Skip to content
Keveun Mason

#26Keveun Mason

Keveun Mason is a Pass-Catching Back for Temple.

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 Keveun Mason'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
167 Rush yards1 Rush TD28 Carries6.0 Yards/carry
Receiving
6 Receptions30 Rec yards0 Rec TD5.0 Yards/rec

Performance Analysis · 2025 · vs RB peers

  • Efficiency70
  • Volume19
  • Explosiveness60
  • Consistency0
  • Receiving83
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)70th %ile · average
Game-to-game consistency0th %ile · below avg
Key findings
  • Limited usage share suggests a rotational or specialist role.
  • High game-to-game variance — boom-or-bust profile.
  • Strong second-half surge — EPA/play improved 0.27 from the first to second half of the season.
  • Peak game: 1.22 EPA/play in Wk 7 vs Navy (SP+ 6).

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

+2.1702.17Wk 2 vs Howard: +0.09 EPA/play2Wk 7 vs Navy: +1.22 EPA/play7Wk 8 vs Charlotte: -0.32 EPA/play8Wk 9 vs Tulsa: -2.17 EPA/play9Wk 10 vs East Carolina: -0.10 EPA/play10Wk 11 vs Army: +0.25 EPA/play11Wk 13 vs Tulane: -0.18 EPA/play13Wk 14 vs North Texas: -0.09 EPA/play14
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDRecRec YdsRec TDEPA/play
2vsHowardW55-7155.000.09
7vsNavyL31-326.222814.001.22
8@CharlotteW49-14-26.76254.20-0.32
9@TulsaW38-37-10.01-7-7.00-2.17
10vsEast CarolinaL14-458.07486.912190-0.10
11@ArmyL13-140.84369.001700.25
13vsTulaneL13-376.3166.00230-0.18
14@North TexasL25-5213.86264.30110-0.09

Usage & Situational · Pro

Snap-share proxy
Overall
6.8%
Passing plays
3.1%
Rushing plays
10.5%
Standard downs
6.4%
Passing downs
8.0%
EPA by down type
Standard downs
0.27
Passing downs
0.19
Pass / Rush EPA
0.52 / 0.18

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.