Like everything else, the rules disappear when Ogden is involved.

As we hit the halfway mark of the season, some teams are already thinking about next year, and in particular, the 2013 draft. If I was in charge of a bad team, and specifically, a bad passing team, I would try to avoid spending a lot of money or a high first round pick on a left tackle. This philosophy is more guideline than rule — if there is a can’t miss prospect there and/or you are underwhelmed with the other top prospects, then draft the tackle — but spending a high pick on an offensive lineman would be my move of last resort.

Let’s pretend for a few minutes that a top-five pick on a left tackle is going to give you Jake Long or Joe Thomas or Jonathan Ogden, and not Jason Smith or Levi Brown or Robert Gallery or Mike Williams. Now, why is having a star left tackle so valuable? The traditional theory goes that since the left tackle is response for protecting the quarterback’s blind side, he’s the most important member of your offensive line. The other corollary is that most star pass rushers play on the defense’s right side (and the offense’s left), amplifying the value of the left tackle.

When it comes to the running game, the left tackle is no more valuable than the right tackle, or (in some systems) any other members of the offensive line, for that matter. To make this a more straightforward analysis, let’s just stick to the passing game, even though obviously most elite left tackles are also very good at run blocking, which of course adds value.

On most passing plays, offensive linemen are basically the equivalent of fences, designed to prevent the opposition from getting to the quarterback. How useful is a fence that’s totally impenetrable on the left side but has a human-sized hole on the right? This isn’t just a snarky comment; an offensive line is often only as valuable as its weakest link. Which defense will get to the quarterback first: one facing five average linemen or one facing three average linemen, an All-Pro left tackle and the worst starting right tackle in the league? If you were a defensive coordinator, which group would you rather scheme against? To me, it’s a pretty simple question: you want to attack your opponent’s weakness, and an offensive line, like a fence or a chain, is only as strong as its weakest link.

Let’s put it another way. In what circumstances does an All-Pro left tackle add value over say, the 25th best starting left tackle in the league? I think those circumstances are basically limited to those plays where:

The All-Pro left tackle does his job, and the other four, five or six blockers do their job, and the quarterback makes the right read and an accurate throw, and the receiver makes the catch, and on this particularly play, the player(s) that was (were) blocked by the All-Pro left tackle would have gotten to the quarterback in time to prevent him from throwing and completing said pass had he (they) been blocked by a replacement-level tackle.

If you think there are a lot of ‘ands’ in that sentence, you’re right. If the other lineman don’t do their job, the star left tackle is meaningless. If the quarterback can’t make the right read or is inaccurate, the left tackle that blocks DeMarcus Ware doesn’t help his team (other than an incomplete pass being better than a sack or a rushed throw that turns into an interception). If the receiver drops the ball, the left tackle doesn’t provide any value. And if we’re talking about a player where the left tackle didn’t do anything that a replacement level linemen wouldn’t have done, then our star tackle has added no value, either.
[continue reading…]

There were close calls in Baton Rouge and in South Bend, but all six undefeated teams escaped week 10 without a blemish. Ohio State is now the first team to win 10 games in 2012, although the Buckeyes are not eligible to participate in postseason play. Louisville ran its record to 9-0 yesterday, with winnable games against Syracuse and Connecticut before a season-defining finale in Piscataway on November 29th.

However, the eyes of the country are now focused on Notre Dame, Kansas State, Oregon, and Alabama. Last weekend, I said there was only a 10% chance that Oregon, Kansas State, and Notre Dame would finish the season undefeated. That was with 13 games left for those teams to win; now those odds are close to 17%. Kansas State has the easiest remaining path, although all three of its remaining opponents have realistic chances of pulling an upset. Oregon has a relatively easy game against Cal this week while Notre Dame shouldn’t have any problem with Boston College.

Alabama has another tough challenge this week in Texas A&M, although it is hard to imagine college football’s most inconsistent team of the last two years winning a close match-up against the country’s most consistent and brutal opponent. If Alabama can defeat the Aggies this weekend, a perfect regular season is all but assured, with the Crimson Tide’s final two games coming against Western Carolina (SRS of 11.6) and Auburn (37.6). The Iron Bowl this year should be more coronation than battle, which leaves just Texas A&M and Georgia — the likely opponent in the SEC Championship Game — as the two remaining hurdles for Alabama to clear.

Here are the week 10 SRS ratings: [continue reading…]

In this post by Neil, he provided a formula to predict each team’s likelihood of winning a game based on the Vegas point spread. With the help of the SRS, we can come up with a projected point spread for each game, and therefore figure out which team is most likely to give the Falcons their first loss.

The table below shows the SRS rating for Atlanta and each of their remaining opponents, along with the projected point spread in the game (based on the difference between the two SRS scores and home field) and the concomitant projected win probability. Note that in the Dallas game, the projected line is Atlanta -8.6, which would yield a 73.2% win probability; since the actual line is Atlanta -4, for the purposes of that game, I will be using the real line and not the projected one.

As you can see, the Falcons are projected to be a favorite in every remaining game, with the Giants game looming as the most difficult challenge. The probability of Atlanta winning each of their remaining 9 games is only 2.4%.

But figuring out which team is most likely to be the first to defeat the Falcons is a trickier question. The Cowboys are the obvious pick, in part because they’re up first and in part because they’re one of the most challenging remaining opponents for the Falcons. What are the odds that the Giants become the first team to knock off the Falcons, like they did to the Patriots in ’07 and the Broncos in ’98? For that to happen, the Giants would need to beat Atlanta (51.4%) plus the Falcons would need to beat Dallas, Arizona, Tampa Bay, Carolina, and New Orleans twice before their game with New York. The probability of Atlanta winning all of those games is just 10.2%, so there is only a 1-in-20 chance that New York performs its giant-killer act again.

To calculate the odds of the opponent in each week being “the team” to knock off the Falcons, we simply have to perform the same math. Therefore, the table below shows the likelihood of Atlanta first losing (in each week) to each team:

Even though they’re not favored to win the game, since we can’t pick “the field”, the Cowboys are the team most likely to ruin the Falcons’ perfect season. As of today, New Orleans is next with a 20.6% chance thanks to two bites at the apple; meanwhile, the Falcons are more likely to go undefeated than they are to go 14-0 only to have the Lions ruin perfection.

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Philip Rivers not pictured.

This is the third straight year where we have such a game on the heels of a 25-year drought. In each of the last two seasons, the Steelers and Patriots have played, with Roethlisberger and Tom Brady starting both games. But prior to 2010, the last NFL matchup between two starting quarterbacks with multiple rings was in 1985, featuring the San Francisco 49ers (Joe Montana) and the Los Angeles Raiders (Jim Plunkett).

But today’s trivia question wants to know: which two quarterbacks starred in the first NFL game between two quarterbacks with multiple Super Bowl rings?

Hat tip to The Jerk from the Footballguys message boards for pointing this out to me.

November 3rd has been circled on the calendars of college football fans for nearly a year. Unfortunately, the two biggest games of the day — Alabama/LSU and Oregon/USC — will compete for the eyeballs of the nation. The Ducks and Trojans kick off at 7PM on the East Coast, with the Crimson Tide stealing our attention one hour later. Making matters worse, the #3 team in the country will be playing in the 8PM time slot, too, as Kansas State hosts Oklahoma State. So with a lot of interesting games this weekend, I thought I’d take a look at my thoughts on each game involving an eligible, undefeated team on Saturday in relation to two key metrics: the SRS ratings and the Vegas lines. I’ll also make heavy use of the Game Scores page, which lists every game from this season for all FBS teams.

Temple at Louisville, 12PM (all times Eastern)

Louisville SRS: 43.7
Temple SRS: 31.5
Projected SRS line: Louisville -15.2
Actual line: Louisville -16.5

Temple had been respectable early this year (minus an ugly home loss to Maryland) but has been miserable the last two weeks, likely driving this line up. The Owls were up 10-0 at halftime being being routed 35-10 by Rutgers at home two weeks ago, and then last week lost by 30 at a terrible Pittsburgh team. Louisville is not great, but they should be able to handle Temple with ease. No thoughts on the point spread, though, which seems right to me.

Pittsburgh at Notre Dame, 3:30PM

Notre Dame SRS: 63.1
Pittsburgh SRS: 37.5
Projected SRS line: Notre Dame -28.6
Actual line: Notre Dame -16.5

Why is this line the same as Louisville-Temple? The only explanations I can think of are: (1) Pittsburgh just played its best game of the week (SRS score of 57.0) in a win over Temple and (2) Notre Dame hasn’t earned the public’s trust just yet. But with the exception of a squeaker over Purdue in week two, the Fighting Irish have been very good each week. They beat Michigan State by 17 (SRS score of 67.5), Michigan by 7 (58.2), Miami by 38 (73.0), Stanford by 7 (60.8), BYU by 3 (51) and Oklahoma by 17 (82.9). Maybe some of those scores are a little inflated — the Hurricanes have several drops and an injured quarterback, the Stanford game was in overtime, the Oklahoma game was closer than the score — but that’s picking nits, in my opinion. This is a ridiculously good defense playing a Pittsburgh team that scored 20 points in its last road game, which was at Buffalo. The Panthers were horrrrrrrrible with probably more Rs than that the first two weeks of the season, losing to FCS Youngstown State and Cincinnati by a combined 38 points. But even if we threw those games out, the SRS would still say the Fighting Irish should be favored by at least three touchdowns.

The pick: Notre Dame -16.5
[continue reading…]

In Tuesday’s post, I outlined a method of regressing a team’s record to the mean to estimate its “true winning percentage talent” (the trick is to add eleven games of .500 ball to their record, at any point in the season). In the comments, FP reader Dave wondered if we could incorporate last year’s true WPct talent into our talent assessment for this season, so I thought I’d run a quick regression to look at that.

My dataset was simply every game from 2003-2012 (including Monday night’s game). For each game, I recorded:

• Whether the game was a win, loss, or tie for the team in question. Wins got you a “1”, ties a “0.5”, losses a “0”.
• The team’s WPct talent estimate going into the game. So in the first game of the season, that’s (0+5.5)/(0+11)=0.500 for everybody; meanwhile, for an 11-4 team going into the final game of the season, it’s (11+5.5)/(15+11)=0.635.
• The team’s WPct talent estimate from the previous season.

I then set up a logistic regression to predict whether the game was a win or a loss based on the two WPct talent variables, this year and last year:

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-1.7686  -1.1489   0.1616   1.1429   1.7072  

Coefficients:
              Estimate Std. Error z value Pr(>|z|)    
(Intercept)    -2.6936     0.1982 -13.589  < 2e-16 ***
currenttalent   4.0297     0.3509  11.485  < 2e-16 ***
prevtalent      1.3571     0.2666   5.091 3.57e-07 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 6712.4  on 4843  degrees of freedom
Residual deviance: 6508.0  on 4841  degrees of freedom
AIC: 6516.1

Number of Fisher Scoring iterations: 4

That means to predict your likelihood of winning any given game, you plug your WPct talent numbers from this season and last season into this formula:

WPct ~ 1 / (1 + EXP(2.693606 - 4.029688*(Current_Talent) - 1.357123*(Prev_Talent)))

It's important to note the size of the coefficients here -- the current WPct talent coefficient is three times as big as that of last season's WPct talent, so it has much more bearing on the prediction.

At any rate, here are the probabilities of winning any given game that this formula implies for this year's teams:

I’d like to extend my best wishes to everyone dealing with the fallout from Sandy. I’m in my fourth location in five nights, and have lost power in my building for two days, but consider myself one of the lucky ones. This has been a tragedy for many out there, and thoughts and prayers go out to those who have been harmed.

But that won’t stop me from publishing the week 8 power rankings. This week it’s time to vault Atlanta to the top of the heap. I don’t love the Falcons, but it’s hard to see them not winning 13 games this year. So why don’t I love them?

The MVP of the first half of the season?

• According to Football Outsiders’ drive stats, Atlanta ranks 8th in yards per drive, 3rd in points per drive (partially because they rank 3rd in starting field position per drive and 5th in fumble rate per drive), and 4th in drive success rate. That’s great; defensively, they’re 11th in yards per drive, 6th in points per drive, and 11th in drive success rate allowed. That’s less impressive but still pretty good. As far as “net” categories go, they are 6th in net yards per drive, 2nd in net points per drive, and 4th in net drive success rate. In other words, they look like an elite team, perhaps the best in the league. Except…
• In Football Outsiders’ Rankings, the Falcons are just 8th. Aaron Schatz sums up why: “First, close wins: four by a touchdown or less. Second, its schedule so far ranks 29th in the NFL. Third, the Falcons have recovered 75 percent of fumbles.” If you ignore SOS — which the drive stats do — Atlanta looks like an elite team. Factor in the fumble luck, and it makes sense why FO does not view the Falcons as a top-five team.
• Brian Burke now has Atlanta as his fifth ranked team; he doesn’t think Atlanta’s schedule has been all that easy. That’s because Denver is his #1 team and his system loves the Panthers and doesn’t think the Raiders are that bad.
• According to the Simple Rating System, the Falcons are just the 7th best team, behind the Texans, Patriots, and Broncos in the AFC and San Francisco, New York, Chicago in the NFC.

Atlanta is a very good team, but probably not the best team in the league. My guess is on a neutral site, they’d be an underdog to at least five teams in the NFL, if not more.

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.

(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.)

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.
[continue reading…]

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.

[continue reading…]

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:

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:

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:

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.

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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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.

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.

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.

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?

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.

The Big 10 used to have good athletes.

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.]

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.

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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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.

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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:

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:

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 2011 ^[1]Upshaw and Barron were All-SEC first team selections by the AP, and Chapman, Hightower and Kirkpatrick earned second-team honors. — 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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Would you trust this man?

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.

Megatron.

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?

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

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):

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.)