Week 1 Adjusted Quarterback Efficiency

Adjusting for the high-variance aspect of value to get a better measure of quarterback play

A couple key drops and a relatively tough opponent moved Brock Purdy’s adjusted efficiency to the top

We’re one week into the new NFL season, with impressions on quarterbacks, young and old, forming with certainty. The old #QBWinz argument can be used already, but there are also a number of massively impactful plays happening each week that might not be correlated to quarterback play. A number of other elements of quarterback efficiency - directly affecting team performance - that are more dependent on luck (variance) than skill.

I aggregated many of those luck-based elements, with additional factors like passing scheme ability to generate yards-after-catch, in my Adjusted Quarterback Efficiency (AQE) metric.

The measures that I believe are most luck-based and part of this analysis:

• Interceptions: FTNData tracks “interception-worthy throws”, which I compare to actual interceptions on a play-by-play basis, and also adjust for expected interception return. Longer INT returns have a dramatic effect on the EPA, whether the quarterback’s fault or not.

• Drops: I calculated the expected drop rate for throws, based on location, and compared them to actual drops and determined the EPA lost/gained.

• Fumbles: Whether a fumble is recovered by the quarterback’s own team or not can turn a slightly negative play into a massive loss. I look at expectations for recovery based on different types of fumbles, and whether the quarterback himself recovers the fumble or a teammate (luckier).

• Yards After Catch: A higher portion of yards after catch should be credited to receivers or scheme than quarterback, at least in comparison to throws where the yards gained were mostly through the air. I adjust down EPA generated on passes with a relatively high proportion of YAC.

• Defensive Pass Interference: There are so many underthrown balls that turn into big DPI gains that need to be recognized as partially luck. By their very nature, DPIs are not “open” receivers with the coverage defender close enough to affect the receiver.

• Strength-of-Schedule: This is the one element that is most difficult to judge this early in the season. With three games played, a great offense can have a bigger effect making the defenses they played look “bad”, and vice versa, than might be the truth. But it still matters.

• Weather: Based on expected EPA gains/loss versus average in different elements, based on wind, humidity and temperature.

If you want more details on many of the calculations, check out the Adjusted Quarterback Efficiency (AQE) primers from last season.

• AQE introduction

• Update to 2.0

• Updated to 3.0

• Archive of past AQE posts, including my analysis of who deserved the 2023 MVP leveraging this metric

YTD 2024 ADJUSTED EFFICIENCY RESULTS

The plot below shows each quarterback who has dropped back to pass 15 times this season. There are two points for each quarterback: 1) The team-colored dot for the actual EPA per play the quarterback has this season and 2) The quarterback headshot representing the adjusted quarterback efficiency (EPA/play). There is also a team-colored line linking the two on each row.

Brock Purdy’s headline efficiency was good last week, ranking sixth among quarterbacks with at least 15 dropbacks. But his EPA efficiency number nearly doubles, combining positive additions for drops (+3.6 EPA), less YAC than expected (+2.3), and facing a tougher defense (+3.5 EPA). The defense adjustment might prove overconfident early in the season, as they’re mostly based on prior-year performance of the defenses faced. Even so, this was an outstanding week for Purdy by the numbers and narrative, especially without Christian McCaffrey suiting up. The fact that Purdy got a positive adjustment for YAC under expected is a major contrast to prior seasons, when Purdy’s total adjustments were some of the most negative, as his receivers generated a ton of value after the catch.

Sam Darnold’s AQE is slightly higher than his fourth-best unadjusted efficiency, firing up his long-suffering believers. I’m not sure it will continue considering his evidence based projections, but it’s been good so far. Purdy’s MNF opponent Aaron Rodgers also got a huge boost in AQE, mostly due to poor luck on receiver drops and a tipped interception. Other huge risers include Joe Burrow, whose receivers had a combination of end-zone drops and post-catch fumbles going across the threshold. Burrow wasn’t great, but his underlying performance wasn’t bad either.

The biggest negative AQE move goes is applied to Baker Mayfield, the leader in unadjusted efficiency for Week 1. Mayfield benefited massively from YAC over expectation from his receivers, and faced the worst passing defense in the NFL last season. Mayfield had a solid game regardless, but MVP levels of production were not unsustainable, they don’t really reflect how good he was for the one week of play we have to judge.

Here are all the total numbers for the week, showing how AQE is derived with the exact adjustments from actual EPA generated.