Chad Kuhl

P Gwinnett Stripers

Age 34 RHP 6'3" / 200 lbs AAA peak 1.7 · 2027

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	30	MLBWSH	16	5	38	8.45	6.23	16.6%	13.9%	-0.7
2024	31	MIX2 levels	44	12	109	4.69	4.10	19.9%	11.8%	0.6	K 18.7% · BB 11.1% · FIP 4.11
2025	32	AAAATL	7	3	22	6.55	4.28	17.1%	11.4%	—	K 14.7% · BB 10.3% · FIP 4.35
2026	33	No MLB games played
2027PROJ	34	MLBATL	3	3	16	4.58	4.52	20.9%	9.9%	0.2
2028PROJ	35	MLBATL	20	20	118	4.75	4.86	19.9%	10.4%	0.7
2029PROJ	36	MLBATL	15	15	89	5.04	5.23	18.9%	11.0%	0.2

Last 3 seasons WAR -0.1 · Next 3 projected WAR 1.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2024

FB Velo57

K%52

xwOBA vs39

CompsKenshin Kawakami (age 34) · Jarrett Grube (age 34) · Manuel Flores (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 117109vR 101

ERA4.58

FIP4.52

K%20.9%

BB%9.9%

K-BB%11.0%

Proj IP163

Value2027 · WAR

Runs saved vs league avg · 163 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p5795.0

Whiff%

p6227.1%

p5222.5%

xwOBA vs

p390.325

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)
2015	22	AA MLE	Altoona Curve	26	26	153	620	101	41	10	100%	5.9	13.2%	7.3%	5.9%	2.1%	2.48	4.07	—
2015	22	AA RAW	Altoona Curve	26	26	153	620	101	41	10	100%	5.9	16.3%	6.6%	9.7%	1.6%	2.48	3.43	—
2016	23	MIX MLE	2 levels	30	30	154	640	119	36	16	100%	5.1	17.4%	5.8%	11.6%	2.8%	3.21	3.92	+2.7
2016	23	MIX RAW	2 levels	30	30	154	640	119	36	16	100%	5.1	18.6%	5.6%	13.0%	2.5%	3.21	3.61	+3.4
2017	24	MLB MLE	Pittsburgh Pirates	31	31	157	680	142	65	17	100%	5.1	20.9%	9.6%	11.3%	2.7%	4.35	4.03	+2.6
2017	24	MLB RAW	Pittsburgh Pirates	31	31	157	680	142	65	17	100%	5.1	20.9%	9.6%	11.3%	2.5%	4.35	3.94	+2.7
2018	25	MLB MLE	Pittsburgh Pirates	16	16	85	373	81	32	14	100%	5.3	21.7%	8.6%	13.1%	4.1%	4.55	4.58	+0.8
2018	25	MLB RAW	Pittsburgh Pirates	16	16	85	373	81	32	14	100%	5.3	21.7%	8.6%	13.1%	3.8%	4.55	4.46	+0.9
2020	27	MLB MLE	Pittsburgh Pirates	11	9	46	197	44	28	8	82%	4.2	22.3%	14.2%	8.1%	4.4%	4.27	5.42	-0.0
2020	27	MLB RAW	Pittsburgh Pirates	11	9	46	197	44	28	8	82%	4.2	22.3%	14.2%	8.1%	4.1%	4.27	5.26	+0.1
2021	28	MIX MLE	2 levels	30	16	87	373	84	45	13	53%	2.9	21.5%	12.0%	9.5%	4.0%	4.57	5.02	+0.4
2021	28	MIX RAW	2 levels	30	16	87	373	84	45	13	53%	2.9	22.5%	12.1%	10.5%	3.5%	4.57	4.67	+0.7
2022	29	MIX MLE	2 levels	28	28	142	638	116	61	25	100%	5.1	17.8%	9.2%	8.6%	3.6%	5.51	4.74	+1.1
2022	29	MIX RAW	2 levels	28	28	142	638	116	61	25	100%	5.1	18.2%	9.6%	8.6%	3.9%	5.51	5.04	+0.6
2023	30	MLB MLE	Washington Nationals	16	5	38	187	31	26	8	31%	2.4	16.6%	13.9%	2.7%	4.3%	8.45	5.81	-0.6
2023	30	MLB RAW	Washington Nationals	16	5	38	187	31	26	8	31%	2.4	16.6%	13.9%	2.7%	4.3%	8.45	6.23	-0.7
2024	31	MIX MLE	2 levels	44	12	109	483	96	57	10	27%	2.5	18.7%	11.1%	7.5%	2.1%	4.69	4.11	+0.6
2024	31	MIX MLE	2 levels	44	12	109	483	96	57	10	27%	2.5	18.7%	11.1%	7.5%	2.1%	4.69	4.11	+0.6
2024	31	MIX RAW	2 levels	44	12	109	483	96	57	10	27%	2.5	19.9%	11.8%	8.1%	2.1%	4.69	4.10	+0.6
2025	32	AAA MLE	Gwinnett Stripers	7	3	22	105	18	12	2	43%	3.1	14.7%	10.3%	4.5%	2.2%	6.55	4.35	—
2025	32	AAA MLE	Gwinnett Stripers	7	3	22	105	18	12	2	43%	3.1	14.7%	10.3%	4.5%	2.2%	6.55	4.35	—
2025	32	AAA RAW	Gwinnett Stripers	7	3	22	105	18	12	2	43%	3.1	17.1%	11.4%	5.7%	1.9%	6.55	4.28	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			174	117	668	2944	590	294	97	67%	3.8	20.0%	10.0%	10.1%	3.3%	4.98	4.54	+6.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	ATL	3	3	16	68	14	7	2	100%	5.3	20.9%	9.9%	11.0%	2.8%	4.58	4.52	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	ATL	20	20	118	498	99	52	16	100%	5.9	19.9%	10.4%	9.5%	3.2%	4.75	4.86	+0.7
2029	36	MLB MLE	ATL	15	15	89	377	71	41	13	100%	5.9	18.9%	11.0%	7.9%	3.5%	5.04	5.23	+0.2
2028	35	MLB CTX	ATL	20	20	118	498	99	52	16	100%	5.9	19.9%	10.4%	9.5%	3.2%	4.75	4.86	+0.7
2029	36	MLB CTX	ATL	15	15	89	376	71	41	13	100%	5.9	18.9%	11.0%	7.9%	3.5%	5.04	5.23	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		209	152	875	3818	760	387	126	73%	4.2	19.9%	10.1%	9.8%	3.3%	4.96	4.52	+9.0
/ 200 IP	—	RAW		48	35	200	872	174	88	29	73%	4.2	19.9%	10.1%	9.8%	3.3%	4.96	4.52	+2.1
Career	—	MLE		239	176	994	4296	790	401	132	74%	4.2	18.4%	9.3%	9.1%	3.1%	4.33	4.42	+7.6
/ 200 IP	—	MLE		48	35	200	864	159	81	27	74%	4.2	18.4%	9.3%	9.1%	3.1%	4.33	4.42	+1.7

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.

2025 AAAGwinnett Stripers · 22 IPFIP 4.15 → 4.35 (+0.21)K% 17.1% → 14.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.14%	—	×0.860	14.74%
BB% (unintentional) /BF	11.43%	—	×0.900	10.29%
HR / BF /BF	1.90%	÷0.961	×1.100	2.18%

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 92).

Result: FIP 4.15 → 4.35, 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 AAACharlotte Knights · 56 IPFIP 4.49 → 4.62 (+0.13)K% 17.3% → 14.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.28%	—	×0.860	14.86%
BB% (unintentional) /BF	13.58%	—	×0.900	12.22%
HR / BF /BF	2.06%	÷1.016	×1.100	2.23%

Result: FIP 4.49 → 4.62, 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).

2022 AAAAlbuquerque Isotopes · 5 IPFIP 3.10 → 3.51 (+0.41)K% 28.6% → 25.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.57%	—	×0.880	25.14%
BB% (unintentional) /BF	19.05%	—	×1.050	20.00%
HR / BF /BF	0.00%	÷1.061	×1.100	0.00%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, 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 112).

Result: FIP 3.10 → 3.51, 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).

2021 AAAIndianapolis Indians · 6 IPFIP 1.52 → 1.98 (+0.46)K% 37.5% → 33.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.50%	—	×0.880	33.00%
BB% (unintentional) /BF	12.50%	—	×1.050	13.12%
HR / BF /BF	0.00%	÷1.096	×1.100	0.00%

Result: FIP 1.52 → 1.98, 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).

2016 AAAIndianapolis Indians · 84 IPFIP 3.51 → 4.00 (+0.49)K% 19.5% → 17.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.47%	—	×0.880	17.13%
BB% (unintentional) /BF	4.72%	—	×1.050	4.96%
HR / BF /BF	2.65%	÷0.933	×1.100	3.13%

Result: FIP 3.51 → 4.00, 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).

2015 AAAltoona Curve · 153 IPFIP 3.45 → 4.07 (+0.63)K% 16.3% → 13.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.29%	—	×0.810	13.20%
BB% (unintentional) /BF	6.61%	—	×1.100	7.27%
HR / BF /BF	1.61%	÷0.912	×1.200	2.12%

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 82).

Result: FIP 3.45 → 4.07, 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
Chad Kuhl (OGILVIE)	—	—	—	—	—	2.8%	—	5.02	19.5%	8.8%	207	+0.50	—	—	—
Kenshin Kawakami R 2009 · 3.97 FIP	34	SP-	3.97	15.7%	7.6%	2.2%	.277	4.06	15.1%	9.5%	87	+0.09	3.97	244	79
Jarrett Grube R 2016 · 4.74 FIP	34	SP-	4.74	18.9%	7.2%	4.2%	.280	4.41	15.8%	7.7%	134	-0.33	3.75	393	73
Manuel Flores R 2019 · 4.32 FIP	33	SP	4.32	17.1%	7.4%	3.1%	.291	—	—	—	—	—	3.46	515	65
Jonathan Castellanos R 2016 · 3.40 FIP	34	SP	3.40	15.2%	7.4%	1.2%	.314	5.04	9.4%	0.3%	174	+1.64	3.40	394	64
Albert Suárez R 2024 · 4.00 FIP	34	SP-	4.00	19.5%	6.8%	3.1%	.293	4.14	17.8%	10.6%	80	+0.14	3.58	616	63
Matt Buschmann R 2016 · 4.84 FIP	32	SP	4.84	12.8%	8.4%	3.2%	.325	—	—	—	—	—	4.03	277	60
Jorge Martinez R 2019 · 3.71 FIP	34	SP	3.71	16.3%	5.7%	2.3%	.348	—	—	—	—	—	3.53	214	60
Leo Medrano R 2016 · 4.34 FIP	33	SP	4.34	11.0%	7.3%	2.3%	.312	—	—	—	—	—	3.76	222	59
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	57
Guillermo Moscoso R 2018 · 5.07 FIP	34	SP-	5.07	18.2%	8.4%	4.5%	.318	4.35	12.6%	5.9%	104	-0.72	3.56	486	57
David Buchanan R 2024 · 4.26 FIP	35	SP-	4.26	14.7%	6.5%	2.9%	.337	5.56	12.2%	4.1%	29	+1.30	3.88	560	56
Paolo Espino R 2021 · 4.32 FIP	34	SP-	4.32	20.2%	5.1%	4.2%	.277	4.81	16.6%	10.9%	260	+0.49	3.42	933	55
Hiroki Kuroda R 2009 · 3.54 FIP	34	SP	3.54	17.9%	4.7%	2.5%	.270	3.43	19.1%	14.2%	618	-0.11	2.96	1,319	55
Michael Nix R 2016 · 4.60 FIP	33	SP	4.60	11.9%	11.6%	1.9%	.322	—	—	—	—	—	3.82	234	54
Josh Lindblom R 2021 · 3.79 FIP	34	SP-	3.79	22.7%	6.9%	3.2%	.319	5.07	20.8%	12.0%	133	+1.28	1.83	480	54
Ryan Vogelsong R 2011 · 3.65 FIP	34	SP	3.65	18.5%	7.3%	2.2%	.274	3.90	18.6%	11.3%	478	+0.25	3.14	1,184	52
Francisco Rodriguez R 2017 · 4.43 FIP	34	SP	4.43	11.4%	8.2%	2.3%	.305	5.18	10.7%	1.4%	83	+0.75	3.16	334	51
Logan Duran R 2016 · 3.77 FIP	34	SP	3.77	15.3%	8.9%	1.5%	.299	3.66	15.5%	6.6%	29	-0.11	3.42	187	50
Orlando Hernandez R 2004 · 3.77 FIP	34	SP	3.77	23.4%	10.0%	2.5%	.278	4.34	20.5%	11.7%	438	+0.57	3.35	1,315	50
Angel Castro R 2017 · 3.51 FIP	34	SP	3.51	14.5%	7.4%	1.3%	.332	—	—	—	—	—	3.51	292	50

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	5.2	94	20.1%	10.4%	1.25	4.90
Bill Butler ('69-'77, 2 WAR*)	3.0	99	22.0%*	11.3%*	1.30*	4.83*
Felix Doubront ('15)	2.6	103	19.5%	9.7%	1.10	4.89
Vince Velasquez ('15-'23, 2 WAR*)	3.8	85	21.9%*	9.2%*	1.37*	4.99*
Jesse Jefferson ('73-'81, -1 WAR*)	5.4	121	17.2%*	10.7%*	1.32*	5.13*
Pete Redfern ('76-'82, 3 WAR*)	3.6	119	21.7%*	9.8%*	1.16*	4.74*
Felipe Paulino ('14)	2.0	101	20.7%	9.5%	1.14	5.22