Coexistence of Distinct Performance Models in High-Level Women's Volleyball

Inter e intra-variability of the best ranked teams: A network analysis in male high-level volleyball

The present research objective was to analyze the offensive phase from Complex I in high-level male volleyball teams in a macro- and micro-level view, through the inter e intra-team variability analysis of eight best teams of the 2018 Men's Volleyball World Championship over the social network analysis and eigenvector centrality. The sample consisted of 22 matches and 2,743 offensive actions, resulting in 8 sub-networks with 368 nodes and 6221 edges. The results showed from macro view the variables that presented highest centrality values were Attack Zone 4 (range 0.56-0.90), Attack Tempo 2 (0.65-0.87), Power Attack (0.62-0.94), No Touch Block (0.61-1), Attack Effect Continuity (0.59-0.94), and Middle Blocker Centralized (0.60-0.95). In a micro view, Reception Effect, Play Position, Reception Zone, and Block Composition showed high variability in each sub-network. The intra- and inter-team variability presented the importance of to respect each team idiosyncrasies and to consider the different approaches to the game and success.

Match Analysis in Team Ball Sports: An Umbrella Review of Systematic Reviews and Meta-Analyses

Background

Match analysis has evolved exponentially over the past decades in team sports resulting in a significant number of published systematic reviews and meta-analyses. An umbrella review of the available literature is needed to provide an integrated overview of current knowledge and contribute to more robust theoretical explanations of team performance.

Methods

The Web of Science (all databases), PubMed, Cochrane Library (Cochrane Database of Systematic Reviews), Scopus, and SPORTDiscus databases were searched for relevant publications prior to 19 February 2021. Appraisal of the methodological quality of included articles was undertaken using the tool for Assessing the Methodological Quality of Systematic Reviews (AMSTAR-2). Twenty-four studies were reviewed that met the following criteria: (1) contained relevant data from match analyses in team ball sports; (2) were defined as systematic reviews or/and meta-analyses; and (3) were written in the English language.

Results

The overall methodological quality of the 24 included reviews, obtained through the AMSTAR-2, revealed very low confidence ratings (Critically Low, n = 12) for the results of most systematic reviews of match analyses in team ball sports. Additionally, the results showed that research is focused mainly on four levels of analysis: (1) dyadic (microlevel); (2) individual (molecular level; predominant); (3) group (mesolevel), and (4) team dynamics (macrolevel). These levels of analysis included tactical, technical, physical, and psychosocial variables. Team performance was contextualized at two levels, with reference to: (1) match context (e.g. match status, match location, match period, quality of opposition) and (2) sociodemographic and environmental constraints (sex, age groups, competitive level, altitude, temperature, pitch surface).

Conclusions

The evolution of methods for match analysis in team ball sports indicates that: (1) an individual-level performance analysis was predominant; (2) the focus on intermediate levels of analysis, observing performance in dyadic and group interactions, has received less attention from researchers; (3) neglected areas of research include psychosocial aspects of team sports and women’s performance; and (4) analyses of match contexts need greater depth.

Registration: The protocol was registered in the International Platform of Registered Systematic Review and Meta-Analysis Protocols with the number 202080067 and the DOI number https://doi.org/10.37766/inplasy2020.8.0067.

The Attack-Block-Court Defense Algorithm: A New Volleyball Index Supported by Data Science

Spiker–blocker encounters are a key moment for determining the result of a volleyball rally. The characterization of such a moment using physical–statistical parameters allows us to reproduce the possible ball’s trajectory and then make calculations to set up the defense in an optimal way. In this work, we present a computational algorithm that shows the possible worst scenarios of ball trajectories for a volleyball defense, in terms of the covered area by the block and the impact time of the backcourt defense to contact the ball before it reaches the floor. The algorithm is based on the kinematic equations of motion, trigonometry, and statistical parameters of the players. We have called it the Attack-Block-Court Defense algorithm (the ABCD algorithm), since it only requires the 3D-coordinates of the attacker and the blocker, and a discretized court in a number of cells. With those data, the algorithm calculates the percentage of the covered area by the blocker and the time at which the ball impacts the court (impact time). More specifically, the structure of the algorithm consists of setting up the spiker’s and blocker’s locations at the time the spiker hits the ball, and then applying the kinematic equations to calculate the worst scenario for the team in defense. The case of a middle-hitter attack with a single block over the net is simulated, and an analysis of the space of input variables for such a case is performed. We found a strong dependence on the average impact time and the covered area on both the attack–block height’s ratio and the attack height. The standard deviation of the impact time was the variable that showed more asymmetry, respecting the input variables. An asymmetric case considering more variables with a wing spiker and three blockers is also shown, in order to illustrate the potential of the model in a more complex scenario. The results have potential applications, as a supporting tool for coaches in the design of customized defense or attack systems, in the positioning of players according to the prior knowledge of the opponent team, and in the development of replay and video-game technologies in multimedia systems.

Mathematical Models to Measure the Variability of Nodes and Networks in Team Sports

Pattern analysis is a widely researched topic in team sports performance analysis, using information theory as a conceptual framework. Bayesian methods are also used in this research field, but the association between these two is being developed. The aim of this paper is to present new mathematical concepts that are based on information and probability theory and can be applied to network analysis in Team Sports. These results are based on the transition matrices of the Markov chain, associated with the adjacency matrices of a network with n nodes and allowing for a more robust analysis of the variability of interactions in team sports. The proposed models refer to individual and collective rates and indexes of total variability between players and teams as well as the overall passing capacity of a network, all of which are demonstrated in the UEFA 2020/2021 Champions League Final.

Unilateral versus Bilateral Landing after Spike Jumps in Male and Female Volleyball: A Systematic Review

Background: The spike is a key action in volleyball, and the landing technique and its asymmetries are commonly associated with an increased risk of injury. Objectives: The aim of this systematic review was to assess how male and female volleyball players land (i.e., unilaterally, or bilaterally) after spike jumps in matches and analytical settings (field or laboratory). Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines were followed, with eligibility criteria defined according to participants, interventions, comparators, study design (PICOS): (p) healthy indoor volleyball players of any sex, age group, or competitive level; (i) exposure to landing after spike actions during official matches AND/OR simulated 6 vs. 6 games AND/OR analytical training conditions AND/OR laboratorial experiments; (c) not mandatory; (o) data on landing mechanics after spike actions, including reporting of whether the landing was unilateral or bilateral; (s) no restrictions imposed on study design. Searches were performed in seven electronic databases (Cochrane Library, EBSCO, PubMed, Scielo, Scopus, SPORTDiscus, and Web of Science) on 23 April 2021. Results: Automated searches provided 420 results. Removal of 119 duplicates resulted in 301 records being screened for titles and abstracts. A total of 25 studies were eligible for full-text analysis. Of these, eight studies were deemed eligible for inclusion in the review. Studies showed that (i) attackers landed asymmetrically 68% of the times (61% left leg, 7% right leg); (ii) bilateral asymmetries were observed for the hip, knee, and ankle joints; (iii) bilateral asymmetries were observed even when players were instructed to land evenly on two feet; (iv) landing contact of the leg opposite to the hitting arm preceded the contact of the homolateral leg. One match analysis study showed that men landed more often on the left (31.5%) or right foot (8.5%) than women (23.7% and 1.6%). Conclusions: Studies analyzing spike landing showed a prevalence of unilateral landings (mostly the left leg first, for right-handed players) in men and women but more prevalently in men. Registration INPLASY202140104, DOI: 10.37766/inplasy2021.4.0104.