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Analysis of sports data by using bivariate Poisson models
Dimitris Karlis 1 and Ioannis Ntzoufras 2
  1 Athens University of Economics and Business, Greece
  2 University of the Aegean, Chios, Greece
Correspondence to Dimitris Karlis, Department of Statistics, Athens University of Economics and Business, Patission 76, 104 34 Athens, Greece.
E-mail: karlis@hermes.aueb.gr
Copyright 2003 Royal Statistical Society
KEYWORDS
Bivariate Poisson regression • Difference of Poisson variates • Inflated distributions • Soccer

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.


[Received November 2001. Final revision April 2003]

DIGITAL OBJECT IDENTIFIER (DOI)
10.1111/1467-9884.00366 About DOI

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