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Max Reese

#7Max Reese

Max Reese is a Slot Specialist TE for North Texas.

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 Max Reese'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.

2026 Production

Receiving
4 Receptions25 Rec yards0 Rec TD6.3 Yards/rec

Performance Analysis · 2026 · vs TE peers

  • Efficiency100
  • Volume13
  • Explosiveness0
  • Consistency50
  • Pass-Down0
Player type
Slot Specialist TE

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
Key findings
  • Top-10% efficiency among TEs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • Peak game: 1.57 EPA/play in Wk 2 vs UNLV (SP+ 2).

NIL Market Tier· 2026

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
Ty ThompsonTulane0.4200.720.2
Seth GreenMinnesota0.3900.032.4
Johnny LanganRutgers0.3000.017.7
Jordan MyersRice0.2700.215.9
Johnny LanganRutgers0.2400.08.9

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

Game Log · box score + EPA, week by week

+1.5701.57Wk 1 vs Indiana: -0.17 EPA/play1Wk 2 vs UNLV: +1.57 EPA/play2
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1@IndianaL16-5224.1393.007-0.17
2vsUNLVW44-62.311616.00161.57

Usage & Situational · Pro

Snap-share proxy
Overall
4.4%
Passing plays
10.0%
Rushing plays
0.0%
Standard downs
1.1%
Passing downs
10.9%
EPA by down type
Standard downs
0.77
Passing downs
0.34
Pass / Rush EPA
0.41 / —

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.