Skip to content
Garrett Miller

#88Garrett Miller

Garrett Miller is a Versatile TE for Purdue. Garrett's 2023 season produced 15.9 total EPA across 31 plays.

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 Garrett Miller'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.

2023 Production

Receiving
30 Receptions243 Rec yards2 Rec TD8.1 Yards/rec

Performance Analysis · 2023 · vs TE peers

  • Efficiency100
  • Volume15
  • Explosiveness7
  • Consistency63
  • Pass-Down100
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 consistency63th %ile · average
Key findings
  • Top-10% efficiency among TEs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • 5 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 — 0.34 EPA/play decline from first to second half.
  • Peak game: 1.70 EPA/play in Wk 5 vs Illinois (SP+ -3).

NIL Market Tier· 2023

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 2013–2025 matched on EPA efficiency, play volume, and adjusted value tier — not just one metric.

PlayerTeamWEPA/playLine valTotal EPA
Ty ThompsonTulane0.4200.720.2
Seth GreenMinnesota0.3900.032.4
Johnny LanganRutgers0.3000.017.7
Evan SvobodaWyoming0.2900.521.8
Jordan MyersRice0.2700.215.9

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

Game Log · box score + EPA, week by week

+1.7001.70Wk 2 vs Virginia Tech: +0.48 EPA/play2Wk 5 vs Illinois: +1.70 EPA/play5Wk 6 vs Iowa: +0.76 EPA/play6Wk 7 vs Ohio State: +0.09 EPA/play7Wk 9 vs Nebraska: -0.20 EPA/play9Wk 10 vs Michigan: +0.46 EPA/play10Wk 11 vs Minnesota: +1.28 EPA/play11Wk 12 vs Northwestern: -0.26 EPA/play12Wk 13 vs Indiana: +0.18 EPA/play13
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+RecRec YdsAvgRec TDLongEPA/play
2@Virginia TechW24-175.8188.0080.48
5vsIllinoisW44-19-2.523115.51281.70
6@IowaL14-205.88718.90160.76
7vsOhio StateL7-4125.22105.0050.09
9@NebraskaL14-310.35265.2011-0.20
10@MichiganL13-4131.3199.0090.46
11vsMinnesotaW49-300.466510.81201.28
12@NorthwesternL15-23-1.34174.3011-0.26
13vsIndianaW35-31-7.4166.0060.18

Usage & Situational · Pro

Snap-share proxy
Overall
5.1%
Passing plays
11.4%
Rushing plays
0.0%
Standard downs
5.2%
Passing downs
5.0%
EPA by down type
Standard downs
0.12
Passing downs
1.34
Pass / Rush EPA
0.51 / —

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.