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Rodney J. Paul, Andrew P. Weinbach

The Uncertainty of Outcome and Scoring Effects on Nielsen Ratings for Monday Night Football. Rodney J. Paul, Andrew P. Weinbach Received 8 April 2005; received in revised form 30 November 2005; accepted 24 May 2006. Existing Data. Economic studies of competitive balance

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Rodney J. Paul, Andrew P. Weinbach

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  1. The Uncertainty of Outcome and Scoring Effects on Nielsen Ratings for Monday Night Football Rodney J. Paul, Andrew P. Weinbach Received 8 April 2005; received in revised form 30 November 2005; accepted 24 May 2006

  2. Existing Data • Economic studies of competitive balance • College Football (Eckard, 1998) • Professional Football (Grier & Tollison, 1984) • Nature of competitive balance • Sanderson & Siegfried (2003), Fort (2003) • Empirical studies • Schmidt & Berri (2001), Humphreys (2003), Utt & Fort (2002) • Sports betting markets • Paul & Weinbech(2002) - NFL • Paul, Weinbech & Wilson (2004) - NBA

  3. Paul & Weinbach • Use regression models to analyze Nielsen Ratings for Monday Night Football (MNF) • Uncertainty of outcome hypothesis and scoring effects • What factors attract and keep viewers? • Start-of-Game  Uncertainty of outcome, quality of teams and expected scoring • Within-Game Changes  Halftime score differential, halftime total points scored and quality of teams playing • Fans prefer games with a quality match-up between winning teams, a high level of uncertainty of outcome and high-scoring

  4. Start-of-Game & Change in Intra-Game • Demand for watching MNF

  5. #1: Start-of-Game • Nielsen Ratings at the start of the game (9pm EST) • Measures of expectations from data about teams in contest • What attracts viewers to a prime time football game?

  6. #1: Regression Results • World Series • Negative & significant • Sep. & Nov. dummies • Significant • Annual dummies (1997-2002) • Negative & significant at 1% • Difference in win percentages • Negative & significant at 1% • Sum of win percentages • Positive & significant at 1% • Expected scoring (Las Vegas total) • Positive & significant at 5%

  7. #2: Change in Within-Game • Change in ratings at halftime (10:30pm EST) • Score differential and total points scored • When will viewers turn off the game? • What might attract viewers of other programs to tune in?

  8. #2: Regression Results • World Series • Positive & significant • Monthly dummies • Not individually significant • Annual dummies • Some significant differences (1993, 1997 and 1998) • Sum of win percentages of teams • Positive & significant at 5% • Halftime score differential • Negative & significant at 1% • Halftime total points scored • Positive & significant at 5%

  9. Conclusions • Fans prefer close games between quality teams • Prefer high-scoring games to low-scoring games • Quality games featuring high-scoring teams: • Attract viewers initially to the game • Retain viewers during the game • Attract new viewers as the game progresses • Thoughts on the paper…

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