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Jordan Brown

#1Jordan Brown

Jordan Brown is a Slot Specialist WR for Nevada.

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 Jordan 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
16 Receptions183 Rec yards0 Rec TD11.4 Yards/rec

Performance Analysis · 2025 · vs WR peers

  • Efficiency83
  • Volume19
  • Explosiveness30
  • Consistency0
  • Pass-Down6
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)83th %ile · above avg
Game-to-game consistency0th %ile · below avg
Key findings
  • Above-average efficiency for the WR position (83th percentile).
  • Limited usage share suggests a rotational or specialist role.
  • High game-to-game variance — boom-or-bust profile.
  • Production faded as the season progressed — 0.18 EPA/play decline from first to second half.
  • Peak game: 1.34 EPA/play in Wk 13 vs Wyoming (SP+ -11).

NIL Market Tier· 2025

On3 valuation ↗
Starter

Meaningful starter. Local collective + position-group 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
Tyler BuchnerNotre Dame0.2500.312.8
Brandon ChatmanNavy0.2300.612.0
Justin LynchTemple0.2400.315.1
Samajie GrantArizona0.2500.315.5
Amare JonesTulane0.2300.813.3

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

Game Log · box score + EPA, week by week

+1.3401.34Wk 1 vs Penn State: -0.72 EPA/play1Wk 2 vs Sacramento State: +0.28 EPA/play2Wk 3 vs Middle Tennessee: +1.01 EPA/play3Wk 4 vs Western Kentucky: -0.18 EPA/play4Wk 8 vs New Mexico: -0.42 EPA/play8Wk 13 vs Wyoming: +1.34 EPA/play13Wk 14 vs UNLV: -0.89 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1@Penn StateL11-4618.123216.0028-0.72
2vsSacramento StateW20-1745513.80210.28
3vsMiddle TennesseeL13-14-16.055811.60211.01
4@Western KentuckyL16-311.62199.5013-0.18
8@New MexicoL22-240.9166.006-0.42
13@WyomingW13-7-11.311313.00131.34
14vsUNLVL17-424.3100.000-0.89

Usage & Situational · Pro

Snap-share proxy
Overall
6.7%
Passing plays
15.5%
Rushing plays
0.0%
Standard downs
4.7%
Passing downs
10.6%
EPA by down type
Standard downs
0.35
Passing downs
0.09
Pass / Rush EPA
0.22 / —

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.