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Analyzing Information Efficiency In The Betting Market For Association Football League Winners

Author

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  • Lars Magnus Hvattum

Abstract

Sports betting markets have attracted a fair amount of research over the years. For association football, most of this research has focused on predicting the outcome of single matches and hence on the evaluating the efficiency of the match results betting markets. This paper presents a study on the betting market for league winners, a market that operates for almost a full year and therefore operates under different conditions than the relatively short-lived match results markets. Attempts are made to analyze both weak and semi-strong forms of information efficiency. Although the results are mixed, there are some indications that the market is inefficient with respect to both forms of information.

Suggested Citation

  • Lars Magnus Hvattum, 2013. "Analyzing Information Efficiency In The Betting Market For Association Football League Winners," Journal of Prediction Markets, University of Buckingham Press, vol. 7(2), pages 55-70.
    • Handle: RePEc:buc:jpredm:v:7:y:2013:i:2:p:55-70
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    File URL: http://ubplj.org/index.php/jpm/article/view/614
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    Citations

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    Cited by:

    1. Pascal Flurin Meier & Raphael Flepp & Egon Franck, 2021. "Are sports betting markets semistrong efficient? Evidence from the COVID-19 pandemic," Working Papers 387, University of Zurich, Department of Business Administration (IBW).
    2. Dominic Cortis, 2015. "Expected Values And Variances In Bookmaker Payouts: A Theoretical Approach Towards Setting Limits On Odds," Journal of Prediction Markets, University of Buckingham Press, vol. 9(1), pages 1-14.
    3. Luca De Angelis & J. James Reade, 2022. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Economics Discussion Papers em-dp2022-01, Department of Economics, University of Reading.
    4. Poojan Thakkar & Manan Shah, 2021. "An Assessment of Football Through the Lens of Data Science," Annals of Data Science, Springer, vol. 8(4), pages 823-836, December.
    5. Hvattum Lars Magnus, 2015. "Playing on artificial turf may be an advantage for Norwegian soccer teams," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(3), pages 183-192, September.
    6. Luca De Angelis & J. James Reade, 2023. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Annals of Operations Research, Springer, vol. 325(1), pages 391-418, June.

    More about this item

    Keywords

    Simulation; Regression; Forecasting; Soccer;
    All these keywords.

    JEL classification:

    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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