Skip to content
A'Marion Peterson
A'Marion Peterson

#28A'Marion Peterson

RB·UTSA·2025

A'Marion Peterson is a Committee Back for UTSA.

What projects, and what doesn't · RBs · 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)0.52
    Beats guessing the RB average by 18%. n=4,219 RB seasons
  • EPA per play (efficiency)0.10
    Not projectable — we do not forecast this. n=3,575 RB seasons
  • Total EPA (value)0.41
    Beats guessing the RB average by 9%. n=3,575 RB seasons

Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So A'Marion Peterson'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

Rushing
177 Rush yards3 Rush TD49 Carries3.6 Yards/carry
Receiving
2 Receptions7 Rec yards0 Rec TD3.5 Yards/rec

Performance Analysis · 2025 · vs RB peers

  • Efficiency0
  • Volume21
  • Explosiveness12
  • Consistency26
  • Receiving22
Player type
Committee Back

Part of a rotation — contributes in a complementary role and keeps the featured back fresh.

Rotational roleSituational use
Peer percentiles
Opponent-adjusted EPA (WEPA/play)0th %ile · below avg
Game-to-game consistency26th %ile · below avg
Key findings
  • Below-average efficiency vs RB 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.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Strong second-half surge — EPA/play improved 0.26 from the first to second half of the season.

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.

Game Log · box score + EPA, week by week

+1.6401.64Wk 1 vs Texas A&M: +0.08 EPA/play1Wk 2 vs Texas State: -1.64 EPA/play2Wk 3 vs Incarnate Word: -0.07 EPA/play3Wk 7 vs Rice: -0.18 EPA/play7Wk 8 vs North Texas: +0.14 EPA/play8Wk 10 vs Tulane: -0.41 EPA/play10Wk 11 vs South Florida: -0.10 EPA/play11Wk 12 vs Charlotte: +0.23 EPA/play12Wk 13 vs East Carolina: -0.01 EPA/play13
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDRecRec YdsRec TDEPA/play
1@Texas A&ML24-4220.76264.300.08
2vsTexas StateL36-432.3210.51-1.64
3vsIncarnate WordW48-20591.80-0.07
7vsRiceW61-13-14.8263.00-0.18
8@North TexasL17-5513.83186.000.14
10vsTulaneW48-266.3133.00-0.41
11@South FloridaL23-5511.66183.00-0.10
12@CharlotteW28-7-26.76264.300.23
13vsEast CarolinaW58-248.010323.21270-0.01
20vsFlorida InternationalW57-20-10.58384.81

Usage & Situational · Pro

Snap-share proxy
Overall
7.4%
Passing plays
0.9%
Rushing plays
14.5%
Standard downs
9.1%
Passing downs
3.7%
EPA by down type
Standard downs
-0.08
Passing downs
0.94
Pass / Rush EPA
-0.48 / 0.10

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.
A Marion Peterson Stats, EPA & Player Profile — Utsa · Gridpex