Using cooperative networks to analyse behaviour in professional Australian Football.
- Publisher:
- Elsevier
- Publication Type:
- Journal Article
- Citation:
- Journal of Science and Medicine in Sport, 2020, 23, (3), pp. 291-296
- Issue Date:
- 2020
Closed Access
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1-s2.0-S1440244019304864-main.pdf | Published version | 460.53 kB | Adobe PDF |
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Full metadata record
Field | Value | Language |
---|---|---|
dc.contributor.author | Sheehan, WB | |
dc.contributor.author |
Tribolet, R https://orcid.org/0000-0001-9252-1900 |
|
dc.contributor.author | Watsford, ML | |
dc.contributor.author | Novak, AR | |
dc.contributor.author | Rennie, MJ | |
dc.contributor.author |
Fransen, J https://orcid.org/0000-0003-3355-1848 |
|
dc.date.accessioned | 2020-10-09T05:36:45Z | |
dc.date.available | 2019-09-17 | |
dc.date.available | 2020-10-09T05:36:45Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Journal of Science and Medicine in Sport, 2020, 23, (3), pp. 291-296 | |
dc.identifier.issn | 1440-2440 | |
dc.identifier.issn | 1878-1861 | |
dc.identifier.uri | http://hdl.handle.net/10453/143188 | |
dc.description.abstract | OBJECTIVES:Reducing the dimensionality of commonly reported complex network characteristics obtained from Australian Football League (AFL) games to facilitate their practical use and interpretability. DESIGN:Retrospective longitudinal design where individual players' interactions, determined through the distribution and receipt of kicks and handballs, during official AFL games were collected over three seasons. METHODS:A principal component analysis was used to reduce the number of characteristics related to the cooperative network analysis. RESULTS:The principal component analysis derived two individual-based principal components pertaining to in- and out-degree importance and three team-based principal components related to connectedness and in- and out-degree centralisation. CONCLUSIONS:This study is the first to provide a simplified, novel method for analysing complex network structures in an Australian Football context with both the team- and individual-derived metrics revealing useful information for coaches and practitioners. This may consequently guide opposition analysis, training implementation, player performance ratings and player selection. | |
dc.format | Print-Electronic | |
dc.language | eng | |
dc.publisher | Elsevier | |
dc.relation | Sydney Swans Limited | |
dc.relation.ispartof | Journal of Science and Medicine in Sport | |
dc.relation.isbasedon | 10.1016/j.jsams.2019.09.012 | |
dc.rights | info:eu-repo/semantics/closedAccess | |
dc.subject | 1106 Human Movement and Sports Sciences, 1116 Medical Physiology, 1117 Public Health and Health Services | |
dc.subject.classification | Sport Sciences | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Retrospective Studies | |
dc.subject.mesh | Longitudinal Studies | |
dc.subject.mesh | Principal Component Analysis | |
dc.subject.mesh | Football | |
dc.subject.mesh | Video Recording | |
dc.subject.mesh | Adult | |
dc.subject.mesh | Australia | |
dc.subject.mesh | Male | |
dc.subject.mesh | Athletic Performance | |
dc.subject.mesh | Young Adult | |
dc.subject.mesh | Adult | |
dc.subject.mesh | Athletic Performance | |
dc.subject.mesh | Australia | |
dc.subject.mesh | Football | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Longitudinal Studies | |
dc.subject.mesh | Male | |
dc.subject.mesh | Principal Component Analysis | |
dc.subject.mesh | Retrospective Studies | |
dc.subject.mesh | Video Recording | |
dc.subject.mesh | Young Adult | |
dc.title | Using cooperative networks to analyse behaviour in professional Australian Football. | |
dc.type | Journal Article | |
utslib.citation.volume | 23 | |
utslib.location.activity | Australia | |
utslib.for | 1106 Human Movement and Sports Sciences | |
utslib.for | 1117 Public Health and Health Services | |
utslib.for | 1106 Human Movement and Sports Sciences | |
utslib.for | 1116 Medical Physiology | |
utslib.for | 1117 Public Health and Health Services | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Health | |
pubs.organisational-group | /University of Technology Sydney | |
pubs.organisational-group | /University of Technology Sydney/Strength - CHSP - Health Services and Practice | |
pubs.organisational-group | /University of Technology Sydney/Students | |
utslib.copyright.status | closed_access | * |
pubs.consider-herdc | true | |
dc.date.updated | 2020-10-09T05:36:40Z | |
pubs.issue | 3 | |
pubs.publication-status | Published | |
pubs.volume | 23 | |
utslib.citation.issue | 3 |
Abstract:
OBJECTIVES:Reducing the dimensionality of commonly reported complex network characteristics obtained from Australian Football League (AFL) games to facilitate their practical use and interpretability. DESIGN:Retrospective longitudinal design where individual players' interactions, determined through the distribution and receipt of kicks and handballs, during official AFL games were collected over three seasons. METHODS:A principal component analysis was used to reduce the number of characteristics related to the cooperative network analysis. RESULTS:The principal component analysis derived two individual-based principal components pertaining to in- and out-degree importance and three team-based principal components related to connectedness and in- and out-degree centralisation. CONCLUSIONS:This study is the first to provide a simplified, novel method for analysing complex network structures in an Australian Football context with both the team- and individual-derived metrics revealing useful information for coaches and practitioners. This may consequently guide opposition analysis, training implementation, player performance ratings and player selection.
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