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#1. Improving predictor selection for injury modelling methods in male footballers
Fraser Philp, Ahmad Al-Shallaw, Theocharis Kyriacou, Dimitra Blana, Anand Pandyan
This study evaluated whether combining existing methods of Elastic net for zero-inflated Poisson and zero-inflated Poisson regression methods could improve real life applicability of injury prediction models in football. Predictor selection and model development was conducted on a pre-existing dataset, from a single English football teams’ 2015/2016 season. The Elastic Net for zero-inflated Poisson penalty method was successful shrinking the total number of predictors in the presence of high levels of multicollinearity. It was additionally identified that easily measurable data, i.e. mass and body fat content, training type, duration and surface, fitness levels, normalised period of “no-play” and time in competition could contribute to the probability of acquiring a time loss injury. Furthermore, prolonged series of match play and increased in-season injury reduced the probability of not sustaining an injury. For predictor selection, the Elastic net for zero-inflated Poisson penalised method in combination with the use of ZIP...
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fdphilp: Here's the link just approved https://t.co/iIGX3pTkIb https://t.co/DhpzElk1Ku
fdphilp: See our recent preprint - Improving predictor selection for injury modelling methods in male footballers https://t.co/iIGX3qaW6L via @OSFramework @SportRxiv
JJoSherwood: 🚨New submission🚨 ⚽️Check out an updated model to predict sports injuries!⚽️https://t.co/uwa6JrxvOX @SportRxiv
JJoSherwood: 🚨New Submission @SportRxiv🚨 ⚽️Check out an updated model to predict sports injuries!!!⚽️ https://t.co/uwa6JrxvOX
JJoSherwood: RT @JJoSherwood: 🚨New submission🚨 ⚽️Check out an updated model to predict sports injuries!⚽️https://t.co/uwa6JrxvOX @SportRxiv
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Sample Sizes : [33]
Authors: 5
Total Words: 6704
Unqiue Words: 2053

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