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Betting markets for English Premier League results and scorelines: evaluating a forecasting model

J Reade (), Carl Singleton () and Leighton Vaughan Williams ()
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Leighton Vaughan Williams: Nottingham Business School, Nottingham Trent University, UK

No em-dp2020-03, Economics Discussion Papers from Department of Economics, Reading University

Abstract: Using betting odds from two recent seasons of English Premier League football matches, we evaluate probability and point forecasts generated from a standard statistical model of goal scoring. The bookmaker odds show significant evidence of the favourite-longshot bias for exact scorelines, which is not generally present for match results. We find evidence that the scoreline probability forecasts from the model are better than what the odds of bookmakers imply, based on forecast encompassing regressions. However, when we apply a simple betting strategy using point forecasts from the model, there are no substantial or consistent financial returns to be made over the two seasons. In other words, there is no evidence from this particular statistical model that the result, scoreline, margin of victory or total goals betting markets are on average inefficient.

Keywords: Forecasting; Statistical modelling; Regression models; Prediction markets (search for similar items in EconPapers)
JEL-codes: C53 G14 G17 L83 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2020-03-20
New Economics Papers: this item is included in nep-for and nep-spo
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