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Justin Smith-Brown
Justin Smith-Brown

#11Justin Smith-Brown

Justin Smith-Brown is a Slot Specialist WR for West Virginia.

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 Justin Smith-Brown'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
7 Receptions117 Rec yards0 Rec TD16.7 Yards/rec

Performance Analysis · 2025 · vs WR peers

  • Efficiency100
  • Volume7
  • Explosiveness65
  • Consistency45
  • Pass-Down100
Player type
Slot Specialist WR

The offense's primary passing-down weapon — routes, separation, and reliability on 3rd down define this role.

3rd-down converterRoute technicianHigh passing-down share
Peer percentiles
Opponent-adjusted EPA (WEPA/play)100th %ile · elite
Game-to-game consistency45th %ile · average
Key findings
  • 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.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Production faded as the season progressed — 1.37 EPA/play decline from first to second half.
  • Peak game: 4.33 EPA/play in Wk 3 vs Pittsburgh (SP+ 8).

NIL Market Tier· 2025

On3 valuation ↗
Star

Top-10 nationally. Multiple mid-to-large collective deals expected.

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 ThompsonVirginia0.3200.412.5
Cade HarrisAir Force0.3300.514.8
Nick NashSan José State0.3100.514.0
Keytaon ThompsonVirginia0.3700.615.2
Micah DavisAir Force0.3700.616.3

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

Game Log · box score + EPA, week by week

+4.3304.33Wk 1 vs Robert Morris: -0.81 EPA/play1Wk 3 vs Pittsburgh: +4.33 EPA/play3Wk 4 vs Kansas: +1.30 EPA/play4Wk 6 vs BYU: -0.48 EPA/play6Wk 8 vs UCF: +0.34 EPA/play8Wk 9 vs TCU: +0.86 EPA/play9
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsRobert MorrisW45-3-0.81
3vsPittsburghW31-248.415656.00564.33
4@KansasL10-414.12199.50111.30
6@BYUL24-3815.9144.004-0.48
8@UCFL13-45-1.222713.50190.34
9vsTCUL17-238.311111.00110.86

Usage & Situational · Pro

Snap-share proxy
Overall
2.5%
Passing plays
5.7%
Rushing plays
0.3%
Standard downs
1.8%
Passing downs
4.2%
EPA by down type
Standard downs
-0.59
Passing downs
1.43
Pass / Rush EPA
0.44 / -0.81

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.