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Choosing the most popular NFL games in a local TV market

Author

Listed:
  • Grimshaw Scott D.

    (Statistics, Brigham Young University, Provo, UT 84602, USA)

  • Burwell Scott J.

    (FOX 13 Television, Salt Lake City, UT, USA)

Abstract

This paper models the TV audience for NFL games in a market without a local team. The model is estimated using all NFL games shown in the Salt Lake City market over the last 10 years. Team popularity varies season to season, with fans preferring high-scoring close games between good teams. The primary motivation of the model was to advise the local station in week-to-week selection of high TV audience games from the slate of FOX games. In 2013 the most popular team was the San Francisco 49ers and the local station broadcast more of their games than any other team. While the predictions offer modest discrimination between popular games, the predicted error precision must be reduced to compete with local station expertise. Reviewing the prediction performance in 2013 reveals insight into strengths and weaknesses of predictive analytics in business decisions.

Suggested Citation

  • Grimshaw Scott D. & Burwell Scott J., 2014. "Choosing the most popular NFL games in a local TV market," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 10(3), pages 1-15, September.
    • Handle: RePEc:bpj:jqsprt:v:10:y:2014:i:3:p:15:n:5
    DOI: 10.1515/jqas-2014-0015
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    References listed on IDEAS

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    1. Jeffery Borland, 2003. "Demand for Sport," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 19(4), pages 478-502, Winter.
    2. Aldrich Eric M & Arcidiacono Peter S. & Vigdor Jacob L, 2005. "Do People Value Racial Diversity? Evidence from Nielsen Ratings," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 5(1), pages 1-24, February.
    3. 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.
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    Cited by:

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    2. 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.
    3. Scott D. Grimshaw & Jeffrey S. Larson, 2021. "Effect of Star Power on NBA All-Star Game TV Audience," Journal of Sports Economics, , vol. 22(2), pages 139-163, February.

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