  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 is 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.
