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Hunter Welcing

#84Hunter Welcing

Hunter Welcing is a Versatile TE for Northwestern. Hunter's 2025 season produced 16.5 total EPA across 32 plays.

2026 Usage Outlook · projected share of team plays

4%
projected
band 2%'25 5%6%

Regressed toward the TE mean. Model correlation r≈0.42 on a 2019-2025 walk-forward — volume only; efficiency not projected.

2025 Production

Receiving
28 Receptions296 Rec yards2 Rec TD10.6 Yards/rec
Returns
2 Kick returns13 KR yards0 KR TD

Performance Analysis · 2025 · vs TE peers

EfficiencyVolumeExplosivenessConsistencyPass-Down
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)100th %ile · elite
Game-to-game consistency59th %ile · average
Key findings
  • Top-10% efficiency among TEs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • 7 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Production faded as the season progressed — 0.69 EPA/play decline from first to second half.
  • Peak game: 2.87 EPA/play in Wk 2 vs Western Illinois.

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 2014–2024 matched on EPA efficiency, play volume, and adjusted value tier — not just one metric.

PlayerTeamYrPlaysWEPA/playLine valTotal EPA
Ty ThompsonTulane2024480.4200.420.2
Seth GreenMinnesota2018830.3900.032.4
Johnny LanganRutgers2020590.3000.017.7
Evan SvobodaWyoming2024750.2900.021.8
Jordan MyersRice2021590.2700.215.9

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

Game Log · box score + EPA, week by week

Wk 1 vs Tulane: -0.60 EPA/play1Wk 2 vs Western Illinois: +2.87 EPA/play2Wk 3 vs Oregon: +0.86 EPA/play3Wk 5 vs UCLA: +1.49 EPA/play5Wk 6 vs UL Monroe: +0.62 EPA/play6Wk 8 vs Purdue: +0.63 EPA/play8Wk 11 vs USC: -0.35 EPA/play11Wk 12 vs Michigan: +0.59 EPA/play12Wk 13 vs Minnesota: +1.03 EPA/play13Wk 14 vs Illinois: +0.22 EPA/play14Wk 1 vs Central Michigan: -0.02 EPA/play1
EPA per play, by weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
1@TulaneL3-236.3122.002-0.60
2vsWestern IllinoisW42-723417.01282.87
3vsOregonL14-3425.92199.50120.86
5vsUCLAW17-14-8.712222.00221.49
6vsUL MonroeW42-7-21.64328.00170.62
8vsPurdueW19-0-6.12189.01150.63
9@NebraskaL21-286.222914.5022
11@USCL17-3816.9221.006-0.35
12vsMichiganL22-2412.448120.30360.59
13vsMinnesotaW38-351.53299.70151.03
14@IllinoisL13-2012.94153.8050.22
1vsCentral MichiganW34-7-8.811313.0013-0.02

Usage & Situational · Pro

Snap-share proxy
Overall
4.5%
Passing plays
9.6%
Rushing plays
0.0%
Standard downs
4.7%
Passing downs
4.0%
EPA by down type
Standard downs
0.55
Passing downs
0.42
Pass / Rush EPA
0.52 / —

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.