IDEAS home Printed from https://ideas.repec.org/p/zbw/hwwirp/1-22.html
   My bibliography  Save this paper

Der Faktor Zufall im Fußball: Eine empirische Untersuchung für die Saison 2007/08

Author

Listed:
  • Quitzau, Jörn
  • Vöpel, Henning

Abstract

Der Zufall kann im Sport durch Fehlentscheidungen der Schiedsrichter, Verletzungen oder abgefälschte Torschüsse eine große Rolle spielen. In der Bundesliga betrug der Einfluss des Zufalls auf den Spielausgang in der Saison 2007/08 im Durchschnitt über 50 Prozent. Wer um die Meisterschaft und wer gegen den Abstieg spielt, ist daher auch eine Frage von Glück und Pech.

Suggested Citation

  • Quitzau, Jörn & Vöpel, Henning, 2009. "Der Faktor Zufall im Fußball: Eine empirische Untersuchung für die Saison 2007/08," HWWI Research Papers 1-22, Hamburg Institute of International Economics (HWWI).
    • Handle: RePEc:zbw:hwwirp:1-22
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/48193/1/640206204.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Figlewski, Stephen, 1979. "Subjective Information and Market Efficiency in a Betting Market," Journal of Political Economy, University of Chicago Press, vol. 87(1), pages 75-88, February.
    2. Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
    3. Sauer, Raymond D & Brajer, Vic & Ferris, Stephen P & Marr, M Wayne, 1988. "Hold Your Bets: Another Look at the Efficiency of the Gambling Market for National Football League Games: Comment," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 206-213, February.
    4. Roger C. Vergin & Michael Scriabin, 1978. "Winning Strategies for Wagering on National Football League Games," Management Science, INFORMS, vol. 24(8), pages 809-818, April.
    5. Quitzau, Jörn, 2005. "Faktor Zufall als Spielverderber: zur Prognostizierbarkeit von Fußballergebnissen – Wettmärkte als effizienter Informationslieferant," Research Notes 18, Deutsche Bank Research.
    6. Woodland, Linda M & Woodland, Bill M, 1994. "Market Efficiency and the Favorite-Longshot Bias: The Baseball Betting Market," Journal of Finance, American Finance Association, vol. 49(1), pages 269-279, March.
    7. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    8. Vöpel, Henning, 2006. "Ein ZIDANE-Clustering-Theorem und Implikationen für den Finanzausgleich in der Bundesliga," HWWI Research Papers 1-3, Hamburg Institute of International Economics (HWWI).
    9. Camerer, Colin F, 1989. "Does the Basketball Market Believe in the 'Hot Hand'?," American Economic Review, American Economic Association, vol. 79(5), pages 1257-1261, December.
    10. Gray, Philip K & Gray, Stephen F, 1997. "Testing Market Efficiency: Evidence from the NFL Sports Betting Market," Journal of Finance, American Finance Association, vol. 52(4), pages 1725-1737, September.
    11. Ali, Mukhtar M, 1979. "Some Evidence of the Efficiency of a Speculative Market," Econometrica, Econometric Society, vol. 47(2), pages 387-392, March.
    12. Snyder, Wayne W, 1978. "Horse Racing: Testing the Efficient Markets Model," Journal of Finance, American Finance Association, vol. 33(4), pages 1109-1118, September.
    13. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    14. repec:bla:jfinan:v:43:y:1988:i:4:p:995-1008 is not listed on IDEAS
    15. Thaler, Richard H & Ziemba, William T, 1988. "Parimutuel Betting Markets: Racetracks and Lotteries," Journal of Economic Perspectives, American Economic Association, vol. 2(2), pages 161-174, Spring.
    16. Zuber, Richard A & Gandar, John M & Bowers, Benny D, 1985. "Beating the Spread: Testing the Efficiency of the Gambling Market for National Football League Games," Journal of Political Economy, University of Chicago Press, vol. 93(4), pages 800-806, August.
    17. 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.
    Full references (including those not matched with items on IDEAS)

    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. Quitzau, Jörn, 2005. "Faktor Zufall als Spielverderber: zur Prognostizierbarkeit von Fußballergebnissen – Wettmärkte als effizienter Informationslieferant," Research Notes 18, Deutsche Bank Research.
    2. Sathya Ramesh & Ragib Mostofa & Marco Bornstein & John Dobelman, 2019. "Beating the House: Identifying Inefficiencies in Sports Betting Markets," Papers 1910.08858, arXiv.org, revised Oct 2019.
    3. 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.
    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. 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.
    6. Ziemba, William, 2020. "Parimutuel betting markets: racetracks and lotteries revisited," LSE Research Online Documents on Economics 118873, London School of Economics and Political Science, LSE Library.
    7. Gray, Philip K & Gray, Stephen F, 1997. "Testing Market Efficiency: Evidence from the NFL Sports Betting Market," Journal of Finance, American Finance Association, vol. 52(4), pages 1725-1737, September.
    8. Jinook Jeong & Jee Young Kim & Yoon Jae Ro, 2019. "On the efficiency of racetrack betting market: a new test for the favourite-longshot bias," Applied Economics, Taylor & Francis Journals, vol. 51(54), pages 5817-5828, November.
    9. Michael Sinkey & Trevon Logan, 2014. "Does the Hot Hand Drive the Market? Evidence from College Football Betting Markets," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 40(4), pages 583-603, September.
    10. Russell Sobel & S. Travis Raines, 2003. "An examination of the empirical derivatives of the favourite-longshot bias in racetrack betting," Applied Economics, Taylor & Francis Journals, vol. 35(4), pages 371-385.
    11. Timothy J. Brailsford & Philip K. Gray & Stephen A. Easton & Stephen F. Gray, 1995. "The Efficiency of Australian Football Betting Markets," Australian Journal of Management, Australian School of Business, vol. 20(2), pages 167-195, December.
    12. Miller, Thomas W. & Rapach, David E., 2013. "An intra-week efficiency analysis of bookie-quoted NFL betting lines in NYC," Journal of Empirical Finance, Elsevier, vol. 24(C), pages 10-23.
    13. Robert Arscott, 2023. "Market Efficiency and Censoring Bias in College Football Gambling," Journal of Sports Economics, , vol. 24(5), pages 664-689, June.
    14. Ray C. Fair & John F. Oster, 2007. "College Football Rankings and Market Efficiency," Journal of Sports Economics, , vol. 8(1), pages 3-18, February.
    15. Philip W. S. Newall & Dominic Cortis, 2021. "Are Sports Bettors Biased toward Longshots, Favorites, or Both? A Literature Review," Risks, MDPI, vol. 9(1), pages 1-9, January.
    16. Jaiho Chung & Joon Ho Hwang, 2010. "An Empirical Examination of the Parimutuel Sports Lottery Market versus the Bookmaker Market," Southern Economic Journal, John Wiley & Sons, vol. 76(4), pages 884-905, April.
    17. Rodney J. Paul & Andrew P. Weinbach, 2005. "Bettor Misperceptions in the NBA," Journal of Sports Economics, , vol. 6(4), pages 390-400, November.
    18. Goto, Shingo & Yamada, Toru, 2023. "What drives biased odds in sports betting markets: Bettors’ irrationality and the role of bookmakers," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 252-270.
    19. Yoon Tae Sung & Scott Tainsky, 2014. "The National Football League Wagering Market," Journal of Sports Economics, , vol. 15(4), pages 365-384, August.
    20. Dagaev, Dmitry & Stoyan, Egor, 2020. "Parimutuel betting on the eSports duels: Evidence of the reverse favourite-longshot bias," Journal of Economic Psychology, Elsevier, vol. 81(C).

    More about this item

    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:zbw:hwwirp:1-22. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/hwwiide.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.