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Joseph Dodds

#27Joseph Dodds

Joseph Dodds is a Committee Back for Baylor.

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 Joseph Dodds'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
104 Rush yards1 Rush TD26 Carries4.0 Yards/carry
Receiving
2 Receptions11 Rec yards0 Rec TD5.5 Yards/rec

Performance Analysis · 2025 · vs RB peers

  • Efficiency0
  • Volume21
  • Explosiveness20
  • Consistency0
  • Receiving23
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 consistency0th %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.
  • Peak game: 0.36 EPA/play in Wk 10 vs UCF (SP+ -1).

NIL Market Tier· 2025

On3 valuation ↗
Starter

Meaningful starter. Local collective + position-group 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

+0.3800.38Wk 3 vs Samford: -0.28 EPA/play3Wk 5 vs Oklahoma State: -0.35 EPA/play5Wk 10 vs UCF: +0.36 EPA/play10Wk 12 vs Utah: -0.38 EPA/play12Wk 14 vs Houston: +0.24 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDRecRec YdsRec TDEPA/play
3vsSamfordW42-7372.30160-0.28
5@Oklahoma StateW45-27-15.14123.00150-0.35
10vsUCFW30-3-1.24164.000.36
12vsUtahL28-5522.2382.70-0.38
14vsHoustonL24-317.412615.110.24

Usage & Situational · Pro

Snap-share proxy
Overall
7.2%
Passing plays
0.9%
Rushing plays
15.8%
Standard downs
8.4%
Passing downs
4.2%
EPA by down type
Standard downs
0.08
Passing downs
0.17
Pass / Rush EPA
0.03 / 0.09

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.