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dc.contributor.authorPettersen, Svein Arne
dc.contributor.authorJohansen, Håvard D.
dc.contributor.authorBaptista, Ivan
dc.contributor.authorHalvorsen, Pål
dc.contributor.authorJohansen, Dag
dc.date.accessioned2018-10-22T09:06:17Z
dc.date.available2018-10-22T09:06:17Z
dc.date.issued2018-07-06
dc.description.abstractPerformance development in international soccer is undergoing a silent revolution fueled by the rapidly increasing availability of athlete quantification data and advanced analytics. Objective performance data from teams and individual players are increasingly being collected automatically during practices and more recently also in matches after FIFA's 2015 approval of wearables in electronic performance and tracking systems. Some clubs have even started collecting data from players outside of the sport arenas. Further algorithmic analysis of these data might provide vital insights for individual training personalization and injury prevention, and also provide a foundation for evidence-based decisions for team performance improvements. This paper presents our experiences from using a detailed radio-based wearable positioning data system in an elite soccer club. We demonstrate how such a system can detect and find anomalies, trends, and insights vital for individual athletic and soccer team performance development. As an example, during a normal microcycle (6 days) full backs only covered 26% of the sprint distance they covered in the next match. This indicates that practitioners must carefully consider to proximity size and physical work pattern in microcycles to better resemble match performance. We also compare and discuss the accuracy between radio waves and GPS in sampling tracking data. Finally, we present how we are extending the radio-based positional system with a novel soccer analytics annotation system, and a real-time video processing system using a video camera array. This provides a novel toolkit for modern forward-looking soccer coaches that we hope to integrate in future studies.en_US
dc.description.sponsorshipUiT The Arctic University of Norwayen_US
dc.descriptionThe following article, Pettersen, S.A., Johansen, H.D., Baptista, I.A.M., Halvorsen, P. & Johansen, D. (2018). Quantified Soccer Using Positional Data: A Case Study. <i>Frontiers in Physiology</i>, 9. https://doi.org/10.3389/fphys.2018.00866, can be accessed at <a href=https://doi.org/10.3389/fphys.2018.00866> https://doi.org/10.3389/fphys.2018.00866</a>.en_US
dc.identifier.citationPettersen, S.A., Johansen, H.D., Baptista, I.A.M., Halvorsen, P. & Johansen, D. (2018). Quantified Soccer Using Positional Data: A Case Study. Frontiers in Physiology, 9. https://doi.org/10.3389/fphys.2018.00866en_US
dc.identifier.cristinIDFRIDAID 1598230
dc.identifier.doi10.3389/fphys.2018.00866
dc.identifier.issn1664-042X
dc.identifier.urihttps://hdl.handle.net/10037/13999
dc.language.isoengen_US
dc.publisherFrontiers Mediaen_US
dc.relation.ispartofBaptista, I. (2020). Football training specificity - Training individualization within the collective periodization. (Doctoral thesis). <a href=https://hdl.handle.net/10037/17359>https://hdl.handle.net/10037/17359</a>.
dc.relation.journalFrontiers in Physiology
dc.relation.projectIDinfo:eu-repo/grantAgreement/RCN/INTPART/250138/Norway/Trans-Atlantic Corpore Sano//en_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/RCN/IKTPLUSS/263248/Norway/Protecting Shared Data with Privacy Automatons//en_US
dc.rights.accessRightsopenAccessen_US
dc.subjectVDP::Medisinske fag: 700::Idrettsmedisinske fag: 850en_US
dc.subjectVDP::Midical sciences: 700::Sports medicine: 850en_US
dc.subjectVDP::Matematikk og naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420en_US
dc.subjectVDP::Mathematics and natural scienses: 400::Information and communication science: 420en_US
dc.titleQuantified Soccer Using Positional Data: A Case Studyen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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