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Analysis of sports data by using bivariate Poisson models

Dimitris Karlis & Ioannis Ntzoufras

Journal of the Royal Statistical Society, Series D (The Statistician)2003https://doi.org/10.1111/1467-9884.00366article
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0.75

Abstract

Summary. Models based on the bivariate Poisson distribution are used for modelling sports data. Independent Poisson distributions are usually adopted to model the number of goals of two competing teams. We replace the independence assumption by considering a bivariate Poisson model and its extensions. The models proposed allow for correlation between the two scores, which is a plausible assumption in sports with two opposing teams competing against each other. The effect of introducing even slight correlation is discussed. Using just a bivariate Poisson distribution can improve model fit and prediction of the number of draws in football games. The model is extended by considering an inflation factor for diagonal terms in the bivariate joint distribution. This inflation improves in precision the estimation of draws and, at the same time, allows for overdispersed, relative to the simple Poisson distribution, marginal distributions. The properties of the models proposed as well as interpretation and estimation procedures are provided. An illustration of the models is presented by using data sets from football and water-polo.

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https://doi.org/https://doi.org/10.1111/1467-9884.00366

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@article{dimitris2003,
  title        = {{Analysis of sports data by using bivariate Poisson models}},
  author       = {Dimitris Karlis & Ioannis Ntzoufras},
  journal      = {Journal of the Royal Statistical Society, Series D (The Statistician)},
  year         = {2003},
  doi          = {https://doi.org/https://doi.org/10.1111/1467-9884.00366},
}

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F · citation impact1.00 × 0.4 = 0.40
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