A closer look at the New England Patriots defense

No one suggests that the Patriots defense is good, or even average. For starters, well, look at the starters. Here was New England’s starting lineup this weekend against the Broncos:

I'm working on it

DE	 Brandon Deaderick 
DT	 Kyle Love 
DT	 Vince Wilfork 
DE	 Andre Carter 
OLB	 Jerod Mayo 
MLB	 Dane Fletcher 
OLB	 Rob Ninkovich 
CB	 Devin McCourty 
FS	 Matt Slater 
SS	 James Ihedigbo 
CB	 Kyle Arrington

Casual fans have heard of Wilfork and Mayo, and McCourty was one of the top rookies in the league last season. But don’t feel bad if you’ve never heard of Deaderick (2010 7th rounder) or Love (undrafted) or Fletcher (undrafted from Montana State) or Slater (5th round draft pick — at wide receiver — who converted to safety in the middle of this season), and it’s not like Ihedigbo (undrafted, special teams ace for the Jets) , Arrington (undrafted, Hofstra) and Ninkovich (5th round pick by New Orleans) are high profile players, either. Now that Andre Carter — New England’s best pass rusher — is out for the season, the situation looks even worse. And among the “name players” on the Patriots’ defense, only Mayo (who missed several games earlier this season) isn’t having a disappointing season.

The Patriots do not have much talent on defense. So it’s not too surprising that the Patriots rank last in the league in yards allowed. But the situation is even bleaker than that. The 1981 Baltimore Colts were one of the worst teams in football history; they’re also the only team that allowed 5800 or more yards in the first 14 games of the season. Well, they were: now the Patriots have joined the list.

But the Patriots total defense is still better than the Patriots pass defense. Until this season, no team had ever allowed more than 3,910 passing yards after 14 games; the Patriots have allowed 4,154.

Part of that historical ineptness is because the Patriots often play with the lead. New England has faced the third highest number of pass attempts this season, and ranks 30th (as opposed to 32nd) in net yards per pass attempt. So instead of having a historically terrible pass defense, it’s probably fairer to just note that they have one of the league’s worst pass defenses. New England’s rush defense isn’t very good — the Pats rank 26th in yards per carry allowed, and because they face so many more passes than rushes, 19th in rushing yards allowed.

But New England ranks 14th in points allowed. That means despite a terrible pass defense and a bad rush defense, the Patriots actually have allowed fewer points than the average team this season. So what gives?


Who should be the NFL rookie of the year? Cam Newton vs. Andy Dalton

Cam Newton and Andy Dalton are having outstanding rookie seasons. Newton has been setting records since the beginning of the season, while Dalton has helped make Cincinnati the NFL’s most surprising playoff contender. With the season 11 weeks old, many fans are thinking about who will wind up winning some of the NFL’s main individual awards. Aaron Rodgers has just about locked up the AP MVP award and should probably grab the AP Offensive Player of the Year Award, too. The AP Defensive Rookie of the Year will almost certainly be Von Miller, also known as the “other” reason the Denver Broncos have won five of their last six games. But what about the Offensive Rookie of the Year award?

"Cam, is the rookie of the year award a done deal?" "Like they say...."

Realistically, either Dalton or Newton will win the award. DeMarco Murray and A.J. Green are having great seasons for a rookie running back and wide receiver, respectively, but the AP Offensive Rookie of the Year award is as much about position as performance.

From 1967 to 1983, the award went to a running back in all but three seasons. In 1968, Terry Cole led all rookie running backs with only 418 yards, so the award went to the top rookie receiver that season, Earl McCullouch. In 1970, the top rookie running back was Dallas’ Duane Thomas, but he had been less impressive than the Cowboys’ 1969 offensive rookie of the year, Calvin Hill. The top receiver, Ron Shanklin, was unspectacular, so the award actually went to Buffalo quarterback Dennis Shaw. Shaw had a an ugly 3-8-1 record, but all of his wins were 4th quarter comebacks. He also finished 6th in the league in passing yards. In 1976, wide receiver Sammy White had a monster year for the Vikings while no rookie running back stood out.

In fact, from the inception of the award in 1967 until 2003, Shaw was the only quarterback to win the award. But since then, Ben Roethlisberger, Vince Young, Matt Ryan and Sam Bradford have taken the award in every even year starting in ’04. In 2005, Kyle Orton was the only rookie QB with at least 200 attempts; while his 10-5 record was nice, his individual statistics were terrible, and Cadillac Williams took home the award. In 2007, Adrian Peterson was an obvious selection, and it probably didn’t hurt that Trent Edwards was his top competition at quarterback. In 2009, Percy Harvin won the award on the basis of his receiving and returner skills, while Matthew Stafford, Mark Sanchez and Josh Freeman were each busy throwing seven to eight more interceptions than touchdowns and completing fewer than 55% of their passes.


Can inexperienced quarterbacks succeed in the playoffs? The Houston Texans and the T.J. Yates experiment

The Houston Texans are currently having the finest season in their nine-year existence. With an 8-3 record, Houston is almost certainly going to make the playoffs. But after losing quarterbacks Matt Schaub and Matt Leinart in consecutive games, the Texans are down to their third string quarterback.

Doing a lot of this

That man is T.J. Yates, a rookie quarterback out of North Carolina. Yates did manage to torch LSU for over 400 yards and 3 touchdowns last season, one of three 400-yard performances by Yates in his senior season. But you can’t fault Texans fans if they’re a little concerned.

Houston signed Jake Delhomme this week, but he’s expected to serve as the primary backup and mentor. If the Texans go with Yates for the final five games of the season, will he be the most inexperienced quarterback to ever start a game in the playoffs?

Hardly. There have been 13 quarterbacks to start a playoff game with five or fewer career regular season starts. In fact, he’d only be the third rookie quarterback with to be inserted into his team’s lineup for the last five games of the season and then start in the playoffs. Perhaps more surprisingly, there have been five times since 1960 when a quarterback made only one regular season start in his entire career before being called on to start a playoff game. Going chronologically:

Tom Matte, 1965 vs. the Green Bay Packers

In 1965, the NFL was a 14-team league with two divisions. The playoffs were simple: the two division winners would play in the last championship game before the start of the Super Bowl era. Under Johnny Unitas, the Colts raced out to 7-1 record, with the only loss coming at Lambeau Field by a score of 20-17 in week two. Unitas missed the Colts’ ninth game with a back injury, but backup Gary Cuozzo (more on his reputation as the best backup quarterback in football here) led the Colts to victory and threw for five touchdowns in his absence. Unitas returned the next week and helped the Colts pick up another victory and one tie. By then, the 9-1-1 Colts held a 1.5 game lead on the 8-3 Packers with only three games left to play. But against the Bears, Stan Jones and Earl Leggett tore Unitas’ knee in a classic high-low hit that ended his season. The Colts offense was helpless against Chicago, losing the game 13-0.


Simple Rating System for 11/28/2011 – Finish line in sight, the final picture sharpens

Last week, the Simple Rating System did not have Arkansas in the top three; the SRS was unimpressed by the Razorbacks, which explains why they didn’t drop too much. Last week, the SRS had Arkansas at #13 with a score of 53.4; this week they’re 13th at 52.1. LSU is now alone at the top, with a 1.2 point edge over Alabama. That jives with the early reports that the Tigers will be a 1.5 to 2 point favorite over the Crimson Tide in the potential rematch. Oklahoma State actually drops by over a point because Tulsa dropped by 2.5 points after getting blown out by Houston, and Texas Tech, Texas A&M and Missouri all dropped by a couple of points after unimpressive conference games (and their opponents did not improve by as much). But the Cowboys are still third, and the SRS puts them within a couple of points of Alabama.

Houston had by far its best game of the season this weekend — a 72.5 score after beating Tulsa (43.0) by 32 on the road (adjusted MOV of 29.5). According to the SRS, Houston’s worst five games all came in September. Since then, Houston has an average SRS score of 60.2 in its last seven games with not a single sub-50 performance. I was (appropriately) skeptical of the Cougars based on an easy schedule for most of the season, but they’ve been playing at an elite level for the last two months. The full SRS results:

Rk.  Team                 Conf  G    MOV      SOS      SRS      W-L
1.   LSU                  SEC   12   24.1     41.1     65.2     12-0
2.   Alabama              SEC   12   23.4     40.7     64.0     11-1
3.   Oklahoma St          B12   11   20.0     42.6     62.6     10-1
4.   Oklahoma             B12   11   17.7     43.3     61.1      9-2
5.   Oregon               P12   12   19.0     41.6     60.6     10-2
6.   Stanford             P12   12   19.3     39.9     59.1     11-1
7.   Wisconsin            B10   12   23.0     35.9     59.0     10-2
8.   Boise St             MWC   11   19.8     36.4     56.2     10-1
9.   Michigan             B10   12   15.3     40.1     55.4     10-2
10.  Houston              CUS   12   26.3     27.7     53.9     12-0
11.  Southern Cal         P12   12   11.0     42.4     53.5     10-2
12.  Texas A&M            B12   12    8.0     44.9     52.9      6-6
13.  Arkansas             SEC   12   12.3     39.8     52.1     10-2
14.  Texas                B12   11    7.1     44.0     51.1      7-4
15.  Georgia              SEC   12   13.4     37.6     51.0     10-2
16.  Michigan St          B10   12   12.7     38.1     50.8     10-2
17.  Notre Dame           IND   12    8.0     41.8     49.8      8-4
18.  Missouri             B12   12    6.3     43.3     49.7      7-5
19.  South Carolina       SEC   12   10.1     39.6     49.7     10-2
20.  Baylor               B12   11    5.7     43.9     49.6      8-3
21.  TCU                  MWC   11   15.6     33.6     49.2      9-2
22.  Kansas St            B12   11    4.7     44.0     48.6      9-2
23.  Nebraska             B10   12    7.0     41.5     48.5      9-3
24.  Virginia Tech        ACC   12   12.8     35.4     48.2     11-1
25.  Florida St           ACC   12   13.2     34.2     47.4      8-4

Simple Rating System: Where the SEC is not 1-2-3 – 11/21/2011

Last week, Oklahoma State, Oklahoma and Oregon all ranked in the top five of the SRS. And while all three lost this weekend as big favorites — and each of their SRS ratings dropped significantly — they had built up such a large lead over the rest of the pack that they remain in the top five. Let’s break it down:

Oklahoma State was at 67.3 but lost to Iowa State (SRS of 38.1 before the game) in Ames, Iowa by six points. How shocking was this? The SRS pegged the Cowboys last week as 26.2 point favorite while the actual point spread was 26.5. Oklahoma State played their worst game of the season, producing an SRS score of 33.7 (a -7 adjusted margin of victory against an opponent that — thanks in part to beating OSU — has an SRS score of 40.7). Oklahoma State is now at just 63.7 for the year.

Oklahoma fared a little better, as Baylor (current SRS of 49.4) is a better opponent. Losing by 7 in Waco (SRS grade for OU of 42.4) was still a better performance for the Sooners than the inexplicable 3-point home loss against Texas Tech (32.4), but the two bad performances are somewhat canceled out by the monster blowouts against Kansas State and Texas. Oklahoma dropped from 66.0 to 62.7 with the loss.

Oregon lost at home, but to a much better opponent. USC is now the 13th best team in the SRS, and not just because they took Stanford to triple overtime. The Trojans beat Notre Dame by 14 in South Bend and blew out California, Washington and Colorado. The Trojans were ugly against the good version of Arizona State, but that wasn’t even their worst performance of the season (in week 1, USC won by only two at home against Minnesota). But USC is one of the hottest teams in colege football, scoring an SRS grade of over 60 in four of their last six games. In fact, for SRS purposes, the Stanford loss was their worst game in that stretch.

Oregon put up a -7 adjusted MOV against USC, but USC’s 52.4 rating makes it a somewhat forgivable loss. The Ducks drop from 64.2 to 61.2.

Prior to the game, Oregon was at 64.2 and USC at 52.5, which suggests a point spread of 14.7 points for a game in Eugene. The actual spread was 15.5. Oklahoma was at 66.0 and Baylor at 47.8, which would put the point spread for a game in Waco at 15.2; the actual line was 17. The SRS standings below, along with the projected line for LSU/Arkansas:

Rk   Team                 Conf   G   MOV      SOS      SRS      Rec
1.   LSU                  SEC   11   24.4     40.5     64.8     11-0
2.   Alabama              SEC   11   23.0     41.4     64.4     10-1
3.   Oklahoma St          B12   11   20.0     43.8     63.7     10-1
4.   Oklahoma             B12   10   17.8     44.9     62.7      8-2
5.   Oregon               P12   11   18.5     42.7     61.2      9-2
6.   Stanford             P12   11   20.0     39.5     59.5     10-1
7.   Wisconsin            B10   11   22.5     35.9     58.3      9-2
8.   Boise St             MWC   10   19.9     37.8     57.7      9-1
9.   Michigan             B10   11   16.0     40.6     56.6      9-2
10.  Texas A&M            B12   11    9.4     45.5     54.9      6-5
11.  Arkansas             SEC   11   15.3     38.1     53.4     10-1
12.  Houston              CUS   11   26.0     27.1     53.0     11-0
13.  Southern Cal         P12   11    8.8     43.6     52.4      9-2
14.  Missouri             B12   11    5.6     46.0     51.6      6-5
15.  Texas                B12   10    7.2     44.4     51.5      6-4

Analyzing NFL running games through 10 weeks

NFL teams are passing more frequently and more effectively than ever before. Given enough opportunities, most teams will eventually connect on big plays through the air. But while running backs have taken a backseat in most offenses, a successful rushing attack is still a significant component in most effective offenses.


As teams — and by extension, their opponents — become more prolific at passing, the opportunity cost of not passing increases. That makes an unsuccessful run particularly damaging. A run on third and short that forces a punt, or a run on 1st or 2nd down that makes it harder for his team to move the chains, hurts a team more significantly than ever before. In the ’70s, the running game was supposed to win games for teams, as running was a more effective optionthan passing. In some ways, the goal of the running game now is to not mess things up for the passing game, by forcing a punt or an unfavorable third down situation.

About 25 years ago, Bob Carroll, Pete Palmer and John Thorn wrote the Hidden Game of Football, a fascinating book on football theory and win probability. They went through and graded each play as a success or failure based on how many yards were gained as a percentage of how many yards were needed to pick up a first down or touchdown.

When I wrote a series on the most dominant running backs of all-time, I noted that yards per carry was a misleading statistic for running backs. Rushing is more about consistent success than passing, and rushing has a positive feedback loop in place that might lower yards per carry averages. Yards per carry is highly sensitive to large runs, decreasing the correlation it would have with the overall strength of a running game. I had a discussion with Brian Burke about this a couple of years ago, and he now uses rush success rate in his team efficiency models.

So to analyze NFL running games so far this season, I decided to use my own version of rush success rate. Here’s exactly what I did:

The Simple Rating System: Bringing order (kinda) to chaos

[Ed. Note: This is the first post by my good friend and stat guru Chase Stuart. For at least the rest of this season, Chase will be contributing his unique perspective to the site. Chase has previously contributed to the New York Times Fifth Down and the Pro-Football Reference Blog. You can also follow Chase on twitter.]

The last two seasons, I have published college football ratings using the Simple Rating System. Before explaining how the Simple Rating System (SRS) works, allow me to first explain what the SRS is trying to do (and just as importantly, what it’s not trying to do).

A want and enjoyment of numerosity

Most rating systems fall into one of two categories. A rating system could simply replicate the standings in any particular league; such a rating system would best be described as retrodoctive or explanatory. A retrodictive rating system fits the data to explain what happened in the past. The BCS computer ratings are mostly retrodictive; so are player or team ratings that give significant weight to high-leverage plays that tend to be highly random (clutch play, fumble recovery rates, etc.). An explanatory rating system tries to measure how much a team or player has accomplished in the past; it does not attempt to answer the question “what will happen next?” When Bill Parcells said “You are what your record says you are,” he’s championing retrodictive ratings. So was Rich Kotite when, coaching the 7-2 Eagles in 1994, he said to the media: “Judge me by my record.” An explanatory rating system would say that Kotite and his Eagles were doing well; but it would never have predicted that Kotite would go 4-35 over the next — and final — 39 games of his career.

The other type of rating system is a predictive system, which works as they name implies: it tries to predict the future. Here is a useful chart detailing some of the differences between the two in college football rating systems. Predictive rating systems are not very concerned with wins and losses; instead, they focus on more granular pieces of data. The best and most obvious example of a predictive rating system would be the formulas used by the folks in Vegas. Those who make point spreads aren’t disturbed if their rankings place Team A, which has “accomplished less” than Team B, higher up in their rankings. This weekend produced a useful example. No purely retrodictive rating system would put the Oklahoma Sooners ahead of the Kansas State Wildcats. Oklahoma was 6-1 but lost to a mediocre Texas Tech team; Kansas State was undefeated and had beaten some solid teams, albeit in less than thrilling fashion. Both the BCS ratings and the Associated Press’ rankings had Kansas State over Oklahoma, because those systems are designed to acknowledge accomplishments. But despite being the higher ranked team and playing at home, Kansas State was a 14-point underdog to the Sooners. And Oklahoma promptly went into Manhattan and blew out the Wildcats, 58-17.