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Just for the hell of it I asked ChatGPT about the list - then specifically if there was any data to know which has the faster/fastest release and who processes faster thru progressions:

CJ Carr — possibly the best natural processor

This is the one I want to emphasize.

If you asked me:

"Which of these guys looks most comfortable going through a full-field progression?"

I'd have Carr and Sayin very close.

Carr doesn't necessarily look spectacular doing it. That's part of what I like.

He gets through the progression, recognizes the coverage, resets his feet and delivers the ball without excessive movement.

He's a very rhythmical quarterback.

The thing I'd like to see more of is Carr doing it against defenses that can consistently disguise coverage and pressure him. Notre Dame's protection and overall offensive structure make his job considerably easier.

But I think his mental processing may actually be one of his biggest NFL selling points.

Sayin vs Carr

If I had to split them:

Sayin

quicker release
perhaps slightly quicker eyes
better at manipulating the pocket
excellent anticipation
very efficient

Carr

perhaps slightly more natural progression QB
excellent anticipation
very calm
very consistent footwork
less reliant on predetermined throws

I'm saying exactly what I've been saying. AI is one useful tool in a toolbox. It's not the be all, end all. I'm also saying everyone has access to AI so there is nothing proprietary about that. Another thing I can tell you is that the question you ask, the way you phrase the question and what AI source you ask will give you differing results.

Once again I was comparing it to NFL GM's who also have all of the AI information as well as the opportunity to interview these players one on one. Something AI can not duplicate and is extremely valuable in the process.

I would like to ask you, do you think that NFL quality scouting departments do not speak directly to the players close friends/relatives/coaches/teammates? That's a critical part of the scouting process. And somewhere along the line here I believe you either forgot about or have totally decided to ignore the fact that every team in the NFL and most professional sports has an analytics department. And that is the very purpose of AI. Breaking down all the numbers and angles on players. It's been in use for a very long time now. I believe coming to some conclusion that NFL teams aren't fully embracing and using AI as a tool is naive at best.

And then I also have to wonder. Does AI value all factors in judging a QB equally or give higher priorities to those special skills? I think most everyone is in agreement that the ability to go through your reads while reading a defense quickly is one of the most valuable and hard to find qualities in a QB. So does AI give those things much more gravity when grading QB's than other QB skills?

Just for giggles I asked Gemini this question. "Rank the 27 quarterback class based upon the most advanced metrics available." And my list ranked them very differently than the answer bone got.

Thee current analytical ranking of the class’s top prospects emphasizes translatable NFL traits, efficiency, and performance under pressure:

1. Dante Moore | Oregon (Model Rank: QB1)

• The Metrics: Led the FBS with 30 big-time throws. He is highly valued by NFL scouts for his elite physical upside and an exceptionally accurate quick game.
• Scouting Outlook: Despite some high-variance tape, evaluators overwhelmingly favor his natural tools. In an ESPN poll of 25 NFL scouts and executives, Moore captured 14 first-place votes to be the top QB selected in 2027.

2. Julian Sayin | Ohio State (Model Rank: QB2)

• The Metrics: Boasts the #1 overall FBS PFF grade among eligible underclassmen and an elite 1.4% turnover-worthy play rate. His analytical profile is anchored by a class-leading 55.3 FRED score, proving his elite down-to-down efficiency.
• Scouting Outlook: Sayin is regarded as the most pure throw-for-throw accurate passer in the class. Concerns exist regarding his average arm velocity and a frame that has invited pressure/sacks, but his microscopic mistake rate keeps him at the top of advanced models
.
3. Arch Manning | Texas (Model Rank: QB3)

• The Metrics: Manning possesses an elite arm and mental processing profile, matching the ideal NFL build (6'4", 222 lbs). However, advanced metrics reflect recent late-September volatility—he currently ranks 29th in ESPN's QBR (67.6) due to deep-ball inconsistency.
• Scouting Outlook: Despite metrics showing a slight plateau in continuous production, his traits are undeniable. He secured 7 first-place votes from NFL executives, locked in as a premier talent whose ceiling matches anyone in the class.

4. Darian Mensah | Miami (Model Rank: QB4)

• The Metrics: Mensah is the fastest-rising statistical marvel in the country, leading the FBS with an astonishing 88.7% completion percentage alongside a 39.4 FRED score.
• Scouting Outlook: Analytical models are heavily heavily weighting Mensah’s absurd efficiency in Miami’s explosive offense. Scouts note he is rising "like a rocket" due to his elite decision-making and coachability.

5. Drew Mestemaker | Oklahoma State (Model Rank: QB5)

• The Metrics: Boasts a strong 40.4 FRED score after leading the nation in passing yards prior to his transfer from North Texas.
• Scouting Outlook: Favored heavily by traditional and volume-based analytical models, Mestemaker was recently named the No. 1 overall quarterback prospect on ESPN analyst Jordan Reid's Big Board.

6. CJ Carr | Notre Dame (Model Rank: QB6)

• The Metrics: Carr operates at a blistering pace with a lightning-fast average time-to-throw of 2.54 seconds. He features a 6.5% big-time throw rate against a 3.2% turnover-worthy play rate.
• Scouting Outlook: Models appreciate his bloodlines and high-floor processing, though a lower FRED score (10.6) and below-average NFL arm velocity push him to a Day 2 projection.