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Way back in early September, before the NFL season began, Robert Mays and Bill Barnwell, staff writers at Grantland, ran a podcast in which they made numerous preseason predictions for fun. At the suggestion of one of them during the podcast, I took down their predictions, but then never sent them in to Grantland, and the notes have just been sitting in my Gmail drafts folder for months. No more!

While Bill Barnwell posted an excellent feature about the Super Bowl champion Seattle Seahawks, quarterback Russell Wilson, and the best contract in football (click here for my own analysis of the best contracts in football; Wilson is certainly up there), I thought it would be fun to analyze Barnwell, and Mays, to determine who made the better predictions this season. Is one more expert than the other? Check it out!

Player Props

Adrian Peterson: 5.1 Yards per Carry
Barnwell: Under
Mays: Over
Result: Under (4.5)

Say it with me now: regression to the mean. Not just to the league average (about four yards) but to Peterson’s own. Peterson has now had two seasons over 5.1 yards per carry and five seasons under it; among those five seasons, even the highest clip is only 4.8.

J.J. Watt: 15.5 Sacks
Mays: Under
Barnwell: Under
Result: Under (10.5)

Regression scores again! J.J. Watt still put up the best season of any defensive player (highest graded by Pro Football Focus on the season), but 16 sacks is a lot for anyone, especially a 3-4 defensive end whose primary job is not rushing the passer.

John Abraham: 8.5 Sacks
Barnwell: Under
Mays: Under
Result: Over (11.5)

A surprisingly impressive season from the 35-year-old.

Andrew Luck: 4,200 Passing Yards
Mays: Over
Barnwell: No bet, agrees with logic, no strong feelings.
Result: Under (3,822)

This result is even more impressive given that Trent Richardson was so completely ineffective (averaged 2.9 yards per carry) this season.

Andrew Luck: 15.5 Interceptions
Barnwell: Over
Mays: Agree? Recognizes similar logic.
Result: Under (9)

The kid is good. Although he did rank 20th among 27 quarterbacks in accuracy percentage (per PFF). Maybe something to consider next season.

Geno Atkins: 9.5 Sacks
Mays: Over
Barnwell: Under
Result: Under (6)

Atkins went down on Halloween against the Dolphins and that was it for his season. He only played in seven games. Injury risk is always something to consider.

Greg Olsen: 775.5 Receiving Yards
Barnwell: Under
Mays: Under
Result: Over (816)

Curious. Prior to 2012, Olsen’s most receiving yards in a season were his 612 with the Bears in 2009. But with Cam Newton he has now gone over 800 twice.

Matt Forte: 1,000.5 Rushing Yards
Mays: Over
Barnwell: Under, later SWITCHES to Over
Result: Over (1,339)

A wise move as Forte put together his first back-to-back 1,000-plus yard seasons. Staying healthy, and amassing the most rushing attempts since his rookie season, certainly helped.

Charles Tillman: 4.5 Forced Fumbles
Barnwell: Under
Mays: No bet (“HOW DARE YOU?”)
Result: Under (3)

Injury cashes Barnwell in again, as Tillman went down only halfway through the season. But this merely underscores that a lot of things have to go right for a corner, or really anyone, to force five fumbles in one season.

Doug Martin: 8.5 Touchdowns
Mays: Over
Barnwell: Pressed by Mays, only says “8 or 9”
Result: Under (1)
Poor Doug Martin’s fate was sealed the instant I drafted him in the first round of my fantasy draft, as he went out for the season in Week 6. Still, a low total nonetheless.
Aaron Rodgers: 38.5 Touchdown Passes
Barnwell: Under
Mays: Over
Result: Under (17)

More injuries, more problems for the over bets. Although in the eight games in which he played more than a few snaps, he only threw 17, not quite on pace for over. Presumably offensive rookie of the year running back Eddie Lacy had something to do with this.

Robert Griffin III: 575.5 Rushing Yards
Mays: Over
Barnwell: Over
Result: Under (489)
Washington never seemed to recover from their opening day track meet against the Eagles, and Griffin missing the final three games while “sort-of-injured-but-healthy-enough-to-play-but-what’s-the-point” was pretty hard to predict.
Jason Babin: 9.5 Sacks
Barnwell: Under (Barnwell’s lock)
Mays: Under
Result: Under (7.5)

Barnwell’s lock comes through, although this must have been a little exciting as Babin came on and posted 5.5 in December.

Brian Orakpo: 7.5 Sacks
Mays: Over (Mays’ lock)
Barnwell: Over
Result: Over (10)

Mays’ lock comes through, as Orakpo went over on December 1st against the New York Giants. He is pretty good when healthy, it would seem.

Alex Smith: 3,350 Passing Yards
Barnwell: Over
Mays: Over
Result: Under (3,313)

This was about Andy Reid being allergic to running backs in Philadelphia and Alex Smith having Dwayne Bowe to throw to, and, uh, hold that thought…

***BONUS BET***
Dwayne Bowe: 1,000.5 Receiving Yards
Mays: Over
Barnwell: Over
Result: Under (673)

Ouch.

Dez Bryant: 92.5 Catches
Mays: Over
Barnwell: Under
Result: Over (93)

Ladies and gentlemen, put your hands together for Grantland staff writer Robert Mays! Really must have sweat it too, with Bryant needing eight receptions in Week 17 against Philadelphia, without Kyle Orton at quarterback. But he eked it out!

Danny Amendola: 950.5 Receiving Yards
Barnwell: Over
Mays: Over
Result: Under (633)

Ouch. Injuries, injuries, injuries… Amendola missed four games.

Tavon Austin: 7.5 Touchdowns (Rushing, Receiving, & Return)
Mays: Over
Barnwell: Over
Result: Under (6)

To be fair, Austin would likely have gone over if it had not taken the Rams coaching staff to realize that Austin was on their team (and/or the Rams special teams return unit had not felt the need to hold or block in the back on approximately 371% of their returns).

Richard Sherman: 4.5 Interceptions
Barnwell: Under
Mays: Under
Result: Over (8)

An incredible result. Among corners who played half or more of their teams’ snaps, Sherman was targeted only 58 times in the regular season, the sixth-fewest. He led the league with eight interceptions. Sherman grabbed a pick every 7.25 throws into his coverage, easily tops in the league. Goodness.

***Mays’ Prediction***
Jonathan Banks leads the league in interceptions.

Very, very difficult to predict; Banks finished tied for 15th with several players, having recorded three interceptions.

Chris Long: 10 sacks
Mays: Over
Barnwell: Over
Result: Under (8.5)

Maybe next year; PFF awarded him 10 sacks, as they do not punish players by awarding only a half-sack when another teammate also gets to the quarterback. Also Long’s 46 quarterback hurries were tied for fourth at his position this season. He generated pressure, but sometimes it takes a little luck (or a bad opponent quarterback) to get the sack numbers.

Josh Freeman: 16.5 Interceptions
Barnwell: Under
Mays: Under
Result: Under (4)

What a year for Freeman, in all the bad ways. Ugh. And he actually was right about on pace, throwing one in every game he played.

Clay Mathews: 11.5 Sacks
Mays: Over
Barnwell: Over
Result: Under (7.5)

Injuries, oh the injuries…

Russell Wilson: 3,400 Passing Yards
Barnwell: Over
Mays: No bet
Result: Under (3,357)

Yeeesh. Perhaps if Percy Harvin had played more than 40 snaps…

Division Winners & Playoffs

First Pick in 2014 Draft
Barnwell: OAK
Mays: OAK
Result: HOU
AFC East
Barnwell: NE
Mays: NE
Result: NE
AFC North
Barnwell: PIT
Mays: CIN (PIT last!)
Result: CIN (PIT actually 2nd, 8-8 and ahead of the 8-8 Ravens)
AFC South
Barnwell: HOU
Mays: HOU
Result: IND
AFC West
Barnwell: KC
Mays: DEN
Result: DEN
AFC Wildcards
Barnwell: DEN, CIN
Mays: KC, BAL
Result: KC, SD
NFC East
Barnwell: NYG
Mays: DAL
Result: PHI
NFC North
Barnwell: GB
Mays: GB
Result: GB
NFC South
Barnwell: TB
Mays: TB
Result: CAR
NFC West
Barnwell: SEA
Mays: SF
Result: SEA
NFC Wildcards
Barnwell: SF, DET
Mays: CHI, SEA
Result: SF, NO
AFC Champion
Barnwell: DEN
Mays: DEN
Result: DEN
NFC Champion
Barnwell: SEA
Mays: GB
Result: SEA
Super Bowl Champion
Barnwell: SEA
Mays: DEN
Result: SEA

Ladies and gentlemen, I give you Grantland staff writer Bill Barnwell! Correctly predicting BOTH conference champions AND the Super Bowl champions! Barnwell would be the very first one to tell you that this result is due to his prodigious SKILL and not at all due to luck…oh right, he is Bill Barnwell. He is not foolish.

Player & Coach Statistical Leaders and Awards

Defensive Player of the Year
Barnwell: Clay Matthews
Mays: Geno Atkins (15 sacks!)
Result: Luke Kuechly

To be fair, Kuechly totally did not deserve this award at all. (Maybe more on that later.) But then with injuries, neither did their selections.

Passing Leader
Barnwell: Peyton Manning
Mays: Andrew Luck
Result: Peyton Manning
Rushing Leader
Barnwell: Trent Richardson
Mays: LeSean McCoy
Result: LeSean McCoy
Receiving Leader
Barnwell: Calvin Johnson
Mays: Dez Bryant
Result: Josh Gordon (in only 14 games!)
First Pick in 2014 Draft
Barnwell: Jadeveon Clowney
Mays: Teddy Bridgewater
Result: TBD
Offensive Rookie of the Year
Barnwell: Tavon Austin
Mays: Eddie Lacey
Result: Eddie Lacey
Defensive Rookie of the Year
Barnwell: Kenny Vaccaro
Mays: Alec Ogletree
Result: Sheldon Richardson
Coach of the Year
Barnwell: Andy Reid
Mays: Greg Schiano
Result: “Riverboat” Ron Rivera
Most Valuable Player
Barnwell: Russell Wilson
Mays: Aaron Rodgers
Result: Peyton Manning

Final Scorecards

Overall, Mr. Mays went a respectable 15/44, 34% on his picks. In pure props he was 6/20, while going 2/9 on individual awards and statistics and 7/15 on team predictions. Mr. Barnwell edged him slightly, going 17/46, 37%. Barnwell went 9/22 on player props, 1/9 on individual awards and statistics, and 7/15 on team predictions. When both Mays and Barnwell agreed, they went 8/21, 38%; 5/15 on props, 0/1 on awards, and 3/5 on teams.

The lesson? Predictions are not easy, and your gut feeling will not take you very far, even if you know a lot. Consider that among their player predictions, designed to have a 50-50 chance, both Mays and Barnwell did worse than a coin flip. This is not because they do not know about football (they know a great deal), but because this stuff is hard, and luck plays a bigger role than anything else. Nonetheless, one can see why a comprehensive examination of numbers might come in handy.

If you see a supposed pundit make a prediction, remember to think twice before buying in. Okay, that is not news. But remember to ALWAYS think twice (and a third time, a fourth, etc), even when the pundits are quite knowledgeable, even when the predictors tell a story that you find logically sound, and perhaps most importantly, even when you already agree with them (and especially when they are not being 100% serious, à la Mays and Barnwell). Or at the very least, think twice before you put any money down.

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 

First off I’d like to dedicate this column to Bill Barnwell, writer at Grantland, who has been pushing a nomentum agenda heavily in his columns this NFL season. After “momentum” came up a couple of times in my first Sh*t Announcers Say post, I thought I’d touch upon it a bit more, in a slightly different light. I’m not going to offer a bunch of numbers; plenty of people have already done that.1 No, I’m going to look at momentum theoretically.2

We sports fans have a lot of theories. We love our theories. We have theories for why that $*&%bird referee made a certain call when he did, what enabled Lebron James to finally win a championship (two of them, actually), and how the Fear the Beard movement propelled the Red Sox to their third world series title in ten years. Milorad Cavic and many others have their theories about Michael Phelps’ touch-out in the 2008 100-meter men’s butterfly Olympic final. Some theories even rise to such prominence that they get names, such as Dave Cirilli’s Ewing Theory. Personally, I have theories about which articles I read covering the 49ers during the week will help them play the best on Sunday3, and when they scored twice to take a 20-14 lead over the Saints in the fourth quarter last week, just after a friend had come over for a little bit, I almost begged him not to leave his seat on the couch.4 We see things, and we try to explain them. Conceptually, it’s like a science. We sports fans are just a little more fanatical about it, that’s all.

Unfortunately, that’s the problem. Struggling for objectivity is boring and lame, but it isn’t like science: It is science! When you watch a game and the momentum shifts in your team’s favor, and you go on to win, it sticks in your mind. “The game totally hinged on that play!” we say. “After that, we knew they couldn’t stop us. You could see it.” When you watch a game and the momentum shifts in your team’s favor, but they go on to lose (or the “momentum” shifts back), it’s forgotten or dismissed. “We had something going, but the game got out of hand.” But just because a team’s momentum didn’t come through once doesn’t mean it’s not responsible for all the times they actually won. After all, theoretically it makes sense, right? That team was in the zone! After that play they knew they were going to win. It was a huge confidence boost, and they put the other guys back on their heels.5

Forget sports (just for a second, don’t worry) and think about a coin flip. Say it’s a fair coin, and you flip heads two times in a row. Does the coin have momentum? Is the coin more likely to come up heads on the next flip? You’re smart, you know the answer is no. It’s just a coin! A fair coin, at that. It’ll come up heads 50% of the time and tails 50% of the time. Even if the coin wasn’t fair, there still wouldn’t be any momentum. If you knew a coin flipped heads 75% of the time, but while flipping there was a run of three tails in a row, would you next bet on heads or tails? Heads, of course. It comes up 75% of the time.6 If you think momentum plays a role in a coin flip, you may be beyond help. But if you agree it doesn’t, you’ve got to agree that momentum plays no role in sports as well.

BUT WE’RE TALKING ABOUT REAL PEOPLE, PLAYING SPORTS, NOT A STUPID COIN FLIP! Well…

In statistics (like, 101, don’t worry, it’s super simple) we say events are either independent or dependent. Coin flips are independent of each other. The outcome of one event does not change the probabilities of the outcomes of any of the others. Two events that would be dependent are whether I wear a rain jacket and whether or not it is raining. The probability that I wear a rain jacket increases dramatically when it is raining.

So sports. Does the outcome of a certain play, or game, or season, change the probabilities of the outcomes of other plays, or games, or seasons? The 49ers just gained a first down. Are they now more (or less) likely to gain another first down than they were before gaining the original first down? Or, the 49ers just won three games. Are they now more (or less) likely to win the fourth game than they would be otherwise? No and no. No! This is not to say the 49ers (and their opponents) are static. The 49ers may have figured out the other team’s defense. That would improve their chances of gaining a first down. They may have gotten better at playing football. That would improve their chances of winning. Those improvements may be reflected in outcomes (gaining a first down, winning a game), as outcomes are certainly dependent on those improvements. But those improvements are not “momentum”! Future outcomes are not the product of prior ones; they’re a product of what the team is doing. The outcomes themselves are independent of one another.

BUT, you say, WHAT THE TEAM IS DOING DEPENDS ON THEIR PREVIOUS OUTCOMES! Sure, teams respond to what’s happened, and may change their strategy, use different players, employ different techniques, etc. And that’s exactly my point. It’s that process, of evaluating performance and making changes, that drives outcomes.

*Hey, over here! Say we have a fair coin that flips heads 50% of the time. We’re having a coin flipping contest (whoo!) and at halftime, we switch to a weighted coin that flips heads 75% of the time. In the second half we flip heads twice in a row. Are we more likely to flip heads on our third flip than we were on our flips in the first half? Yes. Is it because we flipped heads the last two times? No. It’s because this coin comes up heads 25% more often. The probability of flipping heads was 50%, but now it’s 75%, and we’re seeing the difference.

*Say the 49ers offense scores a touchdown against the Rams (whom we7 play this weekend) 50% of the time. At the end of the first half Robert Quinn is injured, also the 49ers have discovered Alec Ogletree and JoLonn Dunbar get out of position on screen passes. These changes improve the 49ers chances of scoring a touchdown to 75%. They come out of half time and score touchdowns on their first two possessions. Are the 49ers more likely to score on their third possession than they were on their possessions in the first half? Yes. Is it because they scored on their last two possessions? No. It’s because Robert Quinn is injured and they are now exploiting Ogletree’s and Dunbar’s weaknesses! The probability of scoring a touchdown was 50%, but now it’s 75%, and we’re seeing the difference.

That’s all football is. Theoretically, that’s all sports are: a coin flip, and the weight of the coin is always changing. Players practice (and take performance enhancing drugs) to weight the coin in their favor. Head coaches spend hours reviewing tape and game planning to weight the coin in their favor. Peyton Manning makes adjustments at the line of scrimmage to weight the coin in his favor. There are no guarantees, and there are a lot of coins. The probability of Dustin Pedroia getting on base coin. The Lebron James free throw coin. The Landon Donovan penalty kick coin. The Jim Harbaugh challenge coin. There are a lot of coins, and they all contribute to The Coin, the probability of winning coin. It could be weighted heavily towards your opponent, as was the 2008 Detroit Lions coin, or strongly in your favor, as was the 2007 New England Patriots coin. But no matter what you do (as those same Patriots would be sure to remind you), the outcome of The Coin is never 100% certain.

So the game starts and maybe the 49ers will score a touchdown 30% of the time against the Rams. After one drive the Rams change their coverage, weighting the coin in their favor, down to 28%. The 49ers try a new wrinkle, weighting the coin in their favor to 31%. Vernon Davis misses a couple drives with a cramp, weighting the coin down to 22%. So it goes. On and on. And if you think looking at the numbers like that takes the fun out of sports, get some glasses, because you’re seeing sports all wrong. Those changes– the freak occurrences, the constant adjustments in preparation and strategy– are what make sports great. And fun. Win or lose.


  1. Again, to get you started, check out the Hot-Hand fallacy. Also a more friendly Bill Barnwell Grantland piece. And an even friendlier New York Times piece
  2. Jeez, it’s almost like I went to a college where a bunch of people wore “That’s all well and good in practice… but how does it work in theory?” t-shirts. Oh wait, I did! Long live Thompson House, and our blessed cake business! 
  3. Surely reading all of Matt Maiocco’s content before kickoff demonstrates my love as a fan, and will be rewarded? Though actually, I didn’t get to all of it before they beat Washington on Monday. But whatever. 
  4. He did, and the 49ers never scored again, losing 23-20. SEE WHAT I HAVE TO PUT UP WITH? 
  5. They made a statement! Changed the complexion of the game. Dictated the game. Took the driver’s seat. Could smell blood.  Answered the call. Started to make some noise. Fired on all cylinders. Hit their stride. Hit a turning point. Turned the corner. Turned the tide. Set the tone. Raised the bar. Played with swagger. Played with a sense of urgency. Were on a mission. Were off to the races. Made a stand up play. Made a gutsy play. Made a textbook play. I could go on… 
  6. An obligatory link to the Gambler’s Fallacy. Three tails in a row doesn’t make heads any more likely either. 
  7. Yes, I say “we” frequently when talking about the team I root for, in this case the San Francisco 49ers. My San Francisco 49ers. Who are (obviously) Jed York’s San Francisco 49ers. Get over it. 

I love sports, and of course I love sports announcing. Though a San Francisco Giants fan1, I’ll definitely watch any west coast Dodger game just to enjoy the magnificence that is Vin Scully.2 And where would I be in the Olympics without Bob Costas guiding me along in the studio? I’ve never had quite as much love for any football game commentators, with the possible exception of Pat Summerall and John Madden. Generally, I feel they do a good job– it actually isn’t easy to sit down for three hours and talk during a football game while being appealing to millions of viewers– but they say many silly things. Or things that are just wrong. I find this most aggravating when it’s the “expert” color commentator, guaranteed to be a former player or coach, whom I feel people usually, often wrongly, trust. While they may offer some fascinating insights, they may also offer some terrible ones. It is rare that I watch a game and at no point think to myself “That’s wrong,” or “That doesn’t make any sense.” Yesterday as usual I started watching football at noon, and unusually finished at 11:30 pm thanks to an overtime thriller in Foxborough. While not a comprehensive list, I tried to make a note when a commentator said something silly.3 Here we go.

With the Ravens trailing the Jets 3-0 and 4:10 remaining in the first quarter, Ray Rice gained two yards on a 2nd&1 from the Jet 28.

CBS play-by-play man Greg Gumbel remarked:

Ray has a little bit of a chip on his shoulder.

And color commentator Dan Dierdorf, 13 year NFL veteran, five-time First-team All-Pro selection, replied in his infinite wisdom:

Well he did, an- and because the criticism was all on him, when in reality I saw a whole bunch of tape on these guys where there were no holes whatsoever. Ray Rice was being met at the line of scrimmage.

At the moment Ray Rice has the worst Pro Football Focus grade4 among all running backs in the NFL, and it’s not close. With a -0.2 in the passing game, a -11.6 in the run game, a -3.1 as a blocker, and a -0.5 in penalties, he totals a -15.4. The next worst running back, C.J. Spiller, checks in with a -11.2, and third worst, Darren McFadden, registers a -7.9. PFF’s “Elusive Rating” is a statistic designed to gauge how well a running back evades tacklers, controlling for the quality of his blocking. Ray Rice is dead last among the 50 running backs with enough snaps to qualify with a 7.0; tops is Marshawn Lynch with a 72.7. (The rating roughly scales from 1-100.) So I know Dan Dierdof “saw a whole bunch of tape” and I believe him. But a whole bunch of guys at PFF saw all of the tape, and firmly conclude that Ray Rice has played abysmally this season. So if you caught a few Ravens’ games and heard Dierdof’s remarks and thought “Oh, it isn’t on Ray Rice, it’s the people around him,” rest assured: it is on Ray Rice. He has truly earned the second worst running back contract in football. Which is to say, he has not earned his contract at all.

With the Steelers leading the Browns 10-3 on a 2nd&10 from the Brown 14 with 20 seconds remaining in the second quarter, Ben Roethlisberger’s pass for Antonio Brown in the end zone was broken up by Joe Haden.

Solomon Wilcots, six year NFL veteran and color commentator of CBS, broke down what happened:

This is a great play by Joe Haden. Watch him knife in underneath. He understands that down around the goal line, look at that play! You have to get between the quarterback and the receiver. He allowed himself to slip underneath, he had great position.

It’s great, except CBS is showing the replay as Wilcots is saying this, the replay in which Haden very clearly grabs Brown’s jersey with his left hand and holds on for a good moment. It wasn’t blatant pass interference, but it was pass interference. It’s one thing for the officials to miss it live; it’s another for Haden to miss it during the slow motion replay, as he remarks what a terrific play it was by Haden. And even though this is the type of penalty that may not be called most of the time, Wilcots doesn’t acknowledge that Haden grabbed Brown at all. Fans at home, Joe Haden is a very good corner in the National Football League, but that doesn’t always mean “slipping underneath”. Sometimes it may mean “gets overly physical without getting whistled”.

Down 10-3 at home after an incomplete Case Keenum pass on 3rd&goal from the Jaguar two yard line with 8:34 remaining in the third quarter, the Texans took their offense off the field to kick a field goal.

Said CBS color commentator Steve Tasker, 13 year veteran, seven-time All-Pro:

And that’s going to force the field goal, the fans aren’t happy about it but it’s the right move.

Of course if you’ve ever heard of Brian Burke, or know the difference between actual good strategy in the NFL and the still-prevailing conventional wisdom, you know that’s the wrong call. A quick rundown of the numbers: on average going for it in that situation produces a win probability of 0.38; kicking a field goal produces a win probability of 0.31.  From up in the press box Kubiak’s decision cost his team a 7% chance of winning the game.5 For going for it to be worthwhile in this situation, the Texans need to convert only 26% of the time. It’s two yards, and lest we forget, THEY’RE PLAYING THE JACKSONVILLE JAGUARS! For Tasker to dismiss this as “the right move” is just… how can he… it’s so obviously… RAGE!!! Furious George, L.O.L. I didn’t watch the end of the game, which the Texans went on to lose 13-6, but I bet at no point during the Texans’ final drive6 did Tasker point out “HEY, the would only need a field goal right now if they had gone for it on fourth down earlier and scored a touchdown, as was quite likely given that they only had two yards to go. And as it is, they STILL need to score a touchdown and are in a situation where they have to go for it on fourth down anyway, even if it’s way more than two yards to go. Jeez, I guess I was just saying what I always say and talking out of my @#$ earlier, huh Bill?” Of course if he did point that out, then, well, tip of the hat to him. But I kinda doubt it.

On a 1st&10 with 8:22 remaining in the 3rd quarter, the Packers, down 20-7 to the Vikings, replaced Scott Tolzien with Matt Flynn, who promptly completed his first pass for nine yards.

Fox play-by-play announcer Kevin Burkhardt stated:

A completion. And it’s got this crowd back in the game.

Color commentator and 15 year NFL veteran, four-time All-Pro safety John Lynch chimed in:

He goes to Matt Flynn and they get a little momentum right away.

Whether or not you “believe” in momentum in sports or not, you probably know there is no factual evidence for it if you feel strongly about it one way or the other. Bill Barnwell, of the great Grantland.com, has sort of made “Nomentum” a thing this year, bringing facts a bit further into the mainstream. I’ll only say this: what do you mean when you refer to “momentum”, exactly? Lynch said they got “a little momentum right away.” Scott Tolzien, just benched, had pulled off two nifty moves on a six yard touchdown run earlier in the game. Did that play accrue momentum? And if so, it must have disappeared, since Tolzien was benched? So was the momentum from this pass from Flynn more noteworthy than any momentum Tolzien had gained, an indication that the Packers’ fortunes would be reversed and cause for the fans to rejoice? I, uhh, kinda doubt it. On the next play James Starks ran for 34 yards, setting up 1st&10 from the Viking 37. The momentum must really be going now, right!?! Then Starks ran for two yards, Flynn threw an incomplete pass, and Flynn threw a pass for a loss of five yards, leaving the Packers with 4th&13 from the Vikings 40. They punted. Tragically neither Burkhardt nor Lynch explained where that momentum had gone, and what impact, if any, it had on the game.

Up 24-3 facing 3rd&1 from the Colt 45 with 4:13 remaining in the 2nd quarter, the Cardinals’ Andre Ellington was stuffed for a loss of two.

After the play, CBS color commentator Dan Fouts, 15 year NFL veteran and two-time First-team All-Pro, praised the Colts for the stop, saying:

It looked like the Colts- er, the Cardinals had momentum.

What a curious statement! It LOOKED like the Cardinals had the momentum. But in fact, the Colts now have the momentum? The Cardinals had the momentum because they were up by three touchdowns at home and driving in their opponent’s territory? But then, in one fell swoop, the Colts got a stop and now they have the momentum? Or some momentum? The Cardinals have less momentum now? WHAT DOES IT ALL MEAN, DAN??? You know, I think I know. I was never the quarterback for any football team, let alone the San Diego Chargers, and I’m not in the NFL Hall of Fame, but hear me out: “momentum” is when a team improves their situation, relative to the previous situation. And it gets thrown around for a variety of situation types: momentum accrued from a winning streak (sometimes dating back to last season!), unanswered points, a string of good plays, or just one good play, or penalty, whatever. So far as I’m aware, there is A LOT of anecdotal, personal claims that such “momentum” helps a team or player perform, but actually zero (scientific) evidence that it does. Certainly, that’s the case in other sports7, and given the fickle nature of momentum’s tangible effects on performance, I sure don’t see a case otherwise.

On 4th&4 down 27-3 with 11:14 left in the third quarter, Andrew Luck’s pass from the Cardinal 36 was batted into the air and nearly intercepted on the Cardinal 20 before hitting the turf.

Fouts pointed out:

Well they’re better off not catching that ball.

And good for him, it’s a good point and he is totally right. On 4th down, unless there’s a good run back opportunity, the defense improves field position by batting the ball down instead of catching it. And then play-by-play man Ian Eagle chimed in:

It doesn’t matter other than the yardage. So you can pad your stats as a defensive player, but you actually are going to benefit if it’s incomplete.

Eagle sort hits on the right point (after Fouts brought it up), but uhhh… “It doesn’t matter other than the yardage”? Yeah, that’s what the teams are doing in football, trying to gain yards and get to the end zone. The yardage matters! According to Advanced NFL Stats‘ Win Probability Calculator, in this situation the yardage matters to the tune of a single percent chance of winning. Starting on their 36, the Cardinals had a win probability of 95%; starting on their 20, it would have been 94%. That’s not a lot, but disregarding yards in a football game, especially 16 of them (nearly a fifth of the field), is pretty silly.

With 4:52 left in the fourth quarter of Sunday Night Football, down 31-24, Wes Welker dropped a pass over the middle on a 1st&10 from the Patriot 36.

Cris Collinsworth, eight year NFL veteran and three-time Second-team All-Pro selection, wondered of Welker’s drop:

How many times do you see that?

Fortunately, NBC play-by-play caller Al Michaels jumped right in:

Once too many for some New England fans.

Fans who don’t obsess over the numbers but just enjoy watching football (God bless ’em) may well think Wes Welker has terrific hands, because nearly without fail, every time he drops a pass, whoever is announcing the game remarks “Oh, a rare drop from Wes Welker!” Except Welker’s drops are hardly rare, so over the course of a season it is a pretty regular occurrence to hear a rare Wes Welker drop proclaimed on television. Going as far back as PFF data goes, through the 2008 season, Welker’s drop rate is the following (league-wide rank among players with 25% of their team’s targets or more in parentheses):

  • 2008: 6.03% (19th of 81)
  • 2009: 4.65% (24th of 101)
  • 2010: 13.13% (70th of 89)
  • 2011: 9.63% (48th of 95)
  • 2012: 11.28% (58th of 82)
  • 2013: 9.72% (54th of 97)

Welker certainly doesn’t have the worst hands in the NFL, but he’s hardly elite. Larry Fitzgerald, for example, finished 13th or higher all of those seasons except 2012, when he finished 24th. To answer Collinsworth’s question, counting 2013, the last four seasons Welker has dropped 9% or more of his catchable passes. Counting last night, so far in 2013 he’s dropped seven passes; only seven players have dropped more than him this season. Kudos to Michaels for hinting to Collinsworth that, in fact, a Wes Welker drop is not all that unusual.

Lastly, I just thought I’d remind everyone who the Top 10 quarterbacks have been in fantasy football this week, pending MNF (standard points in parentheses):

  • 1. Philip Rivers (27.78)
  • 2. Tom Brady (24.76)
  • 3. Ryan Fitzpatrick (24.4)
  • 4. Alex Smith (21.46)
  • 5. Carson Palmer (20.56)
  • 6. Cam Newton (20.06)
  • 7. Drew Brees (18.52)
  • 8. Josh McCown (18.48)
  • 9. Ryan Tannehill (18)
  • 10. Matthew Stafford (16.48)

Ryan Fitzpatrick, Alex Smith, Carson Palmer, and Josh McCown all cracked the Top 10. What is the world coming to? Although to be fair, yesterday at mid-afternoon Mike Glennon, Christian Ponder, Kellen Clemens, and bad quarterback superstar Brandon Weeden were also in the running. Mike Glennon actually scored more points (16.18) than Peyton Manning (13). I give up. Go 49ers!


  1. And also a Seattle Mariners fan. That Pacific Northwest life, being close to the homeland in Alaska. Incidentally my mother’s two favorite baseball teams are the Washington Nationals, where she grew up, and the Mariners, closest to where she lives now. They are the only two active Major League Baseball franchises that do not have a single appearance in the World Series. (Yes, even before when the Nationals were the Montreal Expos.) It’s a hard life. 
  2. Also, Vin Scully had the call for “The Catch”, so it’s even more okay. 
  3. How did I catch calls from so many different games? DirecTV’s NFL Red Zone Channel. God bless DirecTV’s NFL Red Zone Channel. 
  4. Among running backs who’ve played 25% or more of their team’s snaps. PFF has multiple analysts grade every player on every snap of every game. Click here to learn more about PFF’s grading system. 
  5. Poor Kubiak. His recent health scare is keeping him from the sidelines, and after losing to the Jaguars, at home, you’ve got to wonder if he’ll be coaching the Texans next season, or even at the end of this one. I only take issue with his chosen strategy in this case; I’m sure he’s a wonderful human being and I wish him and his family the best. 
  6. Which ended on a Case Keenum interception from the Jaguar 41. If the Texans had only needed a field goal to tie then, they might have squeaked it out. 
  7. See all scientific findings regarding “the hot hand”: http://en.wikipedia.org/wiki/Hot-hand_fallacy 
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