IDEAS home Printed from https://ideas.repec.org/a/eee/joepsy/v81y2020ics0167487020300660.html
   My bibliography  Save this article

Parimutuel betting on the eSports duels: Evidence of the reverse favourite-longshot bias

Author

Listed:
  • Dagaev, Dmitry
  • Stoyan, Egor

Abstract

We analyse betting behaviour patterns of the visitors of the specialized betting website dedicated to the popular eSports game Counter-Strike: Global Offensive. The reverse favourite-longshot bias is found, which is rather unusual for parimutuel betting markets, where favourite-longshot bias is more common. We define simple betting strategies based on the bets on underdogs and show that these strategies make a sufficiently large positive profit both on the in-sample and out-of-sample datasets, which is a sign of market inefficiency. In matches with popular underdogs, the sentiment bias decreases the market inefficiency caused by the reverse favourite-longshot bias. At the same time, the role of the geographical location of teams in the reverse favourite-longshot bias is only marginal.

Suggested Citation

  • Dagaev, Dmitry & Stoyan, Egor, 2020. "Parimutuel betting on the eSports duels: Evidence of the reverse favourite-longshot bias," Journal of Economic Psychology, Elsevier, vol. 81(C).
    • Handle: RePEc:eee:joepsy:v:81:y:2020:i:c:s0167487020300660
    DOI: 10.1016/j.joep.2020.102305
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167487020300660
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joep.2020.102305?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Figlewski, Stephen, 1979. "Subjective Information and Market Efficiency in a Betting Market," Journal of Political Economy, University of Chicago Press, vol. 87(1), pages 75-88, February.
    2. Erik Snowberg & Justin Wolfers, 2010. "Explaining the Favorite-Long Shot Bias: Is it Risk-Love or Misperceptions?," Journal of Political Economy, University of Chicago Press, vol. 118(4), pages 723-746, August.
    3. Kajii, Atsushi & Watanabe, Takahiro, 2017. "Favorite–longshot bias in pari-mutuel betting: An evolutionary explanation," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 56-69.
    4. Richard E. Quandt, 1986. "Betting and Equilibrium," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 101(1), pages 201-207.
    5. Linda M. Woodland & Bill M. Woodland, 2001. "Market Efficiency and Profitable Wagering in the National Hockey League: Can Bettors Score on Longshots?," Southern Economic Journal, John Wiley & Sons, vol. 67(4), pages 983-995, April.
    6. 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.
    7. Angelini, Giovanni & De Angelis, Luca, 2019. "Efficiency of online football betting markets," International Journal of Forecasting, Elsevier, vol. 35(2), pages 712-721.
    8. Rodney J. Paul & Andrew P. Weinbach, 2005. "Bettor Misperceptions in the NBA," Journal of Sports Economics, , vol. 6(4), pages 390-400, November.
    9. 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.
    10. Woodland, Linda M & Woodland, Bill M, 1994. "Market Efficiency and the Favorite-Longshot Bias: The Baseball Betting Market," Journal of Finance, American Finance Association, vol. 49(1), pages 269-279, March.
    11. J. M. Gandar & Richard Zuber & R. S. Johnson & W. Dare, 2002. "Re-examining the betting market on Major League Baseball games: is there a reverse favourite-longshot bias?," Applied Economics, Taylor & Francis Journals, vol. 34(10), pages 1309-1317.
    12. David Forrest & Robert Simmons, 2008. "Sentiment in the betting market on Spanish football," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 119-126.
    13. Dare, William H. & MacDonald, S. Scott, 1996. "A generalized model for testing the home and favorite team advantage in point spread markets," Journal of Financial Economics, Elsevier, vol. 40(2), pages 295-318, February.
    14. 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.
    15. 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.
    16. 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.
    17. Ricard Gil & Steven D. Levitt, 2007. "Testing the Efficiency of Markets in the 2002 World Cup," Journal of Prediction Markets, University of Buckingham Press, vol. 1(3), pages 255-270, December.
    18. Hurley, William & McDonough, Lawrence, 1995. "A Note on the Hayek Hypothesis and the Favorite-Longshot Bias in Parimutuel Betting," American Economic Review, American Economic Association, vol. 85(4), pages 949-955, September.
    19. Gray, Philip K & Gray, Stephen F, 1997. "Testing Market Efficiency: Evidence from the NFL Sports Betting Market," Journal of Finance, American Finance Association, vol. 52(4), pages 1725-1737, September.
    20. Richard Borghesi, 2012. "The Implications Of A Reverse Favourite-Longshot Bias In A Prediction Market," Journal of Prediction Markets, University of Buckingham Press, vol. 6(2), pages 12-21.
    21. Thaler, Richard H & Ziemba, William T, 1988. "Parimutuel Betting Markets: Racetracks and Lotteries," Journal of Economic Perspectives, American Economic Association, vol. 2(2), pages 161-174, Spring.
    22. Ibragimov, Rustam & Müller, Ulrich K., 2010. "t-Statistic Based Correlation and Heterogeneity Robust Inference," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(4), pages 453-468.
    23. Nikolaos Vlastakis & George Dotsis & Raphael N. Markellos, 2009. "How efficient is the European football betting market? Evidence from arbitrage and trading strategies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 426-444.
    24. Golec, Joseph & Tamarkin, Maurry, 1991. "The degree of inefficiency in the football betting market : Statistical tests," Journal of Financial Economics, Elsevier, vol. 30(2), pages 311-323, December.
    25. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Niculaescu, Corina-Elena & Sangiorgi, Ivan & Bell, Adrian R., 2023. "Venture capital financing in the eSports industry," Research in International Business and Finance, Elsevier, vol. 65(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jinook Jeong & Jee Young Kim & Yoon Jae Ro, 2019. "On the efficiency of racetrack betting market: a new test for the favourite-longshot bias," Applied Economics, Taylor & Francis Journals, vol. 51(54), pages 5817-5828, November.
    2. Philip W. S. Newall & Dominic Cortis, 2021. "Are Sports Bettors Biased toward Longshots, Favorites, or Both? A Literature Review," Risks, MDPI, vol. 9(1), pages 1-9, January.
    3. Rebeggiani, Luca & Gross, Johannes, 2018. "Chance or Ability? The Efficiency of the Football Betting Market Revisited," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181563, Verein für Socialpolitik / German Economic Association.
    4. Angelini, Giovanni & De Angelis, Luca & Singleton, Carl, 2022. "Informational efficiency and behaviour within in-play prediction markets," International Journal of Forecasting, Elsevier, vol. 38(1), pages 282-299.
    5. Goto, Shingo & Yamada, Toru, 2023. "What drives biased odds in sports betting markets: Bettors’ irrationality and the role of bookmakers," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 252-270.
    6. Robin Maximilian Stetzka & Stefan Winter, 2023. "How rational is gambling?," Journal of Economic Surveys, Wiley Blackwell, vol. 37(4), pages 1432-1488, September.
    7. Stekler, H.O. & Sendor, David & Verlander, Richard, 2010. "Issues in sports forecasting," International Journal of Forecasting, Elsevier, vol. 26(3), pages 606-621, July.
      • Herman O. Stekler & David Sendor & Richard Verlander, 2009. "Issues in Sports Forecasting," Working Papers 2009-002, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    8. Choi, Darwin & Hui, Sam K., 2014. "The role of surprise: Understanding overreaction and underreaction to unanticipated events using in-play soccer betting market," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 614-629.
    9. Kai Fischer & Justus Haucap, 2020. "Betting Market Efficiency in the Presence of Unfamiliar Shocks: The Case of Ghost Games during the Covid-19 Pandemic," CESifo Working Paper Series 8526, CESifo.
    10. 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.
    11. 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.
    12. Jaiho Chung & Joon Ho Hwang, 2010. "An Empirical Examination of the Parimutuel Sports Lottery Market versus the Bookmaker Market," Southern Economic Journal, John Wiley & Sons, vol. 76(4), pages 884-905, April.
    13. Michael Sinkey & Trevon Logan, 2014. "Does the Hot Hand Drive the Market? Evidence from College Football Betting Markets," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 40(4), pages 583-603, September.
    14. Greg Durham & Mukunthan Santhanakrishnan, 2012. "Point-Spread Wagering Markets' Analogue to Realized Return in Financial Markets," Journal of Sports Economics, , vol. 13(5), pages 554-566, October.
    15. 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).
    16. Sung, Ming-Chien & McDonald, David C.J. & Johnson, Johnnie E.V. & Tai, Chung-Ching & Cheah, Eng-Tuck, 2019. "Improving prediction market forecasts by detecting and correcting possible over-reaction to price movements," European Journal of Operational Research, Elsevier, vol. 272(1), pages 389-405.
    17. Hegarty, Tadgh & Whelan, Karl, 2023. "Disagreement and Market Structure in Betting Markets: Theory and Evidence from European Soccer," MPRA Paper 117243, University Library of Munich, Germany.
    18. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2023. "Gambling on Momentum in Contests," Economics Discussion Papers em-dp2023-08, Department of Economics, University of Reading.
    19. Ziemba, William, 2020. "Parimutuel betting markets: racetracks and lotteries revisited," LSE Research Online Documents on Economics 118873, London School of Economics and Political Science, LSE Library.
    20. Ruud H. Koning & Renske Zijm, 2023. "Betting market efficiency and prediction in binary choice models," Annals of Operations Research, Springer, vol. 325(1), pages 135-148, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:joepsy:v:81:y:2020:i:c:s0167487020300660. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joep .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.