IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v57y2006i8d10.1057_palgrave.jors.2602062.html
   My bibliography  Save this article

Valuation of soccer spread bets

Author

Listed:
  • A D Fitt

    (University of Southampton)

  • C J Howls

    (University of Southampton)

  • M Kabelka

    (University of Southampton)

Abstract

Simple statistical and probabilistic arguments are used to value the most commonly traded online soccer spread bets. Such markets typically operate dynamically during the course of a match and accurate valuations must, therefore, reflect the changing state of the match. Both goals and corners are assumed to evolve as Poisson processes with constant means. Although many of the bets that are typically traded are relatively easy to value, some (including the ‘four flags’ market) require more detailed analysis. Examples are given of the evolution of the spread during typical matches and theoretical predictions are shown to compare closely to spreads quoted by online bookmakers during some of the important matches of the EURO2004 tournament.

Suggested Citation

  • A D Fitt & C J Howls & M Kabelka, 2006. "Valuation of soccer spread bets," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(8), pages 975-985, August.
  • Handle: RePEc:pal:jorsoc:v:57:y:2006:i:8:d:10.1057_palgrave.jors.2602062
    DOI: 10.1057/palgrave.jors.2602062
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/palgrave.jors.2602062
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/palgrave.jors.2602062?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. M. J. Maher, 1982. "Modelling association football scores," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 36(3), pages 109-118, September.
    2. Greenhough, J & Birch, P.C & Chapman, S.C & Rowlands, G, 2002. "Football goal distributions and extremal statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 615-624.
    3. D Dyte & S R Clarke, 2000. "A ratings based Poisson model for World Cup soccer simulation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(8), pages 993-998, August.
    4. 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.
    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. M B Wright, 2009. "50 years of OR in sport," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 161-168, May.
    2. 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.
    3. Oberstone Joel, 2009. "Differentiating the Top English Premier League Football Clubs from the Rest of the Pack: Identifying the Keys to Success," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(3), pages 1-29, July.

    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. S Lessmann & M-C Sung & J E V Johnson, 2011. "Towards a methodology for measuring the true degree of efficiency in a speculative market," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2120-2132, December.
    2. 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.
    3. M Wright & N Hirotsu, 2003. "The professional foul in football: Tactics and deterrents," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(3), pages 213-221, March.
    4. Chater, Mario & Arrondel, Luc & Gayant, Jean-Pascal & Laslier, Jean-François, 2021. "Fixing match-fixing: Optimal schedules to promote competitiveness," European Journal of Operational Research, Elsevier, vol. 294(2), pages 673-683.
    5. Sebastián Cea & Guillermo Durán & Mario Guajardo & Denis Sauré & Joaquín Siebert & Gonzalo Zamorano, 2020. "An analytics approach to the FIFA ranking procedure and the World Cup final draw," Annals of Operations Research, Springer, vol. 286(1), pages 119-146, March.
    6. Leitner, Christoph & Zeileis, Achim & Hornik, Kurt, 2010. "Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EUROÂ 2008," International Journal of Forecasting, Elsevier, vol. 26(3), pages 471-481, July.
    7. Hirotsu Nobuyoshi & Ito Masamitsu & Miyaji Chikara & Hamano Koji & Taguchi Azuma, 2009. "Modeling Tactical Changes of Formation in Association Football as a Non-Zero-Sum Game," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(3), pages 1-15, July.
    8. Corona Francisco & Horrillo Juan de Dios Tena & Wiper Michael Peter, 2017. "On the importance of the probabilistic model in identifying the most decisive games in a tournament," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(1), pages 11-23, March.
    9. Geenens Gery, 2010. "Who Deserved the 2008-2009 Belgian Football Champion Title? A Semiparametric Answer," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(4), pages 1-31, October.
    10. Geenens, Gery, 2014. "On the decisiveness of a game in a tournament," European Journal of Operational Research, Elsevier, vol. 232(1), pages 156-168.
    11. Gross, Johannes & Rebeggiani, Luca, 2018. "Chance or Ability? The Efficiency of the Football Betting Market Revisited," MPRA Paper 87230, University Library of Munich, Germany.
    12. Jeon, Gyuhyeon & Park, Juyong, 2021. "Characterizing patterns of scoring and ties in competitive sports," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    13. Hirotsu Nobuyoshi & Wright Mike B, 2006. "Modeling Tactical Changes of Formation in Association Football as a Zero-Sum Game," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 2(2), pages 1-22, April.
    14. G. K. Skinner & G. H. Freeman, 2009. "Soccer matches as experiments: how often does the 'best' team win?," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(10), pages 1087-1095.
    15. Fry, John & Serbera, Jean-Philippe & Wilson, Rob, 2021. "Managing performance expectations in association football," Journal of Business Research, Elsevier, vol. 135(C), pages 445-453.
    16. Goddard, John, 2005. "Regression models for forecasting goals and match results in association football," International Journal of Forecasting, Elsevier, vol. 21(2), pages 331-340.
    17. Cunniffe Nik J & Cook Alex R, 2009. "Cruel and Unusual Punishment? An Analysis of Point Deduction in European Association Football Leagues," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(4), pages 1-20, October.
    18. Holmes, Benjamin & McHale, Ian G. & Żychaluk, Kamila, 2023. "A Markov chain model for forecasting results of mixed martial arts contests," International Journal of Forecasting, Elsevier, vol. 39(2), pages 623-640.
    19. Scarf, Philip & Yusof, Muhammad Mat & Bilbao, Mark, 2009. "A numerical study of designs for sporting contests," European Journal of Operational Research, Elsevier, vol. 198(1), pages 190-198, October.
    20. Egon Franck & Erwin Verbeek & Stephan Nüesch, 2011. "Sentimental Preferences and the Organizational Regime of Betting Markets," Southern Economic Journal, John Wiley & Sons, vol. 78(2), pages 502-518, October.

    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:pal:jorsoc:v:57:y:2006:i:8:d:10.1057_palgrave.jors.2602062. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave-journals.com/ .

    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.