Did their college game translate to the pros? Percentile-ranked across 5 style dimensions. Click a row to expand year-by-year breakdown.
The composite score is a single number (0–100) that measures how good a QB looked statistically in college. It does not measure arm strength, athleticism, or leadership — only what shows up in the data. That's why some elite NFL QBs who were "raw" in college (Mahomes, Allen, Lamar) rank lower, while polished college producers (Cam Newton, Russell Wilson, Baker Mayfield) rank higher.
We grade every QB across 14 metrics grouped into six categories. For each metric, we rank the QB against every other QB in our database (140+ prospects since 2011). A QB in the 90th percentile on a metric scored better than 90% of all QBs — regardless of era or conference.
Not all metrics are weighted equally. The ones that best predict NFL success carry more weight:
After calculating the weighted average, two adjustments are applied:
QBs are then sorted by composite score and assigned tiers: T1 = top 15%, T2 = 15–40%, T3 = 40–70%, T4 = bottom 30%.
Each metric is converted to a 0–1 percentile by counting how many QBs in the database have a strictly lower value.
A QB at the 85th percentile scored higher than 85% of all QBs on that metric.
This is immune to outliers — one extreme value doesn't compress everyone else toward the middle, unlike min-max normalization.
For inverted metrics (P2S%, Fumble Rate), the percentile is flipped: 1 - percentile.
| Category | Metric | Weight | % of Total | r(wAV) |
|---|---|---|---|---|
| Core Production | TPS | 12 | 13.0% | 0.357 |
| BTT% | 9 | 9.8% | 0.376 | |
| Adj Cmp% | 4 | 4.3% | 0.183 | |
| Aggressiveness | MOF Grade | 10 | 10.9% | 0.406 |
| Deep Grade | 8 | 8.7% | 0.324 | |
| Int Grade | 6 | 6.5% | 0.272 | |
| Short Grade | 5 | 5.4% | 0.249 | |
| Over 10+ Yd% | 3 | 3.3% | 0.117 | |
| Pocket Presence | P2S% | 5 | 5.4% | 0.215 |
| Fumble Rate | 3 | 3.3% | — | |
| Scrambling | Rush YPG | 6 | 6.5% | 0.290 |
| Yds/Scramble | 5 | 5.4% | 0.250 | |
| Clean Pocket | Clean Pkt xANY/A | 6 | 6.5% | 0.283 |
| Pressure | Pressure xANY/A | 10 | 10.9% | 0.403 |
r(wAV) = Pearson correlation between the college metric and NFL career Weighted Approximate Value across 114 drafted QBs (2011–2024). Weights are informed by these correlations but also incorporate domain knowledge — for example, fumble rate has a low linear correlation but represents a real ball-security concern that scouts value.
After computing the raw weighted average, the score is multiplied by a conference factor: P5 × 1.00, G5 × 0.93, FCS × 0.82. This bakes competition strength directly into the composite rather than applying a post-hoc tier demotion.
Five thresholds trigger graduated penalties. The further past the threshold, the larger the deduction (capped at 3 points per flag):
penalty = min(3, 2 × |actual − threshold| / threshold)
| Flag | Threshold | What it catches |
|---|---|---|
| P2S% > 20% | Pressure → sack rate | Collapses under pressure |
| ADOT < 9 | Avg depth of target | Overly conservative / checkdown-heavy |
| Deep Att% < 14.5% | Deep attempt share | Never pushes the ball downfield |
| Dropbacks < 800 | Career volume (2015+ only) | Small sample — stats less reliable |
| TWP% > 4.5% | Turnover-worthy plays | Reckless decision-making. Note: Mahomes (4.0%), Allen (4.4%), Lamar (4.0%) all clear this threshold. |
This is a statistical production model. It cannot evaluate arm talent, release mechanics, football IQ, leadership, scheme fit, or development trajectory. QBs like Patrick Mahomes (#33 composite) and Josh Allen had mediocre college stats but elite physical tools. Conversely, Mac Jones and Bryce Young had excellent college stats but face questions about NFL ceiling. Use this as one input alongside film study and scouting reports, not as a complete evaluation.