The Attack in Volleyball from the Perspective of Social Network Analysis: Refining Match Analysis through Interconnectivity and Composite of Variables

Abstract

This study aimed to develop an instrument for analysing the attack in high-level volleyball considering the refined variables adjacent to the attack action, the interconnection between direct and indirect actions, the impact of the previous action, and the formation of composite variables. The game complexes were approached as interacting subsystems. The primary goal was to understand the influence of game actions adjacent to the attack. Three matches of a National Women’s 1st Division 2018/2019 (nine sets, 415 plays) were analysed, considering all game complexes (except attack coverage due to reduced occurrence). An Eigenvector Centrality network with 420 nodes and 7367 edges was created. The networks showed that ideal setting conditions, and strong attacks by the outside and opposite hitters without having received a perfect ball, were central in side-out. In transition, we highlight ideal setting conditions, preferences of the outside hitter, quick attacks in Z4, and high balls in Z2. This study is distinct because it considers different aspects related to the systemic review of the game by using composite variables and the actions prior to the attack. Of these results, we highlight that players attacked with slower tempos for the double action of receive-attack, and these were either preferably directed to the parallel or explored the block. Moreover, for the double defence-attack actions, attackers sought the soft spike in Z2, Z4, and Z8; and when two consecutive individual errors occurred, the players did not err but instead continued to attack to force the opponent’s error.

Inter-team variability in game play under critical game scenarios: a study in high-level men’s volleyball using social network analysis (Variabilidad entre equipos en el juego bajo escenarios críticos de juego: un estudio en voleibol masculino de alto ni

“…Table 1 presents the study variables. Volleyball is organized in seven co-dependent game complexes (Figure 1) with different game characteristics (Martins et al, 2021): Complex 0 (K0) or serve, Complex I (KI) or side-out, Complex II (KII) or side-out transition, Complex III (KIII) or transition, Complex IV (KIV) or attack coverage, Complex V (KV) or freeball, and Complex VI (KVI) or downball.…”

“…Two variables were considered for Complex 0. The first was type of serve (S), which had three categories (Martins et al, 2021): (i) power jump serve (PJS; with displacement and explosive jump and with ball rotation), (ii) standing serve (STS; no jump -serve in support), and (iii) jumping-float serve (JFLTS; no ball rotation and uniform trajectory). The second variable was serve efficacy (SE), which had five categories (Data Volley, 2019): (i) perfect -direct point ace (SE#), (ii) positive -one cannot see combined, only non-ideal setting conditions, usually only with the possibility of an attack (SE+), (iii) exclamatory -serve bulk but recovered (SE!…”

“…Non-ideal setting conditions in volleyball (i.e., where the team has a poor quality first touch and is consequently in a situation of high difficulty for the construction of the attack) offer one possible avenue for this analysis, as advocated by Laporta et al (2021). Another possibility for this type of analysis in volleyball is when errors occur consecutive to the attack because this puts the team in a pressure situation, as supported in literature (Martins, Afonso, Coutinho, Fernandes, & Mesquita, 2021).…”

“…During the months of training, weekly online sessions were held to respond to questions and to discuss arising issues. The first inter-reliability test was performed in an exploratory study of a play-off in the 2018/2019 Portuguese national championship (Martins et al, 2021). For all variables, Kappa values above 0.75 were obtained (ranging from .774 to .997).…”

Inter-player variability in game patterns in high-level women's volleyball: A study with Outside Hitters (Near vs. Away) using Social Network Analysis. [Variabilidad entre jugadores en los patrones de juego en el voleibol femenino de alto nivel: Un estudio con bateadores externos (Cerca versus Lejos) usando Análisis de Redes Sociales].

“…All the matches were analysed after being recorded in high definition (1080p) from the end of the court. The first inter-reliability test was part of an exploratory study of a play-off in the 2018/2019 Portuguese championship (Martins, Afonso, Coutinho, Fernandes, & Mesquita, 2021). Cohen's kappa values for all variables were above 0.75 (range: 0.774 to 0.997).…”