Facebook Twitter
ProFootballLogic
ARTICLES TEAMS STATS RATINGS STANDINGS GAMES SCHEDULE PLAYERS METHOD SPORTS

Preliminary 2013 Ratings

Once the season begins, our 2013 team ratings will be based solely on games from the 2013 season. Rather than treating all teams equal prior to then, for the 2013 season we have devised a system of preliminary ratings based on our 2012 ratings. The system analyzes how team ratings change on average from one season to the next, and then applies these expected changes to the 2012 ratings.

Overall team ratings typically regress to the mean from one season to the next by about half, whether positive or negative. For instance, a team rated 4.0 can expect to be rated 2.0 on average the following year, while a team rated -3.6 can expect a -1.8 rating. However, further information can be gained by looking as well at individual play types. Just as our mid-season ratings factor in how likely different types of success or failure are to continue, certain play types are more likely to continue at a similar level of success rather than regress to the mean in the next season. Below are the correlation coefficients for different play types between 2 consecutive seasons of ratings. Preliminary 2013 ratings are formed by taking league average values plus the product of the coefficient and the distance from average that a team was in 2012 for each play type.

Correlation Coefficient of Consecutive Season Ratings
Int Sack Pass Run KO Abo FG Punt Pen
Offense0.150.200.550.160.350.000.030.280.34
Defense0.110.200.280.250.180.000.250.140.00

The predictiveness of different play types is relatively similar to their in-season impacts on our ratings, but some categories like kickoffs are relatively reliable indicators for the next season despite not having a big effect on overall mid-season ratings. And because all categories are not equally predictive for the following season, we can distinguish differences in 2013 expectations even from 2 teams with equal 2012 ratings. Below we compare 2012 ratings to our new preliminary 2013 ratings.

Comparing 2012 and Preliminary 2013 Ratings
Rank Team 2012 2013
1DEN6.63.1
2NE6.92.9
3ATL4.22.6
4NO3.52.5
5GB4.42.3
6SEA5.51.8
7DAL2.11.7
8SF5.01.6
9BAL3.11.1
10DET0.00.8
11NYG2.70.8
12PIT0.70.8
13HOU2.40.7
14IND-0.30.6
15WAS2.40.6
16CAR1.20.5
17CHI0.9-0.1
18PHI-1.8-0.1
19CIN0.7-0.1
20SD-1.1-0.3
21OAK-2.9-0.3
22TB-0.1-0.4
23STL-0.8-0.5
24BUF-1.8-0.7
25MIN-0.2-0.8
26MIA-1.4-0.8
27TEN-3.2-1.3
28CLE-3.6-1.7
29NYJ-4.2-1.9
30JAC-5.6-2.1
31KC-5.9-2.5
32ARI-5.9-2.7

The new ratings don't provide many huge surprises, but do produce some interesting quirks. Teams with a strong offensive passing game, the most predictive play type, generally climb up the ratings compared to 2012. Teams that happened to string together strong 2012 performances in several less predictive play types appear more likely to regress.

Keep in mind that these preliminary ratings are based solely on efficiency stats, and do not account for offseason roster changes. We will examine the impacts of individual players such as new starting quarterbacks and how to make rough adjustments that deviate a bit from the above baseline figures in our upcoming division and league preview articles.

Recent Articles
Wk 17 Playoff Scenarios 2017   -   12/31/17
Grading NFL Franchises   -   9/28/17
Tom Brady Is Not The G.O.A.T.   -   8/3/17
NFL Census 2016   -   4/19/17
Do NCAA Basketball Teams Get Hot?   -   3/15/17
How Good Are Pro Bowl Teams?   -   1/28/17
Wk 17 Playoff Scenarios 2016   -   1/1/17
Rating Field Goal Kickers   -   8/28/16
Rating NFL Quarterbacks   -   6/20/16
2016 NCAA Basketball Model   -   3/16/16
Fundamental Articles
Site Summary and Features   -   7/5/12
The ProFootballLogic Method   -   7/5/12
Stats Explained   -   7/5/12
How Variation Affects Outcomes   -   7/5/12
Ratings Explained   -   7/5/12
General Play Type Analysis   -   7/5/12
London and Home Field Disadvantage   -   8/21/12
Ranking College Conferences   -   1/11/13
Draft Position and Player Quality   -   4/25/13
The Changing Landscape of the NFL   -   5/21/13
College Yearly Rating Regression   -   8/28/13
How College Basketball Rankings Fail   -   2/28/14
Franchise Tag Position Problems   -   3/7/14
Developing a World Cup Model   -   6/9/14
Optimizing College Playoff Selection   -   11/26/14
The Science of Football Deflation   -   1/27/15
2015 College Football Model   -   9/3/15
2015 NFL Team Ratings Model   -   10/20/15
NFL Injury Rate Analysis   -   2/22/16
2016 NCAA Basketball Model   -   3/16/16
How Good Are Pro Bowl Teams?   -   1/28/17
Do NCAA Basketball Teams Get Hot?   -   3/15/17
NFL Census 2016   -   4/19/17
Tom Brady Is Not The G.O.A.T.   -   8/3/17
Grading NFL Franchises   -   9/28/17