Analysis of sports data by using bivariate Poisson models

Dimitris Karlis, Ioannis Ntzoufras
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引用次数: 410

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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体育数据的二元泊松模型分析
总结基于二元泊松分布的模型用于对体育数据进行建模。通常采用独立的泊松分布来对两个竞争团队的进球数进行建模。我们通过考虑二元泊松模型及其扩展来取代独立性假设。所提出的模型考虑到了两个分数之间的相关性,这在两支对立球队相互竞争的体育运动中是一个合理的假设。讨论了引入哪怕是轻微相关性的效果。仅使用二元泊松分布可以改进模型拟合和足球比赛平局次数的预测。通过考虑二元联合分布中对角项的通货膨胀因子,对模型进行了扩展。这种通货膨胀提高了绘图估计的精度,同时,相对于简单的泊松分布,允许过分散的边际分布。提供了所提出模型的性质以及解释和估计程序。使用足球和水球的数据集对模型进行了说明。
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