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Paul Perkins

#24Paul Perkins

RB·UCLA·201520144.6 pts line valueDay 2 (Rds 2–3)

Paul Perkins is a 2-year Featured Back for UCLA. Paul's 2014 season ranks in the 53th percentile nationally by opponent-adjusted EPA per play across 260 plays — a average rate for the RB.

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 Paul Perkins'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.

2014 Production

Rushing
1572 Rush yards9 Rush TD250 Carries6.3 Yards/carry
Receiving
26 Receptions201 Rec yards2 Rec TD7.7 Yards/rec

Performance Analysis · 2014 · vs RB peers

  • Efficiency53
  • Volume80
  • Explosiveness66
  • Consistency68
  • Receiving43
Player type
Featured Back

The centerpiece of the run game — high carry volume, used in early downs and goal-line, true workhorse role.

Primary ball carrierHigh volumeGoal-line threat
Peer percentiles
Opponent-adjusted EPA (WEPA/play)53th %ile · average
Game-to-game consistency68th %ile · average
Key findings
  • High-volume role — one of the team's most-used RBs by play share.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Peak game: 0.57 EPA/play in Wk 1 vs Kansas State (SP+ 16).

Historical Comparables · RB · efficiency + volume + value

Players from 2013–2025 matched on EPA efficiency, play volume, and adjusted value tier — not just one metric.

PlayerTeamWEPA/playLine valTotal EPA
James FlandersTulsa0.3904.9103.7
Hassan HaskinsMichigan0.3804.8106.4
Royce FreemanOregon0.3605.199.0
Ameer AbdullahNebraska0.3805.399.6
Blake CorumMichigan0.3805.1107.5

Comps are statistical — efficiency, volume, and value tier all factor in. Style and conference context differ.

Game Log · box score + EPA, week by week

+0.5700.57Wk 1 vs Virginia: +0.03 EPA/play1Wk 2 vs Memphis: +0.03 EPA/play2Wk 3 vs Texas: +0.31 EPA/play3Wk 6 vs Utah: +0.26 EPA/play6Wk 7 vs Oregon: +0.29 EPA/play7Wk 8 vs California: +0.40 EPA/play8Wk 9 vs Colorado: +0.16 EPA/play9Wk 10 vs Arizona: -0.24 EPA/play10Wk 11 vs Washington: +0.04 EPA/play11Wk 13 vs USC: +0.13 EPA/play13Wk 14 vs Stanford: +0.44 EPA/play14Wk 1 vs Kansas State: +0.57 EPA/play1
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDRecRec YdsRec TDEPA/play
1@VirginiaW28-204.016805.0011000.03
2vsMemphisW42-355.623984.323100.03
3vsTexasW20-179.0241265.3056900.31
5@Arizona StateW62-2713.5141379.801-10
6vsUtahL28-308.817995.810.26
7vsOregonL30-4224.7211878.9031300.29
8@CaliforniaW36-34-0.615865.7047520.40
9@ColoradoW40-37-5.0191809.5221200.16
10vsArizonaW17-77.621783.71100-0.24
11@WashingtonW44-307.819985.2041900.04
13vsUSCW38-2017.124933.910.13
14vsStanfordL10-3121.4171166.802300.44
1vsKansas StateW40-3516.3201949.720.57

Usage & Situational · Pro

Snap-share proxy
Overall
28.1%
Passing plays
6.7%
Rushing plays
48.9%
Standard downs
32.1%
Passing downs
18.8%
EPA by down type
Standard downs
0.15
Passing downs
0.31
Pass / Rush EPA
0.16 / 0.18

Usage = share of team plays (CFBD has no true snap counts).

Career · rolling EPA, game by game

Per-game EPA5-game avg
+0.780−0.332015
EPA per play · 2014 — 2015 · 25 games
SeasonTeamLine valueTotal EPA
2014UCLA
4.6
88.6
2015UCLA
3.9
80.6

Chart shows per-game EPA (bars) and rolling 5-game average (line). Season breaks marked with dashed lines. Line value = est. points over replacement per game.

EPA = expected points added (opponent-adjusted). NIL estimates are model-based ranges, not reported deals. Data: CollegeFootballData. Not betting advice.