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Performance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014

2016Journal article Open access
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dc.contributor.authorManuel Clemente, Filipe
dc.contributor.authorG. M. Silva, Frutuoso
dc.contributor.authorM. L. Martins, Fernando
dc.contributor.authorKalamaras, Dimitris
dc.contributor.authorMendes, Rui
dc.date.accessioned2023-09-25T11:48:25Z
dc.date.available2023-09-25T11:48:25Z
dc.date.issued2016
dc.description.abstractThe study of teammates’ interaction on team sports has been growing in the last few years. Nevertheless, no specific software has been developed so far to do this in a user-friendly manner. Therefore, the aim of this study was to introduce a software called the Performance Analysis Tool that allows the user to quickly record the teammates’ interaction and automatically generate the outputs in adjacency matrices that can then be imported by social network analysis software such as SocNetV. Moreover, it was also the aim of this study to process the data in a real-life scenario, thus the seven matches of the German national soccer team in the FIFA World Cup 2014 were used to test the software and then compute the network metrics. A dataset of 3032 passes between teammates in seven soccer matches was generated with the Performance Analysis Tool software, which permitted a study of the network structure. The analysis of variance of centrality metrics between different tactical positions was made. The two-way multivariate analysis of variance revealed that the strategic position (γ=1.305 ; F = 24.394; p = 0.001; η2p=0.652 ; large effect size) had significant main effects on the centrality measures. No statistical differences were found in the phase of competition (γ=0.003 ; F = 0.097; p = 0.907; η2p=0.003 ; very small effect size). The network approach revealed that the German national soccer team based their attacking process on positional attacks and not in counter-attack, and the midfielders were the prominent players followed by the central defenders. The Performance Analysis Tool software allowed the user to quickly identify the teammates’ interactions and extract the network data for process and analysis.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doihttps://doi.org/10.1177/1754337115597335pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.26/46736
dc.language.isoengpt_PT
dc.publisherIMechEpt_PT
dc.subjectMatch analysispt_PT
dc.subjectsoftwarept_PT
dc.subjectgraphical applicationpt_PT
dc.subjectgraphical user interfacept_PT
dc.subjectGerman national teampt_PT
dc.titlePerformance analysis tool for network analysis on team sports: a case study of FIFA Soccer World Cup 2014pt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceLondonpt_PT
oaire.citation.endPage170pt_PT
oaire.citation.issue3pt_PT
oaire.citation.startPage158pt_PT
oaire.citation.titleJournal of Sports Engineering and Technologypt_PT
oaire.citation.volume230pt_PT
person.familyNameClemente
person.familyNameG. M. Silva
person.familyNameMartins
person.familyNameMendes
person.givenNameFilipe Manuel
person.givenNameFrutuoso
person.givenNameFernando Manuel Lourenço
person.givenNameRui
person.identifier375349
person.identifier0000000070715256
person.identifier722571
person.identifier.ciencia-id9E1A-F9DD-3EB8
person.identifier.ciencia-id8512-5BB4-6DFD
person.identifier.ciencia-idA71F-1E22-D496
person.identifier.orcid0000-0001-9813-2842
person.identifier.orcid0000-0002-0611-6157
person.identifier.orcid0000-0002-1812-2300
person.identifier.orcid0000-0002-2433-5193
person.identifier.ridG-2625-2012
person.identifier.ridAAK-6934-2020
person.identifier.scopus-author-id8325080400
person.identifier.scopus-author-id57217191490
person.identifier.scopus-author-id54881476100
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication9ed47482-f742-4139-a2da-1b90c6b3039b
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relation.isAuthorOfPublication.latestForDiscovery805fc13a-0e76-4f11-9d4c-0dc177f8145c

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