Modeling the Number of Claims Data in Sport Insurance

The main goal of sport insurance is to identify and determine the risks and also reducing clubs and players’ costs. Also, in order to provide adequate insurance coverage, based on the analysis of losses, insurance companies determine premiums. Since in insurance industry, zero claims, for many reasons such as non- reporting deductible claims, are high, excess zero arise in the samples and data are faced with zero-inflation. In this paper, by using generalized linear models (GLMs), the claim frequency of Sepahan team during the period 2013-2014 is examined and analyzed by Poisson, zero-inflated Poisson, negative binomial and zero-inflated negative binomial models and finally suitable model for zero claims will be presented. Research finding shows that negative binomial and Poisson distribution presents the best fitness, meanwhile, the post of football players has a significant effect on the frequency of injury.