Week 8 Bayesian Quarterback Rankings

Lamar Jackson now into the top-3, and Trevor Lawrence continues to be an adjusted EPA favorite

The big, fundamental change to the rankings this season is the integration of Adjusted Quarterback Efficiency (AQE) numbers. This produces rankings that align more closely to what the typical football observer or data-based analysts would assign based on a combination of observation and statistics.

For the Week 1 projection, I weaved the AQE figures for 2023 and 2022 into the mix. In Week 2, I discovered the addition of prior years’ charting from FTNData, enabling us to go back to 2019 and calculate AQE. Because we’re shifting the historical data for several years in the new projections, the projection movement from Week 1 wouldn’t be primarily based on last week’s quarterback performances, but mostly on revisions to 2019-2021 efficiencies.

You can find all the previous weekly editions of the Bayesian Quarterback Rankings here, and the backlog for Adjusted Quarterback Efficiency is here.

COMPARING GRADES AND EFFICIENCY

PFF grades aren’t part of the analysis, but I find it helpful to make not of how they align with EPA per play, as many contextual elements of quarterback play (drops, interception-worthy throws, easier throws that become big gains, etc) are part of the grading methodology, but aren’t accounted for in EPA. At the same time, I think EPA does a vastly superior job of weighing what is and isn’t important in points-based results.

The plot below is a bit different than previous iterations of this post, substituting AQE for unadjusted EPA per play, and you might notice that the data has less dispersion (i.e. something like a higher r²) than using straight EPA. Even so, AQE doesn’t perfectly align with PFF grading, and you can decide which measure is more representative of fundamental quarterback play. (hint: it’s AQE!)

Jayden Daniels is still first in adjusted EPA per play, but fourth in PFF grading. The difference can mostly be explained by the Commanders’ offense vastly overperforming in late-down success rate, adding more than 30 expected points on third down and going 10-for-10 on fourth downs. Those plays are high leverage in terms of EPA, but grading treats all contextual down/distance situations the same in its play-level grading.

There’s a virtual tie for second in adjusted EPA this year between Kyler Murray, Broch Purdy and Lamar Jackson, though noticeable differences in their grading. Jackson is first in the NFL according to PFF, with Purdy fifth and Murray seventh. The biggest drivers of PFF grading are what they chart as “big-time throws” and “turnover-worthy plays”. The three quarterbacks are all top-10 in BTT rate, though Murray and Purdy are higher than Jackson. It’s really Jackson’s lack of mistakes that takes him higher in overall grading, with the lowest TWP rate in the NFL.

Very, very (maybe zero?) people would see it this way, but the combination of AQE and PFF grading places Trevor Lawrence in a slightly better position than Josh Allen, with the latter benefiting from intense interception luck (seven interception-worthy throws charted by FTNData but none actually picked) and lots of receiver yards after the catch, and the former hurt by the highest receiver drop rate for any quarterback.

Jordan Love and Sam Darnold are another close pair on the visualization, but they suffer much more in grading than AQE. I think this is driving, at least partially, by the higher-risk nature of their passing decisions, which led to higher TWP rates. Generally, PFF views interception-type plays as more harmful than the well-calibrated EPA numbers show. Love, in particular, has been great at avoiding sacks (seven all season), a trait that doesn’t get as much credit in grading, even though sacks are highly damaging in terms of points-based expectations.

Quarterbacks whose AQE performances built into these projections might be a bit undervalued include Patrick Mahomes, C.J. Stroud and Aaron Rodgers. All three sit below the trendline comparing grading to AQE, a unique position for Mahomes in contrast to the rest of his career. Stroud was one of the luckiest quarterbacks by AQE in 2023, mostly due to interception luck and a lower than expected receiver drop rate. These luck-based elements have regressed this year, making his 2024 campaign look somewhat underwhelming.

PROJECTED ADJUSTED EFFICIENCY

These results are the ranking for the go-forward projections of adjusted quarterback efficiency starting this week. I also included the AQE rankings for each quarterback over the last five seasons (minimum 250 dropbacks) so you can see the evidence going into the projections. All of these ranks are now based on AQB, including the 2024 numbers.

Older data is decayed over time, so the 2023 and 2024 AQE data matters more than those from pre-2020. That said, older data can’t be fully discounted, or else you miss bounce-back performers of great quarterbacks returning to form, like Aaron Rodgers in 2020 and 2021.

The projections have Spencer Rattler continuing to start for the Saints and still lists Jayden Daniels for the Commanders. I’m dubious that the rookie will start after a strong performance by Marcus Mariota in relief, but nothing is official as of the time of publishing. Mariota would be ranked in 25th if he was in the projections in lieu of Daniels.

“Percentile” is the mean (“best guess”) projection as a percentile of historical franchise quarterback results (min 2K career dropbacks).