IDEAS home Printed from https://ideas.repec.org/a/jns/jbstat/v232y2012i3p224-246.html
   My bibliography  Save this article

Beating thy Neighbor: Derby Effects in German Professional Soccer

Author

Listed:
  • Bäker Agnes

    (Eberhard Karls University Tübingen, Faculty of Economics and Social Sciences, Nauklerstr. 47, 72074 Tübingen, Germany)

  • Mechtel Mario

    (Eberhard Karls University Tübingen and IAAEG Trier, Behringstr., 54286 Trier, Germany)

  • Vetter Karin

    (Eberhard Karls University Tübingen, Faculty of Economics and Social Sciences, Nauklerstr. 47, 72074 Tübingen, Germany)

Abstract

It is widely acknowledged that derbies between two teams from the same city or region catch more public attention than “normal” soccer matches. Terms such as “Old Firm” (Rangers vs. Celtic), “Merseyside” (Liverpool FC vs. Everton FC), “Superclásico” (Boca Juniors vs. River Plate), and “Revierderby” (Dortmund vs. Schalke) are well-known even to people outside their respective countries of origin. Using data from the German Bundesliga from 1999 to 2009, we test whether derbies differ from other soccer matches with respect to the number of goals scored by each team, match results, and referee evaluations. The results are very surprising given the enormous amount of public attention that derbies with their special character attract: we find that there are no significant differences between derbies and “normal” matches. Despite the importance of derbies for fans and the public, they turn out to be “normal” soccer matches in all other respects.

Suggested Citation

  • Bäker Agnes & Mechtel Mario & Vetter Karin, 2012. "Beating thy Neighbor: Derby Effects in German Professional Soccer," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 232(3), pages 224-246, June.
    • Handle: RePEc:jns:jbstat:v:232:y:2012:i:3:p:224-246
    DOI: 10.1515/jbnst-2012-0304
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/jbnst-2012-0304
    Download Restriction: no
    File URL: https://libkey.io/10.1515/jbnst-2012-0304?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. 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.
    2. Fiona Carmichael & Dennis Thomas, 2005. "Home-Field Effect and Team Performance," Journal of Sports Economics, , vol. 6(3), pages 264-281, August.
    3. Ben Jann, 2008. "A Stata implementation of the Blinder-Oaxaca decomposition," ETH Zurich Sociology Working Papers 5, ETH Zurich, Chair of Sociology, revised 14 May 2008.
    4. Thomas Bauer & Silja Göhlmann & Mathias Sinning, 2007. "Gender differences in smoking behavior," Health Economics, John Wiley & Sons, Ltd., vol. 16(9), pages 895-909, September.
    5. Fiona Carmichael & Dennis Thomas & Robert Ward, 2001. "Production and Efficiency in Association Football," Journal of Sports Economics, , vol. 2(3), pages 228-243, August.
    6. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    7. M. J. Maher, 1982. "Modelling association football scores," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 36(3), pages 109-118, September.
    8. Mario Mechtel & Agnes Bäker & Tobias Brändle & Karin Vetter, 2011. "Red Cards," Journal of Sports Economics, , vol. 12(6), pages 621-646, December.
    9. Babatunde Buraimo & David Forrest & Robert Simmons, 2010. "The 12th man?: refereeing bias in English and German soccer," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 431-449, April.
    10. Marco Caliendo & Dubravko Radic, 2006. "Ten Do It Better, Do They?: An Empirical Analysis of an Old Football Myth," Discussion Papers of DIW Berlin 592, DIW Berlin, German Institute for Economic Research.
    11. Audas, Rick & Dobson, Stephen & Goddard, John, 2002. "The impact of managerial change on team performance in professional sports," Journal of Economics and Business, Elsevier, vol. 54(6), pages 633-650.
    12. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
    13. Tim Kuypers, 2000. "Information and efficiency: an empirical study of a fixed odds betting market," Applied Economics, Taylor & Francis Journals, vol. 32(11), pages 1353-1363.
    14. A. Colin Cameron & Pravin K. Trivedi, 2010. "Microeconometrics Using Stata, Revised Edition," Stata Press books, StataCorp LP, number musr, March.
    15. 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. Brian P. Soebbing & Pamela Wicker & Daniel Weimar & Johannes Orlowski, 2021. "How do Bookmakers Interpret Running Performance of Teams in Previous Games? Evidence From the Football Bundesliga," Journal of Sports Economics, , vol. 22(3), pages 231-250, April.
    2. van Damme, Nils & Baert, Stijn, 2019. "Home advantage in European international soccer: Which dimension of distance matters?," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-17.
    3. Daniel Weimar & Pamela Wicker, 2017. "Moneyball Revisited," Journal of Sports Economics, , vol. 18(2), pages 140-161, February.
    4. Stijn Baert & Simon Amez, 2018. "No better moment to score a goal than just before half time? A soccer myth statistically tested," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-17, March.
    5. Inna Zaytseva & Daniil Shaposhnikov, 2020. "Moneyball In Offensive Vs Defensive Actions In Soccer," HSE Working papers WP BRP 223/EC/2020, National Research University Higher School of Economics.

    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. Mario Mechtel & Agnes Bäker & Tobias Brändle & Karin Vetter, 2011. "Red Cards," Journal of Sports Economics, , vol. 12(6), pages 621-646, 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. 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.
    4. Gross, Johannes & Rebeggiani, Luca, 2018. "Chance or Ability? The Efficiency of the Football Betting Market Revisited," MPRA Paper 87230, University Library of Munich, Germany.
    5. 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.
    6. Giovanni Angelini & Luca De Angelis, 2017. "PARX model for football match predictions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(7), pages 795-807, November.
    7. 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.
    8. Thomas Y. Mathä & Alessandro Porpiglia & Michael Ziegelmeyer, 2014. "Wealth differences across borders and the effect of real estate price dynamics: Evidence from two household surveys," BCL working papers 90, Central Bank of Luxembourg.
    9. Michael E. Martell & Peyton Nash, 2020. "For Love and Money? Earnings and Marriage Among Same-Sex Couples," Journal of Labor Research, Springer, vol. 41(3), pages 260-294, September.
    10. Jakub Picka, 2014. "Problém "public-private pay gap" v České republice [The Public-Private Pay Gap in the Czech Republic]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(5), pages 662-682.
    11. Greaney, Theresa M. & Tanaka, Ayumu, 2021. "Foreign Ownership, Exporting and Gender Wage Gaps: Evidence from Japanese Linked Employer-Employee Data," Journal of the Japanese and International Economies, Elsevier, vol. 61(C).
    12. Jessen, Jonas & Schmitz, Sophia & Waights, Sevrin, 2020. "Understanding day care enrolment gaps," Journal of Public Economics, Elsevier, vol. 190(C).
    13. Powers, Daniel A. & Yun, Myeong-Su, 2009. "Multivariate Decomposition for Hazard Rate Models," IZA Discussion Papers 3971, Institute of Labor Economics (IZA).
    14. Kamila Kolpashnikova & Man-Yee Kan, 2020. "The gender gap in the United States: Housework across racialized groups," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 43(36), pages 1067-1080.
    15. Liliane Bonnal & Rachid Boumahdi & Pascal Favard, 2013. "The easiest way to estimate the Oaxaca-Blinder decomposition," Applied Economics Letters, Taylor & Francis Journals, vol. 20(1), pages 96-101, January.
    16. Yun Liang & John Gibson, 2017. "Location or Hukou: What Most Limits Fertility of Urban Women in China?," Asia and the Pacific Policy Studies, Wiley Blackwell, vol. 4(3), pages 527-540, September.
    17. Zhang, Li & Sharpe, Rhonda Vonshay & Li, Shi & Darity, William A., 2016. "Wage differentials between urban and rural-urban migrant workers in China," China Economic Review, Elsevier, vol. 41(C), pages 222-233.
    18. Shiba Shankar Pattayat & Jajati Keshari Parida & Kirtti Ranjan Paltasingh, 2023. "Gender Wage Gap among Rural Non-farm Sector Employees in India: Evidence from Nationally Representative Survey," Review of Development and Change, , vol. 28(1), pages 22-44, June.
    19. Michael Martell, 2013. "Do ENDAs End Discrimination for Behaviorally Gay Men?," Journal of Labor Research, Springer, vol. 34(2), pages 147-169, June.
    20. Takuya Hasebe, 2016. "Estimating the variance of decomposition effects," Applied Economics, Taylor & Francis Journals, vol. 48(20), pages 1902-1913, April.

    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:jns:jbstat:v:232:y:2012:i:3:p:224-246. 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: Peter Golla (email available below). General contact details of provider: https://www.degruyter.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.