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The 2014 NFL Draft is 78 days away, and the NFL “New Year” begins March 11th, at which point salary cap implications for teams’ current players will kick in for the coming season.

Last season, the Oakland Raiders had $56-plus million dollars worth of dead money. That is, more than $56,000,000 of their funds last season were tied up in players who were not even members of the Raiders. It was an impressive figure, more than one-third of their $123 million salary cap. Their incoming general manager, Reggie McKenzie, made a courageous decision to dump at once all of the terrible contracts he inherited, guaranteeing a tough season for Raiders fans. (In fact, going 4-12 was something of a pleasant surprise.)

But now McKenzie can reap the rewards, earn the salt, bring home the bacon, have his cake and eat it too1, all those good things. The Raiders have over $60 million in cap space heading into next season. With 2013 behind them, McKenzie and the Raiders can spend nearly half of the yet-to-be-finalized 2014 NFL salary cap (likely $123-126 million or so) however they like. And their terrible season last year has armed them with the fifth, fourth, and third picks of the first three rounds of the draft, respectively. Shake it out, Raiders fans! Remember, it’s always darkest before the dawn.

McKenzie’s management has moved the Raiders to the tenth-best standing in the NFL Dead Zone, brought to you by Richard Seymour. What is the NFL Dead Zone? The NFL Dead Zone is a psychic realm of Roger Goodell’s mind where upon shaking players’ hands he sees visions of their future on-field concussions and disillusioned, depressed lives after retirement, and through the Dead Zone’s apparitions Goodell can actually change the future!

Wait, that isn’t it. The NFL Dead Zone is the long-awaited series finale/made-for-TV movie, ditched by UPN, then USA, and coming to NFL Network this fall as part of the new NFL-CBS deal for Thursday Night Football!

Wait, that isn’t it either.

The NFL Dead Zone is a statistic relating a team’s dead money and salary cap space. Definitively, it is a team’s dead money divided by the sum of their dead money and their salary cap space. That is:

(Dead $$$) / (Dead $$$ + Salary Cap Space) = Dead Zone Rating

The NFL Dead Zone is a hybrid of those two related, interesting-but-not-absolute team management metrics. Neither having some dead money nor having little cap space is insurmountable. But when dead money–accounted to players no longer on a team’s roster–is the primary cause of a team’s tight cap situation (as opposed to, say, signing Peyton Manning), then…

Christopher Walken, is it really you? ARE YOU IN THERE SOMEWHERE?

Christopher Walken, is it really you? ARE YOU IN THERE SOMEWHERE?

…well, it gets ugly.

The NFL Dead Zone is a percentage, and ideally you want as little to do with the Dead Zone as possible, for it is a most terrifying place indeed. It is a place where Christopher Walken looks like that. It is a place where your daughter is screaming and the world is burning. It is a place brought to you by defensive tackle Richard Seymour, whose contract cost the Raiders $13.714 million last season, despite being voided seven months before the season even began. The Dead Zone, both in Stephen King’s writing and in the NFL, is a place ripe with fear and apprehension about the future.

Blessed with McKenzie’s bravery, the Oakland Raiders have mostly emerged from the dark of the Dead Zone, sitting pretty with the 10th-lowest Dead Zone Rating as the dawn of the 2014 season approaches. The Raiders still have $9 million in dead money this coming year, fifth-most in the league; but with nearly $61 million in unallocated salary cap money, that amounts to an NFL Dead Zone rating of 13.25 percent, tenth-lowest in the league. Well done, Mr. McKenzie, well done.

Pictured: Reggie McKenzie, General Manager, Oakland Raiders

Pictured: Reggie McKenzie, General Manager, Oakland Raiders

The team least troubled by the Dead Zone? The New York Jets. This is NOT to say that the Jets are the best team, or will be the best team next season, or that they have objectively gotten the most out of their salary cap (or that they are the team most capable of changing the future). But it does mean that at the moment, the share of the Jets’ potential cap space lost to players not even on their team anymore is the smallest in the league at 0.24 percent. Their mere $0.049 million in dead money is the lowest in the league, while their $20-plus million in cap space ranks eleventh.

At the other end of the spectrum are the New Orleans Saints. The third-most dead money–over $10 million–and the fourth-least cap space–less than $2 million–make for an 87.57 percent dead zone rating. By awarding millions in signing bonuses and guaranteed money to players they would later cut or trade away (Roman Harper, Jabari Greer, Will Smith), the Saints road through the dead zone will be formidable. If I were Saints general manager Mickey Loomis, I would call up Christopher Walken right now for advice. Or at least Stephen King.

Now, here at last is the complete enumeration of where every team2 stands in the NFL Dead Zone.3 It’s over. You’re finished.

Team Rank Dead Zone Rank Dead Money Rank Cap Space
NYJ 1 0.24% 28 48,958 11 20,044,583
TB 2 1.10% 26 139,119 15 12,541,710
IND 3 2.30% 25 800,733 4 33,972,029
CIN 4 3.99% 24 984,281 9 23,662,960
MIN 5 5.92% 21 1,783,163 7 28,331,238
PHI 6 6.30% 23 1,348,343 10 20,059,815
GB 7 8.59% 18 2,677,484 6 28,498,261
JAC 8 10.18% 10 5,600,511 2 49,428,124
MIA 9 13.21% 11 4,942,895 5 32,481,214
OAK 10 13.25% 5 9,286,520 1 60,817,593
CLE 11 13.67% 8 7,194,153 3 45,452,022
STL 12 17.82% 27 133,805 28 617,229
NYG 13 18.08% 17 2,778,141 14 12,588,186
BAL 14 21.16% 12 4,422,216 13 16,479,137
CHI 15 22.61% 22 1,476,669 22 5,054,728
WAS 16 24.89% 7 7,941,733 8 23,969,653
SF 17 26.00% 20 1,934,691 21 5,506,346
DEN 18 26.26% 14 3,992,329 17 11,212,168
TEN 19 27.98% 19 2,449,725 20 6,306,953
ATL 20 32.25% 9 5,922,507 16 12,442,188
BUF 21 38.89% 2 12,070,113 12 18,967,410
DET 22 50.40% 13 4,069,438 23 4,005,130
ARI 23 51.25% 4 10,087,467 18 9,595,088
KC 24 53.13% 15 3,505,823 25 3,092,443
HOU 25 56.29% 16 3,247,174 26 2,521,766
CAR 26 68.35% 1 17,840,240 19 8,260,965
NE 27 70.08% 6 8,533,721 24 3,644,255
NO 28 87.57% 3 10,450,051 27 1,482,990

  1. Because what good is having cake if you can’t eat it? Seriously… 
  2. Okay, almost; four teams–Dallas, Pittsburgh, San Diego, and Seattle–actually have negative projected 2014 salary cap space at the moment, a situation so bad it goes beyond the parameters of the Dead Zone and into something more of an “After-Death Zone”. Perhaps more on this later. 
  3.  Team dead money and salary cap figures determined by Spotrac.com
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I embarked on a pretty sweet mini-project today, if I do say so myself. It starts with a couple of… “problems” that had been nagging me, regarding the lack of use of football’s Pythagorean formula. Pythagorean wins (or winning percentage) have been showing up in NFL analysis for, I dunno, at least a few years now. I learned of them in a Bill Barnwell preseason piece before the 2012 NFL Season (on Grantland.com). A team’s Pythagorean winning percentage (PW%) is as follows:
PW% = (Points Scored ^ 2.37) / {(Points Scored ^ 2.37) + (Points Allowed ^ 2.37)}1
Say the Bengals and Browns are both 8-8. The Bengals blew out their opponents in their eight wins, and lost narrowly in their eight losses, while the Browns won narrowly in their wins and lost big in their losses. You probably agree that even with the same record, the Bengals are likely better than the Browns. PW% is a measure of how much.

What’s bothered me is that Pythagorean analysis usually stops there: with a team’s points scored and points allowed. But one could apply the same analysis to a group of teams, say the 49ers’ opponents in the 2013 season, and determine that group’s PW%. Then one would know how tough the 49ers’ competition had been this year, beyond simple wins and losses. And, instead of using this year’s record as a strength of schedule statistic for next year’s season, one could use it for this very season itself, adding context to those final standings. We don’t have to just assume that all ten-win teams are equally skilled (or that they aren’t); we can quantify other useful metrics and see if there’s any evidence for our assumptions. And that’s exactly what I’ve done. For all 32 teams, and all 13 of their opponents, through 15 games.2 Let’s take a look!

First off, we have our sin-context base, nothing but the ‘W’s:

Rank Team W W%
1 SEA 12 80.00%
1 DEN 12 80.00%
3 SF 11 78.57%
4 CAR 11 73.33%
4 KC 11 73.33%
4 NE 11 73.33%
7 CIN 10 66.67%
7 NO 10 66.67%
7 ARI 10 66.67%
7 IND 10 66.67%
11 PHI 9 60.00%
12 SD 8 53.33%
12 DAL 8 53.33%
12 MIA 8 53.33%
12 BAL 8 53.33%
12 CHI 8 53.33%
17 GB 7.5 50.00%
18 DET 7 46.67%
18 STL 7 46.67%
18 PIT 7 46.67%
18 NYJ 7 46.67%
22 TEN 6 40.00%
22 BUF 6 40.00%
22 NYG 6 40.00%
25 MIN 4.5 30.00%
26 ATL 4 28.57%
27 TB 4 26.67%
27 CLE 4 26.67%
27 OAK 4 26.67%
27 JAC 4 26.67%
31 WAS 3 20.00%
32 HOU 2 13.33%

Alright. Mostly, all that’s good for is figuring out who gets the first pick in the draft. Let’s add some context. Here are the same figures, for Pythagorean wins:

Rank Team Pythagorean Wins PW%
1 SEA 11.9 79.17%
2 CAR 11.1 74.18%
3 SF 10.9 72.95%
4 DEN 10.8 71.88%
5 KC 10.7 71.05%
6 CIN 10.2 68.02%
7 NO 9.7 64.90%
8 NE 9.7 64.62%
9 ARI 9.0 60.29%
10 PHI 8.8 58.76%
11 SD 8.6 57.65%
12 IND 8.4 56.01%
13 DET 8.0 53.18%
14 DAL 7.7 51.29%
15 STL 7.6 50.35%
16 PIT 7.4 49.34%
17 MIA 7.4 49.05%
18 GB 7.1 47.58%
19 BAL 7.1 47.14%
20 CHI 6.9 46.16%
21 TEN 6.9 45.88%
22 BUF 6.6 43.86%
23 MIN 5.6 37.58%
24 ATL 5.4 36.32%
25 TB 5.4 35.76%
26 CLE 5.4 35.68%
27 OAK 4.9 32.53%
28 NYG 4.8 31.94%
29 WAS 4.7 31.19%
30 NYJ 4.6 30.79%
31 HOU 3.9 26.17%
32 JAC 3.1 20.58%

Now Carolina and San Francisco appear a little bit better than Denver; Jacksonville still has a firm grip on last place, in the Pythagorean world. Curious how these little differences do add up and do affect rankings. You can get an idea of how teams landed where they did by checking out their point totals, presented here, in order of most net points through the 15 games so far:

Rank Team Net Points PF PF Rank PA PA Rank
1 DEN 187 572 1 385 22
2 SEA 168 390 8 222 2
3 SF 131 383 10 252 3
4 KC 128 406 6 278 4
5 CAR 124 345 19 221 1
6 CIN 108 396 7 288 6
7 NE 92 410 5 318 9
8 NO 85 372 13 287 5
9 PHI 58 418 2 360 16
9 ARI 58 359 16 301 7
11 SD 45 369 14 324 11
12 IND 35 361 15 326 12
13 DET 20 382 11 362 17
14 DAL 9 417 3 408 25
15 STL 2 339 20 337 13
16 PIT -4 359 16 363 18
17 MIA -5 310 24 315 8
18 BAL -15 303 26 318 9
19 GB -16 384 9 400 24
20 TEN -25 346 18 371 19
21 CHI -28 417 3 445 30
22 BUF -35 319 23 354 15
23 TB -76 271 29 347 14
24 CLE -85 301 27 386 23
25 ATL -89 333 21 422 29
26 MIN -90 377 12 467 32
27 NYG -103 274 28 377 20
28 NYJ -110 270 30 380 21
29 OAK -111 308 25 419 27
30 WAS -130 328 22 458 31
31 HOU -146 266 31 412 26
32 JAC -182 237 32 419 27

Those are the inputs. And the outputs? Subtracting actual wins from Pythagorean wins, we reveal how many “lucky” wins (or losses) each team has:

Rank Team W – PW W PW
1 NYJ 2.4 7 4.6
2 IND 1.6 10 8.4
3 NE 1.3 11 9.7
4 DEN 1.2 12 10.8
5 NYG 1.2 6 4.8
6 CHI 1.1 8 6.9
7 ARI 1.0 10 9.0
8 BAL 0.9 8 7.1
9 JAC 0.9 4 3.1
10 MIA 0.6 8 7.4
11 GB 0.4 7.5 7.1
12 KC 0.3 11 10.7
13 DAL 0.3 8 7.7
14 NO 0.3 10 9.7
15 PHI 0.2 9 8.8
16 SEA 0.1 12 11.9
17 SF 0.1 11 10.9
18 CAR -0.1 11 11.1
19 CIN -0.2 10 10.2
20 PIT -0.4 7 7.4
21 STL -0.6 7 7.6
22 BUF -0.6 6 6.6
23 SD -0.6 8 8.6
24 OAK -0.9 4 4.9
24 TEN -0.9 6 6.9
26 DET -1.0 7 8.0
27 MIN -1.1 4.5 5.6
28 CLE -1.4 4 5.4
29 TB -1.4 4 5.4
30 ATL -1.4 4 5.4
31 WAS -1.7 3 4.7
32 HOU -1.9 2 3.9

The Jets have outperformed by more than two wins! And Rex Ryan still might get fired. Also, Jacksonville’s good luck has ruined formerly promising chances of getting the first pick in the draft, as likely they’ll instead see it go to Houston. It’s really Houston that has performed better, losing by significantly fewer points, albeit more often. Well, perhaps Houston’s competition was much easier? Or perhaps not? You don’t have to wonder, let’s see! Here are the teams ranked by the average net points of their opponents, adjusted by removing totals from games against the team in question.3

Tm Rk O Nt Pts /Gm O PF /Gm Rk O PA /Gm Rk
DET 1 -338 -1.64 5,043 24.48 23 5,381 26.12 3
GB 2 -304 -1.48 5,047 24.50 24 5,351 25.98 4
PHI 3 -282 -1.37 5,106 24.79 27 5,388 26.16 2
KC 4 -279 -1.35 5,118 24.84 28 5,397 26.20 1
CHI 5 -259 -1.26 4,964 24.10 19 5,223 25.35 10
BAL 6 -216 -1.05 5,105 24.78 26 5,321 25.83 6
PIT 7 -211 -1.02 4,859 23.59 11 5,070 24.61 14
BUF 8 -179 -0.87 4,539 22.03 1 4,718 22.90 23
DAL 10 -177 -0.86 5,140 24.95 29 5,317 25.81 7
CIN 9 -177 -0.86 4,934 23.95 16 5,111 24.81 12
OAK 11 -176 -0.85 4,979 24.17 22 5,155 25.02 11
CLE 12 -129 -0.63 4,883 23.70 13 5,012 24.33 15
NYJ 13 -89 -0.43 4,722 22.92 4 4,811 23.35 19
NE 14 -84 -0.41 4,679 22.71 2 4,763 23.12 20
SD 15 -56 -0.27 5,195 25.22 30 5,251 25.49 8
MIN 16 -28 -0.14 5,048 24.50 25 5,076 24.64 13
JAC 17 -1 0.00 4,912 23.84 15 4,913 23.85 16
DEN 18 15 0.07 4,833 23.46 9 4,818 23.39 17
TEN 19 29 0.14 4,846 23.52 10 4,817 23.38 18
WAS 20 78 0.38 5,417 26.30 31 5,339 25.92 5
SEA 21 81 0.39 4,783 23.22 5 4,702 22.83 24
SF 22 109 0.53 4,808 23.34 6 4,699 22.81 25
MIA 23 127 0.62 4,823 23.41 7 4,696 22.80 26
CAR 24 161 0.78 4,829 23.44 8 4,668 22.66 27
ATL 25 208 1.01 4,701 22.82 3 4,493 21.81 32
HOU 26 220 1.07 4,969 24.12 21 4,749 23.05 21
IND 27 222 1.08 4,967 24.11 20 4,745 23.03 22
STL 28 255 1.24 4,902 23.80 14 4,647 22.56 28
NYG 29 328 1.59 5,571 27.04 32 5,243 25.45 9
ARI 30 333 1.62 4,871 23.65 12 4,538 22.03 30
NO 31 361 1.75 4,954 24.05 17 4,593 22.30 29
TB 32 458 2.22 4,961 24.08 18 4,503 21.86 31

You see, there’s really quite a difference. Buffalo’s opponents, in games not against Buffalo, scored an average of 22.03 a game; five points a game fewer than the unfortunate New York Giants, who went up against all four top offenses in the league, two of them (Philadelphia and Dallas) twice! Notice Washington is down there too; teams in the same division tend to clump together, as 75% of their opponents are in common. Kansas City played the worst defenses overall (through 15 games), while Atlanta faced the toughest. All in all, Detroit’s opponents, in games not against Detroit, lost by 1.64 points on average, while Tampa Bay’s opponents won by 2.22 points, nearly a four-point swing between extremes.

Putting it all together, these are the Pythagorean winning percentages of the opponents of all thirty-two teams, along with the PW% of the team itself. The difference, which I quite originally dub “Relative Performance” (actual PW% minus expected PW% given those opponents), indicates how well a team fared against its competition, relative to other teams against the same opponents.

Team Rank Relative Performance Opp. PW% Rank Expected PW% Actual PW%
SEA 1 30.19% 51.01% 21 48.99% 79.17%
CAR 2 26.19% 52.01% 24 47.99% 74.18%
SF 3 24.31% 51.36% 22 48.64% 72.95%
DEN 4 22.06% 50.18% 18 49.82% 71.88%
NO 5 19.37% 54.47% 31 45.53% 64.90%
KC 6 17.90% 46.86% 4 53.14% 71.05%
CIN 7 15.93% 47.91% 9 52.09% 68.02%
ARI 8 14.48% 54.19% 30 45.81% 60.29%
NE 9 13.56% 48.95% 14 51.05% 64.62%
IND 10 8.72% 52.71% 27 47.29% 56.01%
SD 11 7.01% 49.36% 15 50.64% 57.65%
PHI 12 5.58% 46.82% 3 53.18% 58.76%
STL 13 3.51% 53.16% 28 46.84% 50.35%
MIA 14 0.63% 51.58% 23 48.42% 49.05%
DET 15 -0.65% 46.16% 1 53.84% 53.18%
DAL 16 -0.71% 48.00% 11 52.00% 51.29%
PIT 17 -3.17% 47.48% 6 52.52% 49.34%
TEN 18 -3.77% 50.36% 19 49.64% 45.88%
BAL 19 -5.31% 47.55% 7 52.45% 47.14%
GB 20 -5.88% 46.54% 2 53.46% 47.58%
CHI 21 -6.85% 46.99% 5 53.01% 46.16%
BUF 22 -8.43% 47.71% 8 52.29% 43.86%
TB 23 -8.53% 55.71% 32 44.29% 35.76%
ATL 24 -11.00% 52.68% 25 47.32% 36.32%
MIN 25 -12.75% 49.67% 16 50.33% 37.58%
NYG 26 -14.47% 53.59% 29 46.41% 31.94%
CLE 27 -15.87% 48.46% 12 51.54% 35.68%
WAS 28 -17.95% 50.86% 20 49.14% 31.19%
OAK 29 -19.52% 47.94% 10 52.06% 32.53%
NYJ 30 -20.32% 48.89% 13 51.11% 30.79%
HOU 31 -21.15% 52.68% 26 47.32% 26.17%
JAC 32 -29.43% 49.99% 17 50.01% 20.58%

So take my 49ers. Their average opponent should expect to win 51.36% of their games not against the 49ers, but only 27.05% of their games against the 49ers.4 That difference, 24.31%, is the third largest in the league. GO NINERS! Only Carolina and Seattle have dominated more thoroughly, giving their opponents quite a whooping, much more so than their opponents receive from other teams. Kansas City, meanwhile, boasts a healthy 71.05 PW%; but against its crummy competition, other teams have been averaging a 53.14 PW% anyway, so it’s a little less impressive, knocking their relative performance to sixth in the league.

Oh, and check out the Jets! Further evidence that I was right when I declared that their 2013 campaign was quite impressive earlier this week. Other teams facing the Jets’ competition have a respectable 51.11 PW%; they outperform them over half the time. The Jets, meanwhile, only manage 30.79%, getting badly outperformed by mediocre teams. Ick. I should point out that by these measures, Tampa Bay had the toughest schedule, while Detroit had the easiest– and still missed the playoffs. Ouch.

Lastly, we’ll return to the “real” numbers, straight-up wins, side-by-side with their Pythagorean expectations. This post has been about context. Wins and losses mean different things in different contexts; a context of narrow defeats and blowout wins suggests a team is merely having some bad breaks, and inspires optimism; a context of blowout defeats and narrow wins indicates the opposite, and the tempering of future expectations. But context is only that: context. The real content, the wins and losses themselves, is what we care about. Here they are, side by side:

Team Rank W Expected PW Actual PW PW Over/Under Expected W Over/Under PW
SEA 1 12 7.3 11.9 4.5 0.1
DEN 1 12 7.5 10.8 3.3 1.2
CAR 3 11 7.2 11.1 3.9 -0.1
SF 3 11 7.3 10.9 3.6 0.1
KC 3 11 8.0 10.7 2.7 0.3
NE 3 11 7.7 9.7 2.0 1.3
NO 7 10 6.8 9.7 2.9 0.3
CIN 7 10 7.8 10.2 2.4 -0.2
ARI 7 10 6.9 9.0 2.2 1.0
IND 7 10 7.1 8.4 1.3 1.6
PHI 11 9 8.0 8.8 0.8 0.2
SD 12 8 7.6 8.6 1.1 -0.6
MIA 12 8 7.3 7.4 0.1 0.6
DAL 12 8 7.8 7.7 -0.1 0.3
BAL 12 8 7.9 7.1 -0.8 0.9
CHI 12 8 8.0 6.9 -1.0 1.1
GB 17 7.5 8.0 7.1 -0.9 0.4
STL 18 7 7.0 7.6 0.5 -0.6
DET 18 7 8.1 8.0 -0.1 -1.0
PIT 18 7 7.9 7.4 -0.5 -0.4
NYJ 18 7 7.7 4.6 -3.0 2.4
TEN 22 6 7.4 6.9 -0.6 -0.9
BUF 22 6 7.8 6.6 -1.3 -0.6
NYG 22 6 7.0 4.8 -2.2 1.2
MIN 25 4.5 7.5 5.6 -1.9 -1.1
TB 26 4 6.6 5.4 -1.3 -1.4
ATL 26 4 7.1 5.4 -1.6 -1.4
CLE 26 4 7.7 5.4 -2.4 -1.4
OAK 26 4 7.8 4.9 -2.9 -0.9
JAC 26 4 7.5 3.1 -4.4 0.9
WAS 31 3 7.4 4.7 -2.7 -1.7
HOU 32 2 7.1 3.9 -3.2 -1.9

  1. Multiply the % by the number of games played to obtain Pythagorean wins. You may then compare the number of Pythagorean wins to actual wins; if actual wins are greater, the team has been lucky, while if Pythagorean wins are greater, they’ve been unlucky. The two figures even out in the long run but may differ over short stretches. (Even a full sixteen game season. Sixteen games isn’t that many. You know they play 162 in baseball?) 
  2. Remember, teams play 16 games against 13 opponents because they play each team in their division twice; the last game of the season is always an intra-division match-up, so at the moment each team has played 15 games against 13 teams. 
  3. Sorry this chart’s headers are a little lacking; it was the only way I could get it to fit onto one page. It was either that or splitting it into three separate charts, which I thought worse. 
  4. 100% – San Francisco’s actual PW% of 72.95% = 27.05%. 

Two things have been on my mind since yesterday’s NFL action. One, can any team replicate the Arizona Cardinals’ shocking success in Seattle, where they won 17-10 as nine-point underdogs? Two, how is it possible the New York Jets can still finish without a losing record? How did they get to seven wins heading into their final game? As these things aren’t really related at all, I made them related in this post, another feature of “What’s More Impressive?“.

A quick rundown of some numbers I’ll be using to answer:

  • DVOA stands for Defense-adjusted Value Over Average. Football Outsiders created it to determine relative team strength. The idea is that there are only 16 games a season, a small sample to rank teams on. But there are lots of plays in a season, usually more than a hundred every game, so Football Outsiders looks at how successful a team is on an average play, and then compares that to a league-wide average, using percentages. Feel free to read more.
  • PW% stands for Pythagorean Winning Percentage. This uses the idea that the margin of victory (or defeat) is a significant indicator of team strength, especially over the course of the season. The formula is (Points Scored ^ 2.37) / {(Points Scored ^ 2.37)+(Points Allowed ^ 2.37)}.
  • Point spreads have long been used by Las Vegas casinos. They’re designed to get even action on both sides. Most would bet that the Broncos would beat the Texans, so Vegas increases payouts for betting that the Broncos will win by, say, 10.5 points (the line for yesterday’s game). Casinos frequently adjust spreads to ensure that they see half the action on each side. The more a team is favored, the better their chances are of winning outright. (Duh.)
  • HFA stands for Home Field Advantage. In a recent column on Grantland, Bill Barnwell examined a team’s average margin of victory in its current stadium, and compared that margin to their average margin of victory (or defeat) on the road, going back through the 2002 season. The difference between the two average margins, divided by two, is historically the expected “extra” points for the home team, relative to a neutral site.

Let’s start with the Cardinals. They’ve been pretty good this year, sure. They were 9-5 heading into yesterday’s game, still alive for an NFC Wildcard berth. They have been cursed by their company; the league-leading 12-3 Seahawks, as well as the 10-4 49ers, are also in the NFC West division. They had lost to them each once already, heading into Week 16. They’d beaten the Lions (that meant something for most of the season), and the Panthers (who clinched a playoff spot yesterday), and the Colts (who clinched last week), but all at home. The Cardinals were 6-1 at home, and 3-4 on the road, and that home loss came to… the Seahawks. Second-year Seahawks’ quarterback Russell Wilson was a perfect 14-0 at home heading into yesterday. The Seahawks have looked dominant all year, and, well, unbeatable at home.

Cardinals vs. Seahawks

  • Record: 10-5 (66.57%, tied for 7th); Seahawks’ Record: 12-3 (80%, tied for 1st)
  • DVOA (through Week 15): 10.9% (10th); Seahawks’ DVOA: 40.4% (1st)
  • PW%: 60.29% (9th); Seahaw’s PW%: 79.17%% (1st)
  • Record of nine-point underdogs (since 2003): 28-88 (24.1%)
  • Seattle’s HFA (since 2002): 5.2 points/game (1st)
  • Interceptions Thrown By Carson Palmer: 4 (4!!!)

1 2 Here’s the thing: I was considering taking the points in this game, but ultimately decided the Seahawks were just too good. Worst case scenario, Arizona would hang around, but Seattle would eventually cover (see: Broncos-Texans). But if you had guaranteed to me that Carson Palmer would throw four interceptions, I would have put my life savings on Seattle (or, at least some real money). I can’t believe they won with him throwing four picks. I know they did it with a really, really good defensive performance, aided by an injured Seahawk offensive line, but, like, how did they do that?

As for the Jets, they’ve been, uhh, bad. They now have seven wins (!), five of which are against teams with 5-10 records or worse.3 They lost by 25 to the Titans. (Yes, the Titans.) They lost by 40 to the Bengals. (Yes, 40.) They beat the Bills by seven… and later lost to them by 23. But they’re now 6-2 at home, 1-6 on the road, and a remarkable 5-1 in games decided by a touchdown or less. That includes (home) victories over the Patriots by three points4 and the Saints by six points. The thing is that “games decided by a touchdown or less” suggest more luck rather than skill. We love fitting narratives to teams, players, and coaches about how they always pull it out, but a team’s record in close games converges to .500 the more close games they play. The Jets flipped a coin six times and got five victories back. What else suggests the Jets have been lucky?

Jet’s Victories (TB, BUF, @ATL, NE, NO, OAK, CLE)

  • Record: 7-8 (46.67%, tied for 18th); Record of Defeated Opponents: 41-64 (39.05%)
  • DVOA (through Week 15): -13.8% (26th); Average DVOA of Defeated Opponents: -5.27% (Average DVOA Rank of Defeated Opponents: 19.4)
  • PW%: 30.79% (30th); Average PW% of Defeated Opponents: 44.88% (Average PW% Rank of Defeated Opponents: 19.9)
  • Record of teams with Jets’ spread (since 2003) in Jets’ victories: 485-687-1 (41.4%)

That last number is the sum record of teams in match-ups similar to the Jets in their victories, in Vegas’ eyes. The Jets were four-point underdogs in their Week 1 victory over Tampa Bay, and historically four point underdogs have gone 45-91 (straight up, not against the spread). In their Week 3 win over Buffalo, the Jets were 2.5-point favorites, who’ve gone 66-63, etc. Most of the teams the Jets have beaten were bad. But they’re still surprising wins, given that the Jets have seemed even worse (except for, you know, the whole “winning” technicality). What’s more impressive?

Cardinals’ One Win @SEA vs. Jets’ Seven Wins (TB, BUF, @ATL, NE, NO, OAK, CLE)

  • Winning % Gap Between Competition: Cardinals -14.3%; Jets +7.62%
  • DVOA Gap: Cardinals -29.5% (9 ranks); Jets -8.53% (6.6 ranks)
  • PW% Gap: Cardinals -18.88% (8 ranks); Jets -14.09% (10.1 ranks)
  • Historical Winning % Given the Same Spread: Cardinals 24.1%; Jets 41.4%

I feel compelled to declare the New York Jets’ 7-8 record at this point (much) more impressive than the Cardinals’ road victory over the Seahawks, primarily for two reasons. One, ironically this gives the Cardinals more credit. I think they’re a good team, and while I don’t think they’d win in Seattle every time (more like two or three out of ten), this wasn’t a fluke. Two, the Jets have pulled off a bunch of unlikely wins. While the probability of a Jets win in any single one of those games maybe wasn’t as low as the Cardinals’ in Seattle, winning all of them is remarkable.5 Using Vegas spreads, for instance, there was a 24.1% chance the Cardinals won, and on average a 41.4% chance the Jets did. But the Jets won seven times. With an expected winning percentage of 41.4%, the odds you go 7-0 are 0.2%!6 And I think that’s damn impressive.


  1.  http://www.footballoutsiders.com/dvoa-ratings/2013/week-15-dvoa-ratings 
  2.  http://www.teamrankings.com/nfl/odds-history/results/ 
  3. Actually, the Falcons are 5-9. If they beat the 49ers tonight, they would be 6-9. But still. 
  4. Perhaps you recall, this was a bizarre game where the Jets game-winning field goal in overtime actually missed, but then there was some phantom penalty no one had ever heard of on the Patriots, and the Jets got to kick again, from much closer. 
  5. The games are statistically independent, that is, the Jets are a football team with strengths and weaknesses in their match-ups with opponents, and that the outcome of a particular game does not affect the probability (strengths and weaknesses) of an outcome of any other game. 
  6. (414/1000)^7 

At last it has arrived! The final position (excluding special teams) of my mid-season search for the best contract in football, a recurring Economics and Sports Management feature. It’s the last post (until the season is over), and it focuses on the last men to beat in the defensive backfield: safeties. As always, players’ on-field performance grades come from the experts at Pro Football Focus and players’ average annual contract salaries come from the databases at Spotrac.com.

These are the Top 10 safeties this season, through Week 14 (PFF grades in parentheses):

  • 1. Devin McCourty, NE (17.3)
  • 2. Donte Whitner, SF (13.5)
  • 3. T.J. Ward, CLV (13.1)
  • 4. Will Hill, NYG (12.3)
  • 5. James Ihedigbo, BAL (11.8)
  • 6. Eric Berry, KC (10.7)
  • 7. Jairus Byrd, BUF (9.2)
  • 8. Earl Thomas, SEA (5.7)
  • 9. Kam Chancellor, SEA (5.5)
  • 10. Rashad Johnson, ARI (5.4)

I was a little surprised to see Whitner, but it looks like he’s put in the work this year after getting torched in the Super Bowl. I would guess Troy Polamalu is the most famous safety, but despite being big for Head and Shoulders he hasn’t been among the very best on the field, earning a 4.4 grade, good for 17th in the league.1 Here are the Bottom 10:

  • 74. Reshad Jones, MIA (-9.8)
  • 75. Dashon Goldson, SF (-10.9)
  • 76. Bacarri Rambo, WAS (-11)
  • 77. Thomas DeCoud, ATL (-11.2)
  • 78. Josh Evans, JAC (-11.5)
  • 79. Chris Conte, CHI (-12.2)
  • 80. Brandon Meriweather, WAS (-13.1)
  • 81. John Cyprien, JAC (-18.1)
  • 82. Brandian Ross, OAK (-21.8)
  • 83. Major Wright, CHI (-24.3)

Rough times in Chicago and Jacksonville. There are actually 85 safeties who’ve played 25% or more of their potential snaps. Will Allen was released earlier this year by the Dallas Cowboys, and Ed Reed was released by the Texans only to be signed by the Jets. I dropped them both from the analysis, although Reed’s substantial drop in pay will be worth mentioning in a bit. Among the other 83 safeties, the average grade was a -1.25, with a standard deviation of 7.32. And here are the Top 10 safety salaries (average annual salary in millions of dollars in parentheses):

  • 1. Troy Polamalu, PIT ($9.125 million)
  • 2. Eric Berry, KC ($8.341m)
  • 3. Dashon Goldson, TB ($8.25m)
  • 4. Eric Weddle, SD ($8m)
  • 5. Antrel Rolle, NYG ($7.4m)
  • 6. Reshad Jones, MIA ($7.34m)
  • 7. Michael Griffin, TEN ($7m)
  • 8. Jairus Byrd, BUF ($6.916m)
  • 9. Antoine Bethea, IND ($6.75m)
  • 10. LaRon Landry, IND ($6m)

Goldson, 9th worst safety on the year, is the third highest paid, with Jones joining him in the worst-play-best-pay clubhouse. And both Colt safeties also have performance grades below the -1.25 average. Not what you want for top dollar. Here are the Bottom 10 paid safeties:

  • 74. Antonio Allen, NYJ ($0.537m)
  • 75. Jaiquawn Jarrett, NYJ ($0.525m)
  • 76. Robert Lester, CAR & Jeff Heath, DAL ($0.495m)
  • 78. Rodney McLeod, STL ($0.481m)
  • 79. Will Hill, NYG, Tashaun Gipson, CLE, Duke Ihenacho, DEN, & Brandian Ross, OAK ($0.48m)
  • 83. M.D. Jennings, GB ($0.466m)

The average safety’s salary is $2.422 million, with a standard deviation of $2.334 million. As with many positions, salaries vary much less than performance. Now, before awarding another general manager with another award for one of the best contracts in football, I give you Ed Reed.

This past off-season Reed signed a three-year contract with the Houston Texans, averaging $5 million a year, a little less than his previous seven-year contract with the Baltimore Ravens, which averaged $5.726 million. In 2008 (as far back as PFF data goes), Reed was the 4th highest graded safety of 83 who had significant playing time; in 2009, 2nd of 88; in 2010, 9th of 85; in 2011, 12th of 87; and last season, 59th of 88. A 12-year veteran, the Ravens let him go, but the Texans paid him well above average. Through Week 10, in seven games with the Texans Reed graded at -6.3, a -0.9 per game. The current league average among safeties is roughly a -0.09; Reed was playing much worse. Houston released him (still owing him about two million dollars), and the Jets signed him to a one-year contract worth only $0.94 million. With the Jets he’s still played poorly, a -1.5 grade through four games, but his current contract is much more favorable to the Jets than his old one was to the Texans. I estimate that his current contract quality is actually 0.59, a good move for the Jets (as it was a good move for the Texans to cut him). While Reed may be one of the better known safeties, in the period of a season and a half, as his play declined sharply, teams’ willingness to pay him declined sharply as well. On-field performance matters a great deal (duh).

On to the Top 10 safety contracts this season, so far (contract quality2 in parentheses):

  • 1. Devin McCourty, NE (2.72)
  • 2. Will Hill, NYG (2.68)
  • 3. James Ihedigbo, BAL (2.49)
  • 4. T.J. Ward, CLE (2.45)
  • 5. Robert Lester, CAR (1.72)
  • 6. George Iloka, CIN (1.58)
  • 7. Donte Whitner, SF (1.37)
  • 8. Ryan Mundy, NYG & Glover Quin, DET (1.34)
  • 10. Andrew Sandejo, MIN (1.28)

Another ESPM congratulations to New England Patriots General Manager (and head coach) Bill Belichick. Those top six contracts are all top 16 performers (the first four are top five performers) who make less than the average safety. Note that Baltimore, having moved on from Reed, is getting excellent value from Ihedigbo. In a similar play from the losers of last year’s Super Bowl, the 49ers let Dashon Goldson go in free agency, keeping Whitner3 and drafting rookie Eric Reid in the first round, currently the 25th best contract with a +3.3 grade on $2.12 million. As for Goldson, well… here are the Worst 10 contracts this season:

  • 74. Morgan Burnett, GB (-1.71)
  • 75. Thomas DeCoud, ATL (-1.82)
  • 76. John Cyprien, JAC (-1.85)
  • 77. Brandon Meriweather, WAS (-1.87)
  • 78. Brandian Ross, OAK (-1.98)
  • 79. Troy Polamalu, PIT (-2.1)
  • 80. Antoine Bethea, IND (-2.33)
  • 81. Major Wright, CHI (-2.39)
  • 82. Reshad Jones, MIA (-3.28)
  • 83. Dashon Goldson, TB (-3.82)

Yup, the Bucs rewarded Goldson with the third most money among all safeties, and he’s been, in a word, bad. It is worth pointing out that while building through the draft and getting some cheap contracts and all are usually good ideas, they aren’t foolproof. Cyprien went 33rd overall to the Jaguars, the first pick of the second round. Brandian Ross and Major Wright both make well below a million dollars, but they have just been really, really bad out there.

Once again, the data suggest that there is no ironclad, golden rule to attain success in the NFL. If there was, it would be easy. And boring.


  1. Of course, his popularity may benefit the Steelers in other ways, but for now I won’t be getting into it. It’s not a simple task. 
  2. CQ = # SDs a player’s performance grade is above/below the mean – # SDs a player’s average annual salary is above/below the mean 
  3. Soon to be HITner! Oh never mind. Thank goodness, I sure thought that was dumb. 

The football was the most amazing football last Sunday. I’m still processing it, and probably won’t be ready to talk about it until at least Friday. But I must go on with my continuing Economics and Sports Management recurring feature, The Search for the Best (& Worst!) Contract in Football. The end is near!1 We’re finally in the defensive backfield, as I look at cornerback pay and performance. And we have a serious challenger for guard Davin Joseph’s former stranglehold on the worst contract in the league.

First, some usual disclaimers: other things go into a player’s market value besides on-field performance. Measuring those things, how popular a player is, if he makes his teammates better, if he’s a good guy to have around, works well with the coaches, etc, is really, really hard. Certainly performance is a huge component of pay though. Tim Tebow, even Brett Favre, hell even Mike Tyson would still probably sell some tickets, but you don’t see them getting NFL contracts. Also, while certain players may rake in the ticket and jersey sales, that is at least partially controlled for by doing the analysis by position. The backs and receivers, even the tight ends may bring a lot of money in without their play, but take Davin Joseph. Earlier this season I estimated he was overpaid by $10+ million dollars.2 You can’t make a case that he’s helping the Buccaneers recoup that in other ways, certainly not all $10 million. Similarly, with a few exceptions, I don’t think fans go to watch other offensive linemen, or really any defensive players.3

Secondly, the Pro Football Focus grades I use for this analysis are super awesome, but not 100% perfect. I think their main weakness is not controlling for the quality of the opposition, down to the individual level. If a cornerback blankets Calvin Johnson and holds him without a catch on 10 targets with three passes defensed and no penalties, it counts the same as another corner who does exactly the same thing to Greg Little.4 Still, over the course of a season, things should even out a good deal, if not completely. Doing the analysis after one game would be almost meaningless. But after thirteen games of players getting graded on every play, it’s much more compelling.

Cornerbacks! 111 have played 25% or more of their teams’ snaps through Week 14. The Buffalo Bills released Justin Rogers earlier this season, so I dropped him from the sample. (He lost an opportunity to perform, and they stopped paying him, so…) Here are the Top 10 performing cornerbacks on the field this season (PFF grade in parentheses):

  • 1. Darrelle Revis, TB (18.1)
  • 2. Tyrann Mathieu, ARI (15.5)
  • 3. Patrick Peterson, ARI (13.1)
  • 4. Brent Grimes, MIA (12.5)
  • 5. William Gay, PIT (11.1)
  • 6. Jason McCourty, TEN (10.9)
  • 7. Dominique Rodgers-Cromartie, DEN (10.8)
  • 8. Tramaine Brock, SF (10.7)
  • 9. Vontae Davis, IND (10.5)
  • 10. Leon Hall, CIN (8.7)

That Derrelle Revis guy, still pretty good it turns out, even after age and injuries have had their say. Poor rookie sensation Tyrann Mathieu tore his ACL and LCL this past Sunday, ending his season. It’s truly a shame, as Arizona had a good, and entertaining, duo going on with Mathieu and his former LSU teammate Patrick Peterson reunited. And while some of San Francisco’s Tramaine Brock’s grade was as the third corner usually covering the opponent’s third wide receiver, the last few weeks he’s been starting for an injured Tarell Brown, performing very well. On to the Bottom 10:

  • 101. Dee Milliner, NYJ (-9.1)
  • 102. Leonard Johnson, TB (-9.2)
  • 103. David Amerson, WAS (-9.3)
  • 104. Brandon Flowers, KC (-9.7)
  • 105. Antonio Cromartie, NYJ (-10.5)
  • 106. Ike Taylor, PIT (-11.2)
  • 107. Derek Cox, SD (-11.8)
  • 108. Shareece Wright, SD (-12.4)
  • 109. Brice McCain, HOU (-12.7)
  • 110. Cortland Finnegan, STL (-19.7)

Revis left the Jets for Tampa Bay, and his first round draft pick replacement Dee Milliner hasn’t quite fit the bill just yet. (Though note that another thing PFF grades don’t measure is potential.) Antonio Cromartie has played well in the past though, not sure what’s up with him. Down at the bottom, solidly entrenched by his terrible play, is Cortland Finnegan of the Rams. Again, the worst corner so far this season is Cortland Finnegan, by a sound margin. The average grade is a 0.18, with a standard deviation of 6.69. Eeesh, as usual, tremendous variation in player performance.

Here are the Top 10 paid cornerbacks who’ve played 25% or more of their teams’ snaps (average annual salaries in millions of dollars, reported by Spotrac.com, in parentheses):

  • 1. Darrelle Revis, TB ($16 million)
  • 2. Brandon Carr, DAL ($10.02m)
  • 3. Cortland Finnegan, STL ($10m)
  • 4. Johnathan Joseph, HOU ($9.75m)
  • 5. Joe Haden, CLE ($8.547m)
  • 6. Leon Hall, CIN ($8.475m)
  • 7. Lardarius Webb, BAL ($8.333m)
  • 8. Brandon Flowers, KC ($8.225m)
  • 9. Antonio Cromartie, NYJ ($8m)
  • 10. Tramon Williams, GB ($7.615m)

Hey, it’s Cortland Finnegan! He is the third most expensive corner in the league and on average makes $10 million a year. Alright! Also Darrelle Revis’ contract is more than two standard deviations above the next most paid player. Remember, while his play was tops as well, it was less than one standard deviation above the next best player. Not looking like a good contract for the Buccaneers. These are the Bottom 10 paid cornerbacks:

  • 101. Alfonzo Dennard, NE ($0.539m)
  • 102. Byron Maxwell, SEA ($0.538m)
  • 103. Jimmy Wilson, MIA ($0.521m)
  • 104. Robert McClain, ATL ($0.51m)
  • 105. Nolan Carroll, MIA ($0.497m)
  • 106. Nickell Robey, BUF & Melvin White, CAR ($0.495m)
  • 108. Leonard Johnson, TB ($0.483m)
  • 109. Chris Harris Jr, DEN ($0.466m)
  • 110. Isaiah Frey, CHI ($0.45m)

The average annual salary is $2.722 million, with a standard deviation of $2.873 million. As with a couple other positions that unusually had a standard deviation greater than the average, this indicates a few players (or in this case, a Derrelle Revis) who are just paid boatloads of money more than their peers. Are they worth it? What do you think?

The Top 10 cornerback contracts so far this season (contract quality5 in parentheses):

  • 1. Tyrann Mathieu, ARI (2.99)
  • 2. Tramaine Brock, SF & William Gay, PIT (2.06)
  • 4. Chris Harris Jr, DEN & Richard Sherman, SEA (1.85)
  • 6. Will Blackmon, JAC (1.84)
  • 7. Alterraun Verner, TEN (1.81)
  • 8. Vontae Davis, IND (1.78)
  • 9. Alan Ball, JAC (1.77)
  • 10. Corey White, NO (1.75)

And it’s Honey Badger in front! Congratulations to Arizona Cardinals General Manager Steve Keim! And apologies to the Cardinals for their bad luck that Mathieu went out for the season two days ago. That just sucks. But hey, at least he’s really good and you’re not paying him very much money and he’s only a rookie! It could be worse…

… and the Worst 10 contracts (so far):

  • 101. Cary Williams, PHI (-1.93)
  • 102. Darrelle Revis, TB (-1.94)
  • 103. Chris Houston, DET (-2.03)
  • 104. Charles Tillman, CHI (-2.11)
  • 105. Derek Cox, SD (-2.58)
  • 106. Brandon Carr, DAL (-2.81)
  • 107. Ike Taylor, PIT (-3.19)
  • 108. Brandon Flowers, KC (-3.39)
  • 109. Antonio Cromartie, NYJ (-3.43)
  • 110. Cortland Finnegan, STL (-5.5)

Ladies and gentlemen, Cortland Finnegan! A -5.5! AAAUUUGGGHHH!!! That is so, so, so bad. A few players had -3 or so (they may have since improved, or worsened ). Guard Davin Joseph had a -4.78. A -5.5 through thirteen games… There are a couple more things I want to point out (like Darrelle Revis!), but I just… I’m done. There are no words. -5.5.


  1. Well, not really. I’ll be doing this all again, bigger and better, with even MOAR analysis, at the end of the season. 
  2. He only makes $7.5 million a year. He’s so bad is just doesn’t even make sense. He broke the analysis. I’m still working on it. 
  3. Yeah, there are some exceptions. I said that! But when you look at all the starting defensive players in the league, that’s 11 * 32 = 352. How many can you name off the top of your head? How many of those don’t play for your team? 20? 30? The vast majority of them lack “star power”. I may not be able to measure it, but I know it when I see it. Most guys don’t have it. If most guys did have it, we’d have to call it something else, or move to Lake Wobegon. 
  4. Currently PFF’s worst graded receiver with a -13.9 through Week 14. 
  5. Reminder: contract quality is determined by how a player’s on-field performance, relative to the average using standard deviations, relates to his salary, relative to the average using standard deviations. CQ = performance SDs above/below the average – salary SDs above/below the average 
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