The Sequencing of Game Complexes in Women’s Volleyball

Abstract

In volleyball, each team must use no more than three hits to return the ball to the opponent's court. This unique aspect of volleyball means that playing actions can be grouped into different complexes, mainly based on the initial defensive action. The purpose of this study was to find out which game complexes are most common in women's volleyball and how those phases are sequenced. The study analyzed 4,252 complexes from 1,176 rallies or points (seven matches, with 27 sets in total) in the 2015 and 2016 Copa de la Reina. The variables analyzed were the game complex, complex efficacy, and number of complexes per point. Two Markov chains were defined to visualize how the complexes are sequenced. The first chain looked only at categories of the game complex variable, taking seven states and 24 transitions into consideration. The second chain combined the game complex and complex efficacy variables, taking 26 states and 125 transitions into consideration. These chains provide practical information regarding which sequences of complexes occur most frequently in the competition analyzed, and therefore which ones should be the main focus in training sessions. The most frequent sequence was Complex 0 (the serve), followed by Complex I with in-system attack, followed by Complex II without continuity.

Últimas Tendencias en el Análisis Técnico-Táctico del Voleibol de Alto Nivel. Revisión Sistemática (Latest Trends in Technical-Tactical Analysis of High-Level Volleyball. Systematic Review)

“…Estas, por un lado, dan continuidad a las metodologías y variables de rendimiento planteadas por Silva et al (2016) y por otro ofrecen nuevas propuestas y variables de estudio. A modo de ejemplo, dentro de las primeras se encuentran las que analizan los factores de rendimiento por posición (Conti et al, 2018;Drikos et al, 2022a;Matias et al, 2021a;Sanchez et al, 2019); estudian el rendimiento por gesto técnico (Paulo, et al, 2018;Rodrigues Rocha et al, 2020;Sotiropoulos et al, 2021a;Valhondo et al, 2018); o profundizan en las fases del juego (García de Hileno et al, 2020;Laporta et al, 2018a). Dentro de las segundas, se identifican propuestas que utilizan el análisis de redes sociales para comprender las relaciones durante el juego (Laporta et al, 2018a;Martins et al, 2021a;Rodrigues Rocha et al, 2022), calculan la entropía para analizar la variabilidad (Ramos et al, 2017a) o analizan las variables contextuales en profundidad (Drikos et al, 2022b;García de Alcaraz & Marcelino, 2017;Yu et al, 2020).…”

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

“…To the best of our knowledge, only one study assessed the sequencing of game complexes: using Markov chains, the authors showed that, in Spanish high-level women's volleyball, the most likely sequences were K0-KI-KII, K0-KI-KIV, and K0-KI-KV. 23 While in Markov chains the transition probabilities of an event occurring depend only on the immediately preceding event, Social Network Analysis or SNA (through Eigenvector Centrality), allows understanding the relationships between nodes behaviours, interactions and relative importance in a global context, 24,25 where each node is weighted on the basis of n preceding or ensuing events. 26 Despite the growing interest in how the game sequence unfold in an attempt to answer how offensive patterns develop in teams sports, 27,28 to the best of our knowledge, only one study analysed game sequences in volleyball, 23 which constitutes a gap in the literature.…”

“…23 While in Markov chains the transition probabilities of an event occurring depend only on the immediately preceding event, Social Network Analysis or SNA (through Eigenvector Centrality), allows understanding the relationships between nodes behaviours, interactions and relative importance in a global context, 24,25 where each node is weighted on the basis of n preceding or ensuing events. 26 Despite the growing interest in how the game sequence unfold in an attempt to answer how offensive patterns develop in teams sports, 27,28 to the best of our knowledge, only one study analysed game sequences in volleyball, 23 which constitutes a gap in the literature. Furthermore, the study of game sequencing may provide useful information for coaches to better organise and manage the training sessions, especially by understanding which game complexes most likely follow other game complexes (i.e.…”

Influence of different playing styles among the top three teams on action zones in the World Cup in 2018 using a Markov state transition matrix

“…As a vital algorithm for the mathematical simulation of performance diagnoses, the Markov chain model has been applied to diagnostic analysis of net sports, such as table tennis (Zhang, 2003;Pfeiffer et al, 2010;Wenninger and Lames, 2016), tennis (Lames, 1991), and volleyball (Miskin et al, 2010;Hileno et al, 2020). In invasion games, the Markov chain state transition matrix can be used to describe and diagnose important passes in football (Liu and Hohmann, 2013b;Liu, 2014) or important connections in frisbee (Lam et al, 2021).…”