Dynamic Bayesian forecasting of AFL match results using the Skellam distribution

A. A. Manderson; K. Murray; B. A. Turlach

doi:10.1111/anzs.12225

Dynamic Bayesian forecasting of AFL match results using the Skellam distribution

A. A. Manderson, K. Murray, B. A. Turlach

Research output: Contribution to journal › Article › peer-review

5 Citations (Web of Science)

Abstract

The scoring and defensive abilities of Australian Rules Football teams change over time as a result of evolving player rosters, tactics and other management factors. We develop a dynamic model based on the Poisson difference (Skellam) distribution which simultaneously models the two different point scoring mechanisms in Australian Rules Football, the motivation for which comes from work on predicting outcomes in soccer matches. Our model is developed in a Bayesian framework and is fitted using the Stan modelling language. Model validation is performed on the 2015 Australian Football league (AFL) home and away season.

Original language	English
Pages (from-to)	174-187
Number of pages	14
Journal	Australian and New Zealand Journal of Statistics
Volume	60
Issue number	2
DOIs	https://doi.org/10.1111/anzs.12225
Publication status	Published - Jun 2018

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10.1111/anzs.12225

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Dynamic Bayesian forecasting of AFL match results using the Skellam distribution

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