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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.author Commodore-Mensah, Ayeley
dc.date.accessioned 2017-11-09T11:24:59Z
dc.date.available 2017-11-09T11:24:59Z
dc.date.issued 2017-04
dc.identifier.uri http://hdl.handle.net/20.500.11988/291
dc.description Applied project submitted to the Department of Computer Science, Ashesi University College, in partial fulfillment of Bachelor of Science degree in Management Information Systems, April 2017 en_US
dc.description.abstract Football 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.sponsorship Ashesi University College en_US
dc.language.iso en_US en_US
dc.subject football en_US
dc.subject sports injury prediction en_US
dc.subject data mining
dc.subject African Cup of Nations (AFCON)
dc.title 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 en_US
dc.type Applied project en_US


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