Here is a recap of the 2012 Chicago Bears season.  Notice anything strange? Trick question!

The 2012 Bears played two terrible teams, the Titans and the Jaguars. Those were the two biggest blowouts of the season for Chicago. The Bears had five games against really good teams (Seattle, San Francisco, Houston, and the Packers twice): those were the five biggest losses of the season. Chicago had one other loss, which came on the road against the next best team the Bears played, Minnesota.

All of that might sound …. unsurprising to you. And that’s the point. Six years ago, Doug wrote a post titled strange seasons, after he noticed an odd quirk about the 2006 Jaguars. That year — and without adjusting for strength of schedule — Jacksonville played much better against good teams than it did against bad teams.

To measure how “strange” a season was, Doug measured the correlation coefficient between (a) the SRS rating of a team’s opponent in each game, and (b) the margin of victory in that game. You would expect a negative correlation generally: that is, as the rating of the opponent increases, the margin of victory over them should decrease. The 2007 Jaguars had a positive correlation, which is strange, which was the origin of Doug’s post.

I decided to run “strangeness” correlation coefficients for each team in each 16-game season in NFL history, using SRS rating and location-adjusted margin of victory (i.e., awarding three points to the home team) as my two variables. As it turns out, all 32 teams in 2012 had negative correlation coefficients for those two variables (which is what you would expect). The table below lists (for reference purposes) each team’s average MOV, average SOS, and SRS rating in 2012, and the final column shows the CC between each team’s average opponent rating and average margin of victory (after adjusting for location). As you can see, the Bears had the “least strange season” while the Steelers had the “strangest season.”

But the Bears didn’t just have a predictable season. That -0.89 correlation coefficient is the lowest for any 16-game season in NFL history. In other words, Chicago just had the least strange season of the modern era. Here’s a game-by-game breakdown, like at the top of this post, but this time, I’ve sorted the schedule from toughest to easiest opponent. As you can see (and what the -0.89 means), there is almost a perfect negative correlation between the quality of the opponent and the (location-adjusted) final margin:

On some level, this isn’t that interesting. After all, it’s not a story when a team does poorly against great teams, pretty well against mediocre teams, and great against bad teams. But the fact that Chicago was so consistent in its performance is pretty interesting, and by ranking as the least strange season in over 30 years is very interesting. At least to me.

At the end of his post, Doug noted that there may be some predictive utility in this. I decided to run similar tests to see if it means anything to have a predictable or strange season. One could argue that the Steelers — who have shown an ability to play well against better teams, even if they slip up against lousy teams — are more likely to become a great team in 2013 than the Bears, because beating good teams shows a higher ceiling. That’s just a theory, though.

I ran a regression using Year N Wins and Year N Strangeness Coefficient as my inputs; the best fit formula was:

Year N+1 Wins = 5.45 + 0.360 * Year N Wins + 0.74 * Year N SC

The R^2 was 0.36 and the p-value on the Strangeness Coefficient was 0.107, on the border of being statistically significant. This formula would project the 10-6 Bears to win 8.4 games in 2013, while the 8-8 Steelers are projected to win 8.3 games. That’s pretty interesting and would support the “high ceiling” theory. But it’s far from obvious whether the strangeness coefficient has any predictive power. One reason is that the p-value is not very convincing. But here’s another. I re-ran the regression using Year N SRS Rating instead of Year N wins.

Year N+1 Wins = 8.33 + 0.20 * Year N SRS + 0.50 * Year N SC

The R^2 was 0.39 (this makes sense, since SRS is a better predictor than wins), but the p-value on the SC was just 0.27. I suppose the evidence indicates that, all else being equal, it’s better for an 8-8 team to have a really low or even positive Strangeness Coefficient than a really high one like the Bears. But I’m not sure if I’d say it’s anything more than a tiebreaker.

Putting aside all the talk of strangeness and regression and correlations, I think one conclusion is pretty obvious. Bears management saw how that Chicago was very predictable against the league’s best teams. Despite a 10-6 record, Chicago’s struggles against the upper crust of the NFC ultimately cost Lovie Smith his job. And that’s not very strange, either.

Previous “Random Perspective On” Articles:
AFC East: Buffalo Bills, Miami Dolphins, New England Patriots, New York Jets
AFC North: Baltimore Ravens, Cincinnati Bengals, Cleveland Browns, Pittsburgh Steelers
AFC South: Houston Texans, Indianapolis Colts, Jacksonville Jaguars, Tennessee Titans
AFC West: Denver Broncos, Kansas City Chiefs, Oakland Raiders, San Diego Chargers
NFC East: Dallas Cowboys, New York Giants, Philadelphia Eagles, Washington Redskins
NFC North: Chicago Bears, Detroit Lions, Green Bay Packers, Minnesota Vikings
NFC South: Atlanta Falcons, Carolina Panthers, New Orleans Saints, Tampa Bay Buccaneers
NFC West: Arizona Cardinals, San Francisco 49ers, Seattle Seahawks, St. Louis Rams