NFL Preseason Rankings 2016: NFC West Primed For Dominance?
September 5, 2016 - by David Hess
Here are the official TeamRankings 2016 NFL preseason rankings and ratings. Further explanation of our preseason ratings methodology and tips for interpreting the data follow below the table.
2016 NFL Preseason Rankings Highlights
- Top Trio. While Seattle claims the top spot in our 2016 NFL preseason rankings, two teams are close behind, within a half a point of the Seahawks: Arizona and New England. Following that top 3, there’s a 1.1-point gap before the next highest rated team.
- Super Bowl Hangovers. Denver and Carolina met in the Super Bowl, so you would think their game to kick off the 2016 regular season would be a battle of two heavyweights. But our preseason ratings only have them as the #8 (Carolina) and #9 (Denver) teams. Why so low? Denver’s got a gaping hole at quarterback, while Carolina benefitted from by far the best turnover luck in the league last season, which is not expected to continue this year.
- Sam Bradford Trade. When Teddy Bridgewater went down with a knee injury, Vikings fans despaired. When Minnesota traded for Sam Bradford, they rejoiced. But both the injury and the trade impacted our preseason ratings less than you might expect. Both Bridgewater and Bradford are a bit overrated by the general public, and Shaun Hill has performed adequately when he’s been pressed into duty over the course of his career. As a result, the Vikings only moved up from 11th to 10th in our preseason ratings upon news of the Bradford trade. The trade had a bigger impact on the Eagles, who dropped from 26th to 28th. That’s because Carson Wentz, while oozing potential, is projected to struggle a bit as nearly all rookies do.
Official 2016 NFL Preseason Rankings
- NOTE: Team ratings are expressed as points better (positive rating) or worse (negative rating) than the average NFL team, when playing on a neutral field
A Quick Primer On Our NFL Preseason Rankings
Our 2016 NFL preseason rankings are almost entirely data-driven. We’ve used team data from past seasons to find which descriptive statistics have correlated strongly with high end-of-season power ratings. We then used those stats to create a model that predicts a team’s power rating.
Some examples of data points used in the model include:
- A “draft score” for each of the past several years
- Prior season fumble and interception data
- Quarterback stats for teams with a different QB than last year
- End of season team power rating from the last few years
We assign each input factor a weight based on its demonstrated level of predictive power.
The output is a power rating that represents how many points above or below average we think a team is, with 0.0 representing a “perfectly average” team.
Gut-Checking The Initial Preseason Ratings
Once we generate initial 2016 NFL preseason rankings & ratings, we then check them against the betting markets and other preseason ratings.
If our ranking for a team seems severely out of whack with those other sources, we’ll investigate. We check to see if there’s some factor that’s not taken into account by our model, that the betting market is picking up on. In some cases, we’ll manually adjust our rating to be a bit closer to the consensus. Though only rarely will we adjust it all the way to match the consensus.
It’s worth noting that these preseason ratings also drive our NFL season projections — at least before the season begins. As the 2016 season progresses, the impact of these preseason ratings will gradually fade, and actual game results will play a larger role in determining our team power ratings (which continue to drive the season projections).
An Open Letter To Crazy Hardcore Fan Of Team X
Dear Hardcore Fan Of Team X, before you get angry that our models are obviously biased against your favorite team, please keep two things in mind:
- We use a systematic approach to rank all 32 teams. Our approach has done very well over the years when measured by the most important yardstick: the overall accuracy of projecting team performance levels in the upcoming season across the entire system of 32 teams. Being entirely data-driven, our model doesn’t pay attention to some things that mainstream media analysts are convinced is important. It’s also going to get a few individual teams slightly wrong, and some very wrong, for all sorts of reasons.
- Look at ratings, not just rankings. For example, 2.0 points separates #9 Denver from #10 Minnesota, but only 1.7 points separates #9 Denver from #4 Green Bay. In other words, Denver is closer to being #4 than #10, so don’t get overreact to that #9 ranking — look at the rating as well.