What projects, and what doesn't · QBs · held out 2019-2025
How well one season predicts the next, measured on seasons the model never trained on. 1.00 would be perfectly predictable; 0.00 means last year told us nothing.
- Usage share (volume)0.46Beats guessing the QB average by 16%. n=2,421 QB seasons
- EPA per play (efficiency)0.05Not projectable — we do not forecast this. n=1,965 QB seasons
- Total EPA (value)0.51Beats guessing the QB average by 20%. n=1,965 QB seasons
Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Brandon Tennison's projection is a projection of opportunity — how much of the offense he runs through. How well he converts it is something this model does not claim to know a year in advance, and the number above is why.
2025 Production
Performance Analysis · 2025 · vs QB peers
- Efficiency100
- Volume33
- Dual-Threat20
- Consistency0
- Clutch40
Maximises EPA per play through accuracy, decision-making, and getting the ball to the right place.
- ▸Top-10% efficiency among QBs — elite opponent-adjusted EPA rate.
- ▸High game-to-game variance — boom-or-bust profile.
- ▸Production faded as the season progressed — 0.96 EPA/play decline from first to second half.
- ▸Peak game: 1.79 EPA/play in Wk 1 vs Texas A&M (SP+ 21).
NIL Market Tier· 2025
On3 valuation ↗Top-3 player at position nationally. Collective + national brand deals.
Tier is a model estimate based on position, school brand, performance rank, and usage — not a reported deal. NIL deals are private. For a real market valuation, see On3's NIL profile, which factors in social following and actual deal tracking.
Game Log · box score + EPA, week by week
Usage & Situational · Pro
- Standard downs
- 3.29
- Passing downs
- —
- Pass / Rush EPA
- 3.29 / —
Usage = share of team plays (CFBD has no true snap counts).