The Super Bowl is Sunday, and for those of us who have trouble identifying the home team of each city, it can be a bit of a snooze. Well, snooze no more! The Super Bowl has, it turns out, served as a great experiment subject for researchers studying everything from economics to nutrition.
If you’re more into regression analysis than the Ravens, you’re in the right place: Here are five things that science has taught us about the Super Bowl.
1. The National Football League vastly overestimates the economic impact of hosting a Super Bowl. The sports league boasted in 1999 that Superbowl XXXIII, hosted by Miami, brought $339 million in economic benefits to the South Florida area. Economists Victor Matheson and Robert Baade decided to fact-check that claim. They created a regression model to study income attributable to all Super Bowls hosted between 1970 and 2001. Their finding: that the average Super Bowl generates $91.9 million in revenue beyond what would be projected without the large sporting event.
2. Hollywood may see a big advertising payoff. In the Journal of Advertising Research, Rama Yelkur, Chuck Tomkovick and Patty Traczyk looked at how movies fared at the box office. They found that movies that were promoted during the Super Bowl and then released between February and August had higher revenues overall, as well as during their first weekends in theaters.
It’s hard to know how much of this relationship is causal: Movies advertised at the Super Bowl may be benefiting from that ad specifically — or from a larger advertising budget overall. The researchers do attempt to control for this in some ways, by studying only large-budget films (those that spent, at minimum, $35 million). With that restriction in place, they found that Super Bowl-promoted movies earned $31 million more than those not featured.
3. The Super Bowl can be profitable to investors — no betting required. The Super Bowl Market Predictor holds that, should a team from the old National Football League win the Super Bowl, the stock market will finish the year higher than it began — and vice versa for a team from the old American Football League. In a 1990 paper, published in the Journal of Finance, Thomas Krueger and William Kennedy found that, in 91 percent of all Super Bowls played, the predictor had proved accurate.
“The mean annual index change during the years in which the NFL team won ranged from 14.4 to 22.8 percent,” they write. “If the AFL team was victorious, the average decline ranged from -7.1 to -13.1 percent.” Over time, however, the predictor has become less predictive: A 2010 study found its accuracy falling to 77 percent.
And why does it exist in the first place? Here’s Krueger and Kennedy’s take:
How can this phenomenon be explained? A proponent of the efficient market hypothesis might attribute the dominance of the SB SMP [Super Bowl Stock Market Predictor] over the 1967-1988 period to coincidence [but] the posterior possibility of the SB SMP being correct 20 out of 22 times is … 1 in 761.
Another possibility is that the phenomenon exists because a sufficient number of investors believe it exists. While the relationship between the Super Bowl outcome and subsequent stock market behavior might initially have been the result of coincidence, it subsequently may have taken on a life of its own as more investors came to act on it.
4. What about your Super (snack) Bowls? The sporting event isn’t the only thing super about this Sunday: There are also really big portion sizes! Big bowls of snacks, it turns out, will likely lead to higher calorie consumption. Cornell University’s Brian Wansink ran a study in 2005 in which he had undergraduates eat snacks under two different conditions: one where the same amount of pretzel mix was in one big bowl and another where it was served in two smaller containers. He found that the students ate 56 percent more — 142 extra calories — when there was one big bowl of snack mix.
5. Steer clear of the roads when the game ends! The New England Journal of Medicine recently found a 41 percent increase in traffic fatalities in the hours after the Super Bowl broadcast, compared with other Sunday nights. “The increase in fatalities after the telecast was evident for 21 of 27 years and amounted to about seven added deaths on the average Super Bowl Sunday as compared with the average control Sunday,” University of Toronto’s Donald Redelmeier writes.
This actually exceeds the increase in traffic fatalities that is usually seen on New Year’s Eve. One small silver lining: Redelmeier observed a small drop in traffic deaths during the actual broadcast of the game, presumably due to fewer cars on the road.