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Betting Markets for English Premier League Results and Scorelines: Evaluating a Simple Forecasting Model

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  • J Reade
  • C Singleton
  • L Vaughan Williams

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.

Suggested Citation

  • J Reade & C Singleton & L Vaughan Williams, 2020. "Betting Markets for English Premier League Results and Scorelines: Evaluating a Simple Forecasting Model," Economic Issues Journal Articles, Economic Issues, vol. 25(1), pages 87-106, March.
  • Handle: RePEc:eis:articl:120reade
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    Cited by:

    1. Fischer, Kai & Haucap, Justus, 2020. "Betting market efficiency in the presence of unfamiliar shocks: The case of ghost games during the COVID-19 pandemic," DICE Discussion Papers 349, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    2. Vaughan Williams Leighton & Liu Chunping & Dixon Lerato & Gerrard Hannah, 2021. "How well do Elo-based ratings predict professional tennis matches?," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(2), pages 91-105, June.
    3. Kai Fischer & Justus Haucap, 2022. "Home advantage in professional soccer and betting market efficiency: The role of spectator crowds," Kyklos, Wiley Blackwell, vol. 75(2), pages 294-316, May.

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    More about this item

    Keywords

    Forecasting; Statistical modelling; Regression models; Prediction markets;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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