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 Xayvion Turner-Bradshaw'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 WR peers
- Efficiency0
- Volume10
- Explosiveness44
- Consistency0
- Pass-Down100
Balanced profile without a single dominant trait — contributes across multiple dimensions.
- ▸Below-average efficiency vs WR peers — value comes through volume, not per-play impact.
- ▸Limited usage share suggests a rotational or specialist role.
- ▸High game-to-game variance — boom-or-bust profile.
- ▸Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
- ▸Peak game: 1.80 EPA/play in Wk 1 vs Georgia (SP+ 24).
NIL Market Tier· 2025
On3 valuation ↗Rotational contributor. Smaller collective or local 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
- -0.55
- Passing downs
- 0.25
- Pass / Rush EPA
- 0.63 / -3.09
Usage = share of team plays (CFBD has no true snap counts).