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Sam Darnold

#14Sam Darnold

QB·USC·2017201610.9 pts line valueDay 2 (Rds 2–3)

Sam Darnold is a 2-year Clutch Passer for USC. Sam's 2017 season ranks in the 60th percentile nationally by opponent-adjusted EPA per play across 554 plays — a average rate for the QB.

What projects, and what doesn't · QBs · 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)0.46
    Beats guessing the QB average by 16%. n=2,421 QB seasons
  • EPA per play (efficiency)0.05
    Not projectable — we do not forecast this. n=1,965 QB seasons
  • Total EPA (value)0.51
    Beats guessing the QB average by 20%. n=1,965 QB seasons

Across all positions, usage carries year to year at 0.47 and efficiency at 0.07. So Sam Darnold'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.

2017 Production

Passing
303/480 Comp/Att4143 Pass yards26 Pass TD13 INT63.1% Comp %
Rushing
82 Rush yards5 Rush TD75 Carries1.1 Yards/carry

Performance Analysis · 2017 · vs QB peers

  • Efficiency60
  • Volume100
  • Dual-Threat50
  • Consistency84
  • Clutch74
Player type
Clutch Passer

Elevates on passing downs — 3rd-and-medium, two-minute drills, and pressure situations are where this QB is best.

3rd-down precisionLate-game valueHigh passing-down EPA
Peer percentiles
Opponent-adjusted EPA (WEPA/play)60th %ile · average
Game-to-game consistency84th %ile · above avg
Key findings
  • High-volume role — one of the team's most-used QBs by play share.
  • High game-to-game consistency — reliable floor each week.
  • 4 high-impact games (EPA/play > 0.4) this season — elite ceiling.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Peak game: 0.83 EPA/play in Wk 2 vs Stanford (SP+ 16).

Historical Comparables · QB · 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
Kyle McCordSyracuse0.50912.1321.4
Stetson BennettGeorgia0.63512.5323.0
Trace McSorleyPenn State0.51312.7321.0
Sam HartmanWake Forest0.55611.8359.6
Ryan HigginsLouisiana Tech0.58613.7334.6

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

Game Log · box score + EPA, week by week

+0.8300.83Wk 1 vs Western Michigan: +0.33 EPA/play1Wk 2 vs Stanford: +0.83 EPA/play2Wk 3 vs Texas: +0.35 EPA/play3Wk 4 vs California: +0.19 EPA/play4Wk 5 vs Washington State: +0.25 EPA/play5Wk 6 vs Oregon State: +0.34 EPA/play6Wk 7 vs Utah: +0.26 EPA/play7Wk 8 vs Notre Dame: +0.33 EPA/play8Wk 9 vs Arizona State: +0.31 EPA/play9Wk 10 vs Arizona: +0.58 EPA/play10Wk 11 vs Colorado: +0.61 EPA/play11Wk 12 vs UCLA: +0.35 EPA/play12Wk 14 vs Stanford: +0.80 EPA/play14Wk 1 vs Ohio State: +0.04 EPA/play1
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+C/ATTPass YdsPass TDINTQBRRush YdsRush TDEPA/play
1vsWestern MichiganW49-31-2.423/332890271.0-610.33
2vsStanfordW42-2415.821/263164295.8400.83
3vsTexasW27-2410.628/493973254.1-1200.35
4@CaliforniaW30-20-1.026/382232160.51400.19
5@Washington StateL27-308.615/291640137.62520.25
6vsOregon StateW38-10-12.623/353163167.0-1800.34
7vsUtahW28-2712.027/503583050.91500.26
8@Notre DameL14-4920.820/282292153.0700.33
9@Arizona StateW48-171.019/352663075.21900.31
10vsArizonaW49-353.720/26311211000.58
11@ColoradoW38-242.021/343292087.33110.61
12vsUCLAW28-234.917/282640174.31010.35
14vsStanfordW31-2815.817/243252094.5100.80
1vsOhio StateL7-2430.926/453560135.0-1800.04

Usage & Situational · Pro

Snap-share proxy
Overall
53.2%
Passing plays
97.5%
Rushing plays
9.9%
Standard downs
43.3%
Passing downs
75.1%
EPA by down type
Standard downs
0.29
Passing downs
0.46
Pass / Rush EPA
0.38 / 0.15

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

Career · rolling EPA, game by game

Per-game EPA5-game avg
+0.940−0.362017
EPA per play · 2016 — 2017 · 27 games
SeasonTeamLine valueTotal EPA
2016USC
13.4
290.5
2017USC
10.9
301.1

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.