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dc.contributor.authorWakelam, Ed
dc.contributor.authorSteuber, Volker
dc.contributor.authorWakelam, James
dc.date.accessioned2022-03-15T14:00:01Z
dc.date.available2022-03-15T14:00:01Z
dc.date.issued2022-03-11
dc.identifier.citationWakelam , E , Steuber , V & Wakelam , J 2022 , ' The collection, analysis and exploitation of footballer attributes: A systematic review ' , Journal of Sports Analytics , vol. 8 , no. 1 , pp. 37-67 . https://doi.org/10.3233/JSA-200554
dc.identifier.issn2215-020X
dc.identifier.urihttp://hdl.handle.net/2299/25433
dc.description© 2022 – The authors. Published by IOS Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution-Non Commercial License (CC BY-NC 4.0)
dc.description.abstractThere is growing on-going research into how footballer attributes, collected prior to, during and post-match, may address the demands of clubs, media pundits and gaming developers. Focusing upon individual player performance analysis and prediction, we examined the body of research which considers different player attributes. This resulted in the selection of 132 relevant papers published between 1999 and 2020. From these we have compiled a comprehensive list of player attributes, categorising them as static, such as age and height, or dynamic, such as pass completions and shots on target. To indicate their accuracy, we classified each attribute as objectively or subjectively derived, and finally by their implied accessibility and their likely personal and club sensitivity. We assigned these attributes to 25 logical groups such as passing, tackling and player demographics. We analysed the relative research focus on each group and noted the analytical methods deployed, identifying which statistical or machine learning techniques were used. We reviewed and considered the use of character trait attributes in the selected papers and discuss more formal approaches to their use. Based upon this we have made recommendations on how this work may be developed to support elite clubs in the consideration of transfer targets.en
dc.format.extent37
dc.format.extent321590
dc.language.isoeng
dc.relation.ispartofJournal of Sports Analytics
dc.subjectFootballer analytics
dc.subjectAttribute selection and capture
dc.subjectArtificial Intelligence
dc.subjectMachine Learning
dc.titleThe collection, analysis and exploitation of footballer attributes: A systematic reviewen
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionECS Computer Science VLs
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionCentre for Future Societies Research
dc.contributor.institutionCentre of Data Innovation Research
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionBiocomputation Research Group
dc.description.statusPeer reviewed
rioxxterms.versionofrecord10.3233/JSA-200554
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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