The role of hypernetworks as a multilevel methodology for modelling and understanding dynamics of team sports performance
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/20086 |
Resumo: | Despite its importance in many academic fields, traditional scientific methodologies struggle to cope with analysis of interactions in many complex adaptive systems, including team sports. Inherent features of such systems (e.g. emergent behaviours) require a more holistic approach to measurement and analysis for understanding system properties. Complexity sciences encompass a holistic approach to research on collective adaptive systems, which integrates concepts and tools from other theories and methods (e.g. ecological dynamics and social network analysis) to explain functioning of such systems in their natural environments. Multilevel networks and hypernetworks comprise novel and potent methodological tools for assessing team dynamics at more sophisticated levels of analysis, increasing their potential to impact on competitive performance in team sports. Here, we discuss how concepts and tools derived from studies of multilevel networks and hypernetworks have the potential for revealing key properties of sports teams as complex, adaptive social systems. This type of analysis can provide valuable information on team performance, which can be used by coaches, sport scientists and performance analysts for enhancing practice and training. We examine the relevance of network sciences, as a sub-discipline of complexity sciences, for studying the dynamics of relational structures of sports teams during practice and competition. Specifically, we explore the benefits of implementing multilevel networks, in contrast to traditional network techniques, highlighting future research possibilities. We conclude by recommend- ing methods for enhancing the applicability of hypernetworks in analysing team dynamics at multiple levels. |
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The role of hypernetworks as a multilevel methodology for modelling and understanding dynamics of team sports performanceDespite its importance in many academic fields, traditional scientific methodologies struggle to cope with analysis of interactions in many complex adaptive systems, including team sports. Inherent features of such systems (e.g. emergent behaviours) require a more holistic approach to measurement and analysis for understanding system properties. Complexity sciences encompass a holistic approach to research on collective adaptive systems, which integrates concepts and tools from other theories and methods (e.g. ecological dynamics and social network analysis) to explain functioning of such systems in their natural environments. Multilevel networks and hypernetworks comprise novel and potent methodological tools for assessing team dynamics at more sophisticated levels of analysis, increasing their potential to impact on competitive performance in team sports. Here, we discuss how concepts and tools derived from studies of multilevel networks and hypernetworks have the potential for revealing key properties of sports teams as complex, adaptive social systems. This type of analysis can provide valuable information on team performance, which can be used by coaches, sport scientists and performance analysts for enhancing practice and training. We examine the relevance of network sciences, as a sub-discipline of complexity sciences, for studying the dynamics of relational structures of sports teams during practice and competition. Specifically, we explore the benefits of implementing multilevel networks, in contrast to traditional network techniques, highlighting future research possibilities. We conclude by recommend- ing methods for enhancing the applicability of hypernetworks in analysing team dynamics at multiple levels.Springer2020-03-12T11:35:45Z2019-04-23T00:00:00Z2019-04-232020-03-12T11:34:53Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/20086eng0112-164210.1007/s40279-019-01104-xRibeiro, J.Davids, K.Araújo, D.Silva, P.Ramos, J.Lopes, R. J.Garganta, J.info:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:44:43Zoai:repositorio.iscte-iul.pt:10071/20086Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:21:15.383938Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
The role of hypernetworks as a multilevel methodology for modelling and understanding dynamics of team sports performance |
title |
The role of hypernetworks as a multilevel methodology for modelling and understanding dynamics of team sports performance |
spellingShingle |
The role of hypernetworks as a multilevel methodology for modelling and understanding dynamics of team sports performance Ribeiro, J. |
title_short |
The role of hypernetworks as a multilevel methodology for modelling and understanding dynamics of team sports performance |
title_full |
The role of hypernetworks as a multilevel methodology for modelling and understanding dynamics of team sports performance |
title_fullStr |
The role of hypernetworks as a multilevel methodology for modelling and understanding dynamics of team sports performance |
title_full_unstemmed |
The role of hypernetworks as a multilevel methodology for modelling and understanding dynamics of team sports performance |
title_sort |
The role of hypernetworks as a multilevel methodology for modelling and understanding dynamics of team sports performance |
author |
Ribeiro, J. |
author_facet |
Ribeiro, J. Davids, K. Araújo, D. Silva, P. Ramos, J. Lopes, R. J. Garganta, J. |
author_role |
author |
author2 |
Davids, K. Araújo, D. Silva, P. Ramos, J. Lopes, R. J. Garganta, J. |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Ribeiro, J. Davids, K. Araújo, D. Silva, P. Ramos, J. Lopes, R. J. Garganta, J. |
description |
Despite its importance in many academic fields, traditional scientific methodologies struggle to cope with analysis of interactions in many complex adaptive systems, including team sports. Inherent features of such systems (e.g. emergent behaviours) require a more holistic approach to measurement and analysis for understanding system properties. Complexity sciences encompass a holistic approach to research on collective adaptive systems, which integrates concepts and tools from other theories and methods (e.g. ecological dynamics and social network analysis) to explain functioning of such systems in their natural environments. Multilevel networks and hypernetworks comprise novel and potent methodological tools for assessing team dynamics at more sophisticated levels of analysis, increasing their potential to impact on competitive performance in team sports. Here, we discuss how concepts and tools derived from studies of multilevel networks and hypernetworks have the potential for revealing key properties of sports teams as complex, adaptive social systems. This type of analysis can provide valuable information on team performance, which can be used by coaches, sport scientists and performance analysts for enhancing practice and training. We examine the relevance of network sciences, as a sub-discipline of complexity sciences, for studying the dynamics of relational structures of sports teams during practice and competition. Specifically, we explore the benefits of implementing multilevel networks, in contrast to traditional network techniques, highlighting future research possibilities. We conclude by recommend- ing methods for enhancing the applicability of hypernetworks in analysing team dynamics at multiple levels. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-04-23T00:00:00Z 2019-04-23 2020-03-12T11:35:45Z 2020-03-12T11:34:53Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/20086 |
url |
http://hdl.handle.net/10071/20086 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0112-1642 10.1007/s40279-019-01104-x |
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info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Springer |
publisher.none.fl_str_mv |
Springer |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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