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NYT Fifth Down: Post-week 8

My post for the New York Times this week takes a look at the triumvirate of Mike Tannenbaum, Rex Ryan, and Mark Sanchez.

Rex Ryan was hired by Mike Tannenbaum on Jan. 19, 2009. Three months later, they traded up in the 2009 N.F.L. draft to acquire Mark Sanchez. Since that moment, the three of them — the general manager, the head coach and the franchise quarterback — have had their fates intertwined. When the Jets made the A.F.C. championship game in their first season together, they far exceeded expectations, reaching that level far sooner than expected.

In the following off-season, Tannenbaum became the toast of the N.F.L. as he acquired four veterans – Santonio Holmes, LaDainian Tomlinson, Jason Taylor, and Antonio Cromartie — to help put the Jets over the proverbial hump. In August, it was Ryan’s turn to steal the spotlight, as he became a national sensation and the coach everyone wanted to play for following his appearance on HBO’s “Hard Knocks.” During the season, it was Sanchez’s time to shine, as he led the Jets on game-winning drives in the fourth quarter or overtime in six different games, the highest number in the league. The Jets won 11 games and went back to the A.F.C. championship game, but again, were stuck at the Super Bowl’s doorstep.

That was the high-water mark of the Tannenbaum-Ryan-Sanchez era. The Jets regressed to 8-8 last season and with a 3-5 record in 2012, appear to be continuing in a downward spiral. With Tannenbaum, Ryan, and Sanchez forever linked, the question the Jets will have to answer at the end of the season is whether all — or any — of them are the right men to take the Jets back to the Super Bowl.

The Quarterback

Statistically, Sanchez has been a disappointment his entire career with the Jets. On the field, he has struggled with reading defenses and throwing accurate passes, and as a result, he is ranked below the league average in completion percentage and yards per attempt in each of his four seasons in the N.F.L. Only 18 quarterbacks in N.F.L. history have ranked below league average in those categories while playing for the same team in three consecutive years. Perhaps surprisingly, all but three — Joe Ferguson, Mark Malone, and an aging Marc Bulger — returned to the same team for a fourth season.

Of the remaining 15, one was Phil Simms, who tore his knee in the 1982 preseason, ending his streak of mediocre play. It wasn’t until he turned 30 that Simms had his first statistically solid season in 1985. David Woodley returned to Miami but lost his job to Dan Marino. Kyle Boller went back to Baltimore, but Steve McNair was acquired to replace him. Sanchez and Matt Cassel each received a fourth year in 2012 to prove themselves.

That leaves 10 quarterbacks who had three straight years of below average play in both yards per attempt and completion percentage, and were brought back by their team and remained as starters. Five quarterbacks — Donovan McNabb, Tobin Rote, Jim Hart, John Elway, and Drew Bledsoe — responded with above-average seasons in their fourth year in at least one of the two categories.

The other five? All again finished below average in the two categories for a fourth straight season. Mike Phipps in Cleveland, Rick Mirer in Seattle, Trent Dilfer in Tampa Bay and Joey Harrington in Detroit were the first four; the fifth was Eli Manning. I excluded Manning’s rookie season because he did not have enough pass attempts to qualify, but technically, he finished below average in both completion percentage and yards per attempt in each of the first five seasons of his career.

Sanchez currently ranks 33rd in completion percentage and 31st in yards per attempt, so absent Peyton Manning wearing his jersey for the rest of the year, Sanchez is going to finish below average for the fourth straight season in both categories. In Kansas City, Matt Cassel may match his streak, although his days with the Chiefs are numbered.

Can the Jets justify starting Sanchez in Year 5? If previous examples are considered, it’s doubtful. Mike Phipps, like Sanchez, was a top-five pick a franchise gambled on. In fact, Cleveland traded the future Hall of Fame wide receiver Paul Warfield to Miami to acquire Phipps, so the Browns were very hesitant to admit their mistake. In his fifth year, Phipps entered the season as the starter but an injury in the season opener against the Jets allowed Brian Sipe to take the job. Mirer was also a top-five pick, but after his fourth year, the Seahawks traded him to the Bears. Somehow, they were able to package him with a fourth-round pick for Chicago’s first-round selection. Tampa Bay, a team that was able to win despite its poor quarterback play because of a great defense, kept Dilfer as the starter in his fifth year, although an injury paved the way for the team to move on. Detroit traded Harrington after his fourth season to Miami for a late round pick. And while Manning’s individual statistics were not impressive, he had already won a Super Bowl with the Giants, ending any questions about his job security.

If the Jets go into the 2013 season with Sanchez as the starter, they will essentially be giving him as long a leash as any quarterback in N.F.L. history has ever had. There are obviously other considerations with Sanchez. He will cost the Jets salary cap over $17 million if they release him before the start of the 2014 season. As it stands, the Jets will pay him nearly $13 million in 2013. But it’s the extreme exception to the rule for a quarterback to have four consecutive years of mediocre play be given the starting job in his fifth year on a silver platter. When a highly drafted quarterback struggles so consistently and fails to develop, there are usually severe ramifications. And they extend far beyond the quarterback.

For a look at the coach and the general manager, you can read the full article here.

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(I originally posted this at the S-R Blog, but I thought it would be very appropriate here as well.)

WARNING: Math post.

PFR user Brad emailed over the weekend with an interesting question:

“Wondering if you’ve ever tracked or how it would be possible to find records vs. records statistics….for instance a 3-4 team vs. a 5-2 team…which record wins how often? but for every record matchup in every week.”

That’s a cool concept, and one that I could answer historically with a query when I get the time. But in the meantime, here’s what I believe is a valid way to estimate that probability…

  1. Add eleven games of .500 ball to the team’s current record (at any point in the season). So if a team is 3-4, their “true” wpct talent is (3 + 5.5) / (7 + 11) = .472. If their opponent is 5-2, it would be (5 + 5.5) / (7 + 11) = .583.
  2. Use the following equation to estimate the probability of Team A beating Team B at a neutral site:

    p(Team A Win) = Team A true_win% *(1 – Team B true_win%)/(Team A true_win% * (1 – Team B true_win%) + (1 – Team A true_win%) * Team B true_win%)

  3. You can even factor in home-field advantage like so:

    p (Team A Win) = [(Team A true_win%) * (1 – Team B true_win%) * HFA]/[(Team A true_win%) * (1 – Team B true_win%) * HFA +(1 – Team A true_win%) * (Team B true_win%) * (1 – HFA)]

    In the NFL, home teams win roughly 57% of the time, so HFA = 0.57.

This means in Brad’s hypothetical matchup of a 5-2 team vs. a 3-4 team, we would expect the 5-2 team to win .583 *(1 – .472)/(.583 * (1 – .472) + (1 – .583) * .472) = 61% of the time at a neutral site.

Really Technical Stuff:

Now, you may be wondering where I came up with the “add 11 games of .500 ball” part. That comes from this Tangotiger post about true talent levels for sports leagues.

Since the NFL expanded to 32 teams in 2002, the yearly standard deviation of team winning percentage is, on average, 0.195. This means var(observed) = 0.195^2 = 0.038. The random standard deviation of NFL records in a 16-game season would be sqrt(0.5*0.5/16) = 0.125, meaning var(random) = 0.125^2 = 0.016.

var(true) = var(observed) – var(random), so in this case var(true) = 0.038 – 0.016 = 0.022. The square root of 0.022 is 0.15, so 0.15 is stdev(true), the standard deviation of true winning percentage talent in the current NFL.

Armed with that number, we can calculate the number of games a season would need to contain in order for var(true) to equal var(random) using:

0.25/stdev(true)^2

In the NFL, that number is 11 (more accurately, it’s 11.1583, but it’s easier to just use 11). So when you want to regress an NFL team’s W-L record to the mean, at any point during the season, take eleven games of .500 ball (5.5-5.5), and add them to the actual record. This will give you the best estimate of the team’s “true” winning percentage talent going forward.

That’s why you use the “true” wpct number to plug into Bill James’ log5 formula (see step 2 above), instead of the teams’ actual winning percentages. Even a 16-0 team doesn’t have a 100% probability of winning going forward — instead, their expected true wpct talent is something like (16 + 5.5) / (16 + 11) = .796.

(For more info, see this post, and for a proof of this method, read what Phil Birnbaum wrote in 2011.)

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The Jacksonville Jaguars faced an uphill battle on Sunday: they were 15-point underdogs against the Packers in Lambeau Field. Trailing 14-6 in the final seconds of the first half, Blaine Gabbert threw a one-yard touchdown pass to tackle Guy Whimper. At that point, Mike Mularkey decided to go for two in an attempt to tie the game before the teams went into the locker room. The two-point conversion attempt failed, and Jacksonville ultimately lost, 24-15. So, did Mularkey make the right call?

In a lot of ways, this is similar to the decision Chan Gailey faced against the Titans in week seven. Essentially, Mularkey would need to calculate:

— (A) Jacksonville’s win probability in a 14-12 game
— (B) Jacksonville’s win probability in a 14-13 game; and
— (C) Jacksonville’s win probability in a 14-14 game

If we assume a 50% conversion rate on the 2-point attempt — more on this in a minute — then the question is a simple one. We just need to determine whether the difference between (A) and (B) is greater than or less than the difference between (B) and (C). Green Bay was set to receive the ball at the start of the second half, so according to Brian Burke, the values for (A), (B), and (C) are and 41%, 45%, and 48%.

I also looked at all games since 2000 where the team was set to kick to start the second half and was tied, trailing by 1, or trailing by 2 at halftime. In 275 tie games, the team kicking off to start the second half won 52% of the time. There were 70 instances where the team was trailing by 1, but they won just 39% of the time. And in 32 situations where a team was trailing by 2, the trailing team won 41% of the time. The sample sizes here are not large, and the set is of course biased; teams kicking off at halftime obviously had the ball in the first half, so if they trailed at halftime, that’s a signal that they were the inferior team.

So Burke’s model tells us that it’s a very close call; a small sample of results indicates a strong preference for being in a tie game. We can also look at Football Commentary, which theorizes that a team needs only a 36% chance to convert to make going for 2 the right call. So as you can see, the results are a somewhat over the map here.

My thoughts? It’s very close. It’s similar to the Gailey decision, but the uncertainty is magnified here with 30 minutes remaining instead of fifteen. There are a lot of ways for the game to unfold that make me think the difference between (A) and (B) is pretty close to the difference between (B) and (C). Still, my gut does tell me that — assuming a 50% conversion rate — it probably *is* better to go for two, but it’s certainly not obvious or a slam dunk. If I was a Packers fan, I would have preferred to see the Jaguars kick the extra point.

That said, understanding the resulting win probabilities is just one part of the equation. Let’s look at some of the others.
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For years, I was an unabashed Philip Rivers supporter. I had no preexisting affinity for the Chargers or Rivers, but in all the metrics I care about, Rivers was always one of the best. In 2008, 2009, and 2010, Philip Rivers led the league in yards per attempt. He finished first in ANY/A in ’08 and second in ’09 and ’10; he finished second in NY/A in ’08 and then first in NY/A in 2009 and 2010. Simply put, going into the 2011 season, no quarterback had been better over the last three years.

Rank Player Tm Gms Cmp Att Cmp% Yds TD Int Rate Sk Y/A SkYds AY/A ANY/A Y/G
1 Philip Rivers SDG 48 986 1505 65.5% 12973 92 33 103.8 88 8.62 545 8.86 8.02 270.3
2 Tom Brady NWE 33 702 1068 65.7% 8374 64 17 102.9 41 7.84 261 8.32 7.78 253.8
3 Drew Brees NOR 47 1224 1807 67.7% 14077 101 50 98.1 58 7.79 412 7.66 7.20 299.5
4 Aaron Rodgers GNB 47 1003 1552 64.6% 12394 86 31 99.4 115 7.99 730 8.20 7.19 263.7
5 Tony Romo DAL 35 771 1213 63.6% 9536 63 30 94.8 61 7.86 360 7.79 7.13 272.5
6 Matt Schaub HTX 43 1012 1537 65.8% 12183 68 37 94.7 80 7.93 524 7.73 7.02 283.3
7 Peyton Manning CLT 48 1214 1805 67.3% 13202 93 45 95.4 40 7.31 251 7.22 6.93 275.0
8 Kurt Warner CRD 31 740 1111 66.6% 8336 56 28 95.2 50 7.50 354 7.38 6.75 268.9
9 Ben Roethlisberger PIT 43 858 1364 62.9% 10829 60 32 92.5 128 7.94 852 7.76 6.53 251.8
10 Eli Manning NYG 48 945 1527 61.9% 11261 79 49 88.3 73 7.37 507 6.97 6.33 234.6
11 Donovan McNabb TOT 43 887 1486 59.7% 10846 59 36 85.4 95 7.30 684 7.00 6.15 252.2
12 Matt Ryan ATL 46 885 1456 60.8% 10061 66 34 86.9 59 6.91 354 6.77 6.27 218.7
13 Kyle Orton TOT 43 901 1504 59.9% 10427 59 33 84.8 90 6.93 562 6.73 6.00 237.0
14 Joe Flacco RAV 48 878 1416 62.0% 10206 60 34 87.9 108 7.21 788 6.97 5.96 212.6
15 Brett Favre TOT 45 923 1411 65.4% 10183 66 48 88.1 86 7.22 599 6.62 5.84 226.3
16 Jay Cutler TOT 47 981 1603 61.2% 11466 75 60 82.9 98 7.15 625 6.40 5.67 244.0
17 Matt Cassel TOT 45 860 1459 58.9% 9733 64 34 83.9 115 6.67 644 6.50 5.62 211.6
18 David Garrard JAX 46 885 1417 62.5% 9951 53 38 84.7 117 7.02 777 6.56 5.56 216.3
19 Jason Campbell TOT 44 836 1342 62.3% 9250 46 29 85.1 114 6.89 759 6.61 5.57 205.6
20 Carson Palmer CIN 36 719 1181 60.9% 7795 50 37 81.4 63 6.60 481 6.04 5.34 216.5
21 Ryan Fitzpatrick TOT 33 603 1040 58.0% 6327 40 34 74.9 83 6.08 465 5.38 4.57 175.8
22 Matt Hasselbeck SEA 35 668 1141 58.5% 7246 34 44 71.2 80 6.35 503 5.21 4.46 207.0

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Neil once pointed out, that you can approximate a team’s odds of winning a game by using the point spread and the following formula:

p(W) = 1 – (1-NORMDIST(0.5,SPREAD,13.86,TRUE))+0.5*(NORMDIST(0.5,SPREAD,13.86,TRUE)-NORMDIST(-0.5,SPREAD,13.86,TRUE))

For college football games, there is research by Wayne Winston and Jeff Sagarin that the standard deviation in the above formula should be 16 instead of 13.86. One of the nice things about the SRS is that it comes very close to approximating the point spread in each game. If we give 3 points to the home team, we can then approximate each team’s likelihood of winning in their remaining games.

For example, here is a look at Oregon’s remaining schedule and their likelihood of winning each game. Note that for now, I am assuming that the Ducks host the Trojans in the Pac-12 Championship Game:

TmOppLocSRS TmSRS OppProj SpreadWin Prob
OregonSouthern CalRoad65.953.9-8.971.2%
OregonCaliforniaRoad65.942.3-20.690.1%
OregonStanfordHome65.953.8-1582.6%
OregonOregon StRoad65.955.2-7.768.4%
OregonSouthern CalHome65.953.9-14.982.5%
Total29.9%

Winning five games in a row isn’t easy, even for a team as good as Oregon. With four difficult games left, the odds of them going 5-0 are just 29.9%. Things are much more favorable for Kansas State:

TmOppLocSRS TmSRS OppProj SpreadWin Prob
Kansas StOklahoma StHome66.352.5-16.985.4%
Kansas StTCURoad66.346.2-17.185.7%
Kansas StBaylorRoad66.346-17.486.1%
Kansas StTexasHome66.352.1-17.285.9%
Total54.1%

The Big 12 has some good teams, but Kansas State appears to be an elite one. My gut tells me the SRS is underrating the likelihood of one of those teams pulling off an upset, but there’s no doubt that Kansas State would be a double-digit favorite against each of those teams right now. Of course, one thing the SRS ignores in all of these instances is the possibility of a key injury affecting any team.

Notre Dame has a history of dropping games to bad teams, but I don’t think there’s much of a chance the Fighting Irish lose any of their next three games. That means the USC game should have national title implications:

TmOppLocSRS TmSRS OppProj SpreadWin Prob
Notre DamePittsburghHome63.137.2-28.996.5%
Notre DameBoston CollegeRoad63.131.1-29.196.5%
Notre DameWake ForestHome63.127.9-38.399.2%
Notre DameSouthern CalRoad63.153.9-6.265.1%
Total60.1%

There is only a 10% chance (29.9% * 54.1% * 60.1%) that Oregon, Kansas State and Notre Dame all finish the season undefeated, at least according to the assumptions in this post. If you want to look at how all three teams got here, you can check all the NCAA game scores here.

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Week 9 SRS Ratings: When Will Oregon Stop Scoring?

Oregon’s offense is ridiculous, and its defense and special teams aren’t far behind. Entering this weekend, Oregon had outscored opponents 234-46 … in the first half. Prior to their game against Colorado, Bill Connelly ranked Oregon as the third best defense in college football. Against the horrible Buffaloes, the Ducks didn’t disappoint.

Oregon jumped out to a 28-0 lead after the first quarter, and led 56-0 by halftime. Backup quarterback Bryan Bennett led the team with three touchdowns in the 70-14 rout. De’Anthony Thomas rushed for 97 yards on five carries and scored on a 73-yard punt return. Kenjon Barner had 9 carries for 104 yards and 2 touchdowns, and if not for the one-yard score, would have averaged 12.9 yards per carry; he also caught a 48-yard pass.

For the Ducks, this was a going-through-the-motions victory against a very overmatched opponent. Soon, though, we’ll find out a little more about the Ducks. On Saturday, they go to Los Angeles to face a talented but inconsistent USC team. And while California isn’t a serious threat, the Ducks close with games against Stanford and Oregon State, who may at least be able to slow down the mighty Ducks offense. For now, though, Oregon looks like the one hope to make for an exciting BCS National Championship Game.

We can assume Alabama will take one spot, with Oregon, Kansas State and Notre Dame battling for the other golden ticket. The odds of another all-SEC title game dropped with the Florida loss to Georgia. That’s because the Bulldogs now have the inside track on winning the SEC East, with a head-to-head victory over Florida. South Carolina beat Georgia, but UGA will essentially win the division due to luck of the draw. South Carolina drew Arkansas and LSU in Baton Rouge from the SEC West this year, while Georgia gets to play Ole Miss and Auburn — their final two conference opponents. Assuming the Bulldogs can take care of business against Ole Miss next week, their ticket to Atlanta should be secure. Considering Florida could have boosted their SOS against Florida State — and also faced and defeated LSU — replacing Florida with Georgia as the SEC East champion lowers the odds of that division sending a team to Miami.

Without further ado, below are the week 9 SRS ratings. As always, thanks to Dr. Peter R. Wolfe for publishing his game results.
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Wins with quarterbacks drafted by that team

Good stat today by ESPN’s Adam Schefter, who notes that Kansas City has gone 25 years without winning a game with a quarterback drafted by the Chiefs. This Todd Blackledge-led victory over the Chargers in 1987 was the last time a quarterback drafted by the Chiefs won a game in red and gold.

That’s remarkable, but as always, we need context. The table below looks at all team wins from 1988 to 2012 and shows how many games were won by a quarterback drafted by that team. Note: For purposes of this post, I’m considering John Elway, Jim Everett, Kelly Stouffer, Eli Manning, and Philip Rivers as having been drafted by the Broncos, Rams, Seahawks, Giants, and Chargers, respectively. Additionally, quarterbacks drafted before 1988 count, but only their wins starting in 1988 count for purposes of the table below. The last two columns show, for each, the quarterback with the most wins among those quarterbacks drafted and not drafted by that team.

TmWinsWbDQBPercMWbDQBMWbnDQB
NWE22521294.2%Tom Brady (128)Doug Flutie (7)
IND21318185.0%Peyton Manning (141)Jim Harbaugh (20)
PIT23719883.5%Ben Roethlisberger (83)Tommy Maddox (15)
NYG21717781.6%Eli Manning (74)Kerry Collins (35)
PHI22515970.7%Donovan McNabb (92)Michael Vick (18)
DEN22115570.1%John Elway (102)Jake Plummer (39)
TAM17311767.6%Trent Dilfer (38)Brad Johnson (26)
CIN15610466.7%Carson Palmer (46)Jeff Blake (25)
BUF20312662.1%Jim Kelly (91)Drew Bledsoe (23)
SDG19111861.8%Philip Rivers (66)Stan Humphries (47)
ATL18411361.4%Matt Ryan (49)Chris Chandler (34)
MIA20411857.8%Dan Marino (99)Jay Fiedler (36)
WAS18010457.8%Mark Rypien (45)Brad Johnson (17)
DAL20411556.4%Troy Aikman (94)Tony Romo (50)
NYJ1799955.3%Chad Pennington (32)Vinny Testaverde (35)
TEN21611955.1%Steve McNair (76)Warren Moon (51)
CLE1276853.5%Bernie Kosar (29)Derek Anderson (16)
DET1508053.3%Rodney Peete (21)Scott Mitchell (27)
MIN21410850.5%Daunte Culpepper (38)Warren Moon (21)
JAX1397050.4%David Garrard (39)Mark Brunell (63)
BAL1457350.3%Joe Flacco (49)Steve McNair (15)
ARI1497147.7%Jake Plummer (30)Kurt Warner (27)
CHI1968844.9%Jim Harbaugh (35)Jay Cutler (29)
STL1626540.1%Jim Everett (38)Marc Bulger (41)
SFO2298336.2%Alex Smith (37)Steve Young (89)
HOU712433.8%David Carr (22)Matt Schaub (38)
GNB2316929.9%Aaron Rodgers (45)Brett Favre (160)
CAR1263225.4%Kerry Collins (22)Jake Delhomme (53)
SEA1863619.4%Rick Mirer (20)Matt Hasselbeck (69)
OAK1772011.3%Steve Beuerlein (8)Rich Gannon (45)
NOR19921.00%Danny Wuerffel (2)Drew Brees (64)
KAN20200.00%--Trent Green (48)

As bad as the Chiefs record has been, the Saints record isn’t any better. In fact, since Archie Manning’s last game for the Saints, New Orleans has only drafted two quarterbacks – Dave Wilson and Danny Wuerffel – who have started and won a game for the team. JaMarcus Russell couldn’t even break the Raiders list, ending his career with seven wins. Two other interesting notes. Tony Romo is the only undrafted quarterback in the league currently starting. And of the 32 starting quarterbacks, three of them — Michael Vick, Matt Schaub, and Matt Ryan — were drafted by the Falcons.

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New page added to Football Perspective: NCAA Games

At the top of every page there are gray tabs that will take you to the different pages at Football Perspective. I’ve added a new one: NCAA Games. That page will show you the results for every individual game involving any of the 124 FBS teams this year. The page will be updated along with the SRS standings each week. If you’ve got any tips or suggestions, you can leave them here.

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Trivia of the Day – Saturday, October 27th

Last week, I noted that Calvin Johnson was trying to become just the third player since 1970 to lead the NFL in receiving yards in consecutive seasons. The rushing crown is much more likely to go to the same player; in fact, ten rushing champions since 1973 also led the league in rushing yards in the prior season.

Maurice Jones-Drew led the league in rushing in 2011, but isn’t going to repeat in 2012. Who was the last player to win the rushing crown in consecutive years?

Trivia hint 1 Show


Trivia hint 2 Show


Trivia hint 3 Show


Click 'Show' for the Answer Show

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Cam Newton is having an interesting year

I don’t care about any of the nonsense with Cam Newton. Instead, take a look at his 2011 and 2012 stat lines:

                                                                                            
Year   GS  QBrec Cmp Att Cmp%  Yds TD TD% Int Int% Y/A  AY/A Y/C  Yd/G Sk Yds NY/A ANY/A Sk% Rsh Yds TD  YPC Y/G  C/G
2011   16 6-10-0 310 517 60.0 4051 21 4.1  17  3.3 7.8  7.2 13.1 253.2 35 260  6.9   6.2 6.3 126 706 14  5.6 44.1 7.9
2012    6  1-5-0 101 173 58.4 1387  5 2.9   6  3.5 8.0  7.0 13.7 231.2 15 102  6.8   5.9 8.0  46 273  3  5.9 45.5 7.7

His Y/A is actually higher this year (although his sack rate is a little worse), and his rushing yards per game and yards per carry are both slightly up. Obviously the biggest change is that Newton simply isn’t scoring very much — he’s on pace for just 21 touchdowns after scoring 35 last year. But touchdowns are more volatile than metrics like yards per attempt, and tend to rebound quickly when paired with a strong yards per attempt average. Compared to league average, Newton’s only slightly worse in NY/A and ANY/A than he was last year, and he’s still above-average in both statistics. Statistically, he looks fine.

But the eye test certainly says Newton is struggling. And some stats back that up, too. Newton ranks 25th in Total QBR, although he only ranked 17th in that metric a year ago. Perhaps more importantly, the Carolina offense has plummeted to 29th in points per drive so far in 2012 (while ranking 17th and 19th in drive success rate), after ranking 6th in points per drive (and 6th in yards and 5th in DSR) in 2011. So the offense has been quite a bit worse, and significantly worse when it comes to scoring. That sort of matches what the “eye test” tells me.

But as Aaron Schatz pointed out to me, there are some odd splits going on with Newton. Take a look at how Newton’s performed on pass attempts on 1st downs this year:
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Have you taken a look at a passing leaderboard lately? Here’s the PFR passing leaderboard sorted by ANY/A; as always, all columns are sortable.

RkQBTmGCmpAttCmp%YdsTDTD%IntInt%Y/AAY/AY/CSkYdsNY/AANY/ASk%
1Peyton ManningDEN615422767.81808146.241.888.411.710637.47.84.2
2Josh FreemanTAM610418755.61538115.952.78.28.214.89657.57.54.6
3Eli ManningNYG716926563.82109124.572.687.712.55407.77.41.9
4Robert Griffin IIIWAS713318970.4160173.731.68.58.512151067.37.47.4
5Drew BreesNOR616627360.82097186.672.67.77.812.612867.17.24.2
6Ben RoethlisbergerPIT6155235661765114.731.37.57.911.413726.87.25.2
7Tom BradyNWE718628565.32104124.231.17.47.811.314966.77.14.7
8Aaron RodgersGNB718326269.81979197.341.57.68.310.8261426.47.19
9Matt SchaubHOU714022263.11650104.541.87.47.511.88596.973.5
10Jake LockerTEN46710663.278143.821.97.47.311.731676.92.8
11Matt RyanATL616023667.81756145.962.57.47.511131076.66.75.2
12Carson PalmerOAK614824161.4173272.941.77.2711.712936.56.34.7
13Alex SmithSFO712719066.8142794.752.67.57.311.2181006.46.28.7
14Joe FlaccoBAL715025259.5183793.662.47.36.912.2181106.46.16.7
15Andy DaltonCIN715624364.21831135.3104.17.56.811.7171026.75.96.5
16Cam NewtonCAR610117358.4138752.963.58713.7151026.85.98
17Tony RomoDAL615022167.9163683.694.17.46.310.99596.95.83.9
18Ryan FitzpatrickBUF7133218611435156.994.16.66.110.88446.25.73.5
19Christian PonderMIN71522276714929462.66.66.29.816685.95.56.6
20Sam BradfordSTL713121959.8159273.262.77.36.712.2211316.15.58.8
21Ryan TannehillMIA611819859.6145442637.36.412.3121096.45.55.7
22Matthew StaffordDET616426462.1175451.962.36.6610.7128665.44.3
23Michael VickPHI613623158.9163283.583.57.16.21217906.25.46.9
24Andrew LuckIND613425053.6167472.872.86.7612.516995.95.36
25Mark SanchezNYJ711621853.2145394.173.26.7612.514775.95.36
26Jay CutlerCHI610618756.7135984.373.77.36.412.81912165.39.2
27Russell WilsonSEA710417559.4123084.67476.111.8149765.27.4
28Brandon WeedenCLE715427256.6178393.3103.76.65.611.611696.15.13.9
29Philip RiversSDG613920966.51492104.894.37.16.210.7181186.15.17.9
30Kevin KolbARI610918359.6116984.431.66.46.510.7271594.84.912.9
31Matt HasselbeckTEN59615661.593153.242.665.59.710745.24.76
32Blaine GabbertJAX68815855.790663.831.95.75.610.3151054.64.58.7
33Matt CasselKAN510317658.5115052.895.16.54.811.213745.74.16.9

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Week 7 Power Rankings

The Big 10 used to have good athletes.

At 6-1, Houston is sitting pretty atop the AFC. They have to be the Super Bowl favorite right now, as they’re the most likely team in either conference to wrap up the 1 seed and they won’t have to go through two very good teams to get to New Orleans. In addition, they’re also really, really good.

Things are muddy in the NFC, and we get another NFC East showdown this week between the Giants and Cowboys. A New York win would open up a three-game lead over Dallas, but that would make things way too smooth in New York. The Atlanta Falcons already have a four-game lead in the NFC South, but it won’t take much for them to slip and miss out on a bye. The Packers, Bears and Vikings all look like playoff teams; Chicago might be the favorite to win the division right now, but these teams still play each other 5 more times. The NFC West looks like a competitive division but one that everyone assumes the 49ers will win. A Cardinals upset this weekend would send ripple effects throughout the conference. We’re in for a treat, as that’s the Monday Night game this week, and I expect the Cardinals to play well despite the three-game losing streak.

[As always, the number of wins I’m projecting each team to finish the season with is in column 3. The fourth column – PWIN – shows how many wins I projected last week, and the difference column represents how many wins I added or subtracted this week. The “RSOS” column stands for the remaining SOS for the team, based on the number of projected wins I’m giving to each of their opponents. The “RHG” column stands for remaining home games.]

TeamRecWinsPrvWinDiffRemSOSRemHGComment
Houston Texans6-1121200.4584The Texans the clear best team in the AFC; projecting only 12 wins includes a potential loss when they rest starters.
Atlanta Falcons6-0121200.4385Atlanta hasn't had a difficult schedule to date, but the schedule isn't that challenging the rest of the way, either.
San Francisco 49ers5-2121110.5144I keep going back and forth on the 49ers, from 11 to 12 to 11 and now back to 12 wins. But no matter how you say it, they're elite.
Chicago Bears5-1111100.5255A good win against the Lions, but I'm not ready to project a 7-3 finish. Two games with Minnesota, and games left against SF, Hou and GB make 12 wins an uphill battle.
Denver Broncos3-3111100.3945Good news: the Broncos didn't lose a close game after a crazy 4th quarter rally last week. Denver has by far the easiest remaining schedule in the league.
New England Patriots4-3101000.5075The Patriots made Mark Sanchez look good last week. Two games against Miami and a rematch with the Jets doesn't look so easy anymore, not to mention the games still against Houston and San Francisco.
Baltimore Ravens5-2101000.5004I dropped the Ravens a win last week despite the fact that they had just defeated Dallas; can they go 5-4 against a mediocre schedule the rest of the way? Probably.
Green Bay Packers4-3101000.4655The Packers are back, but I'm not sure if I'm ready to call them 7-2 the rest of the way good.
New York Giants5-210910.5494Giants got a big win against the Redskins, and look like the class of the division. We'll see if Dallas can change that.
Pittsburgh Steelers3-39900.4636Pittsburgh took care of business against Cincinnati, but I think we'll see a couple more Raiders-like slip-ups the rest of the way.
Miami Dolphins3-39900.4885Miami is the 4th or 5th best team in the AFC according to nearly every advanced stats metric out there.
Seattle Seahawks4-39900.5075Can't get too disappointed with a loss in San Francisco on a short week, but a loss in Detroit this weekend will be damaging.
Minnesota Vikings5-28800.5694The Vikings face Green Bay and Chicago twice along with Houston in their last six games; they must take care of business against Tampa Bay this weekend.
Philadelphia Eagles3-38800.4945Last week did not feel right without an Eagles meltdown.
San Diego Chargers3-38800.4385Last week did not feel right without a Chargers meltdown.
Dallas Cowboys3-38800.5066Cowboys could flip the script by sweeping the Giants this year and stealing the division. Game of the season for the Cowboys, and 98% of the nation will get to watch (sorry
Washington Redskins3-48800.4865Redskins went on the road against an elite team and nearly won; they don't drop a game for that.
Arizona Cardinals4-378-10.5974Did you know the Arizona Cardinals are 11-5 in their last 16 games? Oh, and the Cardinals have the toughest remaining schedule in the NFL.
New York Jets3-478-10.4654A great effort against the Patriots, but I'm not ready to say this team has turned things around. I don't expect them to beat Miami.
Cincinnati Bengals3-47700.5215Just think: three weeks ago, the Bengals were 3-1 with two home games sandwiched around a trip to Cleveland.
New Orleans Saints2-47700.5635With a difficult schedule in front of them, I'm not ready to put New Orleans even at 8-8 despite the fact that they're playing like a playoff team.
St. Louis Rams3-47700.5354A loss against the Packers isn't going to drop many teams.
Indianapolis Colts3-37610.4884A win at home against Cleveland is essentially holding serve, but I think they can go 4-6 against a workable schedule.
Tennessee Titans3-47610.4935I'm pretty sure this team is still garbage - they've been outscored by 89 points - and I don't expect them to beat Indianapolis this weekend.
Buffalo Bills3-467-10.5145Buffalo is really bad.
Detroit Lions2-46600.5636A loss in Chicago doesn't change my outlook on Detroit: a mediocre team with a brutal schedule.
Tampa Bay Buccaneers2-46600.5254A tough home loss to the Saints but I don't think Tampa Bay is that far from being a good team. A 95-yard pass helps, but Josh Freeman is 2nd in the NFL in ANY/A, NY/A and Y/A.
Oakland Raiders2-46510.4255How is Darren McFadden healthy but terrible? An easy schedule should make Oakland a 6-win team.
Carolina Panthers1-556-10.5134I don't really know when the bleeding will end, but in Chicago this weekend doesn't seem like the answer to that question.
Kansas City Chiefs1-55500.4635Romeo Crennel didn't go for it once on 4th down last week, and he probably won't this week, either.
Jacksonville Jaguars1-545-10.5065Things are not good in Jacksonville, as a loss to the Raiders was combined with injuries to Maurice Jones-Drew and Blaine Gabbert.
Cleveland Browns1-64400.5145Pat Shurmur hates winning.
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NYT Fifth Down: Post-week 7

A couple of weeks ago, I wrote the differing rookie seasons of Andrew Luck and Robert Griffin III. The numbers still hold — Griffin dominating in all traditional stats, while Luck throwing more passes downfield than any other quarterback — so I sat down with ESPN’s Jeff Bennett to figure out why Luck ranks ahead of Griffin in ESPN’s QBR.

After seven weeks, Robert Griffin III of the Redskins has exceeded even the most optimistic expectations. He leads the N.F.L. with a 70.4 completion percentage, and could become the first rookie to lead the league in that category since Parker Hall with the Rams in 1939.

Griffin also ranks first in yards per attempt with an 8.5 average, and could become the first rookie since another Ram, Bob Waterfield in 1945, to lead the N.F.L. in that statistic. Only two rookies in professional football history have ever led the league in both completion percentage and yards per attempt. The first was another Redskin, Sammy Baugh, in 1937; the last was Greg Cook, in the American Football League in 1969 (his career was ruined by a shoulder injury that year).

Griffin’s statistical domination of the record book has been astounding. And that’s before we get to the fact that he has 468 rushing yards and 6 touchdowns in seven games, putting Cam Newton’s rookie rushing records in both categories (706 and 14) in jeopardy.

Griffin will always be compared to the man selected one spot before him in the 2012 draft, Andrew Luck. And on the surface, there’s no comparison. Luck ranks 32nd in completion percentage (53.6) and 25th in yards per attempt (6.7). Whereas Griffin ranks third in traditional passer rating (101.8) behind Aaron Rodgers and Peyton Manning, Luck is tied with Brandon Weeden (72.3) and ahead of only Matt Cassel for last place.

But traditional statistics don’t always tell the full story, especially when we’re dealing with a sample size that’s smaller than half a season. Those watching Luck have usually come away thinking that he’s the next great quarterback, despite the raw numbers. Fortunately, there’s a way to fill in the rather large gap between perception and statistical production. One of those tools is ESPN’s Total QBR, which ranks Luck as the sixth-best quarterback in the N.F.L. this season. That’s even ahead of Griffin, who is eighth in QBR.

Jeff Bennett of ESPN Stats & Information, in a telephone interview, was able to help explain why Luck was not only the best rookie quarterback this season, but also perhaps the most underrated quarterback in the N.F.L.

Difficulty of Throws

It’s a gross generalization, but Luck plays in a vertical offense while Griffin plays in a horizontal one. Griffin ranks first in completion percentage while Luck ranks 32nd, but that has as much to do with the throws they’re asked to make as each quarterback’s accuracy. Luck‘s average pass attempt has traveled 10.2 yards past the line of scrimmage, the longest average pass distance in the league (this was before “Monday Night Football”; Jay Cutler was second at 9.9 entering the game). Griffin averages 7.9 yards downfield per pass attempt, slightly below the league average of 8.2.

And Luck’s long average pass distance isn’t simply a product of throwing lots of incomplete passes down the field. His average pass distance on completions is 8.6 yards past the line of scrimmage, also highest in the N.F.L. (Cutler was fourth at 8.3 entering Monday night). Griffin’s completions come an average of 5.8 yards from the line of scrimmage, well below the league average of 6.5.

Those numbers agree with Brian Burke’s data at Advanced NFL Stats, which show that Griffin has thrown only 14 percent of his passes 15-plus yards past the line of scrimmage, the lowest rate in the league. Luck has thrown only 11 percent of his passes at or behind the line of scrimmage, while Griffin is in an offense that has let him throw 44 passes at or behind the line, accounting for 23 percent of his attempts. Coach Mike Shanahan and his offensive coordinator, Kyle Shanahan, deserve credit for molding an offense that fits Griffin’s strengths. Unfortunately for Luck, nothing is being made easy for him in Indianapolis.

Yards After the Catch

Casting Luck as a downfield thrower is true, but only half the story. Unlike many rookie quarterbacks, whether through design or lack of talent, Luck rarely has a running back as a checkdown option. According to Footballguys.com, Colts running backs have been targeted on just 7 percent of all Indianapolis passes, the lowest mark in the league. Conversely, Colts receivers have been targeted on 72 percent of Indianapolis attempts, the highest mark in the N.F.L.

In the same vein, much of Griffin’s production has come via yards after the catch. On average, passers in 2012 have gained 56 percent of their yards through the air and 44 percent on yards after the catch by their receivers. For Griffin, 51.4 percent of his yards have come via his receivers after the catch, the fifth-highest mark in the league. Luck, in large part because of his downfield passing, has gained 68.9 percent of his yards through the air, the highest percentage in the league, and therefore has been helped the least in terms of yards after the catch.

However, simply putting the stats in this context does not mean that Luck has been a better passer than Griffin; rather, it is to simply close the extraordinary gap created by traditional statistics. Griffin’s completion percentage and yards per attempt average are still more impressive even after adjusting for the difficulty of his throws. If we looked simply at their passing numbers, even ESPN’s Total QBR would rank Griffin ahead of Luck, by a score of 68.7 to 60.7. And while you know there is more to being a quarterback than just passing, you might be surprised to learn that looking at those things actually vaults Luck ahead of Griffin.

You can read the rest of the article here.

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In Buffalo’s loss to Tennessee on Sunday, Chan Gailey faced an interesting decision. Buffalo trailed 28-27 in the final seconds of the third quarter when Ryan Fitzpatrick hit Steve Johnson for a 27-yard touchdown. Now up 33-28, Gailey chose to kick the extra point, and ultimately saw his team lose, 35-34.

Why did Gailey choose to go for 1? Bill Barnwell has his theory:

[The next mistake was] Gailey’s decision to kick an extra point on a touchdown at the end of the third quarter, which created the margin of victory. By going for one with seconds left in the third and a five-point lead (pending the extra point), Gailey paid tribute to the long-standing rule that teams shouldn’t go for two and try to create a seven-point lead before the fourth quarter. It’s an absurd rule, of course, that breaks down when you ask anybody to explain at any length why it makes sense. The two-point conversion chart at footballcommentary.com suggests that the Bills should have tried to tack a two-pointer onto their 33-28 lead if their chances of converting were better than 24 percent. Because the clock hadn’t ticked for 10 additional seconds and bumped the decision into the fourth quarter, though, the Bills kicked and ended up losing by one.

When I read that, my reaction was “yep, that sounds about right.” Up 5 with just over 15 minutes left, it seems like the “stats-geek” move is to go for two while the “conservative old school train of thought” says it’s “too early” to go for two. Of course, if that’s all there was to the story, you wouldn’t be reading this post right now. Take it away, Jason Lisk:

When I look at the game winning probabilities at Advanced NFL Stats, though, Gailey’s decision was different [than Mike Tomlin’s]. It pains me to say that conventional wisdom is right here, but it is. With 15 minutes left, being up 5 is more costly than up 7 is beneficial with all the permutations. There are enough possessions that you can get beat by two field goals gained, or not extend the lead with another field goal.

When is it too late to go for one point in either of these situations, though? As it turns out, the answer is roughly between the 6 and 7 minute mark of the fourth quarter. That’s when possessions become more limited and you must try to tie, or make it where a touchdown doesn’t beat you.

A little surprised, I went over to Advanced NFL Stats and entered the numbers into Brian Burke’s Win Probability Calculator. Up 5, at the start of the 4th quarter, with the opponent having 1st and 10 at the 22 yard line, yields a 72% win probability to the leading team. Up 6 translates to a 77% win probability and up 7 increases it to 80%. That’s what Lisk meant when he said that difference between being up 5 and up 6 — 5% — is greater than the difference between being up 6 and up 7 — 3%.

Nerd Fight! Brian is a good friend of the site and one of the smartest minds out there, but he’d be the first to tell you that his Win Probability model is not perfect. So the question we have to ask is, is this a situation where his Win Probability Model breaks down?

Let’s not forget what Barnwell noted: according to footballcommentary.com, going for 2 is the obvious call here. And let’s used my tried-and-true method for making any football decision. If you were a Titans fan, now trailing by 5 at the end of the 3rd quarter, would you have been happy to see Buffalo’s kicking team run onto the field, or would you have wished that instead they went for it? My gut tells me — and let’s stipulate that the Bills would have had a 50% chance of converting the 2-point attempt — that as a hypothetical Titans fan, I’d want Buffalo to kick the extra point. Being down 7 sounds really bad, while the difference between 5 and 6 seems pretty negligible to my Nashville gut.
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More work on POPIP and predicting INT rates

A couple of weeks ago, I wrote about interceptions per incompletion, or POPIP. In that article I showed how a player’s completion percentage is a better predictor of his future interception rate than his actual interception rate. And in this article by Brian Burke, one comment stuck with me:

Griffin has thrown deep, defined as attempts of greater than 15 yards through the air, on only 13% of his attempts, 30th among league quarterbacks. This is also likely the largest factor in his very low interception rate.

That makes sense — quarterbacks throwing short, safe passes should throw fewer interceptions. But this statement is a more important one than you might originally think, thanks to some great research by Mike Clay.

Clay came up with a metric he calls ‘aDOT’ — average depth of target — which measures exactly what you think it does. For each targeted or aimed pass, Pro Football Focus tracks how far from the line of scrimmage the intended target is. What’s makes this stat particularly appealing to me is that it’s very predictable as far as football statistics go. That’s not all that surprising because aDOT is based on a large sample of plays and basically frames how an offense operates.

Clay posted the 10 passers with the largest and smallest aDOT in 2011, which I’ve reproduced below. Note that there are some passes — spikes, throwaways, passes tipped at the line (these are grouped together as ‘other’) — with no target, and therefore are excluded when calculating aDOT. In the far right column, I’ve shown how the player’s aDOT compares to the league average rate of 8.8.

PasserYrAttAimOtheraDOTlgAVG
Tim Tebow20113182863213.3151%
Vince Young2011114111311.6131%
Jason Campbell20111651511410.5119%
Matt Moore20113473281910.4118%
Carson Palmer20113283121610.3117%
Eli Manning20117526985410.1114%
Cam Newton20115174942310113%
Joe Flacco2011605568379.8111%
Ben Roethlisberger2011553529249.8110%
Chad Henne2011112102109.7110%
T.J. Yates2011189171189.6109%
Matt Hasselbeck2011518490288.394%
Drew Brees2011763730338.293%
Blaine Gabbert2011413381328.192%
Alex Smith2011513463508.191%
Tony Romo2011522497258.191%
Ryan Fitzpatrick201156954425890%
Donovan McNabb2011156145117.989%
Colt McCoy2011463434297.888%
Tyler Palko201113512787.484%
Josh Freeman2011551519327.483%

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Here are the current SRS Ratings, weighted for the recency of each game, along with each team’s quarter-by-quarter Win Probability Added (WPA) so far this season:

RankTeampfr_idOSRSOSOSDSRSDSOSSRSSOSwpa_locwpa_vegaswpa_1stwpa_2ndwpa_3rdwpa_4th/ot
1Chicago Bearschi7.91.08.0-1.415.9-0.4-0.0680.4760.1280.0170.7290.219
2San Francisco 49erssfo-0.2-0.111.42.211.22.00.0680.956-0.0660.0590.566-0.083
3Houston Texanshtx6.9-1.04.2-0.211.1-1.20.0681.419-0.0380.9430.127-0.020
4Green Bay Packersgnb7.53.92.81.910.45.7-0.0680.9260.596-0.011-0.446-0.498
5New York Giantsnyg7.71.62.3-1.610.0-0.10.0680.351-0.0600.2780.0290.834
6Denver Broncosden5.2-0.11.61.56.81.40.000-0.060-0.644-0.8160.1831.338
7New England Patriotsnwe7.4-0.4-0.7-0.36.7-0.7-0.0681.2090.737-0.0170.363-1.724
8Seattle Seahawkssea-2.74.18.70.75.94.8-0.068-0.3350.708-0.588-0.0940.877
9Atlanta Falconsatl2.5-2.53.2-1.25.7-3.60.0000.6320.5250.1990.4041.240
10St Louis Ramsram-2.22.65.21.93.04.60.068-1.039-0.1430.348-0.2830.550
11Minnesota Vikingsmin-0.6-1.33.2-1.32.6-2.60.0680.2110.835-0.3620.0750.673
12Washington Redskinswas5.80.6-3.21.92.62.5-0.068-0.3810.1720.6971.235-2.155
13Dallas Cowboysdal-0.73.32.51.51.74.9-0.1360.365-0.216-0.3590.0510.295
14Arizona Cardinalscrd-4.61.25.0-1.10.40.10.068-0.452-0.0850.088-0.3311.212
15Miami Dolphinsmia-2.90.43.1-0.90.2-0.50.000-0.549-0.0110.7261.272-1.436
16Tampa Bay Buccaneerstam-0.6-2.70.80.50.1-2.20.136-0.5310.583-0.2760.276-1.188
17New York Jetsnyj0.00.60.11.00.11.50.068-0.605-0.080-0.084-0.4950.695
18Baltimore Ravensrav0.2-0.8-1.5-1.1-1.3-1.90.0680.536-0.4520.5870.0570.705
19New Orleans Saintsnor5.6-0.7-7.2-0.4-1.6-1.20.0000.552-0.193-0.476-0.019-0.864
20Detroit Lionsdet4.92.9-6.5-2.4-1.60.5-0.0680.249-0.313-0.833-0.3530.819
21Pittsburgh Steelerspit-2.5-2.60.1-1.3-2.4-3.9-0.1360.700-0.0270.2900.163-0.991
22San Diego Chargerssdg-2.3-3.8-0.4-0.1-2.7-3.90.0000.2020.7530.2140.294-1.463
23Carolina Pantherscar-4.11.50.71.4-3.42.90.136-0.246-0.8330.124-0.212-0.968
24Philadelphia Eaglesphi-6.6-0.62.50.3-4.0-0.40.0000.466-0.675-0.2960.729-0.224
25Indianapolis Coltsclt-3.20.7-3.1-0.4-6.30.30.136-0.5920.446-0.291-0.0660.367
26Cincinnati Bengalscin-0.9-1.2-5.7-2.6-6.7-3.8-0.0680.0090.7620.304-1.197-0.311
27Cleveland Brownscle-5.1-3.0-2.6-0.1-7.7-3.1-0.068-1.153-0.411-0.8000.161-0.229
28Oakland Raidersrai-3.40.6-6.6-1.5-10.0-0.90.000-0.368-0.3900.014-1.5291.272
29Buffalo Billsbuf1.10.0-11.1-1.9-10.0-1.9-0.068-0.3030.313-0.0340.180-0.589
30Tennessee Titansoti-3.0-1.6-8.42.1-11.40.5-0.068-1.194-0.5960.449-0.6671.576
31Jacksonville Jaguarsjax-8.8-0.3-3.31.0-12.10.80.000-0.647-0.229-0.144-0.227-0.754
32Kansas City Chiefskan-8.9-2.6-6.11.0-15.0-1.60.000-0.802-1.0940.049-0.9770.823
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Attempting to measure fatigue in the NFL

Fatigue in the NFL is definitely real, and a team that’s tired is not a team that’s likely to excel. But I don’t know if it’s even possible to accurately measure the effect of fatigue in the NFL, and if it is, I certainly don’t know how to do it. Fatigue is a useful descriptive term but one hard to define. Is playing 3 games in 11 days likely to lead to a fatigued team? What about traveling west to east for a 1:00 game? How does that compare to being on the field for 10 minutes? And how does that compare to playing opposite a defense that’s gone 3 and out on three straight drives?

I don’t know. What I can do is look at the data we have from the last 12 years and see what general trends we can discern. So, are defenses worse off if they’ve been on the field for awhile?

There have been nearly 15,000 instances of teams having 1st and 10 near mid-field, defined as between the two 47 yard lines. On average, when teams gain possession in that area, they scored 2.2 points per drive. And, on average, those teams over the course of the season, averaged 1.75 points per drive over all drives.

So what happens if the “1st and 10 from the 47, 48, 49, 50, 49, 48, or 47″ is the second play of the drive? Or the third? Or the 9th?

The 2.2 points per drive average when the situation occurs on the first play of the drive is the lowest in the group, although I don’t think that’s due to fatigue. Take a look:

Play #Pts/DrvAvg PPD
12.201.75
22.291.76
32.391.75
42.461.76
52.401.78
62.491.76
72.261.75
82.371.81
9+2.341.75

The middle column shows how many points, on average, teams scored in that situation, while the far right column shows the quality of the offenses in general (not that it really matters in this case). If fatigue had an impact in this situation, you would see the teams that start at their own 20, take 6 or 7 plays, and then have 1st and 10 at midfield be very successful. But that’s not the case.
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I didn’t think this was possible.

In 2009, Alabama had an incredible defense, ranking 1st or 2nd in points allowed, yards allowed, first downs allowed, completion percentage allowed and rushing yards allowed en route to a 14-0 season and a national title. In the 2010 draft, Rolando McClain and Kareem Jackson went in the first round, Javier Arenas and Terrence Cody in the second, and Marquis Johnson and Brandon Deaderick in the seventh. In 2010, a young Alabama defense wildly exceeded all expectations — how could they lose so much talent and still dominate? — but the team did regress and finished the year 10-3.

Last year, as the younger defense matured, Alabama had one of the greatest defenses in the history of college football. The Crimson Tide allowed a miniscule 8.2 points per game, by far the fewest in college football. Alabama’s defense also ranked 1st by large margins in rushing yards per game, passing yards per game, and first downs per game. But then Mark Barron, Dre Kirkpatrick, Dont’a Hightower, and Courtney Upshaw were top 35 picks in the NFL draft this year, while cornerback DeQuan Menzie and defensive tackle Josh Chapman were fifth round picks. With six defensive starters for the Crimson Tide getting drafted in 2012 — including five members of the first- or second-team All-SEC defense from 20111 — 2012 should have represented a significant step backwards for what was a historically dominant defense.

But the Crimson Tide death star is at full throttle now. After winning on the road at Tennessee and sucking the life out of another offense — and the Vols have one of the most explosive offenses in the SEC — Alabama continues to look invincible. While every other team in college football has question marks, Alabama has allowed just 8.3 points per game this year and has a mercilessly efficient offense. Quarterback A.J. McCarron still hasn’t thrown an interception in 2012.

Here’s a look at the SRS ratings after eight weeks. As a technical matter, two 7-0 teams square off in Tuscaloosa next week. But according to the SRS, Alabama should be expected to win by about 24 points.

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  1. Upshaw and Barron were All-SEC first team selections by the AP, and Chapman, Hightower and Kirkpatrick earned second-team honors. []
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Would you trust this man?

Most criticisms of 4th down calls spring when teams fail to go for it on 4th down and instead punt or kick a field goal. It is much rarer for stat geeks to cry out for a field goal attempt instead of a punt, and for good reason: field goals aren’t that valuable.

One reason for that: a field goal isn’t really worth 3 points; historical data tells us that a field goal is really worth 2.4 points. That’s because the other team gets the ball following a kickoff, on average, at the 26- or 27-yard line, and possession on 1st and 10 there is worth +0.6 points to that team. Therefore, a touchdown is really worth 6.4 points and a field goal worth 2.4 points, making a touchdown 2.67, and not 2.33, times as valuable as a field goal.

(It’s worth noting that, according to Jim Armstrong of Football Oustiders, since the rules changes last year on kickoffs, the average field position following a kickoff was 22.2 last year and 22.0 so far this season. Teams are at +0.4 in that situation, so a touchdown might now be worth 6.6 points and a field goal 2.6 points.)

Oakland Raiders coach Dennis Allen faced an interesting decision in the first quarter of the game against Atlanta last Sunday. On their second drive of the game, Oakland ran Darren McFadden for 8 yards on 3rd and 16 from the Atlanta 48. Facing 4th and 8 from the 40, Allen chose to punt.

In retrospect, it’s easy to criticize the decision. Shane Lechler’s punt went for a touchback, giving Oakland just 20 additional yards of field position, and after one play, the Falcons were already on the Raiders’ 39-yard line. And, of course, the Raiders lost by 3 in a game where Atlanta’s Matt Bryant nailed a 55-yarder to win the game.

But we can’t look at the outcome when analyzing Allen’s decision. What was the right call? We should probably start by acknowledging that, as a technically matter, the numbers say you should go for it. Considering the fact that the Raiders were an underdog, and that Oakland has (compared to the rest of their team) a pretty good passing game, and Atlanta has (compared to the rest of their team) a weak pass defense, going for it becomes an even more attractive option. But let’s put that to the side for now.

What are the odds of Janikowski hitting from 58 yards away? This season, kickers are 9 of 14 from 55+ yards out, although none have been attempted by Janikowski. Normally I would advise against using such a small sample size, but kickers this year seem to be deadlier than ever from long range. On the other hand, Janikowski is just 4/15 on kickers form 57+ yards over the last five and a half years. Even if you remove the 64, 65 and 66 yard attempts he missed, that’s still just a 33% rate. On the other hand, only two of those came in a dome — two misses in the span of two minutes in a game in New Orleans in 2008. My gut tells me that Janikowski is pretty close to even money in this situation in 2012, but I’m not sure how precise we can get.

But what we *can* do is figure out what the minimum percentage likelihood of success he needs to be at to make kicking the field goal the right call. According to Brian Burke, a missed field goal is worth -1.9 points to the Raiders, since the Falcons would get the ball at midfield, while a punt is worth +0.04 points to the punting team (presumably based on the other team getting the ball at their own 13-yard line).

There breakeven point where you should be indifferent between kicking and punting is therefore 45% (0.45 * 2.4 + 0.55 * -1.9 = +0.04). That seems to make it a pretty neutral decision. Given the fact that the Raiders were a heavy underdog, it’s pretty easy to argue that a 45% chance of 2.4 points (and a 55% chance of -1.9 points) is better than a 100% chance of being in a +0.04 situation. Underdogs need to take aggressive tactics, and this would have been an advisable decision. Of course, the more aggressive strategy with the highest reward would have been to go for it, although the presence of Janikowski does seem to argue in favor of kicking.

This wasn’t a particularly easy decision — or, given the context of the game, a particularly important one. Coaches make far worse decisions every Sunday. I do think in that situation, punting was the worst of the three options available for the Raiders.

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Trivia of the Day – Saturday, October 20th

Megatron.

Calvin Johnson led the league in receiving last season with 1,681 yards. Johnson is fourth in receiving yards this season behind A.J. Green, Wes Welker, and Reggie Wayne, but Johnson is 2nd in yards per game as the Lions have had their bye week while the Bengals and Patriots have not.

If Johnson can lead the league in receiving yards again, he’d become just the third person since the merger to accomplish that feat. Which brings us to today’s trivia question.

Who was the last player to lead the league in receiving yards in consecutive seasons?

Trivia hint 1 Show


Trivia hint 2 Show


Trivia hint 3 Show


Click 'Show' for the Answer Show

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Here are the current SRS Ratings, using the recency-weighted system I described on Monday:

RankTeampfr_idOFFSRSOFFSOSDEFSRSDEFSOSSRSSOS
1Chicago Bearschi7.50.27.6-1.915.1-1.8
2New York Giantsnyg9.93.12.8-1.712.71.4
3San Francisco 49erssfo-0.10.110.92.010.82.1
4New England Patriotsnwe8.90.2-0.3-0.68.6-0.4
5Green Bay Packersgnb5.32.02.01.67.33.7
6Seattle Seahawkssea-2.63.99.11.16.45.0
7Houston Texanshtx4.4-1.31.5-1.55.9-2.8
8Denver Broncosden4.5-1.01.01.05.50.0
9Atlanta Falconsatl1.8-3.33.5-0.75.2-4.0
10Tampa Bay Buccaneerstam-0.6-1.84.41.63.8-0.2
11St Louis Ramsram-2.82.26.61.53.83.7
12Dallas Cowboysdal1.45.12.03.03.58.1
13Baltimore Ravensrav1.4-1.52.0-0.93.4-2.5
14Arizona Cardinalscrd-3.71.75.5-0.81.80.8
15Washington Redskinswas7.41.0-5.8-0.21.60.8
16Minnesota Vikingsmin-2.3-3.72.9-0.50.7-4.2
17Miami Dolphinsmia-2.70.42.3-1.5-0.4-1.1
18Detroit Lionsdet5.32.9-7.5-3.5-2.2-0.6
19Carolina Pantherscar-2.32.7-0.12.1-2.34.8
20New York Jetsnyj-2.1-0.5-0.7-0.2-2.8-0.8
21Philadelphia Eaglesphi-6.5-0.73.71.6-2.81.0
22San Diego Chargerssdg-2.4-4.0-1.6-1.1-4.0-5.1
23Cincinnati Bengalscin0.2-1.9-4.9-1.6-4.7-3.5
24Pittsburgh Steelerspit-2.1-2.4-2.7-3.1-4.8-5.5
25New Orleans Saintsnor2.6-2.3-7.60.0-5.0-2.3
26Cleveland Brownscle-2.1-1.8-3.11.3-5.2-0.5
27Buffalo Billsbuf1.01.3-9.4-1.0-8.40.4
28Indianapolis Coltsclt-2.01.5-6.7-0.5-8.61.0
29Oakland Raidersrai-4.60.6-6.20.0-10.90.6
30Kansas City Chiefskan-7.4-1.2-6.60.6-14.0-0.7
31Jacksonville Jaguarsjax-10.60.1-3.41.7-14.01.8
32Tennessee Titansoti-5.1-1.2-8.91.7-14.00.5


Also, just for fun, here’s how SRS sees this weekend’s games going (with the Vegas lines and over/unders for comparison’s sake):

game_idyear_idgame_datehome_teamsrsaway_teamsrsvegas_linevegas_o/usrs_linesrs_o/u
201210220chi201210/22/2012chi15.1det-2.2-5.047.5-19.658.9
201210210nyg201210/21/2012nyg12.7was1.6-6.550.0-13.566.5
201210210buf201210/21/2012buf-8.4oti-14.0-3.046.5-7.960.3
201210210tam201210/21/2012tam3.8nor-5.03.049.5-11.151.4
201210210min201210/21/2012min0.7crd1.8-6.040.5-1.231.8
201210210clt201210/21/2012clt-8.7cle-5.2-3.045.01.251.9
201210210cin201210/21/2012cin-4.7pit-4.82.546.0-2.452.0
201210210nwe201210/21/2012nwe8.6nyj-2.8-10.547.5-13.854.0
201210210ram201210/21/2012ram3.8gnb7.35.544.51.240.1
201210210rai201210/21/2012rai-10.9jax-14.0-4.043.0-5.540.7
201210210car201210/21/2012car-2.4dal3.52.045.53.543.5
201210210htx201210/21/2012htx5.9rav3.4-6.048.0-4.848.5
{ 7 comments }

In yesterday’s post, I argued that teams were overly hesitant to move on from bad investments. There’s a reason for that: miss on a first-round quarterback, and there are serious ramifications. Sometimes the offensive coordinator gets the axe first — we saw the Jets move on from Brian Schottenheimer this past offseason — but usually the coach and offensive coordinator are a package deal. And the quarterback usually gets at least one more chance with a new staff.

The 2007 draft provides two examples of this. The Oakland Raiders drafted JaMarcus Russell with the first overall pick, and we know how that went. This was part of a regime change, as Lane Kiffin and Greg Knapp replaced Art Shell and John Shoop. But by the end of 2008, both Kiffin and Knapp were gone, as Russell lasted for one more year under Tom Cable. With the 22nd pick, Cleveland selected Brady Quinn. Romeo Crennel and the Browns went 10-6 that season, but the team regressed to 4-12 in 2008. With Brady Quinn barely making an impact in two years and the team struggling, Crennel and offensive coordinator Rob Chudzinski were shown the door; a year later, Quinn was done in Cleveland, too.

Lest anyone forget, Blaine Gabbert is already on his second staff. Jack Del Rio and Dirk Koetter were shown the door for largely non-Gabbert-based reasons, although both have landed well in Denver and Atlanta as coordinators. But let’s take a step back and look at history. From 1998 to 2010, there were 35 quarterbacks selected in the first round of the draft. The table below shows each quarterback, his last year as the main starter for that team, how many years he “survived” there (simply his last year starting minus his draft year plus one); I’ve also listed the team’s offensive coordinator and head coach during the quarterback’s rookie season, and how long each of those two men survived in their positions individually and collectively. Finally, the last column is my subjective “bust/not bust” column, with me grading each quarterback on a scale from 1 to 3 on the “was this player a terrible, average, or good pick.” Again, in all of these cases I’m looking at the success with that team, not with any other team (and for Philip Rivers and Eli Manning, I’m considering them as having been drafted by the Chargers and Giants, respectively.)

YearPickTmQBLast Yr StYrs SurvOCLast YrYrs SurvHCLast YrYrs SurvCombinedbust?
19982SDGRyan Leaf20003Mike Sheppard19981June Jones1998121
19981INDPeyton Manning201013Tom Moore200912Jim Mora20014163
19992PHIDonovan McNabb200911Rod Dowhower20013Andy Reid201214173
19993CINAkili Smith20002Ken Anderson20002Bruce Coslet2000241
199911MINDaunte Culpepper20046Ray Sherman19991Dennis Green2001343
199912CHICade McNown20002Gary Crowton20002Dick Jauron2003571
19991CLETim Couch20024Chris Palmer20002Chris Palmer2000241
200018NYJChad Pennington20067Dan Henning20001Al Groh2000123
20011ATLMichael Vick20066George Sefcik20011Dan Reeves2003343
20023DETJoey Harrington20054Maurice Carthon20021Marty Mornhinweg2002121
200232WASPatrick Ramsey20032Steve Spurrier20032Steve Spurrier2003241
20021HOUDavid Carr20065Chris Palmer20043Dom Capers2005471
20031CINCarson Palmer20108Bob Bratkowski20108Marvin Lewis201210183
20037JAXByron Leftwich20053Bill Musgrave20042Jack Del Rio20119112
200319BALKyle Boller20075Matt Cavanaugh20042Brian Billick2007571
200322CHIRex Grossman20075John Shoop20031Dick Jauron2003121
200422BUFJ.P. Losman20063Tom Clements20052Mike Mularkey2005241
20044SDGPhilip Rivers20118Cam Cameron20063Marty Schottenheimer2006363
20041NYGEli Manning20118John Hufnagel20063Tom Coughlin20129123
200411PITBen Roethlisberger20118Ken Whisenhunt20063Bill Cowher2006363
200525WASJason Campbell20095Don Breaux20051Joe Gibbs2007342
20051SFOAlex Smith20117Mike McCarthy20051Mike Nolan2008452
200524GNBAaron Rodgers20117Tom Rossley20051Mike Sherman2005123
20063TENVince Young20105Norm Chow20072Jeff Fisher2010572
200610ARIMatt Leinart20061Keith Rowen20061Dennis Green2006121
200611DENJay Cutler20083Rick Dennison20083Mike Shanahan2008362
200722CLEBrady Quinn20093Rob Chudzinski20082Romeo Crennel2008241
20071OAKJaMarcus Russell20093Greg Knapp20082Lane Kiffin2008241
200818BALJoe Flacco20114Cam Cameron20125John Harbaugh20125103
20083ATLMatt Ryan20114Mike Mularkey20114Mike Smith2012593
20091DETMatthew Stafford20113Scott Linehan20124Jim Schwartz2012483
200917TAMJosh Freeman20113Greg Olson20113Raheem Morris2011362
20095NYJMark Sanchez20113Brian Schottenheimer20113Rex Ryan2012472
20101STLSam Bradford20112Pat Shurmur20101Steve Spagnuolo2011232
201025DENTim Tebow20112Mike McCoy20123Josh McDaniels2010141

[click to continue…]

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One of the most difficult decisions an organization has to make is when to admit its mistakes. The Jaguars drafted Blaine Gabbert with the 10th overall pick in 2011, and his lack of success is even more striking when compared to the rest of the top dozen selections:

Last year, there were three legitimate excuses the Jaguars could proffer to defend Gabbert’s play: he was a rookie, the lockout prevented him from getting proper training, and Jacksonville had the worst set of receivers in the league. Giving up on a first round quarterback after just one season would be silly, especially one where the expectations were that the rookies would struggle. And the cupboard was bare: Jacksonville became the first team since the 2004 Ravens and only the 5th team in the previous 20 seasons to not have a 500-yard wide receiver, so it’s not like Gabbert had a lot to work with.1

But through five games, little has changed in Jacksonville. The Jaguars should wait to evaluate Gabbert’s career — five games into his second season isn’t a fair sample size — but his production so far have been extremely disappointing:

A few years ago, Jason Lisk wrote this post on when the Lions should have given upon Joey Harrington. One of the most relevant points of that article was Lisk’s supposition

that teams are far more likely to commit errors of holding on to a quarterback for too long, while rarely giving up on a quarterback too early — once they have seen him play any amount of time in a real NFL game. I can think of examples of quarterbacks who were drafted, never started for their original team, and found success elsewhere, but its relatively rare to find a quarterback who started but never had success with his original team, and moved elsewhere to have his first breakout.

There were 70 quarterbacks selected in the first round of NFL drafts between 1978 and 2010. How often did a team give up too early on a good quarterback?2 Vinny Testaverde had success outside of Tampa Bay, but the Bucs didn’t give up “early” on him by any means; he played for six years in Tampa with with varying levels of success. The team did give up too early on Steve Young, although he wasn’t included in this study because he was selected in the supplemental draft. Jim Harbaugh had success in Indianapolis, but it’s not like the Bears didn’t know what they had: Harbaugh was in Chicago for the first seven years of his career.

Jeff George had good years outside of Indianapolis, but I wouldn’t say the Colts gave up early on him. He was inconsistent for four years and caused problems off the field; he was finally traded in connection with a holdout. Mike Vick has had success in Philadelphia, but the Falcons obviously had their hands forced when they gave up on him. Ditto Kerry Collins, whose off the field issues left the Panthers with little choice.

With the exception of Steve Young, who Tampa traded after two years — and who may not have ever turned into a star quarterback in Tampa Bay — you’d be hard pressed to find any examples of teams giving up on first round picks too early (with the exception of those released/traded for nonfootball reasons). Chad Pennington had one great year in Miami, but that was after a long career in New York. Doug Williams and Trent Dilfer won Super Bowls with other teams, but Tampa Bay didn’t give up on either quarterback too early by any reasonable definition of the phrase. The reality is, teams will do just about everything before giving up on a first round quarterback too early and as a result, take way too long to move on from a bad investment. And while teams are (understandably) deathly afraid of giving up on a highly drafted quarterback too early, they’re more likely to harm themselves by waiting to move on for too long on a bad investment.

Through six weeks, NFL teams are averaging 6.44 NY/A, meaning Gabbert is averaging only 67% as many net yards per attempt as the average passer. How does that compare historically? The table below shows all drafted quarterbacks who threw at least 250 passes in their second season, and lists their NY/A and NY/A relative to league average during their sophomore years:

QBYearTmAttNY/ANY/A LgAvRd.Ovrl
Dan Marino1984MIA5648.6146%1.27
Ben Roethlisberger2005PIT2687.8131%1.11
Daunte Culpepper2000MIN4747.4127%1.11
Peyton Manning1999IND5337.3126%1.1
Eric Hipple1981DET2797117%4.85
Boomer Esiason1985CIN4316.8117%2.38
Jay Cutler2007DEN4676.8112%1.11
Matt Robinson1978NYJ2666109%9.227
Bernie Kosar1986CLE5316.3107%1.1
David Carr2003HOU2956.2106%1.1
Josh Freeman2010TAM4746.5105%1.17
Kerry Collins1996CAR3646.1105%1.5
Trent Edwards2008BUF3746.4105%3.92
Brett Favre1992GNB4716104%2.33
Eli Manning2005NYG5576.1104%1.1
Drew Bledsoe1994NWE6916.2104%1.1
Doug Williams1979TAM3975.9103%1.17
Joe Flacco2009BAL4996.3103%1.18
Jim Everett1987RAM3026103%1.3
John Elway1984DEN3806103%1.1
Gus Frerotte1995WAS3966.1103%7.197
Michael Vick2002ATL4216102%1.1
Brian Griese1999DEN4526102%3.91
Rodney Peete1990DET2716101%6.141
Vinny Testaverde1988TAM4665.9100%1.1
Charlie Batch1999DET2705.899%2.60
Joe Montana1980SFO2735.999%3.82
Byron Leftwich2004JAX4416.199%1.7
Tom Brady2001NWE4135.899%6.199
Craig Erickson1993TAM4575.799%4.86
Jake Plummer1998ARI5475.898%2.42
Timm Rosenbach1990PHO4375.998%1.2
Tony Eason1984NWE4315.898%1.15
Matt Ryan2009ATL451697%1.3
Tarvaris Jackson2007MIN2945.997%2.64
Tony Banks1997STL4875.597%2.42
Chuck Long1987DET4165.797%1.12
David Woodley1981MIA3665.897%8.214
Vince Young2007TEN3825.997%1.3
Carson Palmer2004CIN4325.997%1.1
Drew Brees2002SDG5265.696%2.32
Jim McMahon1983CHI2955.795%1.5
Mark Sanchez2010NYJ5075.895%1.5
Billy Joe Tolliver1990SDG4105.795%2.51
Alex Smith2006SFO4425.694%1.1
Mike Pagel1983BAL3285.694%4.84
Steve Walsh1990NOR3365.694%1.1
Shaun King2000TAM4285.493%2.50
Neil O'Donnell1991PIT2865.593%3.70
Chad Henne2009MIA4515.792%2.57
Patrick Ramsey2003WAS3375.392%1.32
David Whitehurst1978GNB3285.192%8.206
JaMarcus Russell2008OAK3685.590%1.1
Don Majkowski1988GNB3365.389%10.255
Tyler Thigpen2008KAN4205.589%7.217
Trent Dilfer1995TAM4155.389%1.6
Danny Kanell1997NYG294588%4.130
Troy Aikman1990DAL3995.288%1.1
Marc Wilson1981OAK3665.287%1.15
Todd Blackledge1984KAN2945.187%1.7
John Friesz1991SDG4875.287%6.138
Chris Miller1988ATL3515.187%1.13
Donovan McNabb2000PHI5695.187%1.2
Steve Fuller1980KAN3205.286%1.23
Browning Nagle1992NYJ387586%2.34
Joey Harrington2003DET554586%1.3
Charlie Frye2006CLE392584%3.67
Kellen Clemens2007NYJ250583%2.49
Cade McNown2000CHI2804.882%1.12
Rick Mirer1994SEA3814.982%1.2
Colt McCoy2011CLE4635.282%3.85
Steve DeBerg1978SFO3024.480%10.275
Phil Simms1980NYG4024.880%1.7
Tim Tebow2011DEN2714.978%1.25
David Klingler1993CIN3434.578%1.6
Sam Bradford2011STL3574.977%1.1
Kyle Boller2004BAL4644.675%1.19
Jeff George1991IND4854.575%1.1
Andrew Walter2006OAK2764.474%3.69
Akili Smith2000CIN2673.560%1.3

If your quarterback plays poorly in his second year, you’re basically hoping he’s Phil Simms (who had his first strong season at age 30) or the good version of Jeff George. Maybe Sam Bradford or [gasp] Tim Tebow, will also become solid starters in the NFL one day. But that’s only one part of the equation, and it’s the minor half. You could have the next Akili Smith or Kyle Boller or David Klingler or Colt McCoy or Rick Mirer or Cade McNown or Joey Harrington, too.

You might think it’s far better to wait a year too long with a first round investment than to cut bait a year too early. Tell that to the Ravens, who after two years of Kyle Boller, chose to wait it out in the 2005 draft and selected Mark Clayton over Aaron Rodgers (why take Rodgers, Cal quarterbacks are terrible!). Detroit selected Joey Harrington with the third pick in the 2002 draft, but as Lisk noted, Detroit could have reasonably “given up” (more on this in a second) on Harrington by the end of the 2003 season. The Lions did not, and selected Roy Williams in the 2004 draft instead of say, Ben Roethlisberger.

And “give up” doesn’t necessarily mean cut or spend a first round pick on another quarterback. Assuming Joe Flacco re-signs with Baltimore, there won’t be any real options in free agency for the Jaguars to address the quarterback position (Jason Campbell is probably the best of the bunch). But they can certainly address the issue in the draft. If a quarterback the Jaguars’ scouts view as elite is available with their (potentially very high) first round pick, then I don’t think you can simply say “let’s give Blaine one more year.” But at a minimum, the Jaguars must spend a pick on a quarterback in the 2013 draft if Gabbert doesn’t improve over the rest of 2012.

  1. Of course, there is the obvious “chicken or the egg” question involved there. The other four teams on that list? The 2004 Ravens (Kyle Boller), 2003 Lions (Joey Harrington), 1997 Buccaneers (Trent Dilfer) and 1992 Bengals (Boomer Esiason/David Klingler) featured four first round quarterbacks who ended up being busts. []
  2. Note that for purposes of this post, I am considering Eli Manning, Philip Rivers, Jim Everett, and John Elway as being drafted by the Giants, Chargers, Rams and Broncos. []
{ 21 comments }

Week 6 Power Rankings

Eli, what is your reaction to people picking the Giants to be #1?

Jason Lisk and the wisdom of crowds say the Giants are the best team in the league; Aaron Schatz’ DVOA numbers agree. The computer operated by Brian Burke prefers Denver and Bill Barnwell’s wheel landed on Chicago. ESPN prefers the Falcons, a pick that is surely more retrodictive than predictive.

Technically, I don’t do power rankings, because I don’t even know what power rankings are supposed to represent. What I do is predict how many games I expect each team to win in 2012. And while it was ugly and under the spotlight, Houston’s performance against the Packers on Sunday Night wasn’t enough to make me think any other team ends up winning more games than the Texans will this season.

[As always, the number of wins I’m projecting each team to finish the season with is in column 3. The fourth column – PWIN – shows how many wins I projected last week, and the difference column represents how many wins I added or subtracted this week. The “RSOS” column stands for the remaining SOS for the team, based on the number of projected wins I’m giving to each of their opponents. The “RHG” column stands for remaining home games.]

TeamRecWinsPrvWinDiffRemSOSRemHGComment
Houston Texans5-11213-10.4695I'm not sure how many teams would have beaten the Packers last week. The gap between Houston and the next best AFC team is still significant.
Atlanta Falcons6-0121200.4445Their last 5 wins have all come against quarterbacks drafted in the top 4: Carson Palmer, Robert Griffin III, Cam Newton, Philip Rivers, and Peyton Manning.
San Francisco 49ers4-21112-10.5315A reality check for a 49ers team that looked unstoppable a week ago. Last week I wrote "I can't imagine projecting SF under 12 wins again this year." My imagination is pretty narrow, apparently.
Chicago Bears4-1111010.5116Chicago just experienced the greatest bye week ever according to every power ranking I've seen.
Denver Broncos3-311920.3945According to Advanced NFL Stats, Denver is the best team in the league. Their remaining schedule is absurdly easy, so I'm going to perhaps prematurely give them a two-win bump. Their week 15 game in Baltimore may be for a bye, and I now think Denver is the favorite.
New England Patriots3-31012-20.5136New England is three plays away from being 6-0, but with terrible pass defense, I'm not sure they're that much better than their record.
Baltimore Ravens5-11011-10.5134Baltimore's defense is forced to rely on the continued good health of Ed Reed. Now, he latest news is that Reed has been playing with a torn labrum.
Green Bay Packers3-310910.4635As bad as the season has been, the Packers looked like world champs against the Texans. Now we just need to see some consistency.
Pittsburgh Steelers2-3911-20.4556Pittsburgh, I just can't quit you. I still kind of think the Steelers are a Super Bowl contender, but only because I'm an idiot. Still, a 7-4 record the rest of the way isn't a high bar for them against this schedule.
New York Giants4-29900.5445I've projected the Giants at 9 wins every week so far, and I'm not going to change now. The Giants are plagued by inconsistency, so I won't drop them from 9 wins if they lose to Washington this week.
Miami Dolphins3-39810.4945I'm on the bandwagon, although the Rams win was really ugly. Still, Philbin Phever!
Seattle Seahawks4-29810.5385Brutal remaining schedule and serious doubts about their offense makes it hard for me to bump them to 10 wins, but a huge win over New England.
Minnesota Vikings4-289-10.5635I knew it! Minnesota could not prove that they were "for real for real"!
Arizona Cardinals4-289-10.5814I'd like to pat myself on the back for having Arizona at 9 wins two weeks ago. :patsback:
Philadelphia Eagles3-389-10.4945Okay, even Eagles apologists have to wonder what's going on here. I'm no longer giving this team the benefit of any doubt.
San Diego Chargers3-38800.4445They're terrible, I know, but they still have games against CLE, KC, TB, CIN, CAR, NYJ and OAK.
Dallas Cowboys2-38800.4896The Cowboys had a bad week, but they still have an edge on the Giants and could win the division if they defeat New York at home in 10 days.
New York Jets3-38710.4944Jets have already been 1-1, 2-2 and 3-3; can see them at 4-4 in two weeks, too.
Washington Redskins3-38620.4945Robert Griffin III is two good games away from being the MVP of the first half of the season. RG3 is 4th in ANY/A and 2nd in both rushing touchdowns and yards per carry.
Cincinnati Bengals3-378-10.5136Lose to the Browns: Drop 1 win.
New Orleans Saints1-47700.5345How is Drew Brees 23rd in completion percentage?
St. Louis Rams3-37700.5505With the exception of the Bears game, St. Louis has looked pretty good every week.
Buffalo Bills3-37610.5066The most uninspiring road win ever against a 4-1 team.
Detroit Lions2-36600.5806Big win over Philadelphia but I'm not sure if much has changed in Detroit. What can they do against that schedule?
Carolina Panthers1-46600.5065Cam Newton's body language last week was invisible.
Tampa Bay Buccaneers2-36600.5175The next five games are against New Orleans, Minnesota, Oakland, San Diego, and Carolina. I have no idea how any of those games will go.
Indianapolis Colts2-36600.4665I pat myself on the back for the extreme caution I advised regarding the Indy bandwagon. The sign that I have only two pats on the back is not good.
Tennessee Titans2-46510.4945Not a lot to like here, which makes them a darkhorse playoff team in the AFC.
Kansas City Chiefs1-556-10.4505Join the 2005 Texans as the only teams to fail to hold a lead for even a second in any of their first six games.
Oakland Raiders1-45500.4206Good showing in Atlanta, but even a 4-7 record might be pushing it for this team the rest of the way.
Jacksonville Jaguars1-45500.4835Big game this week in Oakland, which should show if there's any hope for a playoff push or if they're competing for the #1 pick.
Cleveland Browns1-54310.4945Welcome to 2012, where every AFC team has a chance to make the playoffs.
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NYT Fifth Down: Post-week 6

If you feel like this has been one of the most unpredictable seasons so far, you’re right:

Pete Rozelle dreamed of a parity-filled league in which any team could win on a given Sunday. If alive today, the former N.F.L. commissioner would surely smile at how the 2012 season has started. Half of the league’s 32 teams have 2-3, 3-3 or 3-2 records, just the third time since 1970 that the league was so tightly packed after six weeks.

Only in 2001 — the year New England became one of the unlikeliest Super Bowl champions — were more teams (17) within a half-game of .500 after six weeks. The last two seasons, roughly two-thirds of the teams had at least two more wins than losses or losses than wins. But the first third of the 2012 season has been among the most unpredictable stretches in modern N.F.L. history. Consider: Underdogs are 57-32-2 against the spread this year, the second-highest rate after six weeks in 35 seasons.

Since 1978, underdogs have won just over 50 percent of games against the spread during the first six weeks of a season, and only in 1999 did underdogs fare better than they have this year. Underdogs are 40-51 in games this season, the first time in N.F.L. history that after six weeks, 40 underdogs have won games outright.

In the A.F.C., as noted last week, parity is just a euphemism for mediocrity.

In August, the New England Patriots were the favorites to win the Super Bowl; in mid-October, they’re a 3-3 team with a pass defense that is allowing 7.5 net yards per pass attempt and a pass offense that’s averaging only 6.9 NY/A. The Patriots were everyone’s choice to win the A.F.C. East, and there was similar unanimity that Miami would occupy the division’s cellar. Right now, all four teams in the division are 3-3, with Miami having the longest winning streak — at two games.

The Pittsburgh Steelers won 12 games and led the league in points allowed in three of the last four seasons before 2012. This year, Pittsburgh is 2-3 and ranks in the bottom half of the league in points allowed, as an aging defense has been the team’s Achilles’ heel.

Last year’s surprise team in the conference was the Cincinnati Bengals, who built on that success by starting this year 3-1… before promptly losing consecutive games as favorites in Weeks 5 (Miami) and 6 (Cleveland).

The Tennessee Titans looked to be one of the worst teams in the league entering Week 6 but emerged with an upset win over Pittsburgh.

The Indianapolis Colts appeared to have “arrived” following a come-from-behind victory over Green Bay, only to have been pronounced dead on arrival by halftime in their game against the previously hapless Jets.

A few days ago, the Houston Texans were considered the best team in the league at 5-0, but on Sunday, the Texans lost to… the Packers, who couldn’t even beat the Colts last week, who couldn’t beat the Jets this week, who couldn’t beat… Houston last week.

The Kansas City Chiefs lost a nailbiter, 9-6, to the Ravens last week, but were blown out by Tampa Bay, 38-10, on Sunday.

The Oakland Raiders had been outscored by 15 points per game entering a Week 6 date in Atlanta, home of the only undefeated team in the league. Shockingly — or in 2012 parlance, as expected — Oakland led most of the game, losing only in the final seconds on a 55-yard field goal.

On Monday Night, the 3-2 San Diego Chargers hosted the 2-3 Broncos, so obviously Denver won after San Diego raced out to a 24-0 halftime lead. The Broncos became the first team to trail by 24 or more points at halftime and win by double digits.

The N.F.C. may have the more talented teams, but it is not immune from the parity virus.

You can check out the rest of the article here.

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Checkdowns: Patriots Passing Game Struggles

If there was one thing you can count on in New England, it’s that the Patriots passing attack would be more efficient than their opponent’s nearly every week. From 2003 to 2011, New England averaged 6.9 net yards per pass attempt while their defense allowed 6.0 NY/A. But this season, the Patriots passing offense is struggling by New England standards while the pass defense is worse than ever. Take a look:1

YearAttYdsSkOpp_AttOpp_YdsOpp_SkNY/ANY/A ADiff
20122431758132191733116.97.5-0.7
20116125084326194703407.97.10.8
20105073847256114136367.26.40.8
20095924436185123355317.36.21.1
20085363569464743219316.16.4-0.2
20075864731215263041477.85.32.5
20065273400295183203446.15.70.4
200556441202852737033376.60.3
200448535882653834004575.81.2
200353734323261832324164.91.1
20026053577315313179345.65.60
20014823089465463497415.96-0.1
20005653181485443522295.26.1-1

Playing the Jets on Sunday is the perfect medicine for a NY/A-imbalance, but what do you make of New England’s struggles this year?

  1. Note that the table below lists team passing yards, which already deducts sack yardage lost []
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I’m always interested in creative ways to maximize your team’s chances of winning. A few weeks ago, I wrote that when trailing by 14 or 15 points, teams should go for two if they score a touchdown. A different scenario came up during the Ravens-Cowboys game, as Baltimore was up 24-23 with just under five minutes to go when Ray Rice went in for a one-yard score. At that point, some clamored that Baltimore should have gone for two and essentially put the game away. A conversion would have given the Ravens a 9-point lead, while a miss would still leave Baltimore a touchdown. On the surface, it might sound like a risk-free proposition, where even if the gamble fails, you’re still in good shape.

But I don’t think I’d advocate for the bold decision in that situation. In essence, you’re deciding whether your offense is more likely to convert when going for two than your defense is likely to prevent your opponent’s attempt. The decision depends on the likelihood of success: If the league-average rate was 75%, then you’d want to go for two, but if the average rate was 25%, you’d rather force your opponent to have to convert.

In reality, the conversion rate hovers around 50% in the NFL. From 2007 to 2011, teams went for two on 269 plays and converted on 130 of them (48.3%). We can break that down further:

  • On 21 quarterback runs, the conversion was successful 13 times (62%). That is made consists of a 6-for-11 rate on runs up the middle and a 7-for-10 rate on other quarterback runs (which may include some scrambles on designed pass plays).
  • On 50 running back runs, teams converted 33 times (66%). That includes being 21-of-32 on runs to the outside and a 12-for-18 rate on runs up the middle (which includes two Danny Woodhead runs from shotgun).
  • There were also three trick plays with wide receivers throwing passes (Cedrick Wilson, Josh Cribbs and Anquan Boldin) with two of them being successful.
  • On the other 195 pass plays, four times the quarterback was sacked (2%), twice the pass was complete but short of the end zone (1%), and 107 times the pass was incomplete (55%). That leaves 82 successful passes (42%) on two-point conversion pass attempts.

It’s tempting to say that teams should simply run the ball more frequently in these situations, but I think we need to be careful and not let the data speak too loudly. The fact that teams passed on 74% of these plays is itself an indication that passing is the higher-percentage play. When a backup running back has a higher yards per carry average than the starter, it doesn’t mean that the starter is the worse player. I think running is a nice surprise move in these situations, but if teams ran more frequently, the success rate would surely drop (of course, the success rate on passes would then increase, which might make it wise just as a matter of course for teams to try to run more frequently in these admittedly rare situations).

In any event, I don’t think teams should get overconfident about their ability to convert when going for two. However, it’s worth noting that usually it is losing teams — and perhaps that means bad teams — that are going for two. Indeed, on only 108 of the 269 conversion attempts (40%) was the team winning before attempting to go for two. In those 108 cases, teams converted 60 times (56%). For what it’s worth, 31 of the 71 rushing plays (44%) came in these situations, and teams were 41-of-77 (53%) when passing with the lead.

So there does seem to be something to the idea that “bad” teams are dragging down the league average rate, although we’re dealing with small sample sizes. It’s the easy way out, but my gut tells me the actual rate really is right around 50/50.

In that case, does going for 2 up by 1 (before the touchdown) make sense? I don’t think so, unless your offense is much better than your defense (or your opponent’s offense is much better than its defense). In some ways, we should be indifferent about whether we go for two or if our opponent is forced to; it’s like caring about whether you get to call the coin toss or your opponent does.

Say you are up by 1 point and score a touchdown with two minutes to go. Let’s stipulate that the opponent has a 28% chance (to use what will be round numbers in a minute) of going down and scoring to tie it up. If you kick the extra point to go up 8, you have a 93% chance of winning — a 72% chance you stop your opponent plus a 14% chance that even if they score, you stop them on the 2-point conversion, plus another 7% chance that even if they force overtime, you win.

Now, if you go for two and convert, let’s say you have a 100% chance of winning. So converting gives you an extra 7% chance of winning. If you go for two and miss, you still have an 86% chance of winning — the 72% chance your opponent does not score plus the 14% chance you win in overtime. So choosing to go for two and missing only lowers your odds 7% — again, teams should be relatively indifferent about whether it is them or their opponent who ultimately goes for two, assuming the roughly 50% success rate.

But the above analysis is ignoring something, which to me, makes the decision easy. With a minute to go, and a good offense and bad defense, maybe you go for two. But that’s not the situation Baltimore was in — the clock read 4:41 when Rice scored his touchdown. Here is the part that is counter-intuitive but true assuming a 50% conversion rate: the difference between being up by 7 or being up by 8 is *larger* than the difference between being up by 8 or being up by 9.

That’s because going for 2 and converting doesn’t end the game; your win probability doesn’t shoot up to 100%. Down 9, the opponent will play more aggressively, knowing they need two scores. Assume you go for 1 and extend the lead to 8. If your opponent faces a 4th and short on their next drive, they may still punt, because it’s (in their minds) a one-possession game. They won’t punt if down by 9. They are more likely to take their time trying to score (which is beneficial to you, the leading team), which means the odds are very low that they win in regulation. Trailing by 9, they know they need two scores, and will play more aggressively to win the game. To me, I don’t see any reason to incentive bold moves by my opponent, and the more time remaining, the worse the decision to try to “ice the game” by going up 9 looks.

The Ravens game provides a good example. Suppose Baltimore had gone for two and missed. Well, the Cowboys went down and scored, and would have kicked off to the Ravens. Instead — in this case, it is irrelevant that Baltimore kicked the XP and Dallas missed the 2-point conversion, we can assume Baltimore went for two and made it — the Cowboys went for the onside kick and got the ball back. That’s not a move you make in a tie game, but one an aggressive team trailing has to do. Going for 2 early doesn’t bring your win probabiliy up to 100%, and this effect is magnified the more time remaining in the game.

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Joe Philbin tips his hat to good coaching.

While most coaches act like they’re on autopilot when it comes down to crucial 4th down decisions, let’s credit a coach who took his job title literally this weekend.

Did you hear about what Joe Philbin did? No? Then it must have worked. Leading 17-14 with 4:15 to go, Miami faced 4th and 1 from their own 40. As Jason Lisk noted, going for it here makes a lot of sense due to the time remaining. With 4 minutes to go, the Rams wouldn’t drain the clock even if they scored, so your worst case scenario is something like down by 4 with a minute to go. More likely (and that’s probably being too kind to Jeff Fisher), the Rams would play it uber conservatively, and either miss a long field goal or convert with more than a minute remaining, giving Miami ample time to regain the lead. Miami called for a fake punt — advisable in an age when coaches don’t think teams should go for it in these circumstances — and converted. They punted a few plays later, but the Rams had less than two minutes to go and the ball at their own three. They had to settle for a 66-yard field goal, and missed, giving Miami the win.

Honorable mention: Pete Carroll doesn’t really deserve credit here, but we grade on a scale at Football Perspective. Trailing 23-10 with 7:26 left in the 4th quarter, Carroll chose to go for it on 4th and 3 from the Seattle New England 10. Obvious? Maybe, but how many coaches would “take the 3 points,” thinking they could transform a two-score game into a … two-score game. Carroll had Russell Wilson throw a fade in the end zone to Braylon Edwards, who came down with the touchdown. What coach might kick it there? How about Marvin Lewis, who once did so on 4th and 8 from the 8 with less than 7 minutes to go.

And on the other side…

Bruce Arians twice declined to go for it on 4th and 1 against the Jets. On Indianapolis’ opening drive, the Colts stalled at the Jets 40-yard line. Facing 4th and 1 against a weak offense in enemy territory? On the opening drive of the game, this should be as easy a decision as it gets, but Bruce Arians chose to punt. It was a good one — downed at the Jets 3 — but that’s a poor tactic. New York went three-and-out, and Indianapolis took over at their own 41. They drove down to the Jets one-yard-line, and then… sent Adam Vinatieri in to kick a field goal to take a crucial (?) 3-0 lead midway through the first quarter.

Making those blunders even worse: Rex Ryan’s fake punt with Tim Tebow was perhaps the turning point in the game. New York was up 14-6 with just over two minutes to go, but faced 4th and 11 on the Indianapolis 40. A punt and Andrew Luck gets to work his two-minute drill magic, and we could have a 14-13 or tie game at halftime. The Jets faked the punt, converted, and scored a timeout with only seconds left in the half. That decision set in motion the events that led to a 21-6 halftime lead, and the game was effectively over.

Facing 4th and 1 with an explosive offense and a mediocre defense, against a team with an occasionally explosive offense and always terrible defense, Atlanta’s Mike Smith chose to punt from his own 45-yard line in a tie game with 6:26 remaining. The Raiders would drive down the field, only to have Carson Palmer and Asante Samuel do what they do best — throw lazy out routes and jump on sideline routes for interceptions, respectively — to help give Atlanta the victory. Samuel must have intercepted it because of the big boost of faith his coach put in the defense!

Were you surprised to see the Redskins defeat the Vikings? On each of Minnesota’s first three drives, the Vikings got inside the Washington ten-yard line, but settled for three field goals. The 4th down decisions weren’t terrible, but the third-down calls were. On 3rd-and-goal from the 5, Christian Ponder threw a short pass to Toby Gerhart who was tackled at the 3. An okay call if you plan to go for it on 4th down, but alas, Blair Walsh was sent onto the field for the ill-advised, 20-yard attempt.

On the next series, Minnesota faced 3rd and 12 from the 16, and Ponder threw a short pass to Adrian Peterson who gained seven yards. Why? Admittedly I didn’t see this game so it’s possible this was a checkdown.

On the third series of the game, facing 3rd and 4 from the 10, Minnesota… ran Toby Gerhart over the left guard for one yard. No one needs to have watched the game to roll your eyes at that decision.

Still, the 9-0 lead was huge for Minnesota, or should I say, would have been huge for Minesota if this was 1944. Instead, Robert Griffin III and Washington scored 38 points in the final three quarters, a shocking development for a team that, you know, is ranked third in the league in points. This was some surprisingly conservative playcalling for the team that pulled one of the upsets of the year against San Francisco, which started when Kyle Rudolph scored a one-yard touchdown on 4th and goal in the first quarter.

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Here’s a quick Monday data dump… I ran the Simple Rating System (for offense and defense) on this year’s NFL results, but instead of weighing each game equally, I used Wayne Winston’s method of giving more weight to recent outcomes. Winston’s system is simply to give each game a weight of:

λ ^ (weeks ago)

In the NFL’s case, a λ of 0.95 works best for predicting future outcomes. The games from yesterday were (6 – week 6) = 0 weeks ago, so they get a weight of .95 ^ 0, or 1.00. Last week’s games were (6 – week 5) = 1 week ago, and get a weight of .95 ^ 1 = 0.95; the opening-week games were (6 – week 1) = 5 weeks ago, and get a weight of .95 ^ 5 = 0.77. See how it works?

Using this weighted form of SRS, here are the rankings going into tonight’s game (NOTE: For defenses, negative SRS numbers are better):

RkTeamGmsWLOffDefSRSwpa_locwpa_vegaswpa_1stwpa_2ndwpa_3rdwpa_4th/ot
1Chicago Bears5417.6-7.615.2-0.070.480.130.020.730.22
2New York Giants6429.8-3.012.80.000.260.060.210.050.43
3San Francisco 49ers6420.5-10.410.90.000.80-0.040.210.30-0.28
4New England Patriots6339.00.48.6-0.141.000.620.000.27-1.75
5Green Bay Packers6334.9-2.57.50.000.670.440.06-0.64-0.53
6Seattle Seahawks642-2.0-8.76.60.00-0.200.68-0.740.191.07
7Houston Texans6514.6-1.25.80.001.34-0.190.760.12-0.02
8Atlanta Falcons6602.3-3.25.40.000.610.520.200.411.25
9Denver Broncos5232.5-2.24.70.07-0.13-0.34-0.630.120.41
10Tampa Bay Buccaneers523-0.5-4.54.00.07-0.420.350.200.36-1.06
11St Louis Rams633-2.8-6.73.90.00-0.770.020.27-0.100.58
12Dallas Cowboys5231.4-2.33.6-0.070.23-0.21-0.18-0.400.13
13Baltimore Ravens6511.4-2.13.50.140.65-0.310.760.060.70
14Arizona Cardinals642-3.8-5.71.90.14-0.360.080.10-0.191.22
15Washington Redskins6337.35.51.80.00-0.150.010.751.15-1.76
16Minnesota Vikings642-2.3-3.10.80.00-0.010.71-0.36-0.010.67
17Miami Dolphins633-2.8-2.5-0.30.00-0.59-0.010.741.29-1.43
18Detroit Lions5235.27.2-2.0-0.070.20-0.31-0.82-0.330.83
19Carolina Panthers514-2.5-0.4-2.20.07-0.12-0.84-0.050.24-0.80
20Philadelphia Eagles633-6.5-3.8-2.70.000.52-0.68-0.310.70-0.24
21New York Jets633-2.30.5-2.80.14-0.400.04-0.10-0.410.73
22San Diego Chargers532-3.3-0.5-2.8-0.070.270.450.020.36-0.53
23Cincinnati Bengals6330.34.9-4.6-0.140.170.610.43-1.210.14
24New Orleans Saints5143.27.8-4.60.070.390.05-0.95-0.08-0.99
25Pittsburgh Steelers523-2.02.8-4.8-0.070.540.130.160.18-1.44
26Cleveland Browns615-2.13.0-5.00.00-1.15-0.21-0.740.080.02
27Buffalo Bills6330.99.1-8.3-0.14-0.310.320.02-0.140.25
28Indianapolis Colts523-1.86.8-8.60.07-0.620.25-0.350.020.13
29Oakland Raiders514-4.26.6-10.8-0.07-0.39-0.240.30-1.550.45
30Kansas City Chiefs615-7.16.5-13.60.00-0.76-1.110.05-1.000.82
31Tennessee Titans624-4.98.9-13.80.00-1.15-0.610.39-0.350.72
32Jacksonville Jaguars514-10.73.3-14.00.07-0.60-0.38-0.44-0.210.06


I also included a breakdown of each team’s quarter-by-quarter Win Probability Added (WPA), so you can see where each team’s wins above/below average thus far have come from.

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Rating offenses and defenses since 1970

NFL offenses and defenses are not mirror images of each other. The gap between the best and worst offenses is generally bigger than the spread on the defensive side of the ball. And strength of schedule is more likely to play a key role when it comes to determine the best and worst defenses, too. Today’s post is a two-parter: in Part I, we look at some data on the best and worst teams in the modern era, while Part II analyzes the above claims.

Ranking offenses (or defenses) isn’t easy. I don’t like using yards, which is misleading in a lot of ways. Points scored sounds good, but non-offensive scores and other big plays on defense and special teams can make that metric less telling. There are some very good advanced metrics, but they don’t help us if we want to go back to the 1970s. So I simply used offensive touchdowns scored to rank the offenses and offensive touchdowns allowed to rank the defenses. And since I’m going to go back to 1970, I’ll be comparing each unit to the league average in that season.

Part I – Team Rankings

In addition, I’m going to adjust the offenses and defenses for strength of schedule. I’ll be doing this in an iterative way just like I do with the SRS. Listed below are the top 100 teams since 1970 in terms of offensive touchdowns per game over average (and in addition to adjusting for strength of schedule, I’ve pro-rated the non-16 game seasons to 16 games). The first line shows the 2007 Patriots, who scored 67 offensive touchdowns when the league average was 34.6. Therefore, NE gets credit for being 32.4 touchdowns over average. The Patriots’ schedule was actually difficult (once you adjust for the fact that their opponents faced New England) — it cost the offense nearly 2 touchdowns — so their final rating is +34.4.
[click to continue…]

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