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Evaluating probabilistic forecasts of football matches: the case against the ranked probability score

Wheatcroft, Edward ORCID: 0000-0002-7301-0889 (2021) Evaluating probabilistic forecasts of football matches: the case against the ranked probability score. Journal of Quantitative Analysis in Sports, 17 (4). 273 - 287. ISSN 1559-0410

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Identification Number: 10.1515/jqas-2019-0089


A scoring rule is a function of a probabilistic forecast and a corresponding outcome used to evaluate forecast performance. There is some debate as to which scoring rules are most appropriate for evaluating forecasts of sporting events. This paper focuses on forecasts of the outcomes of football matches. The ranked probability score (RPS) is often recommended since it is 'sensitive to distance', that is it takes into account the ordering in the outcomes (a home win is 'closer' to a draw than it is to an away win). In this paper, this reasoning is disputed on the basis that it adds nothing in terms of the usual aims of using scoring rules. A local scoring rule is one that only takes the probability placed on the outcome into consideration. Two simulation experiments are carried out to compare the performance of the RPS, which is non-local and sensitive to distance, the Brier score, which is non-local and insensitive to distance, and the Ignorance score, which is local and insensitive to distance. The Ignorance score outperforms both the RPS and the Brier score, casting doubt on the value of non-locality and sensitivity to distance as properties of scoring rules in this context.

Item Type: Article
Official URL:
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
Date Deposited: 29 Jul 2021 09:30
Last Modified: 21 Mar 2022 08:27

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