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Maurice Turner

#0Maurice Turner

Maurice Turner is a Committee Back for Tulane. Maurice's 2025 season produced -2.7 total EPA across 33 plays.

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 Maurice Turner'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
127 Rush yards0 Rush TD28 Carries4.5 Yards/carry
Receiving
1 Receptions4 Rec yards0 Rec TD4.0 Yards/rec
Returns
1 Kick returns18 KR yards0 KR TD

Performance Analysis · 2025 · vs RB peers

  • Efficiency0
  • Volume20
  • Explosiveness30
  • Consistency66
  • Receiving65
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 consistency66th %ile · average
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.
  • Production faded as the season progressed — 0.23 EPA/play decline from first to second half.

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

+0.9300.93Wk 1 vs Northwestern: +0.13 EPA/play1Wk 5 vs Tulsa: -0.75 EPA/play5Wk 8 vs Army: -0.06 EPA/play8Wk 10 vs UTSA: -0.55 EPA/play10Wk 13 vs Temple: -0.93 EPA/play13Wk 14 vs Charlotte: +0.02 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDRecRec YdsRec TDEPA/play
1vsNorthwesternW23-35.814866.101400.13
5@TulsaW31-14-10.0111.00-0.75
8vsArmyW24-170.86294.80-0.06
10@UTSAL26-483.72-1-0.50-0.55
13@TempleW37-13-5.1210.50-0.93
14vsCharlotteW27-0-26.72115.500.02
20@Ole MissL10-4124.0100.00

Usage & Situational · Pro

Snap-share proxy
Overall
7.0%
Passing plays
2.5%
Rushing plays
11.7%
Standard downs
7.5%
Passing downs
5.7%
EPA by down type
Standard downs
0.00
Passing downs
-0.34
Pass / Rush EPA
-0.60 / 0.04

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.