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Taylor Kelly

#10Taylor Kelly

QB·Arizona State·20130.8 pts line valueDay 3 (Rds 4–7)

Taylor Kelly is a Clutch Passer for Arizona State. Taylor's 2013 season ranks in the 5th percentile nationally by opponent-adjusted EPA per play across 537 plays — a developing 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 Taylor Kelly'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.

2013 Production

Passing
302/484 Comp/Att3635 Pass yards28 Pass TD12 INT62.4% Comp %
Rushing
608 Rush yards9 Rush TD173 Carries3.5 Yards/carry
Punting
6 Punts223 Punt yards37.2 Yards/punt50 Long0 Inside 20

Performance Analysis · 2013 · vs QB peers

  • Efficiency5
  • Volume100
  • Dual-Threat42
  • Consistency70
  • Clutch100
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)5th %ile · below avg
Game-to-game consistency70th %ile · average
Key findings
  • Below-average efficiency vs QB peers — value comes through volume, not per-play impact.
  • High-volume role — one of the team's most-used QBs by play share.
  • High game-to-game consistency — reliable floor each week.
  • Particularly dangerous on passing downs — efficiency spikes in obvious pass situations.
  • Production faded as the season progressed — 0.21 EPA/play decline from first to second half.
  • Peak game: 0.50 EPA/play in Wk 7 vs Colorado (SP+ -1).

Game Log · box score + EPA, week by week

+0.5000.50Wk 2 vs Sacramento State: +0.46 EPA/play2Wk 3 vs Wisconsin: +0.04 EPA/play3Wk 4 vs Stanford: +0.12 EPA/play4Wk 5 vs USC: +0.35 EPA/play5Wk 6 vs Notre Dame: +0.39 EPA/play6Wk 7 vs Colorado: +0.50 EPA/play7Wk 8 vs Washington: +0.21 EPA/play8Wk 10 vs Washington State: +0.08 EPA/play10Wk 11 vs Utah: -0.06 EPA/play11Wk 12 vs Oregon State: +0.01 EPA/play12Wk 13 vs UCLA: +0.39 EPA/play13Wk 14 vs Arizona: +0.17 EPA/play14Wk 15 vs Stanford: +0.12 EPA/play15Wk 1 vs Texas Tech: -0.11 EPA/play1
EPA per play · x-axis: weekabove 0 = added points · below = lost
WkOpponentResultOpp SP+C/ATTPass YdsPass TDINTQBRRush YdsRush TDEPA/play
2vsSacramento StateW55-023/313005096.02500.46
3vsWisconsinW32-3022.429/513520149.72400.04
4@StanfordL28-4221.730/553673238.0-400.12
5vsUSCW62-4122.523/343513194.97900.35
6vsNotre DameL34-3713.233/473623257.9500.39
7vsColoradoW54-13-0.79/192332096.03610.50
8vsWashingtonW53-2420.526/422712175.68420.21
10@Washington StateW55-218.222/312755196.16620.08
11@UtahW20-1911.819/311441023.8-92-0.06
12vsOregon StateW30-1711.922/371830228.8600.01
13@UCLAW38-3320.020/272251072.49910.39
14vsArizonaW58-2114.613/252742161.62600.17
15vsStanfordL14-3821.717/251731032.93600.12
1vsTexas TechL23-3714.016/291250154.11351-0.11

Usage & Situational · Pro

Snap-share proxy
Overall
55.8%
Passing plays
95.3%
Rushing plays
23.8%
Standard downs
51.1%
Passing downs
67.2%
EPA by down type
Standard downs
0.04
Passing downs
0.44
Pass / Rush EPA
0.20 / 0.11

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

Career · rolling EPA, game by game

Per-game EPA5-game avg
+0.560−0.17
EPA per play · 2013 · 14 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.