It's easy to look up Power Rankings on CBS, ESPN or NFL.com to see where your favorite team is ranked by the "experts"—and it's no surprise to most of us to see any particular team have rankings far apart from each other, especially because most sports writers don't have the ability to watch every game. Subjective rankings can be useful (and perhaps even accurate), but they always leave fans wanting more—or at the very least, shouting "bias" at the top of their lungs.
Here at the Daily Norseman, there have been a few readers who have tried their hand at creating objective power rankings based on specific sets of data that meet their criteria. It's difficult to construct "objective" power rankings, however.
What data you choose says a lot about what you think matters.
To that end, I've constructed three separate power rankings and two separate methods for organizing the data in order to accomplish different goals. In addition, I've created a strength-of-schedule adjustment based on an iterative function that not only takes a team's opponents into account, but their opponents' opponents and those opponents' opponents into account and so on.
For example, the Denver Broncos and the Kansas City Chiefs have both done very well to grab 4-0 records, but have done them against weak opponents (the Broncos have played against teams that have gone 4-12, while the Chiefs have played against teams that put up 3 wins to 13 losses), but the Broncos' opponents achieved that record against slightly tougher opponents than the Chiefs'.
The first way of organizing the data is "blind." It doesn't know if Vince Wilfork is injured or when Von Miller is coming back. It won't be able to figure out that a quarterback change and a running back trade may have saved the Browns, nor will it use injury reports to see if Percy Harvin is finally coming back. It merely uses all of the data to construct it's ranking.
The second way is not "blind" although it is "dumb" in that it doesn't take any of the above into account, but does capture trends in data by weighting the most recent games the most ("What Have You Done For Me Lately?"). Many times the trends are driven by long-term injuries or a coaching revelation (which is sustainable and predictive) or by a home stretch or a two-game injury from a major player (which is neither).
Who Would Win in a Fight?
The first set of ranks grabs data from common efficiency metrics historically designed to predict future wins. There are some serious sins in terms of gathering and weighting the data (the two biggest of which are: 1. The sample size is too small, and 2. Assuming the variable are independent when the assuredly are not) but for the most part is generally predictive in terms of figuring out who will win.
In this particular adjustment, we use 1) Net yards per attempt (passing yards minus sack yards lost divided by sacks and attempts), a strongly predictive statistic; 2) Run success rate (which looks at how often a runner is "successful"); 3) Turnover rate, 4) Touchdown rate, 5) Yards per carry.
Run success rate uses a particular definition of success that fits what Bob Carroll, Pete Palmer and John Thorn came up with in the Hidden Game of Football, a book that in some ways helped begin the advanced statistics movement in football. A run on first down that goes for 40% of the required yardage necessary to create a new set of downs (or grabs a touchdown) is successful, as is a run on second down that goes for 60% of required yardage or a run on third or fourth down that goes for 100% of required yardage.
This is different than what Football Outsiders uses, because they did actual research on the predictive power on success rate, but it is not too far off:
- In general, a play counts as a "hit" if it gains 40% of yards on first down, 60% of yards on second down, and 100% of yards on third down.
- If the team is behind by more than a touchdown in the fourth quarter, the benchmarks switch to 50%/65%/100%.
- If the team is ahead by any amount in the fourth quarter, the benchmarks switch to 30%/50%/100%.
Advanced NFL stats uses a different definition altogether, which is to use a linearized expected points model (that is, how many points can you expect from a particular down and distance at a specific position on the field) and count a run as a "success" if the running back added to the expected points total.
They come up with some different conclusions about the success rate of runners (2012 top five from FO: Willis McGahee, Knowshon Moreno, C.J. Spiller, Stevan Ridley and DeMarco Murray; 2012 top five from ANS: Mike Tolbert, Danny Woodhead, Cedric Peerman, Mike Goodson and Andre Brown—Moreno, McGahee and Spiller are just outside their top five), but both generally do a decent job of adding to team success, oddly enough.
Yards per carry is very weak in predicting wins, and it may be swallowed up entirely by run success rate (that's the issue with not having independent data), but I figured yards were yards and used a generic win correlation found on a few sites as the weight for the statistic.
A few caveats: there is good research that indicates that you can expect different degrees of variability in efficiency from an offensive and defensive perspective. That is, sometimes it is more important to look at offensive data for some statistics (say, turnover rate) and defensive data for other statistics (like run success rate). I did not do the work to weight things differently for offenses and defenses, so there is equal weight given to a defense that has a good touchdown rate as there is for an offense with a poor one.
Modifying the data so that there was an appropriate weight for its importance as well as making sure the distribution of all the data was similar (the modified data all have the same mean value and standard deviation) probably screwed everything up, but I went with it anyway. Here are the efficiency ranks, organized with no recency bias:
Click the header of a column to sort it.
| Rank | Team |
|---|---|
| 1 | Seattle |
| 2 | Carolina |
| 3 | New Orleans |
| 4 | Kansas City |
| 5 | Buffalo |
| 6 | Tennessee |
| 7 | New England |
| 8 | Denver |
| 9 | Houston |
| 10 | Detroit |
| 11 | Tampa Bay |
| 12 | Indianapolis |
| 13 | Dallas |
| 14 | Philadelphia |
| 15 | New York Jets |
| 16 | San Diego |
| 17 | Arizona |
| 18 | Atlanta |
| 19 | Cleveland |
| 20 | San Francisco |
| 21 | Chicago |
| 22 | Washington |
| 23 | Baltimore |
| 24 | New York Giants |
| 25 | Miami |
| 26 | Minnesota |
| 27 | Green Bay |
| 28 | Cincinnati |
| 29 | St. Louis |
| 30 | Oakland |
| 31 | Jacksonville |
| 32 | Pittsburgh |
The strength-of-schedule adjustments were significant, and the team most affected by it was Cincinnati, who would have been a middling team in these rankings otherwise. On the other hand, Tampa Bay had a pretty mediocre rank until the strength-of-schedule adjustment boosted them up the rankings somewhat significantly.
Here are the "What Have You Done For Me Lately" rankings:
Click the header of a column to sort it.
| Rank | Team |
|---|---|
| 1 | Seattle |
| 2 | Carolina |
| 3 | New Orleans |
| 4 | Buffalo |
| 5 | New England |
| 6 | Tennessee |
| 7 | Kansas City |
| 8 | Houston |
| 9 | Detroit |
| 10 | Denver |
| 11 | Tampa Bay |
| 12 | Indianapolis |
| 13 | New York Jets |
| 14 | San Diego |
| 15 | Arizona |
| 16 | Dallas |
| 17 | Philadelphia |
| 18 | Atlanta |
| 19 | Cleveland |
| 20 | Chicago |
| 21 | San Francisco |
| 22 | Minnesota |
| 23 | Washington |
| 24 | Baltimore |
| 25 | Green Bay |
| 26 | Cincinnati |
| 27 | New York Giants |
| 28 | Miami |
| 29 | Oakland |
| 30 | St. Louis |
| 31 | Jacksonville |
| 32 | Pittsburgh |
The biggest change is Minnesota, who moved up four rankings. A number of teams dropped three rankings (Dallas, Kansas City, Philadelphia, the New York Giants and the Miami Dolphins.
Put Them On the Board
The only rankings here are the ones that deal with the scoreboard. Points allowed vs. points scored, with no other frills (besides a points-oriented strength-of-schedule adjustment). It doesn't matter how you got your points (special teams touchdowns or eight field goals), because team quality ultimately played a part.
Generally speaking, point differential does a decent job predicting wins and is a great estimate of how well a team has done in the past. It is functionally a balance between those who care more about what football teams actually try to accomplish (winning, by putting points on the board) and those who care about metrics designed to predict performance.
Point differential ranking, adjusted for strength-of-schedule with no recency bias:
Click the header of a column to sort it.
| Rank | Team |
|---|---|
| 1 | Denver |
| 2 | Seattle |
| 3 | Carolina |
| 4 | New Orleans |
| 5 | New England |
| 6 | Indianapolis |
| 7 | Baltimore |
| 8 | Kansas |
| 9 | Buffalo |
| 10 | Tennessee |
| 11 | Miami |
| 12 | Houston |
| 13 | San Diego |
| 14 | Dallas |
| 15 | Atlanta |
| 16 | New York Jets |
| 17 | Detroit |
| 18 | Cleveland |
| 19 | Green Bay |
| 20 | Chicago |
| 21 | San Francisco |
| 22 | Tampa Bay |
| 23 | Cincinnati |
| 24 | Philadelphi |
| 25 | Oakland |
| 26 | Minnesota |
| 27 | Arizona |
| 28 | Washington |
| 29 | New York Giants |
| 30 | Pittsburgh |
| 31 | St. Louis |
| 32 | Jacksonville |
I imagine no one is surprised to see Denver take the top spot despite the strength-of-schedule and relatively weak defensive efficiency. Adjusted for recency:
Click the header of a column to sort it.
| Rank | Team |
|---|---|
| 1 | Denver |
| 2 | Seattle |
| 3 | Carolina |
| 4 | New Orleands |
| 5 | Indianapolis |
| 6 | Baltimore |
| 7 | New England |
| 8 | Tennessee |
| 9 | Buffalo |
| 10 | Kansas City |
| 11 | Houston |
| 12 | Miami |
| 13 | San Diego |
| 14 | Cleveland |
| 15 | Detroit |
| 16 | Atlanta |
| 17 | San Franscisco |
| 18 | Dallas |
| 19 | Chicago |
| 20 | New York Jets |
| 21 | Green Bay |
| 22 | Cincinnati |
| 23 | Minnesota |
| 24 | Tampa Bay |
| 25 | Oakland |
| 26 | Arizona |
| 27 | Philadelphia |
| 28 | Washington |
| 29 | Pittsburgh |
| 30 | New York Giants |
| 31 | St. Louis |
| 32 | Jacksonville |
Not too many surprises in terms of who moves around as a result of recency—it's functionally similar to what happened with the previous efficiency rankings.
It's Not Everything, It's the Only Thing
What's the stat that matters most? Winning. Football teams do not care how they win, they just want to add to their standings, hopefully to get the Super Bowl ring.
While wins are unsurprisingly a terrible predictor for future performance, efficiency doesn't get you into the playoffs: wins do.
But ranking teams by wins is no fun; we already know everyone's record. Instead, adjusting for the strength of schedule allows you to determine if a teams' wins were "quality" and if a team's losses were "bad". There is a BCS-style of logic at play: if you only have one loss on your schedule, but it's to the top-ranked team in the country, you could still be the second-best team in the country if the rest of your wins were "good".
Without a recency weight:
Click the header of a column to sort it.
| Rank | Team | Record |
|---|---|---|
| 1 | New Orleans | 1.000 |
| 2 | New England | 1.000 |
| 3 | Miami | 0.750 |
| 4 | Seattle | 1.000 |
| 5 | Denver | 1.000 |
| 6 | New York Jets | 0.500 |
| 7 | Buffalo | 0.500 |
| 8 | Kansas City | 1.000 |
| 9 | Houston | 0.500 |
| 10 | Tennessee | 0.750 |
| 11 | Indianapolis | 0.750 |
| 12 | Baltimore | 0.500 |
| 13 | Atlanta | 0.250 |
| 14 | Arizona | 0.500 |
| 15 | San Diego | 0.500 |
| 16 | Detroit | 0.750 |
| 17 | San Francisco | 0.500 |
| 18 | Cleveland | 0.500 |
| 19 | Carolina | 0.333 |
| 20 | Tampa Bay | 0.000 |
| 21 | Chicago | 0.750 |
| 22 | Dallas | 0.500 |
| 23 | St. Louis | 0.250 |
| 24 | Philadelphia | 0.250 |
| 25 | Cincinnati | 0.500 |
| 26 | Oakland | 0.250 |
| 27 | Jacksonville | 0.000 |
| 28 | New York Giants | 0.000 |
| 29 | Green Bay | 0.333 |
| 30 | Minnesota | 0.250 |
| 31 | Washington | 0.250 |
| 32 | Pittsburgh | 0.000 |
Maybe Ben Roethlisberger was right about being the worst team in the league.
But what have you done for me lately?
Click the header of a column to sort it.
| Rank | Team | Record |
|---|---|---|
| 1 | New Orleans | 1.000 |
| 2 | New England | 1.000 |
| 3 | Miami | 0.750 |
| 4 | Seattle | 1.000 |
| 5 | Buffalo | 0.500 |
| 6 | Denver | 1.000 |
| 7 | New York Jets | 0.500 |
| 8 | Tennessee | 0.750 |
| 9 | Baltimore | 0.500 |
| 10 | Indianapolis | 0.750 |
| 11 | Kansas City | 1.000 |
| 12 | Houston | 0.500 |
| 13 | Arizona | 0.500 |
| 14 | Cleveland | 0.500 |
| 15 | Detroit | 0.750 |
| 16 | Atlanta | 0.250 |
| 17 | San Diego | 0.500 |
| 18 | Carolina | 0.333 |
| 19 | San Francisco | 0.500 |
| 20 | Chicago | 0.750 |
| 21 | Tampa Bay | 0.000 |
| 22 | Dallas | 0.500 |
| 23 | Cincinnati | 0.500 |
| 24 | Philadelphia | 0.250 |
| 25 | St. Louis | 0.250 |
| 26 | Minnesota | 0.250 |
| 27 | Oakland | 0.250 |
| 28 | Green Bay | 0.333 |
| 29 | Jacksonville | 0.000 |
| 30 | Washington | 0.250 |
| 31 | New York Giants | 0.000 |
| 32 | Pittsburgh | 0.000 |
Not much else, evidently.
Let's Combine Them!
Here are the combined rankings, with the recency bias removed first:
Click the header of a column to sort it.
| Team | Efficiency | Points | Wins | Average | Ranked Average |
|---|---|---|---|---|---|
| Seattle | 1 | 2 | 4 | 2.33 | 1 |
| New Orleans | 3 | 4 | 1 | 2.66 | 2 |
| New England | 7 | 5 | 2 | 4.66 | 3 |
| Denver | 8 | 1 | 6 | 5 | 4 |
| Buffalo | 5 | 9 | 5 | 6.33 | 5 |
| Carolina | 2 | 3 | 18 | 7.66 | 6 |
| Kansas | 4 | 8 | 11 | 7.66 | 6 |
| Tennessee | 6 | 10 | 8 | 8 | 8 |
| Indianapolis | 12 | 6 | 10 | 9.33 | 9 |
| Houston | 9 | 12 | 12 | 11 | 10 |
| New York Jets | 15 | 16 | 7 | 12.66 | 11 |
| Baltimore | 23 | 7 | 9 | 13 | 12 |
| Miami | 25 | 11 | 3 | 13 | 12 |
| Detroit | 10 | 17 | 15 | 14 | 14 |
| San Diego | 16 | 13 | 17 | 15.33 | 15 |
| Dallas | 13 | 14 | 22 | 16.33 | 16 |
| Atlanta | 18 | 15 | 16 | 16.33 | 16 |
| Cleveland | 19 | 18 | 14 | 17 | 18 |
| Tampa Bay | 11 | 22 | 21 | 18 | 19 |
| Arizona | 17 | 27 | 13 | 19 | 20 |
| San Francisco | 20 | 21 | 19 | 20 | 21 |
| Chicago | 21 | 20 | 20 | 20.33 | 22 |
| Philadelphia | 14 | 24 | 24 | 20.66 | 23 |
| Green Bay | 27 | 19 | 28 | 24.66 | 24 |
| Cincinnati | 28 | 23 | 23 | 24.66 | 24 |
| Minnesota | 26 | 26 | 26 | 26 | 26 |
| Washington | 22 | 28 | 30 | 26.66 | 27 |
| Oakland | 30 | 25 | 27 | 27.33 | 28 |
| New York Giants | 24 | 29 | 31 | 28 | 29 |
| St. Louis Rams | 29 | 31 | 25 | 28.33 | 30 |
| Jacksonville | 31 | 32 | 29 | 30.66 | 31 |
| Pittsburgh | 32 | 30 | 32 | 31.33 | 32 |
And of course, with the "What Have You Done For Me Lately" adjustment:
Click the header of a column to sort it.
| Team | Efficiency | Points | Wins | Average | Ranked Average |
|---|---|---|---|---|---|
| Seattle | 1 | 2 | 4 | 2.33 | 1 |
| New Orleans | 3 | 4 | 1 | 2.67 | 2 |
| New England | 7 | 5 | 2 | 4.67 | 3 |
| Denver | 8 | 1 | 6 | 5.00 | 4 |
| Buffalo | 5 | 9 | 5 | 6.33 | 5 |
| Carolina | 2 | 3 | 18 | 7.67 | 6 |
| Kansas City | 4 | 8 | 11 | 7.67 | 6 |
| Tennessee | 6 | 10 | 8 | 8.00 | 8 |
| Indianapolis | 12 | 6 | 10 | 9.33 | 9 |
| Houston | 9 | 12 | 12 | 11.00 | 10 |
| New York Jets | 15 | 16 | 7 | 12.67 | 11 |
| Baltimore | 23 | 7 | 9 | 13.00 | 12 |
| Miami | 25 | 11 | 3 | 13.00 | 12 |
| Detroit | 10 | 17 | 15 | 14.00 | 14 |
| San Diego | 16 | 13 | 17 | 15.33 | 15 |
| Dallas | 13 | 14 | 22 | 16.33 | 16 |
| Atlanta | 18 | 15 | 16 | 16.33 | 16 |
| Cleveland | 19 | 18 | 14 | 17.00 | 18 |
| Tampa Bay | 11 | 22 | 21 | 18.00 | 19 |
| Arizona | 17 | 27 | 13 | 19.00 | 20 |
| San Francisco | 20 | 21 | 19 | 20.00 | 21 |
| Chicago | 21 | 20 | 20 | 20.33 | 22 |
| Philadelphia | 14 | 24 | 24 | 20.67 | 23 |
| Green Bay | 27 | 19 | 28 | 24.67 | 24 |
| Cincinnati | 28 | 23 | 23 | 24.67 | 24 |
| Minnesota | 26 | 26 | 26 | 26.00 | 26 |
| Washington | 22 | 28 | 30 | 26.67 | 27 |
| Oakland | 30 | 25 | 27 | 27.33 | 28 |
| New York Giants | 24 | 29 | 31 | 28.00 | 29 |
| St. Louis | 29 | 31 | 25 | 28.33 | 30 |
| Jacksonville | 31 | 32 | 29 | 30.67 | 31 |
| Pittsburgh | 32 | 30 | 32 | 31.33 | 32 |
And who has had the hardest go of it? The strength of schedule ranks:
Click the header of a column to sort it.
| Team | Efficiency SOS | Points SOS | Wins SOS | Average | Ranked SOS Average |
|---|---|---|---|---|---|
| New York Jets | 2 | 8 | 4 | 4.67 | 1 |
| Tampa Bay | 4 | 9 | 1 | 4.67 | 1 |
| New York Giants | 1 | 1 | 13 | 5.00 | 3 |
| Houston | 7 | 2 | 6 | 5.00 | 3 |
| Buffalo | 9 | 3 | 3 | 5.00 | 3 |
| Baltimore | 8 | 4 | 7 | 6.33 | 6 |
| Jacksonville | 6 | 5 | 10 | 7.00 | 7 |
| Carolina | 3 | 10 | 11 | 8.00 | 8 |
| Miami | 13 | 7 | 5 | 8.33 | 9 |
| Atlanta | 14 | 11 | 2 | 9.00 | 10 |
| Philadelphia | 10 | 6 | 15 | 10.33 | 11 |
| New England | 11 | 14 | 9 | 11.33 | 12 |
| San Diego | 5 | 12 | 18 | 11.67 | 13 |
| Arizona | 12 | 20 | 12 | 14.67 | 14 |
| New Orleans | 19 | 18 | 8 | 15.00 | 15 |
| San Francisco | 16 | 13 | 17 | 15.33 | 16 |
| Seattle | 15 | 17 | 20 | 17.33 | 17 |
| St. Louis | 17 | 22 | 16 | 18.33 | 18 |
| Oakland | 20 | 16 | 22 | 19.33 | 19 |
| Cleveland | 29 | 15 | 14 | 19.33 | 19 |
| Tennessee | 21 | 19 | 19 | 19.67 | 21 |
| Pittsburgh | 24 | 21 | 23 | 22.67 | 22 |
| Dallas | 18 | 26 | 25 | 23.00 | 23 |
| Washington | 22 | 24 | 29 | 25.00 | 24 |
| Denver | 26 | 23 | 27 | 25.33 | 25 |
| Minnesota | 27 | 25 | 24 | 25.33 | 25 |
| Indianapolis | 31 | 29 | 21 | 27.00 | 27 |
| Detroit | 25 | 31 | 26 | 27.33 | 28 |
| Green Bay | 28 | 28 | 28 | 28.00 | 29 |
| Kansas | 23 | 32 | 32 | 29.00 | 30 |
| Cincinnati | 32 | 27 | 30 | 29.67 | 31 |
| Chicago | 30 | 30 | 31 | 30.33 | 32 |
Miami's 3-1 record is even more interesting here, but Cincinnati's 2-2 record is a bit disappointing, to say the least.
There you go! The best team in the league is clearly *cough*.
We'll use this to predict games for the rest of the season and see who comes out ahead (with no home-field adjustment or reference to the Vegas spread).