What projects, and what doesn't · WRs · 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)0.47Beats guessing the WR average by 16%. n=6,302 WR seasons
- EPA per play (efficiency)0.09Not projectable — we do not forecast this. n=5,767 WR seasons
- Total EPA (value)0.45Beats guessing the WR average by 12%. n=5,767 WR seasons
Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Chris Autman-Bell'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.
2023 Production
Performance Analysis · 2023 · vs WR peers
- Efficiency100
- Volume7
- Explosiveness51
- Consistency66
- Pass-Down58
Balanced profile without a single dominant trait — contributes across multiple dimensions.
- ▸Top-10% efficiency among WRs — elite opponent-adjusted EPA rate.
- ▸Limited usage share suggests a rotational or specialist role.
- ▸3 high-impact games (EPA/play > 0.4) this season — elite ceiling.
- ▸Peak game: 2.56 EPA/play in Wk 11 vs Purdue (SP+ -7).
NIL Market Tier· 2023
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
- 1.26
- Passing downs
- 1.31
- Pass / Rush EPA
- 1.27 / —
Usage = share of team plays (CFBD has no true snap counts).