Skip to main content

How Success and Uncertainty Compel Interest in Related Goods: Playoff Probability and Out-of-Market Television Viewership in the National Football League

Review of Industrial Organization volume 48, pages 29–43 (2016)Cite this article

Abstract

Professional sports league franchises are both on-field competitors and business partners. In this paper, we examine whether local franchise characteristics are associated with the consumption of goods that are produced by other franchises within the same league. Specifically, we investigate how uncertainty over whether the local market team reaches the postseason affects interest in out-of-market National Football League broadcasts. We find that consumers possess a conditional interest in other league contests depending on the degree to which the local franchise is in the race to reach the playoffs. This effect increases at a diminishing rate and reaches a maximum when local franchise playoff probability is approximately 60 %.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Notes

  1. The exception is when the game is not a sellout, in which case the game is blacked out in the home market and a replacement game is not telecast.

  2. We chose the 2006–2009 time frame because it was the first year of a new broadcasting contract for the NFL. Therefore, the channels on which the national broadcasts took place did not change during the time of our data set.

  3. Relegation is the practice (e.g., in European soccer leagues) whereby, at the end of the season, the bottom few teams in a higher league are required to trade places with the top few teams in a lower league for the forthcoming season.

  4. With the use of advanced statistics becoming more common, mainstream media outlets (including ESPN) regularly reference both individual game win probabilities and week-to-week team playoff probabilities. The latter are included on “NFL Standings” pages on many mainstream media websites. Furthermore, media outlets habitually discuss late season "playoff scenarios” where playoff probabilities are either implied or provided.

  5. AdvancedFootballAnalytics.com was founded and is managed by Brian Burke, who is widely considered to be a pioneer in the area of advanced NFL statistics. He is a regular contributor to The New York Times and The Washington Post, among others.

  6. Accordingly, related to this example, the categorical variable Thursday1, with Thursday denoting day of week and 1 denoting early afternoon, is not included in the model.

  7. LocalSubstitute is additive to Substitute.

  8. We estimated an additional model that included an indicator variable that was equal to unity when the probability of the hometown team qualifying for the playoffs was nonzero; however, the effect was not significant (β = 0.00237, t(1247) = 0.08, p = 0.94).

  9. Using the estimates generated by the model, when LocalSub = 0, the function is given as \( f(x) = ax^{2} + bx + cz, \) where z represents the remaining covariates. The first order derivative of the function is set to zero such that \( x = - \frac{b}{2a} \) within \( \epsilon \left[ {0,100} \right] \).

  10. Rascher and Solmes (2007) find the optimal probability to be 66 % for National Basketball Association (NBA) games. McDonald and Rascher (2000) also find a curvelinear relationship between attendance and game uncertainty, while Whitney (1988) finds a quadratic effect of championship probability. Knowles, Sherony, and Haupert (1992) determine that MLB attendance is maximized when the probability of a home win is 60 %.

  11. A single Nielsen rating point is equivalent to one percent of homes in a given market that are tuned into a specific broadcast. However, Nielsen reports ratings on a 0-100 scale. We “transform” our dependent variable back to its original form [0,1] prior to using fractional regression.

  12. This is further substantiated by an alternative model that considered both whether a team was simply in the race to reach the playoffs and winning percentage. In this estimation, which is available upon request, neither the dummy variable nor the linear quality estimate was statistically significant.

References

  • Borland, J. (1987). The demand for Australian rules football. Economic Record, 63, 220–230.

    Article  Google Scholar 

  • Butler, M. (2002). Interleague play and baseball attendance. Journal of Sports Economics, 3, 320–334.

    Article  Google Scholar 

  • Carmichael, F., Millington, J., & Simmons, R. (1999). Elasticity of demand for Rugby League attendance and the impact of BSkyB. Applied Economics Letters, 6, 797–800.

    Article  Google Scholar 

  • Chiang, Y., & Jane, W. (2013). The effects of outcome uncertainties, patriotism, and Asian regionalism in the World Baseball Classic. Journal of Media Economics, 26, 148–161.

    Article  Google Scholar 

  • Dobson, S. M., & Goddard, J. A. (1992). The demand for standing and seated viewing accommodation in the English Football League. Applied Economics, 2, 275–284.

    Google Scholar 

  • Forrest, D., Simmons, R., & Szymanski, S. (2004). Broadcasting, attendance and the inefficiency of cartels. Review of Industrial Organization, 24(3), 243–265.

    Article  Google Scholar 

  • Giuliani, E. (2007). The selective nature of knowledge networks in clusters: Evidence from the wine industry. Journal of Economic Geography, 7, 139–168.

    Article  Google Scholar 

  • Hall, D., Kirkpatrick, I., & Mitchell, M. (2005). Rural tourism and sustainable business. Great Britain: Cromwell Press.

    Google Scholar 

  • Hausman, J. A., & Leonard, G. K. (1997). Superstars in the National Basketball Association: Economic value and policy. Journal of Labor Economics, 14, 586–624.

    Article  Google Scholar 

  • Jennett, N. (1984). Attendance, uncertainty of outcome and policy in Scottish League Football. Scottish Journal of Political Economy, 31, 176–198.

    Article  Google Scholar 

  • Kenney, M., & Von Burg, U. (1999). Technology, entrepreneurship and path dependence: Industrial clustering in Silicon Valley and Route 128. Industrial and Corporate Change, 8, 67–103.

    Article  Google Scholar 

  • Knowles, G., Sherony, K., & Haupert, M. (1992). The demand for major league baseball: A test of the uncertainty of outcome hypothesis. The American Economist, 36(2), 72–80.

    Google Scholar 

  • McDonald, M., & Rascher, D. (2000). Does bat day make cents? The effect of promotions on the demand for Major League Baseball. Journal of Sport Management, 14, 8–27.

    Google Scholar 

  • Michael, E. J. (2003). Tourism micro-clusters. Tourism Economics, 9, 133–145.

    Article  Google Scholar 

  • Noll, R. (1974). Attendance and price setting. In R. Noll (Ed.), Government and the sports business. Washington, DC: Brookings Institute.

    Google Scholar 

  • Papke, L., & Wooldridge, J. M. (1996). Econometric methods for fractional response variables with an application to 401(K) plan participation rates. Journal of Applied Econometrics, 11(6), 619–632.

    Article  Google Scholar 

  • Paul, R. J., & Weinbach, A. P. (2007). The uncertainty of outcome and scoring effects on Nielsen ratings for Monday Night Football. Journal of Economics and Business, 59, 199–211.

    Article  Google Scholar 

  • Peel, D., & Thomas, D. (1992). The demand for football: Some evidence on outcome uncertainty. Empirical Economics, 17, 323–331.

    Article  Google Scholar 

  • Peel, D., & Thomas, D. (1996). Attendance demand: An investigation of repeat fixtures. Applied Economics Letters, 4, 567–570.

    Article  Google Scholar 

  • Pinch, S., & Henry, N. (1999). Paul Krugman’s geographical economics, industrial clustering and the British motor sport industry. Regional Studies, 33, 815–827.

    Article  Google Scholar 

  • Porter, M. E. (2000). Location, competition, and economic development: Local clusters in a global economy. Economic Development Quarterly, 14, 15–34.

    Article  Google Scholar 

  • Rascher, D. (1999). A test of the optimal production network externality in Major League Baseball. In J. Fizel, E. Gustafsen, & L. Hadley (Eds.), Baseball economics: Current research. Westport, CT: Praeger.

    Google Scholar 

  • Rascher, D. A., & Solmes, P. G. (2007). Do fans want close contests? A test of the uncertainty of outcome hypothesis in the National Basketball Association. International Journal of Sport Finance, 2, 130–141.

    Google Scholar 

  • Rosenthal, S. S., & Strange, W. C. (2003). Geography, industrial organization, and agglomeration. The Review of Economics and Statistics, 85, 377–393.

    Article  Google Scholar 

  • Rottenberg, S. (1956). The baseball players’ labor market. The Journal of Political Economy, 64, 242–258.

    Article  Google Scholar 

  • Salaga, S., & Winfree, J. A. (2015). Determinants of secondary market sales prices for National Football League personal seat licenses and season ticket rights. Journal of Sports Economics, 16(3), 227–253.

    Article  Google Scholar 

  • Tainsky, S. (2010). Television broadcast ratings for National Football League contests. Journal of Sports Economics, 11(6), 629–640.

    Article  Google Scholar 

  • Tainsky, S., & Jasielec, M. S. (2014). Television viewership of NFL out-of-market games in league markets: Traditional demand shifters and local team influence. Journal of Sport Management, 28, 94–108.

    Google Scholar 

  • Tainsky, S., & Winfree, J. A. (2010). Short-run demand and uncertainty of outcome in Major League Baseball. Review of Industrial Organization, 37(3), 197–214.

    Article  Google Scholar 

  • Tainsky, S., Xu, J., Salaga, S., & Mills, B. M. (2014). Spillover benefits to local enthusiasm: Increases in league-wide interest as a consequence of local sports team competitiveness. Journal of Economics and Business, 74, 1–10.

    Article  Google Scholar 

  • Vrooman, J. (2014). North American sports league operating rules. Retrieved February 4, 2014, from http://www.vanderbilt.edu/econ/faculty/Vrooman/league-basics-s14.pdf

  • Whitney, J. (1988). Winning games versus winning championships: The economics of fan interest and team performance. Economic Inquiry, 26, 703–724.

    Article  Google Scholar 

Download references

Acknowledgments

The authors wish to thank (without implicating) Craig Depken II and Brad Humphreys for their helpful suggestions.

Author information

Authors and Affiliations

  1. University of Illinois, 104 Huff Hall MC-584, 1206 S. Fourth St., Champaign, IL, 61821, USA

    Scott Tainsky & Jie Xu

  2. Department of Tourism, Recreation and Sport Management, University of Florida, Gainesville, FL, 32611, USA

    Brian M. Mills

  3. Division of Sport Management, Texas A&M University, College Station, TX, 77843, USA

    Steven Salaga

Authors
  1. Scott Tainsky
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jie Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Brian M. Mills
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Steven Salaga
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Scott Tainsky.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Tainsky, S., Xu, J., Mills, B.M. et al. How Success and Uncertainty Compel Interest in Related Goods: Playoff Probability and Out-of-Market Television Viewership in the National Football League. Rev Ind Organ 48, 29–43 (2016). https://doi.org/10.1007/s11151-015-9479-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11151-015-9479-7

Keywords

  • Demand
  • National Football League
  • Postseason uncertainty
  • Television
  • Media