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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.

montenegrin journal of sports science and medicine

A Comprehensive Mapping of High-Level Men’s Volleyball Gameplay through Social Network Analysis: Analysing Serve, Side-Out, Side-Out Transition and Transition