Inter e intra-variability of the best ranked teams : a network analysis in male high-level volleyball
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/267728 |
Resumo: | The present research objective was to analyze the offensive phase from Complex I in highlevel 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. |
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Rocha, Augusto Cezar RodriguesLaporta, Lorenzo IopRodrigues, Geovana PiresGuimarães, Juracy da SilvaNascimento, Marcos Henrique doRodrigues, Marcelo Couto JorgeLeonardi, Thiago JoséLira, Claudio Andre Barbosa deCastro, Henrique de OliveiraCosta, Gustavo De Conti Teixeira2023-11-28T03:23:27Z20231932-6203http://hdl.handle.net/10183/267728001175051The present research objective was to analyze the offensive phase from Complex I in highlevel 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.application/pdfengPloS one. San Francisco. Vol. 18, no. 2 (Feb. 2023), e0280365, 16 p.VoleibolPerformanceInter e intra-variability of the best ranked teams : a network analysis in male high-level volleyballEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001175051.pdf.txt001175051.pdf.txtExtracted Texttext/plain56497http://www.lume.ufrgs.br/bitstream/10183/267728/2/001175051.pdf.txt51fc2ca4b34c8c33e1c060d19b635e17MD52ORIGINAL001175051.pdfTexto completo (inglês)application/pdf2860949http://www.lume.ufrgs.br/bitstream/10183/267728/1/001175051.pdf1bde22f613afaf9dc0327bb0ce35587aMD5110183/2677282024-02-17 05:55:33.473811oai:www.lume.ufrgs.br:10183/267728Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2024-02-17T07:55:33Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
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 |
spellingShingle |
Inter e intra-variability of the best ranked teams : a network analysis in male high-level volleyball Rocha, Augusto Cezar Rodrigues Voleibol Performance |
title_short |
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_sort |
Inter e intra-variability of the best ranked teams : a network analysis in male high-level volleyball |
author |
Rocha, Augusto Cezar Rodrigues |
author_facet |
Rocha, Augusto Cezar Rodrigues Laporta, Lorenzo Iop Rodrigues, Geovana Pires Guimarães, Juracy da Silva Nascimento, Marcos Henrique do Rodrigues, Marcelo Couto Jorge Leonardi, Thiago José Lira, Claudio Andre Barbosa de Castro, Henrique de Oliveira Costa, Gustavo De Conti Teixeira |
author_role |
author |
author2 |
Laporta, Lorenzo Iop Rodrigues, Geovana Pires Guimarães, Juracy da Silva Nascimento, Marcos Henrique do Rodrigues, Marcelo Couto Jorge Leonardi, Thiago José Lira, Claudio Andre Barbosa de Castro, Henrique de Oliveira Costa, Gustavo De Conti Teixeira |
author2_role |
author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Rocha, Augusto Cezar Rodrigues Laporta, Lorenzo Iop Rodrigues, Geovana Pires Guimarães, Juracy da Silva Nascimento, Marcos Henrique do Rodrigues, Marcelo Couto Jorge Leonardi, Thiago José Lira, Claudio Andre Barbosa de Castro, Henrique de Oliveira Costa, Gustavo De Conti Teixeira |
dc.subject.por.fl_str_mv |
Voleibol Performance |
topic |
Voleibol Performance |
description |
The present research objective was to analyze the offensive phase from Complex I in highlevel 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. |
publishDate |
2023 |
dc.date.accessioned.fl_str_mv |
2023-11-28T03:23:27Z |
dc.date.issued.fl_str_mv |
2023 |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
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info:eu-repo/semantics/publishedVersion |
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http://hdl.handle.net/10183/267728 |
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1932-6203 |
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001175051 |
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http://hdl.handle.net/10183/267728 |
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eng |
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eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
PloS one. San Francisco. Vol. 18, no. 2 (Feb. 2023), e0280365, 16 p. |
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info:eu-repo/semantics/openAccess |
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openAccess |
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