Inter-player Variability Within the Same Positional Status in High-level Men's Volleyball

Martins, João Bernardo; Afonso, José; Mendes, Ademilson; Santos, Letícia; Mesquita, Isabel

doi:10.47197/retos.v46.93624

Cited by 3 publications

(3 citation statements)

References 29 publications

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“…The primary emphasis is on positional disparities between players, as well as inter-team and intra-team variability. The goal is to gain a better understanding of how specific scenarios influence the choice of strategy and player behavior on the field [14,29,30,31,32,33].…”

Section: Exploring Variability In Game Scenarios and Positional Diffe...mentioning

confidence: 99%

“…The observed variability both within and among teams highlighted the imperative of recognizing each team's distinct traits and the necessity of adopting diverse strategies towards gameplay and achievement. In separate studies, network analysis was employed to pinpoint the paramount parameters governing player interactions in volleyball [15,16], with some incorporating the use of Gephi software [17].…”

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confidence: 99%

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Statistical match reports of the 2022 volleyball World Championship in the context of network analysis with Gephi

Iermakov,

Yermakova,

Wnorowski

2023

pcult

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Background and Study Aim. Modern volleyball teams participating in tournaments provide extensive statistical data about their actions. These data are available for analysis and represent a valuable source for assessing the potential and future success of both individual athletes and teams as a whole. In this context, tools such as Gephi become particularly valuable for visualizing and analyzing events at high-level tournaments. Our study aims to create and analyze network models of interaction among men's volleyball teams during the qualifying matches of the 2022 World Championship using the Gephi software. Materials and Methods. For the research, data were obtained from a volleyball statistics website renowned for its extensive database. The study centered on Group C, comprising the teams: Poland, USA, Mexico, and Bulgaria. Data from six matches were extracted into Microsoft Excel tables and then converted into CSV format. The data from these tables were processed using the PyCharm programming environment and Python code. Visualization and analysis of the data were conducted using Gephi. Results. The results of the data processing highlight the professional expertise of the teams. The average values for all primary metrics underscore the teams' proficiency in executing fundamental actions at an elevated level. Eigenvector centrality helps determine the significance of nodes in the graph. The graph's density is 0.601, suggesting a relatively dense network of connections within the team. This indicates that volleyball players frequently engage with one another and share information on the court. Such extensive interaction can lead to enhanced coordination and efficiency in team actions. The parameter ε has a value of 1.0E-4, denoting high computational precision. The average interaction degree among volleyball players stands at 46.244. This measure denotes the interaction intensity among team members, hinting at the overall court activity. The modularity measure is 0.483, which signals the structural organization of the graph rooted in modularity. The graph comprises 5 modular communities, hinting at shared characteristics and cohesion among players within these groups. The HITS (Hyperlink-Induced Topic Search) metric assesses the node significance in the graph in terms of hubs and authorities. High HITS values pinpoint pivotal players acting as hubs, signifying their numerous connections with fellow teammates. Such players are crucial for facilitating information flow and coordination within the squad. Conclusions. Utilizing statistical match reports in volleyball, combined with the Gephi software, offers a deeper insight into the dynamics of player interactions. This aids in pinpointing key players, refining team strategies, and enhancing court coordination. Coaches are advised to leverage these tools for an in-depth evaluation of gameplay instances and to make informed decisions. Network analysis methodologies might soon be indispensable tools in the contemporary coaching toolkit.

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Section: Exploring Variability In Game Scenarios and Positional Diffe...mentioning

confidence: 99%

mentioning

confidence: 99%

Statistical match reports of the 2022 volleyball World Championship in the context of network analysis with Gephi

Iermakov,

Yermakova,

Wnorowski

2023

pcult

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“…The development of self-confidence leads to positive changes in one's environment, (Corbin, 2021). The philosophy of selffulfilling prophecy and self-efficacy is closely related to selfconfidence, (Martins et al, 2022). Every human has some level of self-confidence, whether it is high or low.…”

Section: Introductionmentioning

confidence: 99%

Self-Confidence Conceptual Model Development in Volleyball Learning Courses

Astuti,

Zulbahri,

Lawanis

et al. 2023

Retos

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The research was motivated by the problem of students in the Physical Education, Health and Recreation Study Program not exhibiting optimal self-confidence, particularly the confidence to speak in front of the class during lecture activities. Self-confidence is an aspect of the human psyche that must be nurtured and developed. Self-confidence denotes the ability to do something confidently and without fear of failure. Confidence is also part of the subconscious and is unaffected by emotions and feelings. Therefore, it requires a method that can be accomplished by controlling emotions, feelings, and imagery. The volleyball learning course necessitates good psychological conditions for students to be confident when practicing in small groups and later when conducting teaching practice at school. In this course students are equipped with basic techniques in playing volleyball and how to construct volleyball learning tools, then students are able to practice teaching in small groups. This study employs a qualitative approach with a classroom action research design that follows the lecture schedule. The research procedure is divided into two cycles, with each cycle consisting of five stages: planning, action, observation, evaluation, and reflection. This research was conducted in two cycles and the time required was 5 weeks for each cycle so that the total time required was 10 weeks with two cycles. The research subjects were 50 students who took the volleyball learning course. Data collection methods include observations and interviews. The results of the study show that in an effort to increase student self-confidence, the strategy chosen is role-playing which provides broad opportunities for students to explore themselves in order to be able to demonstrate their quality in front of other friends to become teachers in the teaching practice of the material chosen by each student. In this study, the role-playing technique was seen to be successful in increasing the self-confidence of the students. Keyword: self-confidence, Role-playing, Learning, Volleyball

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Attack efficiency in first league men’s volleyball for playing positions, according to the value level of the teams

Mocanu,

Harabagiu,

Parvu

2024

ppcs

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Background and Study Purpose. The attack is a crucial technical element in scoring points in volleyball. This research aims to identify differences in attack efficiency and errors based on the value level of teams in the competitive system, considering different playing positions. Material and Methods. The analysis included 86 attacking players from the rosters of 12 teams in the men’s domestic first league. The distribution by positions was as follows: 37 outside hitters, 19 opposites, and 30 middle blockers. Statisticians from each team recorded the data using Data Volley software during three championship matches. For each player, the following parameters were interpreted: Attack Efficiency (E%), Error% (=), Blocked Attack% (/), Poor% (-), Blocked but Recovered% (!), Positive% (+), and Winning% (#). Attack efficiency was analyzed for each playing position across top teams (positions 1-4 in the final ranking), mid-level teams (positions 5-8), and lower-level teams (positions 9-12). Results. Across all three playing positions, top teams demonstrate higher percentages in attack efficiency, winning executions, and positive outcomes compared to average and lower-level teams. Top and average teams also have lower percentages of errors in attack executions. For the outside hitter position, no statistically significant superiority is observed between top and middle teams for any attack variable, indicating a balance in player performance. In the opposite hitter position, top and middle-level players show higher attack efficiency and direct point scores (Winning). They also have lower poor execution rates, despite the lack of statistical confirmation for superiority in many attack variables. Among all positions, top middle blockers exhibit a clear superiority over low-level teams across all attack variables. Conclusions. The findings of the study highlight the critical role of team value level in influencing attack efficiency and execution quality across different playing positions in volleyball. The results underscore the importance of strategic differentiation in training and game planning. This is especially crucial for teams aiming to optimize their performance. Coaches and trainers should focus on tailored approaches that address the specific strengths and weaknesses of each playing position. They should also consider the overall team value level in their strategies. This approach could lead to improved competitive outcomes and a more effective utilization of player potential across all levels of competition.

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Inter-player Variability Within the Same Positional Status in High-level Men's Volleyball

Cited by 3 publications

References 29 publications

Statistical match reports of the 2022 volleyball World Championship in the context of network analysis with Gephi

Statistical match reports of the 2022 volleyball World Championship in the context of network analysis with Gephi

Self-Confidence Conceptual Model Development in Volleyball Learning Courses

Attack efficiency in first league men’s volleyball for playing positions, according to the value level of the teams

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