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The market for English Premier League (EPL) odds

Author

Listed:
  • Feng Guanhao
  • Polson Nicholas

    (Booth School of Business, University of Chicago, 5807 S Woodlawn Avenue, Chicago, IL 60637, USA)

  • Xu Jianeng

    (Department of Statistics, University of Chicago, 5747 S Ellis Avenue, Chicago, IL 60637, USA)

Abstract

This paper employs a Skellam process to represent real-time betting odds for English Premier League (EPL) soccer games. Given a matrix of market odds on all possible score outcomes, we estimate the expected scoring rates for each team. The expected scoring rates then define the implied volatility of an EPL game. As events in the game evolve, we re-estimate the expected scoring rates and our implied volatility measure to provide a dynamic representation of the market’s expectation of the game outcome. Using a dataset of 1520 EPL games from 2012–2016, we show how our model calibrates well to the game outcome. We illustrate our methodology on real-time market odds data for a game between Everton and West Ham in the 2015–2016 season. We show how the implied volatility for the outcome evolves as goals, red cards, and corner kicks occur. Finally, we conclude with directions for future research.

Suggested Citation

  • Feng Guanhao & Polson Nicholas & Xu Jianeng, 2016. "The market for English Premier League (EPL) odds," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(4), pages 167-178, December.
    • Handle: RePEc:bpj:jqsprt:v:12:y:2016:i:4:p:167-178:n:1
    DOI: 10.1515/jqas-2016-0039
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    References listed on IDEAS

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    1. Vecer Jan & Kopriva Frantisek & Ichiba Tomoyuki, 2009. "Estimating the Effect of the Red Card in Soccer: When to Commit an Offense in Exchange for Preventing a Goal Opportunity," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(1), pages 1-20, January.
    2. Polson Nicholas G. & Stern Hal S., 2015. "The implied volatility of a sports game," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(3), pages 145-153, September.
    3. Ole E. Barndorff-Nielsen & Neil Shephard, 2012. "Basics of Levy processes," Economics Papers 2012-W06, Economics Group, Nuffield College, University of Oxford.
    4. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    5. Steven D. Levitt, 2004. "Why are gambling markets organised so differently from financial markets?," Economic Journal, Royal Economic Society, vol. 114(495), pages 223-246, April.
    6. Avery, Christopher & Chevalier, Judith, 1999. "Identifying Investor Sentiment from Price Paths: The Case of Football Betting," The Journal of Business, University of Chicago Press, vol. 72(4), pages 493-521, October.
    7. 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.
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    Cited by:

    1. Chu Dani & Wu Yifan & Swartz Tim B., 2018. "Modified Kelly criteria," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 14(1), pages 1-11, March.

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