Data modeling for inter- and intra-individual stability of young swimmers’ performance: a longitudinal cluster analysis
Autor(a) principal: | |
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Data de Publicação: | 2020 |
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/10198/21956 |
Resumo: | The aims of this study were to classify, identify and follow-up young swimmers' performance and its biomechanical determinants during two competitive seasons (in seven different moments of assessment-M), and analyze the individual variations of each swimmer. Method: Thirty young swimmers (14 boys: 12.70 +/- 0.63 years-old; 16 girls: 11.72 +/- 0.71 years-old) were recruited. A set of anthropometric, kinematic, efficiency, hydrodynamic and mechanical power variables were assessed. Results: The cluster solution (i.e., number of ideal clusters for this sample) resulted in three clusters, which were named as: cluster 1 ("talented"), cluster 2 ("proficient"), and cluster 3 ("non-proficient"). The performance improved between moments of assessment in all clusters (cluster 1-M1: 68.07 +/- 6.62s vs M7: 61.46 +/- 3.43s; cluster 2-M1: 73.14 +/- 4.87s vs M7: 65.33 +/- 2.97s; cluster 3-M1: 82.60 +/- 4.18s vs M7: 70.09 +/- 3.48s). Anthropometric features also increased between moments of assessment, and remaining biomechanical variables (kinematic, efficiency, hydrodynamic and mechanical power) also increased between M1 and M7, in all clusters. Cluster 1 increased their swimmer's membership between M1 and M7 (4 to 11), cluster 2 decreased (12 to 5), and cluster 3 maintained (14). Conclusion: It can be concluded that the cluster formation depends on different determinant factors during two competitive seasons, and young swimmers are prone to change from one cluster to another over this period of time |
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Data modeling for inter- and intra-individual stability of young swimmers’ performance: a longitudinal cluster analysisBiomechanicsTrainingYouthPerformanceThe aims of this study were to classify, identify and follow-up young swimmers' performance and its biomechanical determinants during two competitive seasons (in seven different moments of assessment-M), and analyze the individual variations of each swimmer. Method: Thirty young swimmers (14 boys: 12.70 +/- 0.63 years-old; 16 girls: 11.72 +/- 0.71 years-old) were recruited. A set of anthropometric, kinematic, efficiency, hydrodynamic and mechanical power variables were assessed. Results: The cluster solution (i.e., number of ideal clusters for this sample) resulted in three clusters, which were named as: cluster 1 ("talented"), cluster 2 ("proficient"), and cluster 3 ("non-proficient"). The performance improved between moments of assessment in all clusters (cluster 1-M1: 68.07 +/- 6.62s vs M7: 61.46 +/- 3.43s; cluster 2-M1: 73.14 +/- 4.87s vs M7: 65.33 +/- 2.97s; cluster 3-M1: 82.60 +/- 4.18s vs M7: 70.09 +/- 3.48s). Anthropometric features also increased between moments of assessment, and remaining biomechanical variables (kinematic, efficiency, hydrodynamic and mechanical power) also increased between M1 and M7, in all clusters. Cluster 1 increased their swimmer's membership between M1 and M7 (4 to 11), cluster 2 decreased (12 to 5), and cluster 3 maintained (14). Conclusion: It can be concluded that the cluster formation depends on different determinant factors during two competitive seasons, and young swimmers are prone to change from one cluster to another over this period of timeThis project was supported by the National Funds through FCT - Portuguese Foundation for Science and Technology [UID/DTP/04045/2019], and the European Fund for regional development (FEDER) allocated by European Union through the COMPETE 2020 Programme [POCI-01-0145-FEDER-006969].Taylor & FrancisBiblioteca Digital do IPBMorais, J.E.Forte, PedroSilva, A.J.Barbosa, Tiago M.Marinho, D.A.2020-05-20T09:50:16Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10198/21956engMorais, J.E.; Forte, Pedro; Silva, A.J.; Barbosa, Tiago M.; Marinho, D.A. (2020). Data modeling for inter- and intra-individual stability of young swimmers’ performance: a longitudinal cluster analysis. Research Quarterly for Exercise and Sport. ISSN 0270-13670270-136710.1080/02701367.2019.1708235info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-21T10:47:15Zoai:bibliotecadigital.ipb.pt:10198/21956Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:11:51.666928Repositório 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 |
Data modeling for inter- and intra-individual stability of young swimmers’ performance: a longitudinal cluster analysis |
title |
Data modeling for inter- and intra-individual stability of young swimmers’ performance: a longitudinal cluster analysis |
spellingShingle |
Data modeling for inter- and intra-individual stability of young swimmers’ performance: a longitudinal cluster analysis Morais, J.E. Biomechanics Training Youth Performance |
title_short |
Data modeling for inter- and intra-individual stability of young swimmers’ performance: a longitudinal cluster analysis |
title_full |
Data modeling for inter- and intra-individual stability of young swimmers’ performance: a longitudinal cluster analysis |
title_fullStr |
Data modeling for inter- and intra-individual stability of young swimmers’ performance: a longitudinal cluster analysis |
title_full_unstemmed |
Data modeling for inter- and intra-individual stability of young swimmers’ performance: a longitudinal cluster analysis |
title_sort |
Data modeling for inter- and intra-individual stability of young swimmers’ performance: a longitudinal cluster analysis |
author |
Morais, J.E. |
author_facet |
Morais, J.E. Forte, Pedro Silva, A.J. Barbosa, Tiago M. Marinho, D.A. |
author_role |
author |
author2 |
Forte, Pedro Silva, A.J. Barbosa, Tiago M. Marinho, D.A. |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Biblioteca Digital do IPB |
dc.contributor.author.fl_str_mv |
Morais, J.E. Forte, Pedro Silva, A.J. Barbosa, Tiago M. Marinho, D.A. |
dc.subject.por.fl_str_mv |
Biomechanics Training Youth Performance |
topic |
Biomechanics Training Youth Performance |
description |
The aims of this study were to classify, identify and follow-up young swimmers' performance and its biomechanical determinants during two competitive seasons (in seven different moments of assessment-M), and analyze the individual variations of each swimmer. Method: Thirty young swimmers (14 boys: 12.70 +/- 0.63 years-old; 16 girls: 11.72 +/- 0.71 years-old) were recruited. A set of anthropometric, kinematic, efficiency, hydrodynamic and mechanical power variables were assessed. Results: The cluster solution (i.e., number of ideal clusters for this sample) resulted in three clusters, which were named as: cluster 1 ("talented"), cluster 2 ("proficient"), and cluster 3 ("non-proficient"). The performance improved between moments of assessment in all clusters (cluster 1-M1: 68.07 +/- 6.62s vs M7: 61.46 +/- 3.43s; cluster 2-M1: 73.14 +/- 4.87s vs M7: 65.33 +/- 2.97s; cluster 3-M1: 82.60 +/- 4.18s vs M7: 70.09 +/- 3.48s). Anthropometric features also increased between moments of assessment, and remaining biomechanical variables (kinematic, efficiency, hydrodynamic and mechanical power) also increased between M1 and M7, in all clusters. Cluster 1 increased their swimmer's membership between M1 and M7 (4 to 11), cluster 2 decreased (12 to 5), and cluster 3 maintained (14). Conclusion: It can be concluded that the cluster formation depends on different determinant factors during two competitive seasons, and young swimmers are prone to change from one cluster to another over this period of time |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-05-20T09:50:16Z 2020 2020-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10198/21956 |
url |
http://hdl.handle.net/10198/21956 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Morais, J.E.; Forte, Pedro; Silva, A.J.; Barbosa, Tiago M.; Marinho, D.A. (2020). Data modeling for inter- and intra-individual stability of young swimmers’ performance: a longitudinal cluster analysis. Research Quarterly for Exercise and Sport. ISSN 0270-1367 0270-1367 10.1080/02701367.2019.1708235 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Taylor & Francis |
publisher.none.fl_str_mv |
Taylor & Francis |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799135388353167360 |