IDEAS home Printed from https://ideas.repec.org/a/sae/jospec/v16y2015i4p390-409.html
   My bibliography  Save this article

Using Monte Carlo Simulation to Calculate Match Importance

Author

Listed:
  • Jiří LahviÄ ka

Abstract

This article presents a new method of calculating match importance. Match importance is defined as strength of relationship between the match result and a given season outcome. Probabilities of all necessary match result-season outcome combinations are estimated by Monte Carlo simulation. Using actual results of 12 seasons of English Premier League and betting odds, it is shown that both match result and season outcome predictions are realistic. The method provides results that are close to Jennett’s approach; however, it does not require ex post information and can be used for any type of season outcome.

Suggested Citation

  • Jiří LahviÄ ka, 2015. "Using Monte Carlo Simulation to Calculate Match Importance," Journal of Sports Economics, , vol. 16(4), pages 390-409, May.
    • Handle: RePEc:sae:jospec:v:16:y:2015:i:4:p:390-409
    DOI: 10.1177/1527002513490172
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1527002513490172
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1527002513490172?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
    ---><---

    References listed on IDEAS

    as
    1. Jennett, Nicholas I, 1984. "Attendances, Uncertainty of Outcome and Policy in Scottish League Football," Scottish Journal of Political Economy, Scottish Economic Society, vol. 31(2), pages 176-198, June.
    2. Peel, David A & Thomas, Dennis A, 1992. "The Demand for Football: Some Evidence on Outcome Uncertainty," Empirical Economics, Springer, vol. 17(2), pages 323-331.
    3. Men‐Andri Benz & Leif Brandes & Egon Franck, 2009. "Do Soccer Associations Really Spend On A Good Thing? Empirical Evidence On Heterogeneity In The Consumer Response To Match Uncertainty Of Outcome," Contemporary Economic Policy, Western Economic Association International, vol. 27(2), pages 216-235, April.
    4. Ioannis Asimakopoulos & John Goddard, 2004. "Forecasting football results and the efficiency of fixed-odds betting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(1), pages 51-66.
    5. Rodney J. Paul, 2003. "Variations in NHL Attendance: The Impact of Violence, Scoring, and Regional Rivalries," American Journal of Economics and Sociology, Wiley Blackwell, vol. 62(2), pages 345-364, April.
    6. Dries Goossens & Jeroen Beliën & Frits Spieksma, 2012. "Comparing league formats with respect to match importance in Belgian football," Annals of Operations Research, Springer, vol. 194(1), pages 223-240, April.
    7. Jaume García & Plácido Rodríguez, 2002. "The Determinants of Football Match Attendance Revisited," Journal of Sports Economics, , vol. 3(1), pages 18-38, February.
    8. Michael Cain & David Law & David Peel, 2000. "The Favourite‐Longshot Bias and Market Efficiency in UK Football betting," Scottish Journal of Political Economy, Scottish Economic Society, vol. 47(1), pages 25-36, February.
    9. Baimbridge, Mark & Cameron, Samuel & Dawson, Peter, 1996. "Satellite Television and the Demand for Football: A Whole New Ball Game?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 43(3), pages 317-333, August.
    10. David Forrest & Rob Simmons, 2006. "New Issues in Attendance Demand," Journal of Sports Economics, , vol. 7(3), pages 247-266, August.
    11. M. J. Maher, 1982. "Modelling association football scores," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 36(3), pages 109-118, September.
    12. Feddersen, Arne & Humphreys, Brad & Soebbing, Brian, 2012. "Cost Incentives in European Football," Working Papers 2012-13, University of Alberta, Department of Economics.
    13. 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.
    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. Pascal Courty & Jeffrey Cisyk, 2024. "Sports injuries and game stakes: Concussions in the National Football League," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 430-448, January.
    2. Lahvicka, Jiri, 2013. "Does Match Uncertainty Increase Attendance? A Non-Regression Approach," MPRA Paper 48571, University Library of Munich, Germany.
    3. Daniel Goller & Sandro Heiniger, 2024. "A general framework to quantify the event importance in multi-event contests," Annals of Operations Research, Springer, vol. 341(1), pages 71-93, October.
    4. Brad R. Humphreys & Li Zhou, 2015. "The Louis–Schmelling Paradox and the League Standing Effect Reconsidered," Journal of Sports Economics, , vol. 16(8), pages 835-852, December.
    5. Jiří LahviÄ ka, 2015. "The Impact of Playoffs on Seasonal Uncertainty in the Czech Ice Hockey Extraliga," Journal of Sports Economics, , vol. 16(7), pages 784-801, October.

    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. Lahvicka, Jiri, 2012. "Using Monte Carlo simulation to calculate match importance: the case of English Premier League," MPRA Paper 40998, University Library of Munich, Germany.
    2. Besters, Lucas, 2018. "Economics of professional football," Other publications TiSEM d9e6b9b7-a17b-4665-9cca-1, Tilburg University, School of Economics and Management.
    3. Tim Pawlowski, 2013. "Testing the Uncertainty of Outcome Hypothesis in European Professional Football," Journal of Sports Economics, , vol. 14(4), pages 341-367, August.
    4. Lahvicka, Jiri, 2010. "Attendance of ice hockey matches in the Czech Extraliga," MPRA Paper 27653, University Library of Munich, Germany.
    5. Dominik Schreyer & Sascha L. Schmidt & Benno Torgler, 2019. "Football Spectator No-Show Behavior," Journal of Sports Economics, , vol. 20(4), pages 580-602, May.
    6. Schreyer, Dominik & Schmidt, Sascha L. & Torgler, Benno, 2016. "Against all odds? Exploring the role of game outcome uncertainty in season ticket holders’ stadium attendance demand," Journal of Economic Psychology, Elsevier, vol. 56(C), pages 192-217.
    7. Nicholas King & P. Dorian Owen & Rick Audas, 2012. "Playoff Uncertainty, Match Uncertainty and Attendance at Australian National Rugby League Matches," The Economic Record, The Economic Society of Australia, vol. 88(281), pages 262-277, June.
    8. Dominik Schreyer, 2019. "Football spectator no-show behaviour in the German Bundesliga," Applied Economics, Taylor & Francis Journals, vol. 51(45), pages 4882-4901, September.
    9. 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.
    10. Wen-Jhan Jane, 2014. "The Relationship Between Outcome Uncertainties and Match Attendance: New Evidence in the National Basketball Association," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 45(2), pages 177-200, September.
    11. Ferda HALICIOGLU, 2005. "Forecasting the Professional Team Sporting Events: Evidence from Euro 2000 and 2004 Football Tournaments," Industrial Organization 0508001, University Library of Munich, Germany.
    12. Kevin Alavy & Alison Gaskell & Stephanie Leach & Stefan Szymanski, 2010. "On the Edge of Your Seat: Demand for Football on Television and the Uncertainty of Outcome Hypothesis," International Journal of Sport Finance, Fitness Information Technology, vol. 5(2), pages 75-95, May.
    13. Farai Jena & Barry Reilly, 2022. "Are spectator preferences weaker for cup compared to league competitions? Evidence from Irish soccer," Applied Economics Letters, Taylor & Francis Journals, vol. 29(9), pages 835-841, May.
    14. Jeffery Borland, 2003. "Demand for Sport," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 19(4), pages 478-502, Winter.
    15. Hvattum, Lars Magnus & Arntzen, Halvard, 2010. "Using ELO ratings for match result prediction in association football," International Journal of Forecasting, Elsevier, vol. 26(3), pages 460-470, July.
    16. Dominik Schreyer & Benno Torgler, 2018. "On the Role of Race Outcome Uncertainty in the TV Demand for Formula 1 Grands Prix," Journal of Sports Economics, , vol. 19(2), pages 211-229, February.
    17. David Forrest & Robert Simmons & Babatunde Buraimo, 2005. "Outcome Uncertainty And The Couch Potato Audience," Scottish Journal of Political Economy, Scottish Economic Society, vol. 52(4), pages 641-661, September.
    18. Christian Gjersing Nielsen & Rasmus K. Storm & Tor Georg Jakobsen, 2019. "The impact of English Premier League broadcasts on Danish spectator demand: a small league perspective," Journal of Business Economics, Springer, vol. 89(6), pages 633-653, August.
    19. Marco Di Domizio & Raul Caruso, 2015. "Hooliganism and Demand for Football in Italy: Attendance and Counterviolence Policy Evaluation," German Economic Review, Verein für Socialpolitik, vol. 16(2), pages 123-137, May.
    20. Budzinski, Oliver & Pawlowski, Tim, 2014. "The behavioural economics of competitive balance: Implications for league policy and championship management," Ilmenau Economics Discussion Papers 89, Ilmenau University of Technology, Institute of Economics.

    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:sae:jospec:v:16:y:2015:i:4:p:390-409. 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: SAGE Publications (email available below). General contact details of provider: .

    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.