Cargando…
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 analy...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894390/ https://www.ncbi.nlm.nih.gov/pubmed/36730279 http://dx.doi.org/10.1371/journal.pone.0280365 |
_version_ | 1784881727720652800 |
---|---|
author | Rocha, Augusto Cezar Rodrigues Laporta, Lorenzo Rodrigues, Geovana Pires Guimarães, Juracy da Silva do Nascimento, Marcos Henrique Rodrigues, Marcelo Couto Jorge Leonardi, Thiago José de Lira, Claudio Andre Barbosa Castro, Henrique de Oliveira Costa, Gustavo De Conti Teixeira |
author_facet | Rocha, Augusto Cezar Rodrigues Laporta, Lorenzo Rodrigues, Geovana Pires Guimarães, Juracy da Silva do Nascimento, Marcos Henrique Rodrigues, Marcelo Couto Jorge Leonardi, Thiago José de Lira, Claudio Andre Barbosa Castro, Henrique de Oliveira Costa, Gustavo De Conti Teixeira |
author_sort | Rocha, Augusto Cezar Rodrigues |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9894390 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-98943902023-02-03 Inter e intra-variability of the best ranked teams: A network analysis in male high-level volleyball Rocha, Augusto Cezar Rodrigues Laporta, Lorenzo Rodrigues, Geovana Pires Guimarães, Juracy da Silva do Nascimento, Marcos Henrique Rodrigues, Marcelo Couto Jorge Leonardi, Thiago José de Lira, Claudio Andre Barbosa Castro, Henrique de Oliveira Costa, Gustavo De Conti Teixeira PLoS One Research Article 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. Public Library of Science 2023-02-02 /pmc/articles/PMC9894390/ /pubmed/36730279 http://dx.doi.org/10.1371/journal.pone.0280365 Text en © 2023 Rocha et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Rocha, Augusto Cezar Rodrigues Laporta, Lorenzo Rodrigues, Geovana Pires Guimarães, Juracy da Silva do Nascimento, Marcos Henrique Rodrigues, Marcelo Couto Jorge Leonardi, Thiago José de Lira, Claudio Andre Barbosa Castro, Henrique de Oliveira Costa, Gustavo De Conti Teixeira Inter e intra-variability of the best ranked teams: A network analysis in male high-level volleyball |
title | Inter e intra-variability of the best ranked teams: A network analysis in male high-level volleyball |
title_full | Inter e intra-variability of the best ranked teams: A network analysis in male high-level volleyball |
title_fullStr | Inter e intra-variability of the best ranked teams: A network analysis in male high-level volleyball |
title_full_unstemmed | Inter e intra-variability of the best ranked teams: A network analysis in male high-level volleyball |
title_short | Inter e intra-variability of the best ranked teams: A network analysis in male high-level volleyball |
title_sort | inter e intra-variability of the best ranked teams: a network analysis in male high-level volleyball |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894390/ https://www.ncbi.nlm.nih.gov/pubmed/36730279 http://dx.doi.org/10.1371/journal.pone.0280365 |
work_keys_str_mv | AT rochaaugustocezarrodrigues intereintravariabilityofthebestrankedteamsanetworkanalysisinmalehighlevelvolleyball AT laportalorenzo intereintravariabilityofthebestrankedteamsanetworkanalysisinmalehighlevelvolleyball AT rodriguesgeovanapires intereintravariabilityofthebestrankedteamsanetworkanalysisinmalehighlevelvolleyball AT guimaraesjuracydasilva intereintravariabilityofthebestrankedteamsanetworkanalysisinmalehighlevelvolleyball AT donascimentomarcoshenrique intereintravariabilityofthebestrankedteamsanetworkanalysisinmalehighlevelvolleyball AT rodriguesmarcelocoutojorge intereintravariabilityofthebestrankedteamsanetworkanalysisinmalehighlevelvolleyball AT leonardithiagojose intereintravariabilityofthebestrankedteamsanetworkanalysisinmalehighlevelvolleyball AT deliraclaudioandrebarbosa intereintravariabilityofthebestrankedteamsanetworkanalysisinmalehighlevelvolleyball AT castrohenriquedeoliveira intereintravariabilityofthebestrankedteamsanetworkanalysisinmalehighlevelvolleyball AT costagustavodecontiteixeira intereintravariabilityofthebestrankedteamsanetworkanalysisinmalehighlevelvolleyball |