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Gabe Milbourn

#82Gabe Milbourn

Gabe Milbourn is a Versatile TE for Oregon State.

What projects, and what doesn't · TEs · 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)0.42
    Beats guessing the TE average by 9%. n=2,225 TE seasons
  • EPA per play (efficiency)0.04
    Not projectable — we do not forecast this. n=2,016 TE seasons
  • Total EPA (value)0.46
    Beats guessing the TE average by 13%. n=2,016 TE seasons

Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Gabe Milbourn'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
17 Receptions185 Rec yards1 Rec TD10.9 Yards/rec

Performance Analysis · 2025 · vs TE peers

  • Efficiency100
  • Volume14
  • Explosiveness26
  • Consistency14
  • Pass-Down0
Player type
Versatile TE

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 consistency14th %ile · below avg
Key findings
  • Top-10% efficiency among TEs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • High game-to-game variance — boom-or-bust profile.
  • Production faded as the season progressed — 0.42 EPA/play decline from first to second half.
  • Peak game: 0.63 EPA/play in Wk 8 vs Lafayette.

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 · TE · 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
Johnny LanganRutgers0.2400.08.9
Jordan MyersRice0.2700.215.9
Johnny LanganRutgers0.3000.017.7
D'Vaughn PennamonOle Miss0.2000.011.0
Evan SvobodaWyoming0.2900.521.8

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

Game Log · box score + EPA, week by week

+0.6300.63Wk 5 vs Houston: +0.26 EPA/play5Wk 6 vs App State: -0.10 EPA/play6Wk 7 vs Wake Forest: +0.58 EPA/play7Wk 8 vs Lafayette: +0.63 EPA/play8Wk 11 vs Sam Houston: +0.02 EPA/play11Wk 12 vs Tulsa: -0.23 EPA/play12Wk 14 vs Washington State: -0.31 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
5vsHoustonL24-277.411010.00100.26
6@App StateL23-27-11.4155.005-0.10
7vsWake ForestL14-395.744411.00180.58
8vsLafayetteW45-136488.01200.63
11vsSam HoustonL17-21-27.835719.00260.02
12@TulsaL14-31-10.011313.0013-0.23
14@Washington StateL8-323.8188.008-0.31

Usage & Situational · Pro

Snap-share proxy
Overall
5.0%
Passing plays
9.6%
Rushing plays
0.0%
Standard downs
4.8%
Passing downs
5.6%
EPA by down type
Standard downs
0.76
Passing downs
-0.97
Pass / Rush EPA
0.27 / —

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.