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Anyone for Tennis (Betting)?

Author

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  • David Forrest
  • Ian Mchale

Abstract

The most robust anomaly noted in the literature on wagering markets is (positive) longshot bias: over a period of 50 years, it has been well documented in horse betting that higher expected returns accrue to short- than to long-odds bets. However, a few examples of betting markets with zero or negative bias have been found, for example in certain American sports. The understanding of longshot bias is likely to be informed by comparing and contrasting conditions in markets displaying positive, zero, and negative bias but, to date, relatively few markets have been examined. This paper employs a large data set on professional men's tennis matches and a new econometric approach to the estimation of the relationship between returns and odds. It finds positive bias throughout the range of odds. It discusses this finding in the context of the debate on why biases exist and persist in wagering markets, focusing particularly on bettors' attitudes towards risk and skewness.

Suggested Citation

  • David Forrest & Ian Mchale, 2007. "Anyone for Tennis (Betting)?," The European Journal of Finance, Taylor & Francis Journals, vol. 13(8), pages 751-768.
    • Handle: RePEc:taf:eurjfi:v:13:y:2007:i:8:p:751-768
    DOI: 10.1080/13518470701705736
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    Cited by:

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    2. Frantisek Kopriva, 2015. "Constant Bet Size? Don't Bet on It! Testing Expected Utility Theory on Betfair Data," CERGE-EI Working Papers wp545, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    3. Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico & Johnson, Johnnie E.V., 2018. "It takes all sorts: A heterogeneous agent explanation for prediction market mispricing," European Journal of Operational Research, Elsevier, vol. 270(2), pages 556-569.
    4. 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.
    5. Norton, Hugh & Gray, Steve & Faff, Robert, 2015. "Yes, one-day international cricket ‘in-play’ trading strategies can be profitable!," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 164-176.
    6. Julio del Corral, 2009. "Competitive Balance and Match Uncertainty in Grand-Slam Tennis," Journal of Sports Economics, , vol. 10(6), pages 563-581, December.
    7. Jiř� Lahvička, 2014. "What causes the favourite-longshot bias? Further evidence from tennis," Applied Economics Letters, Taylor & Francis Journals, vol. 21(2), pages 90-92, January.
    8. Karl Whelan, 2024. "Risk aversion and favourite–longshot bias in a competitive fixed‐odds betting market," Economica, London School of Economics and Political Science, vol. 91(361), pages 188-209, January.
    9. Merz, Oliver & Flepp, Raphael & Franck, Egon, 2021. "Sonic Thunder vs. Brian the Snail: Are people affected by uninformative racehorse names?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 93(C).
    10. Isabel Abinzano & Luis Muga & Rafael Santamaria, 2019. "Hidden Power of Trading Activity: The FLB in Tennis Betting Exchanges," Journal of Sports Economics, , vol. 20(2), pages 261-285, February.
    11. Jennifer Brown & Dylan B. Minor, 2014. "Selecting the Best? Spillover and Shadows in Elimination Tournaments," Management Science, INFORMS, vol. 60(12), pages 3087-3102, December.
    12. Whelan, Karl & Hegarty, Tadgh, 2023. "Calculating The Bookmaker's Margin: Why Bets Lose More On Average Than You Are Warned," MPRA Paper 116924, University Library of Munich, Germany.
    13. McHale, Ian & Morton, Alex, 2011. "A Bradley-Terry type model for forecasting tennis match results," International Journal of Forecasting, Elsevier, vol. 27(2), pages 619-630.
    14. Angelini, Giovanni & Candila, Vincenzo & De Angelis, Luca, 2022. "Weighted Elo rating for tennis match predictions," European Journal of Operational Research, Elsevier, vol. 297(1), pages 120-132.
    15. He, Xue-Zhong & Treich, Nicolas, 2017. "Prediction market prices under risk aversion and heterogeneous beliefs," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 105-114.
    16. 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.
    17. McHale, Ian & Morton, Alex, 2011. "A Bradley-Terry type model for forecasting tennis match results," International Journal of Forecasting, Elsevier, vol. 27(2), pages 619-630, April.
    18. del Corral, Julio & Prieto-Rodríguez, Juan, 2010. "Are differences in ranks good predictors for Grand Slam tennis matches?," International Journal of Forecasting, Elsevier, vol. 26(3), pages 551-563, July.
    19. Ramirez, Philip & Reade, J. James & Singleton, Carl, 2023. "Betting on a buzz: Mispricing and inefficiency in online sportsbooks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1413-1423.
    20. Niko Suhonen & Jani Saastamoinen & Mika Linden, 2018. "A dual theory approach to estimating risk preferences in the parimutuel betting market," Empirical Economics, Springer, vol. 54(3), pages 1335-1351, May.
    21. Hegarty, Tadgh & Whelan, Karl, 2023. "Disagreement and Market Structure in Betting Markets: Theory and Evidence from European Soccer," CEPR Discussion Papers 18144, C.E.P.R. Discussion Papers.

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