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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%. 
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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 

Following up my evaluation of quarterback contracts yesterday, today I examine the performance and pay of NFL wide receivers. There are 110 wide receivers who have played 25% or more of their team’s snaps this season. 109 of them are still under contract; as Kyle Williams was released by the San Francisco 49ers earlier this week, I dropped him from the calculations.1 While hovering on the subject of releases, I wanted to mention Matt Flynn. Seahawks General Manager John Schneider is worthy of praise for finding Russell Wilson, but equally responsible for Flynn, to whom he gave $10 million in guaranteed money that same year before tiring of him after one season. He was able to maneuver out $6 million with a trade to the Raiders, but Seattle still has $4 million in dead money this season as a result of signing Flynn.2

Before looking at the numbers, here are a few more notes about contract quality. If players don’t play, Pro Football Focus has no performance to evaluate. That could mean a variety of things concerning the contract. A backups is like any other insurance; you hope you don’t have to use it, but you’re willing to pay for it. Speaking of injuries, if a player misses a season for one, does that mean his contract was wasteful? Are NFL front offices accountable for avoiding injuries? Perhaps to some extent, but it’s difficult to quantify. Even so, teams may pay players for other things besides on-field performance. Popularity to the fans, the ability to sell tickets and jerseys, intangibles like “he’s a good locker room guy”, having worked well previously with members of the team and/or coaching staff, etc. Such qualities, while beyond the scope of this analysis, should not be forgot.

With that, here are PFF’s Top 10 wide receivers who’ve played 25% or more of their teams’ snaps so far this season (grades in parentheses)3:

  • 1. Brandon Marshall, CHI (20)
  • 2. Andre Johnson, HOU & Calvin Johnson, DET (16.8)
  • 4. Jordy Nelson, GB (14.9)
  • 5. Antonio Brown, PIT (14.7)
  • 6. Pierre Garcon, WAS (14.4)
  • 7. Demaryius Thomas, DEN (13.4)
  • 8. Wes Welker, DEN (10.6)
  • 9. Doug Baldwin, SEA (10.5)
  • 10. Marvin Jones, CIN (10.4)

Wouldn’t it be great if Andre and Calvin were brothers? And it’s Marvin Jones, not A.J. Green, of the Cincinnati Bengals rounding out the Top 10, although a substantial chunk comes from a dominating four touchdown performance against the New York Jets in Week 8. (Green himself grades at a 6.3 at the moment, good for 23rd in the league.) Here are the Bottom 10:

  • 100. Aaron Dobson, NE (-4.4)
  • 101. Mike Williams, TB (-4.5)
  • 102. Ryan Broyles, DET (-4.8)
  • 103. Dexter McCluster, KC (-4.9)
  • 104. Donnie Avery, KC (-5)
  • 105. Mike Wallace, MIA (-5.8)
  • 106. Mohamed Sanu, CIN & Greg Little, CLE (-6.7)
  • 108. T.J. Graham, BUF (-6.9)
  • 109. Kenny Britt, TEN (-9.7)

The last undefeated team in the NFL at 9-0, the Kansas City Chiefs could apparently still use an upgrade in the wide receiver department. (Dwayne Bowe will appear in a bit.) Note the effective scale, at this point in the season, ranges from a -9.7 at the bottom to a firm 20 at the top. The average PFF wide receiver grade is a 2.2, and the standard deviation is a 5.6. Brandon Marshall up in first is a full standard deviation in performance ahead of 6th best Pierre Garcon. No wonder Bears fans love him. Marshall also finds himself among the most paid wide receivers, 11th in the league at $8.956 million a year. Here are the Top 10 average annual salaries under contract this season4 (millions of dollars in parentheses):

  • 1. Calvin Johnson, DET ($18.813 million)
  • 2. Larry Fitzgerald, AZ ($15.75m)
  • 3. Mike Wallace, MIA ($12m)
  • 4. Dwayne Bowe, KC ($11.2m)
  • 5. Vincent Jackson, TB ($11.111m)
  • 6. Andre Johnson, HOU ($9.686m)
  • 7. Steve Smith, CAR ($9.438m)
  • 8. DeSean Jackson, PHI ($9.4m)
  • 9. Santonio Holmes, NYJ & Greg Jennings, MIN ($9m)

The two Johnsons are the only wide receivers tops of the league in both performance (so far) and pay. And yes, Mike Wallace is the Joe Flacco of wide receivers, the 3rd highest paid with the 4th worst performance. (Actually, this is more impressive than Flacco, since there are more than three times as many wide receivers as quarterbacks.) Unsurprisingly we see no teams doubling up here. Even in the NFL, you can’t afford to. Only 7 teams spend more than $20 million on all their wide receivers5, with 24 spending less than the Lions spend on Johnson alone.  And here are the least paid wide receivers, who’ve played at least 25% of their teams’ snaps this season:

  • 100. Kenbrell Thompkins, NE (0.496m)
  • 101. Marlon Brown, BAL (0.495m)
  • 102. Riley Cooper, PHI (0.49m)
  • 103. Rod Streater, OAK (0.483m)
  • 104. Cole Beaseley, DAL (0.481m)
  • 105. Jarrett Boykin, GB & Jermaine Kearse, SEA (0.48m)
  • 107. Doug Baldwin, SEA (0.47m)
  • 108. Drew Davis, ATL (0.435m)
  • 109. Mike Brown, JAX (0.398m)

Doug Baldwin? Really? Yup, it’s looking like another top contract will belong to the Seahawks. (SPOILER ALERT: It does.) 106 wide receivers make more than Baldwin, but only 8 have done more on the field this season. Goodness. Not bad for a kid who went undrafted out of Stanford. Looking at the whole field, the average annual salary of all these wide receivers is $3.258 million, with a slightly larger standard deviation of $3.61 million. Calvin Johnson makes nearly a full SD more than #2 Larry Fitzgerald, who in turn makes more than a full SD more than #3 Mike Wallace. Obviously, it’s not nearly so spread out at the bottom.

Again, for contract quality, we look at where the player ranks in pay and performance relative to the average among his peers, using standard deviations. CQ = #SDs above/below the average grade – #SDs above/below the average salary. Positive is good for the front office. Negative is bad. Zero suggests a player’s performance is worth exactly how well he’s played (theoretically). Without further adieu, here are the 10 best wide receiver contract so far this season (contract quality in parentheses):

  • 1. Doug Baldwin, SEA (2.26)
  • 2. Marvin Jones, CIN (2.21)
  • 3. Jordy Nelson, GB (2.2)
  • 4. Demaryius Thomas, DEN (2.12)
  • 5. Golden Tate, SEA (1.87)
  • 6. Keenan Allen, SD (1.85)
  • 7. Alshon Jeffery, CHI (1.74)
  • 8. Jerricho Cotchery, PIT (1.65)
  • 9. Brandon Marshall, CHI (1.59)
  • 10. Randall Cobb, GB (1.47)

Another obligatory ESPM congratulations to Seattle Seahawks General Manager John Schneider! Two in the top five for Seattle, to go with quarterback contract quality leader Russell Wilson, puts together a sound passing attack for a very good price. Interesting that while no team has two Top 10 most expensive contracts on its roster, and only Denver has two Top 10 performing wide receivers on their roster, Seattle, Chicago, and Green Bay each have two of the best wide receiver contracts in the NFL. (And Green Bay has a third wide receiver, Jarrett Boykin, at 15th in the league with a 1.10 contract quality. Wow.) Now, the Bottom 10:

  • 100. Calvin Johnson, DET (-1.7)
  • 101. Kenny Britt, TEN (-1.71)
  • 102. Greg Jennings, MIN (-1.92)
  • 103. Miles Austin, DAL (-1.94)
  • 104. Roddy White, ATL (-1.98)
  • 105. Mike Williams, TB (-2.14)
  • 106. Dwayne Bowe, KC (-2.35)
  • 107. Vincent Jackson, TB (-2.49)
  • 108. Larry Fitzgerald, ARZ (-2.81)
  • 109. Mike Wallace, MIA (-3.83)

Oh dear. Ohhhhh dear. Turns out, the five highest paid wide receivers in the league are some of the ten worst contracts. And Greg Jennings makes it a solid six of the ten highest paid to make the ugly contract list. Incidentally, this is Jennings first season with the Vikings, after seven with the… who was it? Oh right, the Green Bay Packers! The same Green Bay Packers with three of the best wide receiver contracts in the league. Hmmmm. Lots of times we hear about how a team just “can’t afford” to lose a player in free agency. But, maybe sometimes, someone ought to ask: “Can they afford not to?” The Packers said no to Jennings, and they’re certainly not regretting it.

That said, there is a lesson here. A pretty common one in life, and as in life, as in football: there is no simple “magic rule” that guarantees success. While many of the richest contracts are poor quality, some are worthwhile. Brandon Marshall is earning his 11th highest salary with the best play in the league. Antonio Brown, 15th in performance, 18th in pay, is good for the 14th best contract among all 109 wide receivers. Andre Johnson (3rd, 6th, and 22nd), Julio Jones (19th, 32nd, 23rd), Wes Welker (8th, 23rd, 29th), and Pierre Garcon (6th, 12th, 32nd) all enjoy lucrative contracts in the upper tier of the league, and have more than earned them with their play. And, while perhaps more difficult, teams can buy cheap and still not get their money’s worth. Ace Sanders (94th, 84th, 69th), Nick Toon (97th, 89th, 73rd), Brice Butler (93rd, 94th, 66th), Kenbrell Thompkins (89th, 100th, 60th), and Marlon Brown (99th, 101st, 71st) are all paid less than $0.7 million a year, yet have managed to under-perform their salaries. They haven’t “lost” their teams nearly as much money, but a loss is still a loss. The competitive nature of the NFL makes me think that if you asked a general manager “Would you care to save a few extra hundred thousand dollars this season?”, he would say “Yes.”


  1. His performance and pay were both below average, so his contract quality would probably have been middling to poor, but not terrible. 
  2. In a test of the “Greater Fool” theory, Flynn went to Oakland, was subsequently released, signed with the Bills, again released, and is currently back with the Green Bay Packers after injuries to Aaron Rodgers and Seneca Wallace, though presumably still behind other backup Scott Tolzien. 
  3. More than three times as many wide receivers than quarterbacks means longer lists. 
  4. With many thanks to Spotrac.com
  5. DET spends $27.262 million on WRs; CHI $25.987; MIA $22.998; AZ $21.725; WAS $21.313; SEA $21.236; and TB $20.809 
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