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dc.contributor.authorCordeiro, Mauricio
dc.contributor.authorÓ Catháin, Ciarán
dc.contributor.authorMurray, Niall
dc.contributor.authorRodrigues, Thiago B.
dc.identifier.citationCordeiro, M., Ó Catháin, C., Murray, N., Rodrigues, T.B. (2022). Analytics can be used to predict fatigue and improve athletes' performance in various sports. Presented at TUS MMW Poster Presentation Seminar January 2022en_US
dc.description.abstractIn sports analytics, statistics are plugged into a mathematical model to predict the outcome of a given play or game. Coaches use it to optimize plays during games,while front offices can use it to decide which players need development. The prediction of key variables have been explored through the use of artificial intelligence1 . For this to happen, predictive models can provide insight into an athlete's condition by acting as an “automated data analyst”2 . Fatigue is usually defined when a person feels tired,sluggish, weary, or exhausted.There are many types of fatigue described in sport science literature, including cardiovascular fatigue, biomechanical fatigue, respiratory fatigue, and mental fatigue3 . Our results do not focus on a specific type, it is a general approach.en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.subjectSports analyticsen_US
dc.subjectFatigue in athletesen_US
dc.titleAnalytics can be used to predict fatigue and improve athletes' performance in various sportsen_US
dc.contributor.affiliationTechnological University of the Shannon Midlands Midwesten_US
dc.identifier.orcid 0000-0001-6484-8762en_US
dc.identifier.orcid 0000-0002-8526-8924en_US
dc.identifier.orcid 0000-0002-5919-0596en_US
dc.identifier.orcid 0000-0002-2017-4492en_US
dc.subject.departmentFaculty of Engineering and Informatics TUS MMWen_US

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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International