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Journal of Quantitative Analysis in Sports

An official journal of the American Statistical Association

Editor-in-Chief: Steve Rigdon, PhD

4 Issues per year

CiteScore 2017: 0.67

SCImago Journal Rank (SJR) 2017: 0.290
Source Normalized Impact per Paper (SNIP) 2017: 0.853

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Volume 8, Issue 1


Volume 1 (2005)

Solving the Problem of Inadequate Scoring Rules for Assessing Probabilistic Football Forecast Models

Anthony Costa Constantinou / Norman Elliott Fenton
Published Online: 2012-03-12 | DOI: https://doi.org/10.1515/1559-0410.1418

Despite the massive popularity of probabilistic (association) football forecasting models, and the relative simplicity of the outcome of such forecasts (they require only three probability values corresponding to home win, draw, and away win) there is no agreed scoring rule to determine their forecast accuracy. Moreover, the various scoring rules used for validation in previous studies are inadequate since they fail to recognise that football outcomes represent a ranked (ordinal) scale. This raises severe concerns about the validity of conclusions from previous studies. There is a well-established generic scoring rule, the Rank Probability Score (RPS), which has been missed by previous researchers, but which properly assesses football forecasting models.

Keywords: association football forecasting; forecast assessment; forecast verification; predictive evaluation; probability forecasting; rank probability score; sports forecasting

About the article

Published Online: 2012-03-12

Citation Information: Journal of Quantitative Analysis in Sports, Volume 8, Issue 1, ISSN (Online) 1559-0410, DOI: https://doi.org/10.1515/1559-0410.1418.

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