Skip to content
Jobi Malary

#28Jobi Malary

Jobi Malary is a Explosive Back for James Madison.

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 Jobi Malary'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
349 Rush yards4 Rush TD43 Carries8.1 Yards/carry

Performance Analysis · 2025 · vs RB peers

  • Efficiency57
  • Volume21
  • Explosiveness100
  • Consistency46
  • Receiving0
Player type
Explosive Back

Elite per-carry efficiency — breaks big runs and creates chunk plays at a top rate while in a limited role.

Big-play threatHigh EPA per carryCapitalises on opportunities
Peer percentiles
Opponent-adjusted EPA (WEPA/play)57th %ile · average
Game-to-game consistency46th %ile · average
Key findings
  • Limited usage share suggests a rotational or specialist role.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Production faded as the season progressed — 0.26 EPA/play decline from first to second half.
  • Peak game: 1.42 EPA/play in Wk 12 vs App State (SP+ -11).

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

+1.4201.42Wk 1 vs Weber State: +0.37 EPA/play1Wk 8 vs Old Dominion: +0.06 EPA/play8Wk 10 vs Texas State: -0.08 EPA/play10Wk 12 vs App State: +1.42 EPA/play12Wk 13 vs Washington State: -0.47 EPA/play13Wk 14 vs Coastal Carolina: +0.92 EPA/play14Wk 15 vs Troy: +0.10 EPA/play15
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDEPA/play
1vsWeber StateW45-105316.200.37
8vsOld DominionW63-275.9111.000.06
10@Texas StateW52-202.33103.30-0.08
12vsApp StateW58-10-11.4810513.131.42
13vsWashington StateW24-203.86172.80-0.47
14@Coastal CarolinaW59-10-15.11215412.810.92
15vsTroyW31-14-4.86254.200.10
20@OregonL34-5125.9263.00

Usage & Situational · Pro

Snap-share proxy
Overall
7.4%
Passing plays
0.0%
Rushing plays
12.8%
Standard downs
9.3%
Passing downs
2.9%
EPA by down type
Standard downs
0.18
Passing downs
0.38
Pass / Rush EPA
— / 0.21

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.