Forecasting football matches by predicting match statistics

Wheatcroft, Edward ORCID: 0000-0002-7301-0889 (2021) Forecasting football matches by predicting match statistics. Journal of Sports Analytics, 7 (2). 77 - 97. ISSN 2215-020X

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Abstract

This paper considers the use of observed and predicted match statistics as inputs to forecasts for the outcomes of football matches. It is shown that, were it possible to know the match statistics in advance, highly informative forecasts of the match outcome could be made. Whilst, in practice, match statistics are clearly never available prior to the match, this leads to a simple philosophy. If match statistics can be predicted pre-match, and if those predictions are accurate enough, it follows that informative match forecasts can be made. Two approaches to the prediction of match statistics are demonstrated: Generalised Attacking Performance (GAP) ratings and a set of ratings based on the Bivariate Poisson model which are named Bivariate Attacking (BA) ratings. It is shown that both approaches provide a suitable methodology for predicting match statistics in advance and that they are informative enough to provide information beyond that reflected in the odds. A long term and robust gambling profit is demonstrated when the forecasts are combined with two betting strategies.

Item Type:	Article
Official URL:	http://www.journalofsportsanalytics.com/
Additional Information:	© 2021 The Author
Divisions:	Centre for Analysis of Time Series
Subjects:	H Social Sciences > HA Statistics G Geography. Anthropology. Recreation > GV Recreation Leisure Q Science > QA Mathematics
Date Deposited:	29 Jul 2021 09:48
Last Modified:	17 Oct 2024 17:40
URI:	http://eprints.lse.ac.uk/id/eprint/111495

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