I built an opponent-adjusted college football QB rating — looking for feedback on CQI

[u/PerceraAnalytics]

I’ve spent the last few weeks building a college football analytics project, and I finally have the first model in a state where I’m comfortable putting it in front of people who actually care about this stuff.

It’s called CQI — Contextual Quarterback Index.

My goal is pretty simple: to measure observed quarterback performance while adding some of the context that raw box-score numbers miss.

CQI currently looks at:

• down-to-down success
• opponent-adjusted passing efficiency
• opponent-adjusted TD creation
• sack avoidance
• rushing value

The opponent-adjusted portions try to account for the quality of defenses each QB has faced, rather than treating production against every opponent equally.

A couple important things CQI isn’t trying to do:

It isn’t a projection, NFL scouting grade, recruiting grade, or an attempt to completely isolate the QB from his offensive line/receivers/scheme. It’s meant to describe how well a quarterback has actually performed in the sample being used have.

For the live rankings, I've added some limitations so QBs need 30+ season-to-date attempts and at least 2 usable context games. Small samples are flagged rather than removed or artificially penalized, skewing results.

I also published the methodology instead of making the rating a black box.

2026 rankings + methodology:
perceraanalytics.com

I’m genuinely interested in criticism here. If there’s something about the methodology, presentation, opponent adjustment, or rankings that looks wrong or incomplete, I’d rather hear it now while this is still starting out in v1.0.

[u/basedonactualmath]

love the flag-not-remove approach for small samples. one question on the opponent adjustment: are you adjusting the components separately or adjusting the final composite? adjusting passing efficiency and td creation separately feels right since good defenses suppress those differently.

[u/PerceraAnalytics → u/basedonactualmath]

Yeah, that’s basically the approach I ended up taking. The opponent adjustment is applied to the individual components rather than to the final CQI score. Passing efficiency is adjusted through the QB/pass-defense network, and sack avoidance gets its own adjustment for the opposing pass rush. I tested opponent-adjusting rushing too, but it didn’t improve the forward signal, so I left that component unadjusted.

One change since this post: TD creation ended up getting dropped as a standalone component in the final v1.1 model. The current weights are 40% passing efficiency, 35% sack avoidance and 25% rushing.

[u/coacht246]

Would you be able to build a model that shows a QBs completion %, touchdowns against different defensive coverages with down and distance factored in, another one which shows average air yards against different coverages and lastly how likely they’ll scramble/take a sack against different coverages?

[u/heymikeyyyy66 → u/coacht246]

This...some college qbs have obvious deficiencies against cover 2, for example