2024 Adjusted Quarterback Efficiency: Through Week 4

Adding offensive line sack value adjustments to the best measure of quarterback value

The update this week is introducing adjustments for sack value specifically related to those prevented or given over expected based on pass blocking that each quarterback received. This is a complicated problem, which is one reason I didn’t add it before. We all know that pass blocking affects quarterback play, but determining how to divide the credit or blame among quarterback and offensive line is really hard. A quarterback having a higher pressure rate can mean his offensive line is poor at pass blocking, or he’s holding the ball too long, or a combination of both. I’ll explain more below on how I derive and incorporate sack adjustments.

This analysis is my best attempt to discount and adjust various elements of quarterback efficiency and get to the number that most accurately reflects fundamental play. There are a number of elements of quarterback efficiency - which also directly affect 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

INCORPORATING SACK ADJUSTMENTS

First off, my method for making adjustments for blocking focuses only on sacks prevented (or given) versus expectation. I understand that pressure affects quarterbacks on play when sacks don’t happen, but it’s much more difficult with pressures to disentangle how to proportion blame, and determine how big the effect sizes were.

Not all pressures are created equal, which is one of the reasons clean-pocket passing metrics are more stable for quarterbacks than those under pressure. Some pressures are invited by the quarterback and hardly affect the throw, others can be a swarm around the quarterback completely forcing him into a throw-away or highly inaccurate pass (even an interception). While not all sacks are also not created equally, we can accurately measure the value lost for each of them, making it a lot easier to incorporate adjustments in EPA results.

My method for creating sack adjustments is based on an older analysis from PFF’s Timo Riske using pressure survival curves. Rather than look at pressure and sacks without context, I pulled the exact time-to-throw and time-to-pressure numbers on a play-by-play basis. With that data, plus modeling on the context of different dropback types (screens, 3- or 5-step drops, rollout, shotgun, down, distance), we can compare actual time-to-throw and time-to-pressure versus expectations for each play, then determine how much of the pressure and ultimately sack rates for quarterbacks are determined by them holding the ball, or the offensive line giving up quicker pressure.

Quarterbacks with relatively good sack rates overall tend to have those results partially because of their play and partially due to their blocking. The inverse is true for those with poor sack rates. An encouraging result I found with the survival curve modeling is that it determined that roughly 2/3 of sack responsibility goes to quarterbacks on average, which aligns with what we know about sacks being mostly a quarterback stat.

For the 2024 season so far, the plot below visualizes how sack responsibility breaks out for each quarterback.

We get one interesting case here with the Panthers having two quarterbacks with substantial samples already this year, showing that the offensive line effect has remained fairly steady, but Andy Dalton has been much better at preventing sacks than Bryce Young, who himself wasn’t bad.

These prevention rates are built into the EPA results already, so the adjustment for sacks that I’m adding to the analysis backs out the blocking portion. These are not huge adjustments, as most of the responsibility falls on quarterbacks, and we don’t want to take that out of an adjustment to isolate quarterback play.

YTD 2024 ADJUSTED EFFICIENCY RESULTS

The plot below shows each quarterback who has dropped back to pass 80 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.