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Will Swartz

#84Will Swartz

TE·Rice·2026

Will Swartz is a Versatile TE for Rice.

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 Will Swartz'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

Returns
1 Kick returns2 KR yards0 KR TD

Performance Analysis · 2026 · vs TE peers

  • Efficiency0
  • Volume7
  • Explosiveness0
  • Consistency50
  • Pass-Down50
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)0th %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.

NIL Market Tier· 2026

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
A.J. DoyleMassachusetts0.0400.02.1
Robby PreckelNorthwestern0.0600.12.5
Blake BellOklahoma0.0700.14.4
Kaden FeaginIllinois0.0400.04.6

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

Game Log · EPA per play, week by week

WkOpponentResultOpp SP+EPA/playPassRush
1vsHouston ChristianW31-3-0.35-0.35

Usage & Situational · Pro

Snap-share proxy
Overall
2.4%
Passing plays
20.0%
Rushing plays
0.0%
Standard downs
3.2%
Passing downs
0.0%
EPA by down type
Standard downs
-0.35
Passing downs
Pass / Rush EPA
-0.35 / —

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.