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
Date
2017-04
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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.
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
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Applied project
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Keywords
football, sports injury prediction, data mining, African Cup of Nations (AFCON)