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Nate Sullivan Jr.
Nate Sullivan Jr.

#80Nate Sullivan Jr.

TE·UL Monroe·2025

Nate Sullivan Jr. is a Slot Specialist TE for UL Monroe.

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 Nate Sullivan Jr.'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
6 Receptions48 Rec yards0 Rec TD8.0 Yards/rec
Returns
2 Kick returns25 KR yards0 KR TD

Performance Analysis · 2025 · vs TE peers

  • Efficiency0
  • Volume7
  • Explosiveness7
  • Consistency0
  • Pass-Down78
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)0th %ile · below avg
Game-to-game consistency0th %ile · below avg
Key findings
  • ▸Below-average efficiency vs TE peers — value comes through volume, not per-play impact.
  • ▸Limited usage share suggests a rotational or specialist role.
  • ▸High game-to-game variance — boom-or-bust profile.
  • ▸3 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • ▸Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • ▸Strong second-half surge — EPA/play improved 0.50 from the first to second half of the season.
  • ▸Peak game: 1.46 EPA/play in Wk 14 vs Louisiana (SP+ -10).

NIL Market Tier· 2025

On3 valuation ↗
Contributor

Rotational contributor. Smaller collective or local 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
Robby PreckelNorthwestern0.0600.12.5
A.J. DoyleMassachusetts0.0400.02.1
Blake BellOklahoma0.0700.14.4
Kaden FeaginIllinois0.1500.07.8
Jaheim BellSouth Carolina0.1100.08.0

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

Game Log · box score + EPA, week by week

+1.460−1.46Wk 1 vs St. Francis (PA): -0.46 EPA/play1Wk 6 vs Northwestern: +1.04 EPA/play6Wk 7 vs Coastal Carolina: -1.03 EPA/play7Wk 8 vs Troy: +0.92 EPA/play8Wk 9 vs Southern Miss: +0.16 EPA/play9Wk 13 vs Texas State: -0.58 EPA/play13Wk 14 vs Louisiana: +1.46 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1vsSt. Francis (PA)W29-0—2115.5012-0.46
6@NorthwesternL7-425.8—————1.04
7@Coastal CarolinaL8-23-15.1—————-1.03
8vsTroyL14-37-4.8199.0090.92
9@Southern MissL21-49-7.111414.00140.16
13@Texas StateL14-312.3133.003-0.58
14@LouisianaL27-30-10.111111.00111.46

Usage & Situational · Pro

Snap-share proxy
Overall
2.3%
Passing plays
5.2%
Rushing plays
0.0%
Standard downs
1.6%
Passing downs
3.5%
EPA by down type
Standard downs
-0.06
Passing downs
0.10
Pass / Rush EPA
0.04 / —

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.