IDEAS home Printed from https://ideas.repec.org/p/inn/wpaper/2012-09.html
   My bibliography  Save this paper

History Repeating: Spain Beats Germany in the EURO 2012 Final

Author

Listed:
  • Achim Zeileis
  • Christoph Leitner
  • Kurt Hornik

Abstract

Four years after the last European football championship (EURO) in Austria and Switzerland, the two finalists of the EURO 2008 - Spain and Germany - are again the clear favorites for the EURO 2012 in Poland and the Ukraine. Using a bookmaker consensus rating - obtained by aggregating winning odds from 23 online bookmakers - the forecast winning probability for Spain is 25.8% followed by Germany with 22.2%, while all other competitors have much lower winning probabilities (The Netherlands are in third place with a predicted 11.3%). Furthermore, by complementing the bookmaker consensus results with simulations of the whole tournament, we can infer that the probability for a rematch between Spain and Germany in the final is 8.9% with the odds just slightly in favor of Spain for prevailing again in such a final (with a winning probability of 52.9%). Thus, one can conclude that - based on bookmakers' expectations - it seems most likely that history repeats itself and Spain defends its European championship title against Germany. However, this outcome is by no means certain and many other courses of the tournament are not unlikely as will be presented here. All forecasts are the result of an aggregation of quoted winning odds for each team in the EURO 2012: These are first adjusted for profit margins ("overrounds"), averaged on the log-odds scale, and then transformed back to winning probabilities. Moreover, team abilities (or strengths) are approximated by an "inverse" procedure of tournament simulations, yielding estimates of all pairwise probabilities (for matches between each pair of teams) as well as probabilities to proceed to the various stages of the tournament. This technique correctly predicted the EURO 2008 final (Leitner, Zeileis, Hornik 2008), with better results than other rating/forecast methods (Leitner, Zeileis, Hornik 2010a), and correctly predicted Spain as the 2010 FIFA World Champion (Leitner, Zeileis, Hornik 2010b). Compared to the EURO 2008 forecasts, there are many parallels but two notable differences: First, the gap between Spain/Germany and all remaining teams is much larger. Second, the odds for the predicted final were slightly in favor of Germany in 2008 whereas this year the situation is reversed.

Suggested Citation

  • Achim Zeileis & Christoph Leitner & Kurt Hornik, 2012. "History Repeating: Spain Beats Germany in the EURO 2012 Final," Working Papers 2012-09, Faculty of Economics and Statistics, Universität Innsbruck.
  • Handle: RePEc:inn:wpaper:2012-09
    as

    Download full text from publisher

    File URL: https://www2.uibk.ac.at/downloads/c4041030/wpaper/2012-09.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Forrest, David & Goddard, John & Simmons, Robert, 2005. "Odds-setters as forecasters: The case of English football," International Journal of Forecasting, Elsevier, vol. 21(3), pages 551-564.
    2. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Visualizing Euro 2012 with ggplot2
      by diffuseprior in DiffusePrioR on 2012-06-09 15:58:40
    2. Home Victory for Brazil in the 2014 FIFA World Cup
      by ? in R-bloggers on 2014-05-26 16:58:00
    3. Predictive Bookmaker Consensus Model for the UEFA Euro 2016
      by ? in R-bloggers on 2016-05-31 19:43:00

    Citations

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


    Cited by:

    1. Groll Andreas & Abedieh Jasmin, 2013. "Spain retains its title and sets a new record – generalized linear mixed models on European football championships," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 9(1), pages 51-66, March.
    2. Achim Zeileis & Christoph Leitner & Kurt Hornik, 2014. "Home Victory for Brazil in the 2014 FIFA World Cup," Working Papers 2014-17, Faculty of Economics and Statistics, Universität Innsbruck.
    3. Groll Andreas & Schauberger Gunther & Tutz Gerhard, 2015. "Prediction of major international soccer tournaments based on team-specific regularized Poisson regression: An application to the FIFA World Cup 2014," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 11(2), pages 97-115, June.
    4. Achim Zeileis & Christoph Leitner & Kurt Hornik, 2016. "Predictive Bookmaker Consensus Model for the UEFA Euro 2016," Working Papers 2016-15, Faculty of Economics and Statistics, Universität Innsbruck.
    5. Achim Zeileis & Christoph Leitner & Kurt Hornik, 2018. "Probabilistic forecasts for the 2018 FIFA World Cup based on the bookmaker consensus model," Working Papers 2018-09, Faculty of Economics and Statistics, Universität Innsbruck.

    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. da Costa, Igor Barbosa & Marinho, Leandro Balby & Pires, Carlos Eduardo Santos, 2022. "Forecasting football results and exploiting betting markets: The case of “both teams to score”," International Journal of Forecasting, Elsevier, vol. 38(3), pages 895-909.
    2. Marc Garnica-Caparrós & Daniel Memmert & Fabian Wunderlich, 2022. "Artificial data in sports forecasting: a simulation framework for analysing predictive models in sports," Information Systems and e-Business Management, Springer, vol. 20(3), pages 551-580, September.
    3. J. James Reade & Sachiko Akie, 2013. "Using Forecasting to Detect Corruption in International Football," Working Papers 2013-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    4. Constantinou Anthony Costa & Fenton Norman Elliott, 2013. "Determining the level of ability of football teams by dynamic ratings based on the relative discrepancies in scores between adversaries," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 9(1), pages 37-50, March.
    5. Karol Kempa & Hannes Rusch, 2019. "Dissent, sabotage, and leader behaviour in contests: Evidence from European football," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 40(5), pages 500-514, July.
    6. Jonas Hammerschmidt & Fabian Eggers & Sascha Kraus & Paul Jones & Matthias Filser, 2020. "Entrepreneurial orientation in sports entrepreneurship - a mixed methods analysis of professional soccer clubs in the German-speaking countries," International Entrepreneurship and Management Journal, Springer, vol. 16(3), pages 839-857, September.
    7. A. C. Titman & D. A. Costain & P. G. Ridall & K. Gregory, 2015. "Joint modelling of goals and bookings in association football," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(3), pages 659-683, June.
    8. Jaume García & Levi Pérez & Plácido Rodríguez, 2017. "Forecasting football match results: are the many smarter than the few?," Chapters, in: Plácido Rodríguez & Brad R. Humphreys & Robert Simmons (ed.), The Economics of Sports Betting, chapter 5, pages 71-91, Edward Elgar Publishing.
    9. Jonas Hammerschmidt & Fabian Eggers & Sascha Kraus & Paul Jones & Matthias Filser, 0. "Entrepreneurial orientation in sports entrepreneurship - a mixed methods analysis of professional soccer clubs in the German-speaking countries," International Entrepreneurship and Management Journal, Springer, vol. 0, pages 1-19.
    10. 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.
    11. Andrés Ramírez Hassan & Johnatan Cardona Jiménez, 2014. "Which team will win the 2014 FIFA World Cup? A Bayesian approach for dummies," Documentos de Trabajo de Valor Público 10898, Universidad EAFIT.
    12. 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.
    13. 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.
    14. Bert Scholtens & Wijtze Peenstra, 2009. "Scoring on the stock exchange? The effect of football matches on stock market returns: an event study," Applied Economics, Taylor & Francis Journals, vol. 41(25), pages 3231-3237.
    15. 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.
    16. Babatunde Buraimo & David Peel & Rob Simmons, 2013. "Systematic Positive Expected Returns in the UK Fixed Odds Betting Market: An Analysis of the Fink Tank Predictions," IJFS, MDPI, vol. 1(4), pages 1-15, December.
    17. David Winkelmann & Marius Ötting & Christian Deutscher & Tomasz Makarewicz, 2024. "Are Betting Markets Inefficient? Evidence From Simulations and Real Data," Journal of Sports Economics, , vol. 25(1), pages 54-97, January.
    18. Singleton, Carl & Reade, J. James & Brown, Alasdair, 2020. "Going with your gut: The (In)accuracy of forecast revisions in a football score prediction game," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 89(C).
    19. James Reade, 2014. "Information And Predictability: Bookmakers, Prediction Markets And Tipsters As Forecasters," Journal of Prediction Markets, University of Buckingham Press, vol. 8(1), pages 43-76.
    20. Christoph Buehren & Tim Meyer & Christian Pierdzioch, 2020. "Experimental Evidence on Forecaster (anti-) Herding in Sports Markets," MAGKS Papers on Economics 202038, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).

    More about this item

    Keywords

    consensus; agreement; bookmakers odds; sports tournaments; EURO 2012;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:inn:wpaper:2012-09. 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: Janette Walde (email available below). General contact details of provider: https://edirc.repec.org/data/fuibkat.html .

    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.