I’ve been a fan of Chase Stuart’s blog for a while now. My only quibble is that he spends a lot more time delving into the statistical universe of the pro game than he does college football. But thanks to Marty (who deserves a lot more attention for the work he does at cfbstats.com than he gets, by the way), it sounds like I’m about to get a lot happier.
A few weeks ago, I discovered cfbstats.com, which has made available for download an incredible amount of college football statistics from the last eight seasons. Thanks to them, I plan to apply some of the same techniques I’ve used on NFL numbers over the years to college statistics. If you’re a fan of college football, you’re probably already reading talented writers like Bill Connelly and Brian Fremeau, but hopefully I can bring something new to the table for you to enjoy.
Since that’s the start of a piece on the best passing college quarterbacks from last season, I’d say he’s already succeeded.
You can read about the metric he employs to rate quarterbacks here. (Short explanation: “ANY/A is calculated by starting with passing yards per attempt, adding 20 yards for each touchdown and subtracting 45 yards for each interception, and subtracting sack yards lost from the numerator and adding sacks to the denominator.”) He then describes the tweaks he made for the college game:
There’s a small problem, however, if you want to calculate ANY/A at the college level: the NCAA counts sacks as rush attempts and sack yards lost as negative rushing yards. I manually overrode2 that decision in my data set, so going forward, all rushing and passing data will include sack data in the preferred manner (keep this in mind when you compare the statistics I present to the “official” ones).
But calculating each quarterback’s ANY/A isn’t enough, as the varying strengths of schedule faced by college quarterbacks are too significant to ignore. So using the method described here, I came up with SOS-adjusted ANY/A for each quarterback in each game last year. This method involves an iterative process, so each quarterback’s performance is adjusted for the strength of the opposing defense, which has a rating that is adjusted for the quarterbacks it faced (including the quarterback in question), and so on, until the ratings converge. The usual caveats apply about defenses and quarterbacks that change in ability level over the course of the year.
Adjusted for defensive strength, Aaron Murray tops his list.
Let’s use Georgia’s Aaron Murray as an example. He averaged 3.88 ANY/A over average against a schedule that was 0.68 ANY/A tougher than average; that means he gets credit for being 4.56 ANY/A over average against a neutral schedule. Since he had 412 dropbacks last year (386 passes, 26 sacks), we multiply 4.56 by 412 to get his value added over average.
Honestly, I’m not that surprised, given Murray’s statistical dominance in the generic ypa stat last season. What is a little more surprising is the presence of SEC quarterbacks high on Chase’s list – five of the top ten. Some of that can be chalked up to the strength of the defenses they saw – six of the top ten SOS numbers belong to SEC quarterbacks, and another, Ole Miss’ Bo Wallace, ranked eleventh – but those players still had to perform well.
One other thing that caught my eye was his list of top 25 quarterback games of 2012. Murray’s was the only name to appear on that list three times. And it’s the third one, against Kentucky, that made me go back and think about something. Murray gets his fair share of criticism for not winning the big game, but does Georgia win that game if he doesn’t pick the team up and put it on his back?