Forecasting number of corner kicks taken in association football using compound Poisson distribution
本文提出复合泊松回归模型框架预测足球角球次数，利用贝叶斯几何泊松分布处理序列相关性，并引入博彩赔率信息提升预测效果。
This article presents a holistic compound Poisson regression model framework to forecast number of corner kicks taken in association football. Corner kick taken events are often decisive in the match outcome and inherently arrive in batch with serial clustering pattern. Providing parameter estimates with intuitive interpretation, a class of compound Poisson regression including a Bayesian implementation of geometric-Poisson distribution are introduced. With a varying shape parameter, the corner counts serial correlation between matches is handled naturally within the Bayesian model. In this study, information elicited from cross-market betting odds was used to improve the model predictability. Margin application methods to adjust market inefficiency in raw odds are also discussed.