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Joey Mattord

#24Joey Mattord

Joey Mattord is a Pass-Catching Back for Eastern Michigan.

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 Joey Mattord'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
48 Rush yards1 Rush TD6 Carries8.0 Yards/carry
Receiving
4 Receptions33 Rec yards0 Rec TD8.3 Yards/rec
Returns
3 Kick returns61 KR yards0 KR TD

Air yards

Where the ball goes, and how much of the gain is the throw rather than the run after it.

6
Targets
-4.0y
Avg depth
6.8y
After catch
83%
Catch rate

The ball travels -4.0 yards in the air on an average target 13.0 yards shorter than the median. Another 6.8 comes after the catch.

Where he is targeted

targets · completion rate · yards
deep
0
0
0
short
1
100% · 9y
0
5
80% · 9y
leftmiddleright

Depth and direction come from CFBD’s passing detail, which is backfilled after the games: this covers weeks 1–2 only. Spikes, throwaways and intentional grounding are excluded before any average.

Performance Analysis · 2025 · vs RB peers

  • Efficiency100
  • Volume11
  • Explosiveness100
  • Consistency78
  • Receiving100
Player type
Pass-Catching Back

Third-down weapon out of the backfield. Routes, hands, and separation in coverage define this role as much as rushing.

3rd-down backReceiving threatPass protection
Peer percentiles
Opponent-adjusted EPA (WEPA/play)100th %ile · elite
Game-to-game consistency78th %ile · above avg
Key findings
  • Top-10% efficiency among RBs — elite opponent-adjusted EPA rate.
  • Limited usage share suggests a rotational or specialist role.
  • High game-to-game consistency — reliable floor each week.
  • 3 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Peak game: 2.69 EPA/play in Wk 3 vs Kentucky (SP+ 2).

NIL Market Tier· 2025

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.

Game Log · box score + EPA, week by week

+2.6902.69Wk 1 vs Texas State: +0.62 EPA/play1Wk 3 vs Kentucky: +2.69 EPA/play3Wk 7 vs Northern Illinois: +1.47 EPA/play7Wk 9 vs Ohio: +0.27 EPA/play9
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDRecRec YdsRec TDEPA/play
1@Texas StateL27-522.35387.612500.62
3@KentuckyL23-481.812202.69
5@Central MichiganL13-24-8.8
7vsNorthern IllinoisW16-10-16.711010.001.47
9vsOhioL21-28-4.01600.27
11vsBowling GreenW27-21-12.6
14vsWestern MichiganL21-31-1.4

Usage & Situational · Pro

Snap-share proxy
Overall
3.8%
Passing plays
2.9%
Rushing plays
5.0%
Standard downs
3.3%
Passing downs
5.0%
EPA by down type
Standard downs
0.89
Passing downs
1.90
Pass / Rush EPA
0.86 / 1.59

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.