For teams with a lot of roster turnover, it can be tempting to take too much out of their Week 1 performance: a dominant win can be a sign that a team is headed for the Superbowl, a demoralizing loss could contribute to a “Fail for Cardale” movement.
In particular, big wins when you’re expected to lose can be very promising. All the doubt your team faced coming into the season, which contributed to making them underdogs in Week 1, has disappeared. At least until next Sunday. It can be tempting to think that that big Week 1 win is a sign that all the haters are wrong, and those teams will outperform all expectations for the season. And betting with that mentality can be expensive.
Looking at the same dataset we used for the last feature, we can see that since 1985 there have been 51 teams that have won in Week 1 by more than 10 points when they were expected to lose. The following week, Week 2, only 20 of those 51 teams won their second game. But, even more strikingly, only 17 of those 51 teams covered the spread (two pushed). That means of the teams that didn’t push, just under 35 percent of them covered the spread in their Week 2 contests. That percentage, even with just 49 observations, has a p-value that is significant at the 0.05 level (0.0443).
We can see that when underdogs win their season opener, the larger their victory the less likely it is that they will cover the spread the following week. Below is a graph of how underdog stunners fare ATS in Week 2 based on their margin of victory.
The correct way to read this graph is for any margin of victory on the x-axis, the data point corresponding to it looks at teams who won by more than that many points, and more specifically looks at how many of those teams covered the spread (that didn’t push) in Week 2. As evidenced, as you restrict your interest to underdogs that win by larger amounts in Week 1, the odds that they will cover the spread the next week decrease.
When the underdog wins by only a few points, the lines are pretty accurate the next week. But when the underdog wins by around eight or more points, the lines start to be a little off.
Intuitively, we would expect to see the opposite happen for favorites who lose big in Week 1, believing they would perform better against the spread in Week 2. And while this is true, it is not nearly as extreme as what we witness with big underdog winners.
A second chart is below, showing favorites and their margin of loss on the x-axis. Once again, for each margin of loss the corresponding data point represents all favorites who lost by more than that amount.
As margin of loss increases, so does the chance of covering the spread. But at a margin of loss of 10, teams only cover the spread 57 percent of the time, about half as extreme as the 35 percent we see from underdogs that win by 10 points in Week 1.
Another difference is that while underdogs who barely won in Week 1 have essentially at 50/50 chance of covering the spread the next week, favorites who barely lost have nearly a 55 percent shot of covering. While not significantly different, due to a relatively small sample size, it is more extreme than underdogs.
What is the cause of these discrepancies? It could very well just be random noise, but by nature humans are optimistic beings and it’s possible they read more into good news (their team winning big as an underdog) than into bad news (their team losing big as a favorite).
Going into Week 2, there are five teams that won as underdogs in Week 1, three of which won by large enough margins that the Week 2 lines may be skewed in their favor.
Finally, lets check up on our advice that we gave last week. As we continuously give tips throughout the year, it is helpful to check how we are doing. We don’t expect to be perfect, but ideally our bets will do a little better than average. And if not, we can try to learn where we are going wrong and remember that for next year.
If you bet against teams (i.e. on their opponents) that finished last year undefeated against the spread here’s how you would have done:
New England @ Pittsburgh: NE Line -7.5 (LOSS)
St. Louis vs Seattle: STL Line +3.5 (WIN)
N.Y. Giants @ Dallas: NYG Line +7 (WIN)
If you bet on teams that finished last year without a win against the spread here’s how you would have done:
Miami @ Washington: MIA Line -4 (WIN)
Tennessee @ Tampa Bay: TEN Line +3 (WIN)
San Francisco vs Minnesota: SF Line +2.5 (WIN)
Last Week: 5-1
Harrison Chase is the Co-President of the Harvard Sports Analysis
Collective, a student-run organization at Harvard College dedicated to
the quantitative analysis of sports strategy and management.