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What is the difference between a winning and a losing team: insights from Euroleague basketball

dc.contributor.authorCene, Erhan
dc.date.accessioned2026-06-27T14:09:57Z
dc.date.issued2018
dc.description.abstractThe purpose of this study is to determine which game-related factors have the most influence on game outcome for basketball matches based on the 2016-2017 Euroleague season. Games are divided into three groups with cluster analysis based on final score differences. First, independent samples t-test is used to detect differences between winning and losing teams among game-related variables. Later, Bayesian Model Averaging is employed to determine key candidate variables. Finally, conditional interference classification trees are constructed for all game groups. According to classification tree results, true shooting percentage, steals and committed fouls separates winners from losers for the close games. While 2-point field goal made, 3-point field goal made, steals and defensive rebounds are crucial for the balanced games; 2-point field goal made and defensive rebounds are the most influential game statistics on the game outcome for the unbalanced games. The results from the classification trees implied that in close games, quality of the shots are more important than the quantity of shots, whereas, the inverse deduction can be made for balanced and unbalanced games. These results may show guidance to basketball coaches and players in terms of training and game preparation.en
dc.description.urihttps://doi.org/10.1080/24748668.2018.1446234
dc.identifier.doi10.1080/24748668.2018.1446234
dc.identifier.eissn1474-8185
dc.identifier.endpage68
dc.identifier.issn2474-8668
dc.identifier.issue1
dc.identifier.startpage55
dc.identifier.urihttps://hdl.handle.net/20.500.14981/57439
dc.identifier.volume18
dc.identifier.wos000430501000004
dc.language.isoeng
dc.publisherROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
dc.relation.ispartofINTERNATIONAL JOURNAL OF PERFORMANCE ANALYSIS IN SPORT
dc.subjectClassification tree
dc.subjectBayesian model averaging
dc.subjectBMA
dc.subjectmachine learning
dc.subjectteam sports
dc.subjectgame outcome
dc.subjectGAME-RELATED STATISTICS
dc.subjectDISCRIMINATE
dc.subjectPERFORMANCE
dc.subjectQUALITY
dc.subjectSport Sciences
dc.titleWhat is the difference between a winning and a losing team: insights from Euroleague basketball
dc.typeArticle
dspace.entity.typePublication
local.import.sourceWOS

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