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Parimutuel Betting On The Esports Duels: Reverse Favourite-Longshot Bias And Its Determinants

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Listed:
  • Dmitry Dagaev

    (National Research University Higher School of Economics)

  • Egor Stoyan

    (National Research University Higher School of Economics)

Abstract

We analyse betting behaviour patterns of the visitors of the specialized betting website dedicated to the popular eSports game Counter-Strike: Global O ensive. The reverse favourite-longshot bias is found both in the in-sample and out-of-sample datasets. This phenomenon is rather unusual for parimutuel betting markets because favourite-longshot bias is more common. We de ne simple betting strategies based on the bets on underdogs and show that these strategies make a suciently large positive pro t, which is a sign of market ineciency. Next, we investigate determinants of the reverse favourite-longshot bias. We hypothesize that popular teams attract more unsophisticated gamblers which adds to the stronger reverse favourite-longshot bias in matches with such teams. Geographical proximity is found to be a signi cant factor that increases the bias, whereas the e ect of internet popularity measured by the number of team players' followers on Twitter surprisingly follows the U-shape curve

Suggested Citation

  • Dmitry Dagaev & Egor Stoyan, 2019. "Parimutuel Betting On The Esports Duels: Reverse Favourite-Longshot Bias And Its Determinants," HSE Working papers WP BRP 216/EC/2019, National Research University Higher School of Economics.
    • Handle: RePEc:hig:wpaper:216/ec/2019
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    References listed on IDEAS

    as
    1. Alasdair Brown & Dooruj Rambaccussing & J. James Reade & Giambattista Rossi, 2016. "Using Social Media to Identify Market Inefficiencies: Evidence from Twitter and Betfair," Dundee Discussion Papers in Economics 293, Economic Studies, University of Dundee.
    2. Randall W. Bennett, 2019. "Holdover Bias in the College Football Betting Market," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 47(1), pages 103-110, March.
    3. Angelini, Giovanni & De Angelis, Luca, 2019. "Efficiency of online football betting markets," International Journal of Forecasting, Elsevier, vol. 35(2), pages 712-721.
    4. Karen Croxson & J. James Reade, 2014. "Information and Efficiency: Goal Arrival in Soccer Betting," Economic Journal, Royal Economic Society, vol. 124(575), pages 62-91, March.
    5. Borghesi, Richard, 2007. "The home team weather advantage and biases in the NFL betting market," Journal of Economics and Business, Elsevier, vol. 59(4), pages 340-354.
    6. William Dare & A. Steven Holland, 2004. "Efficiency in the NFL betting market: modifying and consolidating research methods," Applied Economics, Taylor & Francis Journals, vol. 36(1), pages 9-15.
    7. Ali, Mukhtar M, 1977. "Probability and Utility Estimates for Racetrack Bettors," Journal of Political Economy, University of Chicago Press, vol. 85(4), pages 803-815, August.
    8. Berkowitz, Jason P. & Depken, Craig A. & Gandar, John M., 2017. "A favorite-longshot bias in fixed-odds betting markets: Evidence from college basketball and college football," The Quarterly Review of Economics and Finance, Elsevier, vol. 63(C), pages 233-239.
    9. Alasdair Brown & Dooruj Rambaccussing & J. James Reade & Giambattista Rossi, 2016. "Using Social Media to Identify Market Ine!ciencies: Evidence from Twitter and Betfair," Working Papers 2016-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    10. Asch, Peter & Malkiel, Burton G & Quandt, Richard E, 1984. "Market Efficiency in Racetrack Betting," The Journal of Business, University of Chicago Press, vol. 57(2), pages 165-175, April.
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    More about this item

    Keywords

    eSports; betting; market ineciency; favourite-longshot bias.;
    All these keywords.

    JEL classification:

    • Z23 - Other Special Topics - - Sports Economics - - - Finance
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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