#81Hudson Habermehl

TE·UCLA·2025

Hudson Habermehl is a Slot Specialist TE for UCLA.

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 Hudson Habermehl'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

20 Receptions138 Rec yards0 Rec TD6.9 Yards/rec

Performance Analysis · 2025 · vs TE peers

Efficiency0
Volume12
Explosiveness0
Consistency2
Pass-Down90

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 consistency2th %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.
▸Production faded as the season progressed — 0.55 EPA/play decline from first to second half.
▸Peak game: 1.08 EPA/play in Wk 7 vs Michigan State (SP+ -3).

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.

Player	Team	Yr	Plays	WEPA/play	Line val	Total EPA
Robby Preckel	Northwestern	2025	42	0.060	0.1	2.5
A.J. Doyle	Massachusetts	2013	53	0.040	0.0	2.1
Blake Bell	Oklahoma	2013	63	0.070	0.1	4.4
Jaheim Bell	South Carolina	2022	73	0.110	0.0	8.0
Kaden Feagin	Illinois	2024	52	0.150	0.0	7.8

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

Game Log · box score + EPA, week by week

EPA per play · x-axis: weekabove 0 = added points · below = lost

Wk	Opponent	Result	Opp SP+	Rec	Rec Yds	Avg	Long	EPA/play
1	vsUtah	L10-43	22.2	1	9	9.0	9	0.71
3	vsNew Mexico	L10-35	0.9	4	20	5.0	9	-0.08
5	@Northwestern	L14-17	5.8	2	20	10.0	11	0.12
6	vsPenn State	W42-37	18.1	1	6	6.0	6	0.28
7	@Michigan State	W38-13	-3.4	3	35	11.7	26	1.08
8	vsMaryland	W20-17	0.6	2	6	3.0	7	-0.54
9	@Indiana	L6-56	32.4	2	9	4.5	5	-0.47
11	vsNebraska	L21-28	6.2	1	11	11.0	11	0.41
13	vsWashington	L14-48	18.4	1	5	5.0	5	-0.25
14	@USC	L10-29	16.9	3	17	5.7	8	0.22

Usage & Situational · Pro

Snap-share proxy

Overall

4.1%

Passing plays

7.9%

Rushing plays

0.0%

Standard downs

2.8%

Passing downs

7.0%

EPA by down type

Standard downs: -0.10
Passing downs: 0.14
Pass / Rush EPA: 0.02 / —

Usage = share of team plays (CFBD has no true snap counts).