IDEAS home Printed from https://ideas.repec.org/a/sae/jospec/v13y2012i3p314-320.html
   My bibliography  Save this article

Upsets

Author

Listed:
  • Evan Osborne

Abstract

The article models the upset—a low-probability outcome of a periodic competition. It is assumed that the upset is an independent component of consumer preferences, whose marginal willingness to pay grows with time. The decision rule for a league on upset timing is a competitive-balance problem but is unlike standard models of competitive balance. Upset timing is likened partially to the optimal redemption time of a growing asset, and implications for competitive balance in this environment are derived.

Suggested Citation

  • Evan Osborne, 2012. "Upsets," Journal of Sports Economics, , vol. 13(3), pages 314-320, June.
    • Handle: RePEc:sae:jospec:v:13:y:2012:i:3:p:314-320
    DOI: 10.1177/1527002511416562
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1527002511416562
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1527002511416562?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. Krugman, Paul, 1980. "Scale Economies, Product Differentiation, and the Pattern of Trade," American Economic Review, American Economic Association, vol. 70(5), pages 950-959, December.
    2. Stefan Szymanski, 2010. "Income Inequality, Competitive Balance and the Attractiveness of Team Sports: Some Evidence and a Natural Experiment from English Soccer," Palgrave Macmillan Books, in: Football Economics and Policy, chapter 9, pages 182-201, Palgrave Macmillan.
    3. Glenn Knowles & Keith Sherony & Mike Haupert, 1992. "The Demand for Major League Baseball: A Test of the Uncertainty of Outcome Hypothesis," The American Economist, Sage Publications, vol. 36(2), pages 72-80, October.
    4. William Chan & Pascal Courty & Li Hao, 2009. "Suspense: Dynamic Incentives in Sports Contests," Economic Journal, Royal Economic Society, vol. 119(534), pages 24-46, January.
    5. Rodney Fort & James Quirk, 1995. "Cross-subsidization, Incentives, and Outcomes in Professional Team Sports Leagues," Journal of Economic Literature, American Economic Association, vol. 33(3), pages 1265-1299, September.
    6. 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.
    7. El-Hodiri, Mohamed & Quirk, James, 1971. "An Economic Model of a Professional Sports League," Journal of Political Economy, University of Chicago Press, vol. 79(6), pages 1302-1319, Nov.-Dec..
    8. Young Lee & Rodney Fort, 2008. "Attendance and the Uncertainty-of-Outcome Hypothesis in Baseball," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 33(4), pages 281-295, December.
    9. Samuelson, Paul A, 1976. "Economics of Forestry in an Evolving Society," Economic Inquiry, Western Economic Association International, vol. 14(4), pages 466-492, December.
    10. Anthony C. Krautmann & Lawrence Hadley, 2006. "Dynasties versus pennant races: competitive balance in major league baseball," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 287-292.
    11. Christophe Pérignon & Jean Marc Falter & Olivier Vercruysse, 2008. "Impact of Overwhelming Joy on Consumer Demand," Post-Print hal-00461063, HAL.
    12. John Vrooman, 2009. "Theory of the Perfect Game: Competitive Balance in Monopoly Sports Leagues," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 34(1), pages 5-44, February.
    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. Humphreys, Brad R & Pérez, Levi, 2019. "Loss aversion, upset preference, and sports television viewing audience size," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 78(C), pages 61-67.

    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. Martin Grossmann & Helmut Dietl & Markus Lang, 2010. "Revenue Sharing and Competitive Balance in a Dynamic Contest Model," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 36(1), pages 17-36, February.
    2. Stefan Szymanski, 2010. "The Economic Design of Sporting Contests," Palgrave Macmillan Books, in: The Comparative Economics of Sport, chapter 1, pages 1-78, Palgrave Macmillan.
    3. Raul Caruso & Francesco Addesa & Marco Di Domizio, 2019. "The Determinants of the TV Demand for Soccer: Empirical Evidence on Italian Serie A for the Period 2008-2015," Journal of Sports Economics, , vol. 20(1), pages 25-49, January.
    4. Brown, Katie M. & Salaga, Steven, 2018. "NCAA football television viewership: Product quality and consumer preference relative to market expectations," Sport Management Review, Elsevier, vol. 21(4), pages 377-390.
    5. 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.
    6. Brian Mills & Rodney Fort, 2014. "League-Level Attendance And Outcome Uncertainty In U.S. Pro Sports Leagues," Economic Inquiry, Western Economic Association International, vol. 52(1), pages 205-218, January.
    7. Thomas Peeters, 2011. "Optimal gate revenue sharing in sports leagues," Working Papers 1122, International Association of Sports Economists;North American Association of Sports Economists.
    8. Jason P. Berkowitz & Craig A. Depken II & Dennis P. Wilson, 2011. "When Going in Circles is Going Backward: Outcome Uncertainty in NASCAR," Journal of Sports Economics, , vol. 12(3), pages 253-283, June.
    9. Dennis Coates & Brad R. Humphreys & Li Zhou, 2014. "Reference-Dependent Preferences, Loss Aversion, And Live Game Attendance," Economic Inquiry, Western Economic Association International, vol. 52(3), pages 959-973, July.
    10. Coates, Dennis & Humphreys, Brad & Zhou, Li, 2012. "Outcome Uncertainty, Reference-Dependent Preferences and Live Game Attendance," Working Papers 2012-7, University of Alberta, Department of Economics.
    11. Alexander John Bond & Francesco Addesa, 2020. "Competitive Intensity, Fans’ Expectations, and Match-Day Tickets Sold in the Italian Football Serie A, 2012-2015," Journal of Sports Economics, , vol. 21(1), pages 20-43, January.
    12. Adam Cox, 2018. "Spectator Demand, Uncertainty of Results, and Public Interest," Journal of Sports Economics, , vol. 19(1), pages 3-30, January.
    13. Gyimesi, András, 2021. "Hosszú távú versenyegyensúly egy csapatsportliga közgazdasági modelljében [Long-term competitive balance in an economic model of a team sports league]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 585-616.
    14. Thomas Peeters, 2015. "Profit-Maximizing Gate Revenue Sharing In Sports Leagues," Economic Inquiry, Western Economic Association International, vol. 53(2), pages 1275-1291, April.
    15. Wladimir Andreff, 2014. "Building Blocks for a Disequilibrium Model of a European Team Sports League," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00971782, HAL.
    16. Masaki Fujimoto, 2023. "A Dynamic Analysis of Equal Revenue Sharing and Endogenous Salary Caps in the N-Team Leagues," Journal of Sports Economics, , vol. 24(5), pages 624-638, June.
    17. Jean‐Pascal Gayant & Nicolas Le Pape, 2017. "Increasing Downside or Outer Risk? The Challenge of Measuring Competitive Imbalance in Closed and Open Leagues," Southern Economic Journal, John Wiley & Sons, vol. 83(3), pages 774-795, January.
    18. Helmut M. Dietl & Martin Grossmann & Markus Lang, 2011. "Competitive Balance and Revenue Sharing in Sports Leagues With Utility-Maximizing Teams," Journal of Sports Economics, , vol. 12(3), pages 284-308, June.
    19. Robert J. Lemke & Matthew Leonard & Kelebogile Tlhokwane, 2010. "Estimating Attendance at Major League Baseball Games for the 2007 Season," Journal of Sports Economics, , vol. 11(3), pages 316-348, June.
    20. Trung Minh Dang & Ross Booth & Robert Brooks & Adi Schnytzer, 2015. "Do TV Viewers Value Uncertainty of Outcome? Evidence from the Australian Football League," The Economic Record, The Economic Society of Australia, vol. 91(295), pages 523-535, December.

    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:13:y:2012:i:3:p:314-320. 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.