Predicting injury in football using pitch quality, player’s function, player’s age and match intensity: A case study of the 2017 African Cup of Nations

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dc.contributor.authorCommodore-Mensah, Ayeley
dc.date.accessioned2017-11-09T11:24:59Z
dc.date.available2017-11-09T11:24:59Z
dc.date.issued2017-04
dc.descriptionApplied project submitted to the Department of Computer Science, Ashesi University College, in partial fulfillment of Bachelor of Science degree in Management Information Systems, April 2017en_US
dc.description.abstractFootball is the most popular sport in the world, and many individuals have taken advantage of it to earn a living and improve upon their standards of living. Injuries are also unfortunate incidents that occur in daily life and in sports, which affect an individual’s ability to make good use of his sporting talent to earn a living for himself and his family. In this project, modifiable risk factors that affect a player’s likelihood of getting an injury are identified, and their individual contributions to injury of a player is assessed. A predictive model for determining important risk factors for determining injuries in football is generated using the identified risk factors: pitch quality, match intensity, player function and player age.en_US
dc.description.sponsorshipAshesi University Collegeen_US
dc.identifier.urihttp://hdl.handle.net/20.500.11988/291
dc.language.isoen_USen_US
dc.subjectfootballen_US
dc.subjectsports injury predictionen_US
dc.subjectdata mining
dc.subjectAfrican Cup of Nations (AFCON)
dc.titlePredicting injury in football using pitch quality, player’s function, player’s age and match intensity: A case study of the 2017 African Cup of Nationsen_US
dc.typeApplied projecten_US

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