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Marlon Mack

#5Marlon Mack

RB·South Florida·201620153.5 pts line valueDay 2 (Rds 2–3)

Marlon Mack is a 2-year Pass-Catching Back for South Florida. Marlon's 2016 season ranks in the 85th percentile nationally by opponent-adjusted EPA per play across 187 plays — a above-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 Marlon Mack'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.

2016 Production

Rushing
1187 Rush yards15 Rush TD174 Carries6.8 Yards/carry
Receiving
28 Receptions227 Rec yards0 Rec TD8.1 Yards/rec

Performance Analysis · 2016 · vs RB peers

  • Efficiency85
  • Volume70
  • Explosiveness76
  • Consistency71
  • Receiving91
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)85th %ile · above avg
Game-to-game consistency71th %ile · average
Key findings
  • Above-average efficiency for the RB position (85th percentile).
  • High game-to-game consistency — reliable floor each week.
  • 3 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Peak game: 0.64 EPA/play in Wk 3 vs Syracuse (SP+ -3).

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
Travis EtienneClemson0.4704.7100.1
Clyde Edwards-HelaireLSU0.4905.0105.8
Saquon BarkleyPenn State0.4105.298.4
Nick WilsonArizona0.4105.2102.5
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

+0.6400.64Wk 1 vs Towson: +0.20 EPA/play1Wk 3 vs Syracuse: +0.64 EPA/play3Wk 4 vs Florida State: +0.09 EPA/play4Wk 5 vs Cincinnati: +0.17 EPA/play5Wk 6 vs East Carolina: +0.02 EPA/play6Wk 7 vs UConn: +0.46 EPA/play7Wk 8 vs Temple: +0.27 EPA/play8Wk 9 vs Navy: +0.61 EPA/play9Wk 11 vs Memphis: +0.32 EPA/play11Wk 12 vs SMU: +0.13 EPA/play12Wk 1 vs South Carolina: -0.20 EPA/play1
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+CarRush YdsAvgRush TDRecRec YdsRec TDEPA/play
1vsTowsonW56-209586.410.20
3@SyracuseW45-20-2.7911512.821800.64
4vsFlorida StateL35-5524.012423.510.09
5@CincinnatiW45-20-3.6201185.920.17
6vsEast CarolinaW38-22-9.0181528.423500.02
7vsUConnW42-27-11.6161076.7167500.46
8@TempleL30-4611.913675.2133300.27
9vsNavyW52-456.81112511.4132500.61
11@MemphisW49-427.715694.6196100.32
12@SMUW35-27-10.8181297.210.13
13vsUCFW48-31-2.2201557.82180
1vsSouth CarolinaW46-39-4.013503.802120-0.20

Usage & Situational · Pro

Snap-share proxy
Overall
24.6%
Passing plays
12.3%
Rushing plays
33.0%
Standard downs
27.9%
Passing downs
17.0%
EPA by down type
Standard downs
0.24
Passing downs
0.27
Pass / Rush EPA
0.08 / 0.29

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

Career · rolling EPA, game by game

Per-game EPA5-game avg
+0.960−0.402016
EPA per play · 2015 — 2016 · 23 games
SeasonTeamLine valueTotal EPA
2015South Florida
2.9
61.1
2016South Florida
3.5
68.6

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.