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DJ Epps

#2DJ Epps

WR·Troy·2025

DJ Epps is a Versatile WR for Troy. DJ's 2025 season ranks in the 100th percentile nationally by opponent-adjusted EPA per play across 76 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 DJ Epps'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
46 Receptions498 Rec yards5 Rec TD10.8 Yards/rec
Returns
24 Kick returns554 KR yards0 KR TD

Performance Analysis · 2025 · vs WR peers

  • Efficiency100
  • Volume23
  • Explosiveness26
  • Consistency0
  • Pass-Down62
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 consistency0th %ile · below avg
Key findings
  • Top-10% efficiency among WRs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • High game-to-game variance — boom-or-bust profile.
  • 5 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Production faded as the season progressed — 0.49 EPA/play decline from first to second half.
  • Peak game: 1.30 EPA/play in Wk 6 vs South Alabama (SP+ -13).

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
Justin LynchTemple0.2400.315.1
Samajie GrantArizona0.2500.315.5
Davis BrysonKennesaw State0.2000.019.4
Tyler BuchnerNotre Dame0.2500.312.8
Amare JonesTulane0.1800.012.8

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

Game Log · box score + EPA, week by week

+1.3001.30Wk 1 vs Nicholls: +0.60 EPA/play1Wk 2 vs Clemson: +0.69 EPA/play2Wk 3 vs Memphis: -0.45 EPA/play3Wk 4 vs Buffalo: -0.63 EPA/play4Wk 6 vs South Alabama: +1.30 EPA/play6Wk 7 vs Texas State: +0.57 EPA/play7Wk 9 vs Louisiana: +0.60 EPA/play9Wk 10 vs Arkansas State: -0.55 EPA/play10Wk 12 vs Old Dominion: -0.52 EPA/play12Wk 13 vs Georgia State: +0.33 EPA/play13Wk 14 vs Southern Miss: +0.13 EPA/play14Wk 15 vs James Madison: -0.09 EPA/play15
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsNichollsW38-200.60
2@ClemsonL16-279.533010.00170.69
3vsMemphisL7-287.6-0.45
4@BuffaloW21-17-7.52189.0014-0.63
6vsSouth AlabamaW31-24-12.755911.81221.30
7@Texas StateW48-412.31014814.82480.57
9vsLouisianaW35-23-10.13248.00130.60
10vsArkansas StateL10-23-8.8200.004-0.55
12@Old DominionL0-335.9188.008-0.52
13vsGeorgia StateW31-19-24.5810312.92350.33
14@Southern MissW28-18-7.16406.7090.13
15@James MadisonL14-3112.345012.5020-0.09
20vsJacksonville StateL13-17-6.72189.0018

Usage & Situational · Pro

Snap-share proxy
Overall
8.2%
Passing plays
15.3%
Rushing plays
0.9%
Standard downs
6.8%
Passing downs
11.0%
EPA by down type
Standard downs
0.21
Passing downs
0.28
Pass / Rush EPA
0.24 / 0.24

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.