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Cooper Hoch

#13Cooper Hoch

Cooper Hoch is a Versatile WR for San José State.

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)0.47
    Beats guessing the WR average by 16%. n=6,302 WR seasons
  • EPA per play (efficiency)0.09
    Not projectable — we do not forecast this. n=5,767 WR seasons
  • Total EPA (value)0.45
    Beats 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 Cooper Hoch'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

Receiving
5 Receptions43 Rec yards0 Rec TD8.6 Yards/rec
Returns
1 Punt returns7 PR yards0 PR TD

Performance Analysis · 2025 · vs WR peers

  • Efficiency0
  • Volume7
  • Explosiveness11
  • Consistency12
  • Pass-Down100
Player type
Versatile WR

Balanced profile without a single dominant trait — contributes across multiple dimensions.

Balanced usageMulti-role
Peer percentiles
Opponent-adjusted EPA (WEPA/play)0th %ile · below avg
Game-to-game consistency12th %ile · below avg
Key findings
  • 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: 0.52 EPA/play in Wk 2 vs Texas (SP+ 16).

NIL Market Tier· 2025

On3 valuation ↗
Contributor

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.

Historical Comparables · WR · efficiency + volume + value

Players from 2013–2025 matched on EPA efficiency, play volume, and adjusted value tier — not just one metric.

PlayerTeamWEPA/playLine valTotal EPA
Amare JonesTulane0.1800.012.8
De'Michael HarrisSouthern Miss0.1300.715.2
Hyleck FosterMarshall0.1800.518.2
Brandon ChatmanNavy0.2300.612.0
Davis BrysonKennesaw State0.2000.019.4

Comps are statistical — efficiency, volume, and value tier all factor in. Style and conference context differ.

Game Log · box score + EPA, week by week

+0.5200.52Wk 2 vs Texas: +0.52 EPA/play2Wk 7 vs Wyoming: +0.11 EPA/play7Wk 8 vs Utah State: -0.29 EPA/play8
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
2@TexasL7-3816.22147.0080.52
7@WyomingL28-35-11.3166.0060.11
8@Utah StateL25-30-3.122311.5013-0.29
12@NevadaL10-55-13.4

Usage & Situational · Pro

Snap-share proxy
Overall
2.5%
Passing plays
3.8%
Rushing plays
0.0%
Standard downs
2.1%
Passing downs
3.3%
EPA by down type
Standard downs
-0.41
Passing downs
0.25
Pass / Rush EPA
-0.11 / —

Usage = share of team plays (CFBD has no true snap counts).

EPA = expected points added (opponent-adjusted). NIL estimates are model-based ranges, not reported deals. Data: CollegeFootballData. Not betting advice.