How Mad is Too Mad?: Cinderellas, Blue Bloods and TV Ratings

Each Spring I teach a course on sports marketing analytics.  As part of this course I ask student to develop a research project focused on either a marketing or player analytics topic.  What follows is a project that looks at the relationship between upsets and TV ratings in the NCAA tournament.  This project is interesting in several respects.  It has an interesting foundation in consumer behavior theory as it is motivated by an open question of whether fans prefer a tournament dominated by Cinderellas (upsets) or Blue Bloods (high brand equity teams).  This underlying theory then drives the data collection and modeling efforts.  Finally, the results speak to what fans actually prefer.

I think this project was interesting as it could be the starting point for deeper analyses.  Additional data could be collected and we could develop different models.  This is a great lesson because this is the case with almost all analytics projects.  We also did a podcast episode where we talked through the analysis and possible extensions.

LINK: https://soundcloud.com/fanalytics/march-madness-cinderella-stories-blue-bloods-and-tv-ratings

How Mad is too Mad?

by Katie Hoppenjans

“March Madness” is a fitting nickname for the NCAA Division I Men’s Basketball Tournament. Since its inception in 1939, the tournament has been characterized by Cinderella stories; in years that are particularly “mad” with upsets, the underdog winners seem to be on everyone’s mind. In a year of historic upsets like this one, however, I have to wonder whether the level of excitement in a tournament really has any impact on fans’ engagement. Do people really love an underdog, or would they prefer to watch the same old powerhouses? Is “madness” really what viewers want?

To examine the value of an “exciting” March Madness, I built a model examining the relationship between the number of upsets in a tournament and the number of viewers who watch the championship game. The model includes data from 2005 to 2017, and upsets are defined as games won by teams seeded 11 or lower. Since no team seeded 11 or lower has ever made it farther than the Final Four, only the first four rounds of competition were counted. Finally, since significant upsets in later rounds are arguably more unexpected than those in early rounds, I assigned more points to the later rounds in my analysis; 1 point was given for each upset in the Round of 64, 6 were given for the Round of 32, 12 were given for the Sweet Sixteen, and 24 were given for the Elite Eight.

Using this model, I found that there is actually a significant negative correlation between the number of upsets in the early rounds of a tournament and the number of viewers who watch the championship game. In other words, the more “exciting” the tournament, the fewer the viewers who stick around until the end. One possible explanation for this may be that many people only watch March Madness because they have filled out a bracket; if their bracket is “busted” by early upsets, they might tune out of the tournament entirely. It may also be true that historically strong teams (like Kentucky, Indiana, Kansas, etc.) have more fans than small, Cinderella-story schools. Since powerhouse teams win more often, their fans are also more likely to be engaged and loyal viewers than smaller teams’ fans. As a result, when a major team is taken out of the tournament by a smaller school, viewership may drop off as the larger school’s fans lose interest. This is only conjecture, and further analysis would be needed to determine the cause of the relationship between viewers and upsets. However, as demonstrated by the graph below, upsets certainly seem to have an impact on how many people watch the championship game.

As advertising spend for the March Madness championship game continues to climb (per the graph below), the continued volatility in viewership must be troubling to sponsors. Particularly in a year like this one, in which a 1-seed lost in the Round of 64 for the first time in history, things are not looking good for the championship game ratings; with a tournament this unpredictable, it may be more important than ever for advertisers to find reliable ways of predicting the impact of their championship game sponsorship. Early-round upsets may be one factor in determining viewership, but there are many more questions that need to be answered before championship game ratings can be accurately estimated. “Madness” in the NCAA tournament may sound exciting, but if its negative correlation with viewership is to be believed, it’s actually bad news for fans and sponsors alike.

Sources

“NCAA Men’s Final Four Ratings Hub.” Sports Media Watch, www.sportsmediawatch.com/ncaa-final-four-ratings-history-most-watched-games-cbs-tbs-nbc/.

“NCAA Records Books.” NCAA.org – The Official Site of the NCAA, 17 Jan. 2018, www.ncaa.org/championships/statistics/ncaa-records-books.

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