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Josh Cameron

#34Josh Cameron

Josh Cameron is a Versatile WR for Baylor. Josh's 2025 season ranks in the 100th percentile nationally by opponent-adjusted EPA per play across 92 plays — a elite rate for the WR.

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 Josh Cameron'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
69 Receptions872 Rec yards9 Rec TD12.6 Yards/rec
Returns
18 Punt returns141 PR yards0 PR TD

Performance Analysis · 2025 · vs WR peers

  • Efficiency100
  • Volume31
  • Explosiveness38
  • Consistency79
  • Pass-Down57
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)100th %ile · elite
Game-to-game consistency79th %ile · above avg
Key findings
  • Top-10% efficiency among WRs — elite opponent-adjusted EPA rate.
  • High game-to-game consistency — reliable floor each week.
  • 9 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Production faded as the season progressed — 0.44 EPA/play decline from first to second half.
  • Peak game: 1.08 EPA/play in Wk 1 vs Auburn (SP+ 12).

NIL Market Tier· 2025

On3 valuation ↗
Elite

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.

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
Keytaon ThompsonMississippi State0.4601.232.2
Quadree HendersonPittsburgh0.5301.633.4
DeAndre HughesAir Force0.4701.328.2
Savion WilliamsTCU0.4501.125.2
Javion PoseyFlorida Atlantic0.4501.423.8

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

Game Log · box score + EPA, week by week

+1.0801.08Wk 1 vs Auburn: +1.08 EPA/play1Wk 2 vs SMU: +0.85 EPA/play2Wk 3 vs Samford: +1.07 EPA/play3Wk 4 vs Arizona State: +0.35 EPA/play4Wk 5 vs Oklahoma State: +0.62 EPA/play5Wk 6 vs Kansas State: +0.77 EPA/play6Wk 8 vs TCU: +0.69 EPA/play8Wk 9 vs Cincinnati: +0.64 EPA/play9Wk 10 vs UCF: -0.36 EPA/play10Wk 12 vs Utah: +0.63 EPA/play12Wk 13 vs Arizona: +0.64 EPA/play13Wk 14 vs Houston: -0.10 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsAuburnL24-3811.625427.00271.08
2@SMUW48-4513.4915116.82480.85
3vsSamfordW42-74399.81151.07
4vsArizona StateL24-273.966510.80230.35
5@Oklahoma StateW45-27-15.169816.30400.62
6vsKansas StateW35-347.05499.80160.77
8@TCUL36-428.388610.80160.69
9@CincinnatiL20-414.54348.51160.64
10vsUCFW30-3-1.2351.713-0.36
12vsUtahL28-5522.21316512.72290.63
13@ArizonaL17-4112.067111.81300.64
14vsHoustonL24-317.435518.3131-0.10

Usage & Situational · Pro

Snap-share proxy
Overall
10.9%
Passing plays
19.0%
Rushing plays
0.0%
Standard downs
9.8%
Passing downs
13.6%
EPA by down type
Standard downs
0.52
Passing downs
0.57
Pass / Rush EPA
0.54 / —

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.