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Justin Bowick

#0Justin Bowick

Justin Bowick is a Red Zone Weapon WR for Illinois. Justin's 2025 season produced 25.3 total EPA across 35 plays.

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 Bowick'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
22 Receptions265 Rec yards5 Rec TD12.0 Yards/rec

Performance Analysis · 2025 · vs WR peers

  • Efficiency100
  • Volume14
  • Explosiveness34
  • Consistency73
  • Pass-Down100
Player type
Red Zone Weapon WR

Goes from good to great inside the 20 — high TD conversion on limited looks makes this receiver a scoring machine.

Red zone targetHigh TD rateSize/catch radius advantage
Peer percentiles
Opponent-adjusted EPA (WEPA/play)100th %ile · elite
Game-to-game consistency73th %ile · average
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 consistency — reliable floor each week.
  • 7 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 — 0.75 EPA/play decline from first to second half.
  • Peak game: 2.83 EPA/play in Wk 5 vs USC (SP+ 17).

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
Quadree HendersonPittsburgh0.5301.633.4
DeAndre HughesAir Force0.4701.328.2
Keytaon ThompsonMississippi State0.4601.232.2
Savion WilliamsTCU0.4501.125.2
Bert Emanuel Jr.Central Michigan0.4601.624.4

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

Game Log · box score + EPA, week by week

+2.8302.83Wk 1 vs Western Illinois: +1.34 EPA/play1Wk 2 vs Duke: +1.09 EPA/play2Wk 3 vs Western Michigan: +2.25 EPA/play3Wk 5 vs USC: +2.83 EPA/play5Wk 6 vs Purdue: -0.15 EPA/play6Wk 7 vs Ohio State: +0.01 EPA/play7Wk 9 vs Washington: -0.04 EPA/play9Wk 10 vs Rutgers: +1.23 EPA/play10Wk 12 vs Maryland: +1.12 EPA/play12Wk 13 vs Wisconsin: +0.58 EPA/play13
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsWestern IllinoisW52-33237.72131.34
2@DukeW45-196.645012.51211.09
3vsWestern MichiganW38-0-1.411313.00132.25
5vsUSCW34-3216.912525.01252.83
6@PurdueW43-27-6.122412.0016-0.15
7vsOhio StateL16-3430.111515.00150.01
9@WashingtonL25-4218.4144.004-0.04
10vsRutgersW35-131.023316.50171.23
12vsMarylandW24-60.622311.50131.12
13@WisconsinL10-27-4.422412.00130.58
20vsTennesseeW30-2815.033110.3118

Usage & Situational · Pro

Snap-share proxy
Overall
4.9%
Passing plays
10.3%
Rushing plays
0.0%
Standard downs
3.8%
Passing downs
7.5%
EPA by down type
Standard downs
0.51
Passing downs
0.97
Pass / Rush EPA
0.72 / —

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.