Kohl Drake

P Reno Aces

Age 27 LHP 6'5" / 220 lbs AAA peak 0.1 · 2027

Overview

AAASP40-MANROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	MIX3 levels	23	19	106	2.29	2.29	35.4%	7.4%	—	K 26.9% · BB 8.5% · FIP 3.32
2025	25	MIX2 levels	20	19	89	4.23	3.39	28.2%	9.6%	—	K 23.3% · BB 9.8% · FIP 4.16
2026	26	MIX2 levels	26	24	101	7.31	5.78	17.5%	10.6%	-0.4	K 15.5% · BB 9.7% · FIP 5.76
2027PROJ	27	MLBARI	15	15	89	4.89	5.20	18.3%	8.7%	0.2
2028PROJ80% MLB	28	MLBARI	14	14	84	5.03	5.19	18.6%	8.7%	0.2
2029PROJ85% MLB	29	MLBARI	13	13	77	5.15	5.28	18.2%	8.9%	0.1

Last 3 seasons WAR -0.4 · Next 3 projected WAR 0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%21

FB Velo10

xwOBA vs10

Career WAR0.0 WAR median (P10 -0.5 / P90 0.5, comp-based) · star 0% · didn't stick 96%

CompsBrad Mills (age 26) · Matt Lujan (age 27) · Ben Holmes (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 116124vR 132

ERA4.89

FIP5.20

K%18.3%

BB%8.7%

K-BB%9.6%

Proj IP126

Value2027 · WAR

Runs saved vs league avg · 126 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1091.6

Whiff%

p2722.0%

p2117.9%

xwOBA vs

p100.412

Contract

No contract data on file. Pre-MLB players and minor-league free agents do not yet have salary projections — entries are added at first 40-man roster placement.

Career Stats + Projections

Real MLB stats plus park-adjusted projections — this season (so far / rest / full), then future seasons and career totals.

show model inputsbasis chips: RAW = as recorded · CTX = with park/league context · A+C = actual + context combined · MLE = level/park-neutral

Methodology▸ how WAR & MLE are computed

Stats are park-neutral MLB equivalents. The "TEAM" column shows current org affiliation only — we do NOT project at that team's park.
Rates (K%, BB%, HR-BF) are park-stripped; MiLB stat lines are translated to their MLB-equivalent via per-level MLE factors.
WAR is computed from projected runs prevented vs a replacement pitcher (the marginal arm a team would call up if this pitcher were unavailable) — calibrated to the standard WAR scale.

Year	Age	Lvl	Team	G	GS	IP	BF	K	BB	HR	GS%	IP/G	K%	BB%	K-BB%	HR%	ERA	FIP	WAR
▸ Career — actual stats, one row per year (as recorded, no adjustments)
▸ Career — adjusted (each season translated to a park/league-neutral MLB-equivalent line; levels combined per year)
▸ Model inputs — neutral MLE (past 3 seasons + 2027 so far)
2023	23	MIX MLE	2 levels	14	4	47	217	55	20	4	29%	3.3	16.3%	11.9%	4.4%	2.9%	6.36	4.81	—
2023	23	MIX RAW	2 levels	14	4	47	217	55	20	4	29%	3.3	25.3%	9.2%	16.1%	1.8%	6.36	3.14	—
2024	24	MIX MLE	3 levels	23	19	106	418	148	31	9	83%	4.6	26.9%	8.5%	18.5%	2.6%	2.29	3.32	—
2024	24	MIX MLE	3 levels	23	19	106	418	148	31	9	83%	4.6	26.9%	8.5%	18.5%	2.6%	2.29	3.32	—
2024	24	MIX RAW	3 levels	23	19	106	418	148	31	9	83%	4.6	35.4%	7.4%	28.0%	2.2%	2.29	2.29	—
2025	25	MIX MLE	2 levels	20	19	89	376	106	36	10	95%	4.5	23.3%	9.8%	13.5%	3.3%	4.23	4.16	—
2025	25	MIX MLE	2 levels	20	19	89	376	106	36	10	95%	4.5	23.3%	9.8%	13.5%	3.3%	4.23	4.16	—
2025	25	MIX RAW	2 levels	20	19	89	376	106	36	10	95%	4.5	28.2%	9.6%	18.6%	2.7%	4.23	3.39	—
2026	26	MIX MLE	2 levels	26	24	101	480	84	51	22	92%	3.9	15.5%	9.7%	5.8%	5.0%	7.31	5.76	-0.4
2026	26	MIX MLE	2 levels	26	24	101	480	84	51	22	92%	3.9	15.5%	9.7%	5.8%	5.0%	7.31	5.76	-0.4
2026	26	MIX RAW	2 levels	26	24	101	480	84	51	22	92%	3.9	17.5%	10.6%	6.9%	4.6%	7.31	5.78	-0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			5	5	21	95	17	7	5	100%	4.1	17.9%	7.4%	10.5%	5.3%	6.53	5.62	-0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	ARI	15	15	89	376	69	33	15	100%	5.9	18.3%	8.7%	9.6%	3.9%	4.89	5.20	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	ARI	17	17	105	443	82	39	17	100%	6.2	18.6%	8.7%	9.8%	4.0%	5.03	5.19	+0.2
2029	29	MLB MLE	ARI	15	15	91	383	70	34	15	100%	6.0	18.2%	8.9%	9.3%	4.0%	5.15	5.28	+0.1
2030	30	MLB MLE	ARI	13	13	80	337	60	31	14	100%	6.1	17.7%	9.1%	8.6%	4.2%	5.30	5.43	-0.0
2028	28	MLB CTX	ARI	14	14	84	355	66	31	14	100%	6.0	18.6%	8.7%	9.8%	4.0%	5.03	5.19	+0.2
2029	29	MLB CTX	ARI	13	13	77	325	59	29	13	100%	5.9	18.2%	8.9%	9.3%	4.0%	5.15	5.28	+0.1
2030	30	MLB CTX	ARI	12	12	70	296	52	27	12	100%	5.8	17.7%	9.1%	8.6%	4.2%	5.30	5.43	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		43	43	251	1069	194	94	44	100%	5.8	18.2%	8.8%	9.4%	4.2%	5.27	4.96	+1.3
/ 200 IP	—	RAW		35	35	200	851	154	75	35	100%	5.8	18.2%	8.8%	9.4%	4.2%	5.27	4.96	+1.0
Career	—	MLE		83	66	343	1491	310	145	53	80%	4.1	20.8%	9.7%	11.1%	3.6%	4.83	4.53	+0.3
/ 200 IP	—	MLE		48	38	200	869	181	84	31	80%	4.1	20.8%	9.7%	11.1%	3.6%	4.83	4.53	+0.2

How the minor-league lines were translated

One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.

2026 AAAReno Aces · 80 IPFIP 5.50 → 5.81 (+0.30)K% 17.4% → 15.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.40%	—	×0.860	14.97%
BB% (unintentional) /BF	11.43%	—	×0.900	10.29%
HR / BF /BF	4.42%	÷1.000	×1.100	4.86%

Factors used: pitcher AAA level factors (Triple-A 2023+ robo-zone set: walks improve on promotion) — K ×0.86, BB ×0.90, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 100).

Result: FIP 5.50 → 5.81, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2025 AAFrisco RoughRiders · 55 IPFIP 2.93 → 3.85 (+0.92)K% 31.8% → 25.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.82%	—	×0.810	25.77%
BB% (unintentional) /BF	10.00%	—	×1.100	11.00%
HR / BF /BF	2.27%	÷0.976	×1.200	2.79%

Factors used: pitcher AA level factors — K ×0.81, BB ×1.10, HR ×1.20. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 95).

Result: FIP 2.93 → 3.85, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2025 AAAReno Aces · 34 IPFIP 4.05 → 4.59 (+0.54)K% 23.1% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.08%	—	×0.860	19.85%
BB% (unintentional) /BF	8.97%	—	×0.900	8.08%
HR / BF /BF	3.21%	÷0.904	×1.100	3.90%

Result: FIP 4.05 → 4.59, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2024 A+Hickory Crawdads · 43 IPFIP 2.37 → 3.46 (+1.09)K% 33.9% → 26.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.93%	—	×0.770	26.13%
BB% (unintentional) /BF	6.55%	—	×1.150	7.53%
HR / BF /BF	2.38%	÷1.014	×1.250	2.94%

Factors used: pitcher A+ level factors — K ×0.77, BB ×1.15, HR ×1.25. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 103).

Result: FIP 2.37 → 3.46, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2024 ADown East Wood Ducks · 43 IPFIP 0.86 → 2.10 (+1.24)K% 42.3% → 31.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	42.26%	—	×0.740	31.27%
BB% (unintentional) /BF	5.36%	—	×1.180	6.32%
HR / BF /BF	1.19%	÷1.008	×1.300	1.54%

Factors used: pitcher A level factors — K ×0.74, BB ×1.18, HR ×1.30. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 102).

Result: FIP 0.86 → 2.10, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2024 AAFrisco RoughRiders · 20 IPFIP 4.75 → 5.53 (+0.78)K% 24.4% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.39%	—	×0.810	19.76%
BB% (unintentional) /BF	13.41%	—	×1.100	14.76%
HR / BF /BF	3.66%	÷1.080	×1.200	4.06%

Result: FIP 4.75 → 5.53, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2023 ADown East Wood Ducks · 35 IPFIP 3.83 → 4.81 (+0.98)K% 22.0% → 16.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.02%	—	×0.740	16.30%
BB% (unintentional) /BF	10.12%	—	×1.180	11.94%
HR / BF /BF	2.38%	÷1.082	×1.300	2.86%

Result: FIP 3.83 → 4.81, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2023 ROKACL Rangers · 12 IPFIP 0.77 → 1.96 (+1.19)K% 36.7% → 25.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.73%	—	×0.680	24.98%
BB% (unintentional) /BF	6.12%	—	×1.250	7.65%
HR / BF /BF	0.00%	÷1.124	×1.400	0.00%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 125).

Result: FIP 0.77 → 1.96, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

Career Path Comps

What happened to similar pitchers from this age · Y-axis: ERA+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

			Profile at Match Age					Next 3 Yrs				Career
Comp	Age	Role	FIP	K%	BB%	HR/BF	BABIP	FIP	K%	K-BB%	IP	ΔFIP	Low FIP	IP	Match
Kohl Drake (OGILVIE)	—	—	—	—	—	3.9%	—	5.29	18.2%	9.3%	275	+0.09	—	—	—
Brad Mills L 2011 · 5.37 FIP	26	SP-	5.37	19.8%	12.1%	4.4%	.328	5.61	18.8%	7.9%	21	+0.24	4.22	243	80
Matt Lujan L 2016 · 5.05 FIP	27	SP	5.05	18.5%	11.3%	3.8%	.319	4.69	14.3%	7.9%	70	-0.36	4.06	227	71
Ben Holmes L 2019 · 5.57 FIP	27	SP	5.57	19.7%	11.1%	5.0%	.331	—	—	—	—	—	3.09	451	70
Hayden Wynja L 2024 · 4.79 FIP	25	SP-	4.79	18.0%	10.5%	3.4%	.274	—	—	—	—	—	4.74	154	68
Aaron Rozek L 2023 · 4.87 FIP	27	SP-	4.87	17.4%	8.8%	3.9%	.311	4.34	16.7%	9.5%	356	-0.53	3.68	579	67
Jack Snodgrass L 2015 · 4.66 FIP	27	SP-	4.66	12.6%	10.7%	2.3%	.278	5.01	15.7%	5.6%	45	+0.35	4.66	118	67
Matt Walker L 2023 · 4.73 FIP	25	SP-	4.73	12.7%	10.0%	2.6%	.333	—	—	—	—	—	4.21	156	66
Marlon Arias L 2015 · 4.32 FIP	30	SP	4.32	16.8%	12.2%	2.0%	.330	3.73	17.2%	9.5%	22	-0.59	3.73	154	65
Houston Harding L 2024 · 4.54 FIP	26	SP-	4.54	16.5%	11.2%	2.6%	.268	5.19	12.0%	0.5%	61	+0.65	3.41	239	65
Taylor Varnell L 2021 · 4.48 FIP	26	SP	4.48	20.1%	10.3%	3.2%	.278	—	—	—	—	—	2.89	248	65
Dylan Dodd L 2024 · 4.71 FIP	26	SP-	4.71	17.5%	6.0%	4.2%	.338	3.97	26.5%	21.7%	123	-0.74	3.31	475	64
Matt Chico L 2008 · 5.34 FIP	25	SP-	5.34	14.2%	7.3%	4.6%	.327	—	—	—	—	—	5.15	215	64
Chris O'Grady L 2017 · 4.33 FIP	27	SP-	4.33	21.4%	9.0%	3.5%	.280	—	—	—	—	—	3.50	232	64
Dan Serafini L 2000 · 5.27 FIP	26	SP-	5.27	11.7%	9.0%	3.7%	.300	5.44	9.2%	0.0%	30	+0.17	3.71	259	63
Danny Wirchansky L 2024 · 4.47 FIP	27	SP-	4.47	16.2%	7.4%	3.3%	.246	5.88	13.0%	0.2%	68	+1.41	4.47	179	63
Tyler Alexander L 2019 · 5.56 FIP	27	SP-	5.56	21.7%	9.8%	5.6%	.289	5.27	15.7%	5.0%	26	-0.29	5.27	128	63
Justin Marks L 2015 · 4.60 FIP	27	SP-	4.60	15.4%	10.5%	2.7%	.323	3.88	19.0%	9.1%	216	-0.72	3.83	324	63
David Purcey L 2009 · 4.75 FIP	27	SP	4.75	17.5%	13.0%	2.7%	.322	4.13	18.2%	5.4%	68	-0.62	3.60	206	63
Avery Weems L 2022 · 4.87 FIP	25	SP-	4.87	21.3%	8.6%	4.5%	.323	5.13	20.5%	12.3%	38	+0.26	2.46	227	63
Edgar Osuna L 2017 · 5.05 FIP	29	SP	5.05	10.6%	8.2%	3.3%	.345	5.09	10.0%	2.8%	83	+0.04	5.05	175	62

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 historical, 1901-2023), also matched on career-to-date at the same age. * Historical (Lahman) careers: rates era-adjusted to 2001-24 league levels; WAR is an OGILVIE proxy.

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	2.1	84	18.2%	8.7%	1.58	5.14
Andrew Suárez ('23)	1.2	77	18.0%	8.1%	1.48	4.96
Jason Bergmann ('10)	1.9	97	17.5%	9.0%	1.50	5.04
Mike Gardiner ('90-'95, -1 WAR*)	2.0	98	18.3%*	8.8%*	1.37*	5.10*
Hector Noesí ('19)	2.1	70	16.4%	8.7%	1.53	5.51
Steve Shields ('85-'89, -3 WAR*)	1.1	55	17.0%*	9.0%*	1.61*	5.49*
Rich Folkers ('70-'77, -0 WAR*)	2.1	85	19.1%*	8.8%*	1.35*	4.91*