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What’s the real effect of strength of schedule in the NFL?

Sometimes it’s big, but not very often.

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Our own OCC recently posted some very interesting insights on how traditional “strength of schedule” stories you’ll see this time of year are somewhat meaningless. First, most of those stories will use 2017 results to predict 2018 results. Second, and more interestingly, OCC shows us how every team drives their own strength of schedule numbers:

The Cowboys are a 9-7 team with a SOS of .500, meaning their 2017 opponents combined for a 128-128 record in 16 regular season games in 2017.

For argument’s sake, let’s assume the Cowboys had a 0-16 record last year. Everything else being equal, their opponents’ W/L record would have increased by nine wins and decrease by nine losses to 137-119 or .535, which would have given the Cowboys the second-toughest schedule in 2018.

Similarly, if the Cowboys had ended the regular season with a 16-0 record, their opponent W/L would have been 121-135, or .473, tied for the third-easiest schedule in 2018.

That is a significant swing in strength of schedule (second toughest or third easiest) based on your own winning percentage alone, which in very simple terms means that the more games you win, the softer your SOS gets.

In short, the better the team, the “easier” that team’s strength of schedule and the worse the team the “harder” that team’s strength of schedule.

That got me pondering about strength of schedule (SOS) in general. Specifically, what is the variance from the “hardest” to the “easiest” schedule? And could those variances play a significant role in a team’s final record?

Luckily for us the good folks at Pro Football Reference have a strength of schedule metric that allows us to gain some insights into those questions. If you’ve ever visited the PFR website you’ve probably seen a standings table that looked like this:

Most of these metrics will be familiar to most NFL fans:

  • Wins/losses/win percentage
  • Points for/points against/points differential

The final five columns, however, might be unfamiliar to many. But they contain some very interesting information, including the strength of schedule metric. Let’s review them:

  • MoV: margin of victory. This is simply each team’s point differential divided by number of games played or average margin of victory.

SoS: strength of schedule. PFR uses a different method of calculating SOS than most, relying upon point differentials, rather than win percentage. You can read about it here. While it seems rather complicated at first blush it’s actually pretty simple (just hard to determine because it requires many calculations).

The gist of it is the SOS number we see in the above table represents how much better (or worse) a team’s opponents were than an average team. A positive number means the team faces a harder than average schedule and a negative number means a team faced an easier than average schedule.

Thus, using the above table the Eagles faced a schedule that was, on average, 0.7 points per game easier than the league average while the Redskins faced a schedule that was 1.6 points more difficult than the league average.

  • SRS: simple rating system. This is PFR’s effort to measure the quality of every team. It’s a very simple formula:

margin of victory + strength of schedule

So every team’s rating is their average point margin, adjusted up or down depending on the strength of their opponents. Thus an average team would have a rating of zero. Suppose a team plays a schedule that is, overall, exactly average. Then the sum of the terms in parentheses would be zero and the team’s rating would be its average point margin. If a team played a tougher-than-average schedule, the sum of the terms in parentheses would be positive and so a team’s rating would be bigger than its average point margin.

The Cowboys’ average margin of victory was 1.4 points. When combined with the team’s strength of schedule of 0.2 we get the team’s SRS of 1.6. Thus, the simple rating system is simply each teams average margin of victory while taking their strength of schedule into account.

We’re only concerned with strength of schedule today. So I looked at every team’s 2017 strength of schedule as determined by PFR and these are the results:

These results are consistent with most other years. Teams rarely have a number higher than 3.0 or lower than -3.0 and usually half of all teams will fall between 1.0 and -1.0.

This chart tells us the Chicago Bears had the most difficult schedule in the NFL last season, facing teams that, on average, were 2.2 points per game better than the league average. By contrast, the Jacksonville Jaguars faced the easiest schedule, facing teams that were 2.8 points worse than league average. Dallas was right in the middle, with a 0.2 SOS.

One way to think about these numbers is in terms of point spreads. Jacksonville, for instance, was essentially getting a 2.8 point per game head start while Chicago was forced to overcome a 2.2 point deficit. Those aren’t huge numbers but they’re not insignificant either. In fact, if you combined them there was a five point difference between having the easiest schedule instead of the most difficult schedule.

These, of course, are all per game metrics. Across an entire season those five points would add up to 80 points. Changing any individual team’s final point differential by 80 points would probably change their final record by at least two games.

Of course, we’re looking at the extremes here. Nearly half the teams had an SOS of 1.0 or less, making their schedule pretty much neutral. And, as OCC so rightly illustrated, teams drive their own strength of schedule numbers to a large extent.

A driving factor in the 2.3 point gap between the Eagles and Redskins SOS numbers is the fact the Redskins had to face the Eagles twice. The Eagles’ plus 162 point differential had a huge impact on the Redskins’ 1.6 SOS number.

So, to get back to our original questions....can strength of schedule impact a team’s overall record? Sure. If we look at a few teams we can see instances where it likely played a role:

  • The Tennessee Titans finished 9-7, claiming the final wild card spot in the AFC. This despite a -22 point differential and a SOS of -2.1. This gave them a -3.5 SRS. Had the Titans faced a league average schedule or a difficult schedule it’s not hard to envision them losing one more game and not making the playoffs.
  • The Atlanta Falcons claimed the sixth seed in the NFC playoffs with a 10-6 record. They had the league’s fourth most difficult schedule (1.9 SOS). Had they been in an easier division (three NFC South team made the playoffs with 10+ wins) it’s not unreasonable to think they might have won the division, had a higher playoff seed and fared better than they did. This is supported by the fact they handily beat the 11-5 Rams on the road then traveled to Philadelphia and came within a Julio Jones missed catch of defeating the eventual Super Bowl champions.

It seems reasonable to say that strength of schedule is probably given too much weight by many preseason stories you’ll come across but it’s also not meaningless. We’ll finish with a few random observations from the SOS numbers:

  • They are largely division-driven. All four of the AFC South teams had negative SOS numbers (-6.4 overall) because it was a weak division with poor overall point differentials. By contrast, the NFC South teams all had positive SOS numbers (7.2 overall).
  • They are also conference driven. The NFC was significantly better than the AFC in 2017. The nine teams facing the most difficult schedules all came from the NFC while the ten teams facing the easiest schedules all came from the AFC.
  • Finally, we find support for one of OCC’s findings from his original post:

Let me get this out of the way at the beginning: Strength of Schedule doesn’t mean Jack. There is no correlation whatsoever between a team’s strength of schedule going into the season and the number of wins that team has at the end of the season.

Now, OCC is talking specifically about using prior year SOS numbers (based upon winning percentage) to predict results for the current year. But his theory holds true even for using SOS numbers from the prior year to look at results from the prior year.

The following plots each team’s point differential on the horizontal axis their SOS on the vertical axis:

Just as OCC theorized, there is absolutely no correlation between strength of schedule and overall results.

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