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dc.contributor.authorWiig, Astrid Salte
dc.contributor.authorHåland, Else Marie
dc.contributor.authorStålhane, Magnus
dc.contributor.authorHvattum, Lars Magnus
dc.date.accessioned2020-01-31T08:45:48Z
dc.date.available2020-01-31T08:45:48Z
dc.date.created2019-09-18T13:19:02Z
dc.date.issued2019
dc.identifier.citationInternational Journal of Computer Science in Sport. 2019, 18 (3), 44-68.nb_NO
dc.identifier.issn1684-4769
dc.identifier.urihttp://hdl.handle.net/11250/2638977
dc.description.abstractThis paper investigates the use of network analysis to identify key players on teams, and patterns of passing within teams, in association football. Networks are constructed based on passes made between players, and several centrality measures are investigated in combination with three different methods for evaluating individual passes. Four seasons of data from the Norwegian top division are used to identify key players and analyze matches from a selected team. The networks examined in this work have weights based on three different aspects of the passes made: their probability of being completed, the probability that the team keeps possession after the completed pass, and the probability of the pass being part of a sequence leading to a shot. The results show that using different metrics and network weights leads to the identification of key passers in different phases of play and in different positions on the pitch.nb_NO
dc.language.isoengnb_NO
dc.publisherSciendonb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleAnalyzing passing networks in association football based on the difficulty, risk, and potential of passesnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber44-68nb_NO
dc.source.volume18nb_NO
dc.source.journalInternational Journal of Computer Science in Sportnb_NO
dc.source.issue3nb_NO
dc.identifier.doi10.2478/ijcss-2019-0017
dc.identifier.cristin1726221
dc.description.localcode© 2019 DOI: 10.2478/ijcss-2019-0017. Open Access etter CC BY-NC-ND-lisensen (http://creativecommons.org/licenses/by-nc-nd/4.0/).nb_NO
cristin.unitcode194,60,25,0
cristin.unitnameInstitutt for industriell økonomi og teknologiledelse
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.fulltextoriginal
cristin.qualitycode1


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