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Zack Marshall
Zack Marshall

#83Zack Marshall

TE·Michigan·2025

Zack Marshall is a Slot Specialist TE for Michigan.

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 Zack Marshall'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 Receptions199 Rec yards1 Rec TD12.4 Yards/rec

Performance Analysis · 2025 · vs TE peers

  • Efficiency100
  • Volume11
  • Explosiveness36
  • Consistency81
  • Pass-Down37
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
Game-to-game consistency81th %ile · above 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 consistency — reliable floor each week.
  • ▸4 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • ▸Peak game: 1.03 EPA/play in Wk 8 vs Washington (SP+ 18).

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 · 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
Evan SvobodaWyoming0.2900.521.8
Jordan MyersRice0.2700.215.9

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

Game Log · box score + EPA, week by week

+1.030−1.03Wk 2 vs Oklahoma: +0.04 EPA/play2Wk 4 vs Nebraska: +0.17 EPA/play4Wk 6 vs Wisconsin: +0.95 EPA/play6Wk 8 vs Washington: +1.03 EPA/play8Wk 10 vs Purdue: +0.71 EPA/play10Wk 12 vs Northwestern: +0.29 EPA/play12Wk 13 vs Maryland: +0.72 EPA/play13
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
2@OklahomaL13-2418.311212.00120.04
4@NebraskaW30-276.2166.0060.17
6vsWisconsinW24-10-4.411111.00110.95
8vsWashingtonW24-718.457214.41191.03
10vsPurdueW21-16-6.135819.30370.71
12vsNorthwesternW24-225.8263.0040.29
13@MarylandW45-200.623015.00200.72
20vsTexasL27-4116.2144.004—

Usage & Situational · Pro

Snap-share proxy
Overall
4.0%
Passing plays
9.3%
Rushing plays
0.0%
Standard downs
3.4%
Passing downs
5.7%
EPA by down type
Standard downs
0.63
Passing downs
0.55
Pass / Rush EPA
0.60 / —

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.