categorical game variables and their interactions using Social Network Analysis. Game actions were counted as nodes and their interactions as edges. Eigenvector centrality values were calculated for each node. Eight matches of the Men's World Cup 2015 were analysed, composing a total of 27 sets (1,209 rallies). Four game complexes were considered: Complex 0 (Serve), Complex I (Side-out), Complex II (Side-out transition) and Complex III (Transition). Results showed that teams frequently play in-system when in Complex I (i.e. under ideal conditions), but present reduced variation with regard to attack zones and tempos, whereas in Complex II teams most often play out-of-system. Based on these fi ndings, it was concluded that practicing with non-ideal conditions is paramount for good performance in Complex II. Furthermore, most literature combines Complex II and Complex III as a single unit (counter-attack); however, our results reinforce the notion that these two game complexes differ and should be analysed separately.

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In sports, it is often assumed that distinct game patterns may influence the outcome of the play differently. However, a few articles about men’s volleyball have suggested that play efficacy may rely more on the quality of individual attack actions, and not on game patterns. Therefore, the goal of this paper was to scrutinize if and how game patterns influence play efficacy in high-level women’s volleyball. Eigenvector Centrality was assessed to integrate direct and indirect relationships between games actions. Thirteen matches from the women’s World Grand Prix’2015 were analysed (46 sets; 2,016 plays). Actions were categorized according to game complex (K0 to KV) and three levels of the efficacy of each play: error, continuity, and point. The results showed that play efficacy was independent of game patterns (the central pattern was non-ideal setting conditions in all complexes and preference for using slow attacks in the extremities of the net). There were, however, some regularities for each game complex. For example, while in KI to KIII, Zone 4 was the most used attack zone, in KIV and KV there was a complete inversion to Zone 2. Moreover, results revealed that women’s volleyball games are more predictable in relation to the play space (attack zones) while increasing the risk through enhanced game speed (attack tempo), in comparison with what studies in men’s volleyball have shown. Future studies should consider situational variables (e.g., match status, home vs away matches), and individual players’ actions should be considered in order to understand their relationships with team patterns better.

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