Super Bowl Loser’s Curse: Is the Hangover Real?

We analyzed over 20 years of data to see if Super Bowl Losers really underperform the next season. Here's what the numbers say.

June 3, 2025 - by Jason Lisk

There’s a long-standing theory in NFL circles: the team that loses the Super Bowl tends to stumble the following season. This is often known as the “Super Bowl Loser’s Curse”, but is there any truth to it?

We put that idea to the test. Using data from 2004 to 2023, we analyzed how Super Bowl runners-up performed the following year. We compared them to Super Bowl winners and other playoff teams and even built a control group of statistically similar squads to see if the drop-off is real.

Here’s what we found.

Super Bowl Losers: Falling Short of Expectations

Let’s start with performance. The 20 Super Bowl Losers from 2004 to 2023 averaged -1.09 wins vs. their preseason win total line the next year. In plain terms, the market expected them to be elite again, and they weren’t. While 13 of these 20 teams returned to the playoffs (65%), that came with significant underperformance.

For context, here’s how the teams that reached other NFL playoff milestones performed the next year, over the same time span.

Playoff Round	Team Count	% Over	% Under	% Push	Avg Win Diff	% Returned to Playoffs
Wildcard Loss	88	56.8%	42.0%	1.1%	0.2	45.5%
Divisional Loss	80	40.0%	53.8%	6.3%	-0.6	51.3%
Conf Champ Loss	40	50.0%	45.0%	5.0%	0.0	57.5%
SB Loss	20	30.0%	50.0%	20.0%	-1.1	65.0%
SB Win	20	55.0%	40.0%	5.0%	0.4	70.0%

Super Bowl winners averaged +0.4 wins more than their preseason win total the next year (best of all playoff categories) and returned to the playoffs 70% of the time. Meanwhile, the Super Bowl Losers had the worst performance relative to expectations of any of the previous year’s playoff participants on average. Teams that lost in the Divisional Round were the only other category that averaged fewer wins than their expected win totals, and went over the win total the next year less than half the time.

How Statistically Similar Teams Fared

To really test the pattern, we explored whether something about the statistical profile or characteristics of the Super Bowl-losing team led to underperformance. We created a comparison group for each Super Bowl Loser by identifying the five most statistically similar teams from the 2004-2023 window (excluding other “Super Bowl Losers” so they were not double-counted). These similar teams were matched across 10 performance metrics using z-score proximity.

Here’s what those similar teams did:

• Had +0.35 actual wins the next year vs. win total line
• Went over their win total the next year 52% of the time
• 62% playoff return rate

These teams looked the same statistically as our Super Bowl Losers, except they didn’t lose the Super Bowl the previous year.

The 1994-2003 Decade: A Harsher Hangover

While we did our deep dive into the most recent 20-year period, where we have detailed preseason win total information and team stats, those results are not simply the result of choosing a favorable cutoff to advance a Super Bowl Loser narrative.

Going back a decade, we also quickly examined Super Bowl Losers from 1994 to 2003:

• Average wins the next year: 8.3
• Playoff return rate: 40%

It was even worse then, suggesting the modern era may have softened the fall but hasn’t eliminated it.

The QB Factor: Injuries a Leading “Curse” Factor

The simplest explanation is often the most effective: maybe these teams underperform because their quarterbacks fall off. But here’s where it gets interesting.

Every Super Bowl Loser from 2004-2023 returned their starting QB the next season. But those QBs averaged just 13.7 games played. Compare that to Super Bowl winners, whose returning starters (excluding Peyton Manning, who retired, and Nick Foles, who was a backup) averaged 15.4 games played.

Only one SB-winning QB in that span (Matthew Stafford, 2022) played fewer than 15 games the next year. On the losing side, five starters missed at least four games, including Tom Brady (1 game played in 2008), Jimmy Garoppolo (6 in 2020), and Donovan McNabb (9 in 2005).

Is the Super Bowl Hangover Really About QB Health?

When we look at the four Super Bowl Losers who had their starting QB play in fewer than 10 games, those teams underperformed the expected win total by an average of -3.7 wins. The other 16 Super Bowl Losers in the data set still underperformed by -0.4 wins on average, a number that puts them closer to, but still below, similar playoff categories like Super Bowl winners and Conference Championship Game losers from the previous year.

We will caution, though, that those teams that lost their QBs were in many cases already struggling the following season. Tom Brady’s injury came right away in the 2008 season. However, the 2020 San Francisco 49ers were already underperforming and were at 4-4 when Garoppolo was shut down for the year. The 2004 Philadelphia Eagles had dropped to 4-5 and lost three straight when Donovan McNabb played his final game. The 2007 Chicago Bears started 1-2 and were blown out by 24 points in the final game before Rex Grossman was first injured.

So, the injuries were both a cause and a potential effect of a team that played worse the following year if the protection and game situations were worse for the quarterback.

Statistical Suspects: What Predicts the Fall?

We ran correlations between Year X stats and Year X+1 underperformance (vs. win total and playoff misses). The most telling were:

• Wins and Point Differential from the Super Bowl year had the strongest negative correlation with next-season win difference relative to expectation. In other words, the better the season, the potentially harder the fall.
• Points Against had a moderate positive correlation to performance against expectation the next year. That means that the relatively worse defenses among the Super Bowl Losers did relatively better compared to how they were expected to perform the next year. This is consistent with other research that offense is more stable than defense, and perhaps the subset of defensive-dominated teams experienced more regression.

Sample size limits prevent any definitive conclusions, but these hints support the idea that dominant teams often regress simply because they’ve set an unsustainable bar.

Final Word: Context Matters

Let’s be clear: 20 teams are not a large enough sample to claim a law of nature. We’re not saying losing the Super Bowl dooms a team. But the pattern is strong enough, and the contrast with similarly strong teams is sharp enough, that it raises real questions.

There are likely a mix of reasons: expectations, physical and emotional toll, regression to the mean, and, yes, quarterback injuries that have played a big role in a subset of the underperformers. But when strong, statistically similar teams consistently do better than the ones who lose the Super Bowl, we can’t ignore the possibility that something about losing that game has carried enough of a cost for teams over the last 20 to 30 years.