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Factors Influencing Nielsen Ratings in Monday Night Football: An Analysis

This study explores how the uncertainty of outcome and scoring effects impact Nielsen Ratings for Monday Night Football, using regression models and empirical data. Factors such as team quality, scoring levels, and viewer preferences are analyzed to understand viewer behavior during games.

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Factors Influencing Nielsen Ratings in Monday Night Football: An Analysis

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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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