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Camerun Peoples

#6Camerun Peoples

RB·App State·20205.3 pts line value1st Round

Camerun Peoples is a Explosive Back for App State. Camerun's 2020 season ranks in the 93th percentile nationally by opponent-adjusted EPA per play across 163 plays — a elite 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 Camerun Peoples'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.

2020 Production

Rushing
1124 Rush yards12 Rush TD168 Carries6.7 Yards/carry
Receiving
3 Receptions14 Rec yards0 Rec TD4.7 Yards/rec

Performance Analysis · 2020 · vs RB peers

  • Efficiency93
  • Volume64
  • Explosiveness74
  • Consistency57
  • Receiving11
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)93th %ile · elite
Game-to-game consistency57th %ile · average
Key findings
  • Top-10% efficiency among RBs — elite opponent-adjusted EPA rate.
  • 4 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Strong second-half surge — EPA/play improved 0.17 from the first to second half of the season.
  • Peak game: 1.09 EPA/play in Wk 1 vs North Texas (SP+ -8).

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
Clyde Edwards-HelaireLSU0.4905.0105.8
Travis EtienneClemson0.4704.7100.1
Devon JohnsonMarshall0.5206.0108.2
Dalvin CookFlorida State0.4505.8102.6
Tyjae SpearsTulane0.4505.7105.3

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

Game Log · box score + EPA, week by week

+1.0901.09Wk 2 vs Charlotte: +0.61 EPA/play2Wk 3 vs Marshall: +0.09 EPA/play3Wk 8 vs Arkansas State: -0.31 EPA/play8Wk 9 vs UL Monroe: -0.01 EPA/play9Wk 10 vs Texas State: +0.53 EPA/play10Wk 11 vs Georgia State: +0.20 EPA/play11Wk 12 vs Coastal Carolina: +0.32 EPA/play12Wk 13 vs Troy: +0.65 EPA/play13Wk 14 vs Louisiana: -0.01 EPA/play14Wk 15 vs Georgia Southern: -0.12 EPA/play15Wk 1 vs North Texas: +1.09 EPA/play1
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDRecRec YdsRec TDEPA/play
2vsCharlotteW35-20-6.6131027.810.61
3@MarshallL7-179.512574.801000.09
4vsCampbellW52-21
8vsArkansas StateW45-17-6.512211.80-0.31
9@UL MonroeW31-13-18.49525.81-0.01
10@Texas StateW38-17-13.47679.610.53
11vsGeorgia StateW17-13-5.717673.9111200.20
12@Coastal CarolinaL23-346.6271786.610.32
13vsTroyW47-102.310959.511200.65
14vsLouisianaL21-248.121994.71-0.01
15@Georgia SouthernW34-260.218693.80-0.12
1vsNorth TexasW56-28-8.02231714.451.09

Usage & Situational · Pro

Snap-share proxy
Overall
22.5%
Passing plays
1.4%
Rushing plays
36.0%
Standard downs
26.2%
Passing downs
14.0%
EPA by down type
Standard downs
0.29
Passing downs
0.20
Pass / Rush EPA
0.37 / 0.28

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

Career · rolling EPA, game by game

Per-game EPA5-game avg
+1.230−0.45
EPA per play · 2020 · 11 games

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.