I’ve been on a major QB kick lately, and there’s no reason to stop now. Today, I want to look at a method that might tease out a quarterback’s “true talent” better than if we simply use his raw stats from the season.

Three years ago, our colleague Jason Lisk had a post on the old PFR Blog about which rate stats stay consistent when a QB changes teams. Basically, he grabbed QBs who were still in their primes and changed teams, looking at how their key rate stats correlated from one year to the next. Here’s what Jason found:

[…]I looked at the correlation coefficient for our group of 48 passers, for the year N advanced passing score compared to the year N+1 advanced passing score in each category. This should tell us whether the passers who were good in a performance area (or bad) tended to be the ones who remained good in that performance area the following season, even with the uncertainty of team changes (some positive, some negative for the quarterback).

Sack Percentage:  0.31
Completion Percentage: 0.25
Yards Per Attempt:  0.20
Touchdown Percentage: 0.12
Interception Percentage: 0.10

What do those correlations mean, exactly? Well, take sack percentage as an example. In general, a correlation of 0.31 means you can expect 31% of a QB’s difference from the mean to be repeated next year when he changes teams. In other words, you have to regress the QB’s sack rate 69% towards the mean to get the true rate that “belongs” to him. If the average sack rate is 6.1%, and a QB has a rate of 4.0% (like, say, Drew Brees this year), his “true” sack rate is probably something like 5.4% — 31% of the distance between .061 and .040.

The same concept applies to the other stats listed above. Tony Romo’s observed 66.7% completion percentage is really more like 62.5% after regressing to the mean, and so forth. Do that for every QB who had a reasonable number of attempts this year, and you get these rate stats:

(“A-” before a stat means the actual observed rate; “R-” means the regressed rate.)

Now we just need to reconstruct the player’s raw passing line as though he posted those rate stats instead of his actual rates. Cmp%, YPA, TD%, and INT% are easy (just multiply by attempts), and Sack% can be derived via simple algebra:

Sacks_new = (-reg_sk% * Attempts) / (reg_sk% – 1)

(Sack yards can be assumed by multiplying raw sack yards per sack by the new sack total.)

Finally, we plug the new totals into the Adjusted Net Yards Per Attempt formula, and we have a QB stat that is sort of like baseball’s Fielding Independent Pitching (FIP), which also seeks to reduce the noise and teammate interactions in a pitcher’s ERA by reducing his performance to only those elements he has control over — strikeouts, walks, and home runs.

Here are the 2012 leaders in QB-FIP (along with their regressed totals):

These guys are pretty good.

Over at Football Outsiders, Aaron Schatz has always compared to “replacement level”, borrowing a concept from baseball. I like that approach, but replacement level can be hard to empirically determine. So for the purposes of this post, I wanted to come up with a quick-and-dirty baseline to which we can compare QBs.

To that end, I looked at all players who were not their team’s primary passer in each game since 2010. Weighted by recency and the number of dropbacks by each passer, they performed at roughly a 4.4 Adjusted Net Yards Per Attempt level. This is not necessarily the replacement level, but it does seem to be the “bench level” — i.e., the ANYPA you could expect from a backup-caliber QB across the league.

Using 4.4 ANYPA as the baseline, we get the following values for 2012:

If we weigh each game by how recent the results took place, we get this list:

This kind of thing isn’t exactly the most advanced stat in the world, but it’s pretty good if you want to sort QBs into general groups based on how good they are (the assumption being that a player who never plays is implicitly a bench-level player by definition).

Here’s a quick set of quarterback ratings I was messing around with, based on Doug’s Simple Rating System. The basic setup: I took every passer-game (Att > 0) since the 2010 season, weighting for recency according to Wayne Winston’s method. I ran the data through the SRS to adjust for the quality of opponent pass defenses, creating a predicted Net YPA rate for each passer in each game via the following formula:

Predicted NYPA = League Constant + Home-Field Advantage + Passer Rating – Opponent Pass D Rating

The league constant in this case was a Net YPA of 6.24; the homefield component (which was positive while at home, negative on the road, and 0 in Super Bowls) was 0.05. Minimize the sum of squared errors between predicted and actual NYPA for each passer-game (weighted by recency and how many dropbacks the passer had in the game), and you’ve got a set of opponent-adjusted, recency-weighted QB ratings.

Throwing out the Brett Favres and Curtis Painters of the world who haven’t been active this year, here are the full ratings:

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You’re probably hearing a lot right now about how Matt Schaub is not a primetime player — literally. Schaub and the Texans struggled in embarassing losses on Sunday Night Football to the Packers earlier in the season and on Monday Night Football two days ago to the Patriots. Schaub posted terrible numbers in a defensively-driven 13-6 win over the Jay Cutler/Jason Campbell Bears.

For his career, Schaub is 2-5 (0.286 winning percentage) in night games and 41-31 (0.569) in day games. Among the 24 quarterbacks studied (more on that below), that drop in winning percentage is the largest such decline. You might think this is due to facing better defenses in night games, but that’s not really the case.

Schaub has averaged 7.8 Adjusted Yards per Attempt during day games and 6.0 AY/A during night games; that difference of 1.8 AY/A is the second largest among the twenty-four quarterbacks.

So yes, there is no debate: Schaub has been noticeably worse during night games in his career.

The table below shows all quarterbacks who have started a game this season and that have started at least five night games in their career. The data consist of all games throughout their career in which they were the starter. To make it a little easier to read, I’ve shaded the day and night categories differently:

So you're telling me they were 1-15 last year?

In 1992, one year B.P., the New England Patriots were 2-14, in part thanks to a 1-5 record in one-score games. Throw in some regression to the mean and the first pick in every round of the ’93 draft, and going 5-11 in 1993 wasn’t so much of an accomplishment as it was pre-ordained.

In 1996, one year B.P., the Jets went 1-15. New York was a horrific 0-7 in one-score games. Throw in the #1 pick in every round, and they were an attractive target. Parcells did do a masterful job cleaning up the mess left by Rich Kotite, but getting them to 9-7 looked very impressive in large part thanks to the poor fortunes of the team the prior year.

The Big Tuna again went after the low-hanging fruit again when he took over as the Executive Vice President of Football Operations in Miami (it is here my old friend would get particularly annoyed, noting that Parcells found a way to have his cake and eat it too. If the Dolphins succeeded, Parcells would have “done it again.” Had they failed, well, he wasn’t the coach.) He took over a 1-15 team that was bad but not 1-15 bad; they had faced one of the harder schedules in the league and gone 1-6 in close games. Enter Jake Long, Chad Pennington, and the Wildcat, and the Dolphins went 11-5. Parcells did it again!

In any event, that’s just background. The 2013 Panthers are the real topic today — and they are the lowest hanging fruit any potential coach has seen in decades. Consider:

• The Panthers are currently 3-9, and little is expected of them going forward. They are now just 9-19 in the Cam Newton era.
• Despite that, Carolina ranks 4th in Brian Burke’s Advanced NFL Stats efficiency ratings. Now maybe they aren’t the 4th best team in the league, but Brian’s system is purely predictive and minimizes events that shape our views but are unlikely to impact future records. I have no doubt that they’re closer to the 4th best team in the league than the 4th worst, which is where they are by record.
• Football Outsiders ranks Carolina 18th — which, by the way, still means they’re much better than their record — but even that is misleading. Schatz ranks Carolina 32nd in special teams — a unit that Burke ignores — but instead has them 15th in offensive DVOA and 14th in defensive DVOA. That means excluding special teams the Panthers are above average, and special teams performance is notoriously fickle.
• So why are the Panthers 3-9? Carolina is currently 0-7 in one-score games.

There’s an even simpler way to show how the Panthers are massively underachieving this year. Net yards per attempt isn’t the only stat in the world, but it’s one of the most important indicators of an offense’s effectiveness. Net yards per attempt is just as important on defense; NY/A differential, the difference between how many net yards you gain per offensive attempt and how many you allow per defensive attempt, is a simple shorthand to highlight the best in the league. Here are the results through 13 weeks (i.e., not counting last night’s game):
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Things are getting ugly in Pittsburgh. Really ugly.

Ben Roethlisberger started the first nine games of the season, but things are getting ugly quickly in Pittsburgh. After suffering a right shoulder injury and bruising his ribs against the Chiefs, Byron Leftwich started last weekend against the Ravens. Leftwich injured his ribs against Baltimore, leaving Pittsburgh to now turn to Charlie Batch against the Browns tomorrow.

When was the last time a team started three different quarterbacks in consecutive games? Three teams last year pulled off that feat. After Jason Campbell started the first six games of the season, Kyle Boller started the next week before the team permanently switched to Carson Palmer.

Matt Schaub was the Texans starting quarterback for ten games, but a foot injury ended his season. Matt Leinart took over, but a broken collarbone ended his season, leaving the reins in the hands of rookie T.J. Yates. In St. Louis, an ankle injury caused Sam Bradford to miss a December game against the 49ers, leaving A.J. Feeley to start. Feely injured his right thumb, but Bradford was back the next week. He would miss the rest of the year due to his ankle, though, and Kellen Clemens started the last three games.

So it’s actually not all that rare for a team to go with three different quarterbacks in three weeks; at some point this season, it’s possible the Cardinals will, as well, with John Skelton, Ryan Lindley, and Kevin Kolb. From 2000 to 2011, teams started three different quarterbacks in consecutive games on 36 different occasions:

Excluding the 1987 season, the 1974 49ers were the only team since the merger to start four different quarterbacks in four weeks. As you can imagine, their story is interesting. Joe Reed entered the season as the starter, after splitting time with a 38-year-old John Brodie (who retired after the season) and Steve Spurrier (who suffered a severely dislocated shoulder in the final pre-season game in ’74) in 1973. He started the first three games of the year, and played miserably, so the team moved on to Dennis Morrison, who had been a 14th-round draft selection in 1973.

Morrison started the 4th and 5th games of the season for the 49ers, which is when the streak began. Morris started game five in Detroit, but threw three interceptions, so in week 6, the 49ers went back to Reed. Reed went 2/8 for 1 interception and was promptly traded later that week. So in week 7, 13th-round rookie Tom Owen started the game and performed reasonably well, but he was just the interim quarterback. That’s because in connection with the Reed trade, San Francisco acquired Norm Snead from the Giants, who sent Snead to San Francisco after acquiring Craig Morton from Dallas. Injuries and ineffectiveness limited Snead to just that one start for the 49ers in ’74, however, and Owen would go on to play (somewhat competently) for the remainder of the year.

On November 15, 2010, Michael Vick humiliated the Washington Redskins before a national television audience on Monday Night Football. The big news right before kickoff was that the ‘Skins had signed former Eagle QB Donovan McNabb to a five-year, $78 million contract extension, an ironic note that wouldn’t be lost on observers as McNabb’s replacement, Vick, put together one of the greatest all-around quarterbacking performances in NFL history:

McNabb, on the other hand, was mediocre, going 17-31 with 295 yards and 2 TDs, but also 3 picks. More damning, Washington’s offense produced zero points until the Redskins were in a 35-0 hole and the game was essentially over.

Fast-forward 735 days, though, and the Redskins got their payback. An injured Vick was on the shelf, the Eagles entered the game on a 5-game losing streak, and electrifying rookie Robert Griffin III extended it to six with a brilliant performance of his own:

So, which performance was better, Vick’s original or RGIII’s remix? Vick threw for 133 more yards, rushed for practically the same amount as Griffin (on 4 fewer carries), and produced more total TDs. Then again, Griffin completed 93% of his passes and put together the vaunted 158.3 “perfect” QB rating. It’s a tough call.

Sound off with your opinion below!