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AJ Szymanski

#89AJ Szymanski

AJ Szymanski is a Red Zone Weapon TE for Maryland.

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 AJ Szymanski'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
5 Receptions32 Rec yards1 Rec TD6.4 Yards/rec
Returns
1 Kick returns11 KR yards0 KR TD

Performance Analysis · 2025 · vs TE peers

  • Efficiency0
  • Volume6
  • Explosiveness0
  • Consistency0
  • Pass-Down17
Player type
Red Zone Weapon TE

Goes from good to great inside the 20 — high TD conversion on limited looks makes this receiver a scoring machine.

Red zone targetHigh TD rateSize/catch radius advantage
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.
  • Strong second-half surge — EPA/play improved 0.11 from the first to second half of the season.
  • Peak game: 1.10 EPA/play in Wk 10 vs Indiana (SP+ 32).

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

+1.1001.10Wk 2 vs Northern Illinois: -0.31 EPA/play2Wk 3 vs Towson: +0.08 EPA/play3Wk 6 vs Washington: +0.04 EPA/play6Wk 8 vs UCLA: -0.62 EPA/play8Wk 10 vs Indiana: +1.10 EPA/play10Wk 12 vs Illinois: -0.33 EPA/play12
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
2vsNorthern IllinoisW20-9-16.7122.002-0.31
3vsTowsonW44-17155.0050.08
6vsWashingtonL20-2418.4122.0120.04
8@UCLAL17-20-8.7122.002-0.62
10vsIndianaL10-5532.412121.00211.10
12@IllinoisL6-2412.9-0.33

Usage & Situational · Pro

Snap-share proxy
Overall
2.0%
Passing plays
3.2%
Rushing plays
0.0%
Standard downs
2.2%
Passing downs
1.7%
EPA by down type
Standard downs
-0.25
Passing downs
-0.45
Pass / Rush EPA
-0.32 / —

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.