Joel Kuhnel

P San Francisco Giants

Age 32 RHP 6'5" / 290 lbs MLB

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MIX2 levels	41	0	52	3.29	2.85	16.8%	5.1%	1.1	K 15.2% · BB 5.7% · FIP 2.86
2025	30	AAAScranton/Wilk…	50	2	64	3.53	2.88	21.6%	4.2%	—	K 18.6% · BB 3.8% · FIP 3.10
2026	31	MIX2 levels	58	0	59	3.66	4.51	16.4%	8.2%	0.0	K 15.6% · BB 8.0% · FIP 4.66
2027PROJ	32	MLBSF	40	0	42	4.50	4.44	17.0%	6.1%	0.1
2028PROJ95% MLB	33	MLBSF	27	0	28	4.63	4.72	16.2%	6.6%	-0.1
2029PROJ90% MLB	34	MLBSF	15	0	16	4.86	5.02	15.2%	7.1%	-0.1

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

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo61

K%10

xwOBA vs10

CompsJuan Sandoval (age 34) · Hector Navarro (age 35) · Angel Castro (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 125117vR 109

ERA4.50

FIP4.44

K%17.0%

BB%6.1%

K-BB%10.9%

Proj IP43

Value2027 · WAR

Runs saved vs league avg · 43 IP

Grades · Statcast · Contract

Scouting Grades

STUF4545

CTRL7070

CMD5555

K†4040

Statcast Percentiles

FB Velo

p6195.3

Whiff%

p3222.8%

p1013.9%

xwOBA vs

p100.362

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)
2016	21	ROK MLE	Billings Mustangs	18	0	21	92	14	1	1	0%	1.2	10.3%	1.4%	9.0%	1.5%	3.43	3.23	—
2016	21	ROK RAW	Billings Mustangs	18	0	21	92	14	1	1	0%	1.2	15.2%	1.1%	14.1%	1.1%	3.43	2.53	—
2017	22	A MLE	Dayton Dragons	48	0	64	276	54	10	6	0%	1.3	14.5%	4.3%	10.2%	2.4%	4.36	3.75	—
2017	22	A RAW	Dayton Dragons	48	0	64	276	54	10	6	0%	1.3	19.6%	3.6%	15.9%	2.2%	4.36	3.10	—
2018	23	A+ MLE	Daytona Tortugas	44	0	53	225	56	9	2	0%	1.2	19.2%	4.6%	14.6%	1.1%	3.04	2.64	—
2018	23	A+ RAW	Daytona Tortugas	44	0	53	225	56	9	2	0%	1.2	24.9%	4.0%	20.9%	0.9%	3.04	1.99	—
2019	24	MIX MLE	3 levels	52	0	63	257	59	18	7	0%	1.2	19.5%	6.5%	13.0%	3.4%	2.56	4.13	+0.3
2019	24	MIX RAW	3 levels	52	0	63	257	59	18	7	0%	1.2	23.0%	7.0%	16.0%	2.7%	2.56	3.53	+0.8
2020	25	MLB MLE	Cincinnati Reds	3	0	3	13	3	0	2	0%	1.0	23.1%	0.0%	23.1%	15.4%	6.00	9.60	-0.2
2020	25	MLB RAW	Cincinnati Reds	3	0	3	13	3	0	2	0%	1.0	23.1%	0.0%	23.1%	15.4%	6.00	9.77	-0.2
2021	26	MIX MLE	2 levels	8	1	8	31	11	1	1	12%	1.0	35.5%	3.2%	32.3%	3.2%	1.12	2.28	—
2021	26	MIX RAW	2 levels	8	1	8	31	11	1	1	12%	1.0	35.5%	3.2%	32.3%	3.2%	1.12	2.35	—
2022	27	MIX MLE	2 levels	63	0	68	297	63	14	9	0%	1.1	22.0%	5.1%	16.9%	2.9%	5.80	3.49	+0.9
2022	27	MIX RAW	2 levels	63	0	68	297	63	14	9	0%	1.1	21.2%	4.7%	16.5%	3.0%	5.80	3.58	+0.8
2023	28	MIX MLE	2 levels	47	0	57	258	34	20	6	0%	1.2	11.5%	7.1%	4.4%	2.7%	6.04	4.51	+0.0
2023	28	MIX RAW	2 levels	47	0	57	258	34	20	6	0%	1.2	13.2%	7.8%	5.4%	2.3%	6.04	4.34	+0.1
2024	29	MIX MLE	2 levels	41	0	52	214	36	11	2	0%	1.3	15.2%	5.7%	9.6%	0.6%	3.29	2.86	+1.1
2024	29	MIX MLE	2 levels	41	0	52	214	36	11	2	0%	1.3	15.2%	5.7%	9.6%	0.6%	3.29	2.86	+1.1
2024	29	MIX RAW	2 levels	41	0	52	214	36	11	2	0%	1.3	16.8%	5.1%	11.7%	0.9%	3.29	2.85	+1.1
2025	30	AAA MLE	Scranton/Wilkes-Barre RailRiders	50	2	64	259	56	11	5	4%	1.3	18.6%	3.8%	14.8%	2.0%	3.53	3.10	—
2025	30	AAA MLE	Scranton/Wilkes-Barre RailRiders	50	2	64	259	56	11	5	4%	1.3	18.6%	3.8%	14.8%	2.0%	3.53	3.10	—
2025	30	AAA RAW	Scranton/Wilkes-Barre RailRiders	50	2	64	259	56	11	5	4%	1.3	21.6%	4.2%	17.4%	1.9%	3.53	2.88	—
2026	31	MIX MLE	2 levels	58	0	59	256	42	21	8	0%	1.0	15.6%	8.0%	7.6%	3.4%	3.66	4.66	-0.1
2026	31	MIX MLE	2 levels	58	0	59	256	42	21	8	0%	1.0	15.6%	8.0%	7.6%	3.4%	3.66	4.66	-0.1
2026	31	MIX RAW	2 levels	58	0	59	256	42	21	8	0%	1.0	16.4%	8.2%	8.2%	3.1%	3.66	4.51	+0.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			127	0	139	609	104	39	21	0%	1.1	17.1%	6.4%	10.7%	3.4%	5.39	4.41	+0.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	SF	40	0	42	177	30	11	5	0%	1.1	17.0%	6.1%	10.9%	2.9%	4.50	4.44	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	SF	28	0	29	124	20	8	4	0%	1.1	16.2%	6.6%	9.6%	3.2%	4.63	4.72	-0.1
2029	34	MLB MLE	SF	17	0	18	76	12	5	3	0%	1.1	15.2%	7.1%	8.2%	3.5%	4.86	5.02	-0.1
2028	33	MLB CTX	SF	27	0	28	118	19	8	4	0%	1.0	16.2%	6.6%	9.6%	3.2%	4.63	4.72	-0.1
2029	34	MLB CTX	SF	15	0	16	68	10	5	2	0%	1.1	15.2%	7.1%	8.2%	3.5%	4.86	5.02	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		169	0	183	796	134	52	27	0%	1.1	16.8%	6.5%	10.3%	3.4%	5.22	4.38	+0.4
/ 200 IP	—	RAW		185	0	200	870	147	57	30	0%	1.1	16.8%	6.5%	10.3%	3.4%	5.22	4.38	+0.4
Career	—	MLE		432	3	512	2178	372	117	53	1%	1.2	17.1%	5.4%	11.7%	2.4%	4.01	3.67	+0.1
/ 200 IP	—	MLE		169	1	200	850	145	46	21	1%	1.2	17.1%	5.4%	11.7%	2.4%	4.01	3.67	+0.1

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 AAANashville Sounds · 14 IPFIP 2.87 → 3.18 (+0.31)K% 25.9% → 22.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.93%	—	×0.860	22.30%
BB% (unintentional) /BF	7.41%	—	×0.900	6.67%
HR / BF /BF	1.85%	÷1.000	×1.100	2.04%

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 2.87 → 3.18, 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 AAAScranton/Wilkes-Barre RailRiders · 64 IPFIP 2.87 → 3.10 (+0.23)K% 21.6% → 18.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.62%	—	×0.860	18.59%
BB% (unintentional) /BF	4.25%	—	×0.900	3.82%
HR / BF /BF	1.93%	÷1.070	×1.100	1.99%

Result: FIP 2.87 → 3.10, 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 AAADurham Bulls · 42 IPFIP 2.71 → 2.86 (+0.14)K% 17.7% → 15.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.71%	—	×0.860	15.23%
BB% (unintentional) /BF	6.29%	—	×0.900	5.66%
HR / BF /BF	0.57%	÷1.061	×1.100	0.59%

Result: FIP 2.71 → 2.86, 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 AAASugar Land Space Cowboys · 44 IPFIP 3.90 → 4.23 (+0.33)K% 15.5% → 13.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.50%	—	×0.860	13.33%
BB% (unintentional) /BF	8.00%	—	×0.900	7.20%
HR / BF /BF	2.00%	÷0.896	×1.100	2.45%

Result: FIP 3.90 → 4.23, 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 AAALouisville Bats · 10 IPFIP 3.30 → 3.30 (−0.00)K% 16.7% → 14.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.67%	—	×0.880	14.67%
BB% (unintentional) /BF	2.38%	—	×1.050	2.50%
HR / BF /BF	2.38%	÷1.282	×1.100	2.04%

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 156).

Result: FIP 3.30 → 3.30, 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).

2019 AAChattanooga Lookouts · 36 IPFIP 3.69 → 4.51 (+0.82)K% 21.1% → 17.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.13%	—	×0.810	17.11%
BB% (unintentional) /BF	3.52%	—	×1.100	3.87%
HR / BF /BF	3.52%	÷0.979	×1.200	4.31%

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 96).

Result: FIP 3.69 → 4.51, 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).

2019 AAALouisville Bats · 18 IPFIP 2.93 → 3.39 (+0.46)K% 27.4% → 24.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.40%	—	×0.880	24.11%
BB% (unintentional) /BF	10.96%	—	×1.050	11.51%
HR / BF /BF	1.37%	÷0.957	×1.100	1.57%

Result: FIP 2.93 → 3.39, 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).

2018 A+Daytona Tortugas · 53 IPFIP 1.99 → 2.64 (+0.65)K% 24.9% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.89%	—	×0.770	19.16%
BB% (unintentional) /BF	4.00%	—	×1.150	4.60%
HR / BF /BF	0.89%	÷1.058	×1.250	1.05%

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 112).

Result: FIP 1.99 → 2.64, 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
Joel Kuhnel (OGILVIE)	—	—	4.44	17.0%	6.1%	2.9%	—	4.83	15.8%	9.1%	47	+0.39	—	—	—
Juan Sandoval R 2015 · 3.82 FIP	34	SU	3.82	15.4%	6.0%	2.3%	.294	3.33	17.4%	8.8%	116	-0.49	3.24	225	84
Hector Navarro R 2015 · 4.35 FIP	35	SU	4.35	15.0%	5.4%	3.3%	.281	3.00	15.2%	9.0%	81	-1.35	2.30	126	84
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	81
Felipe Arredondo R 2019 · 4.65 FIP	32	SU	4.65	16.2%	7.1%	3.7%	.272	—	—	—	—	—	3.92	337	79
Mike Buddie R 2002 · 4.26 FIP	31	SU	4.26	15.1%	7.6%	2.7%	.297	—	—	—	—	—	3.76	123	78
Esteban Haro R 2017 · 3.91 FIP	31	SU	3.91	13.9%	5.1%	2.4%	.386	3.76	9.5%	3.9%	39	-0.15	3.76	164	78
Pedro Rodriguez R 2019 · 4.14 FIP	31	SU	4.14	14.7%	4.9%	3.0%	.368	—	—	—	—	—	3.21	145	78
Tyler Sturdevant R 2017 · 4.48 FIP	31	SU	4.48	13.5%	6.7%	3.0%	.300	—	—	—	—	—	3.44	149	77
Arcenio Leon R 2019 · 3.61 FIP	32	SU	3.61	21.4%	8.1%	2.4%	.314	—	—	—	—	—	3.00	115	77
Ryan Kelly R 2019 · 4.33 FIP	31	SU	4.33	14.7%	7.2%	2.8%	.307	—	—	—	—	—	2.49	131	77
Jose Manuel Lopez R 2017 · 3.61 FIP	32	SU	3.61	20.4%	10.0%	1.8%	.331	6.14	17.9%	3.7%	41	+2.53	3.50	170	76
Erik Davis R 2018 · 3.52 FIP	31	SU	3.52	17.4%	8.9%	1.4%	.317	—	—	—	—	—	3.05	227	76
Jean Machi R 2014 · 3.33 FIP	32	SU	3.33	20.5%	6.0%	2.2%	.225	4.34	17.8%	10.6%	186	+1.01	2.16	306	76
Ben Weber R 2002 · 3.41 FIP	32	SU	3.41	13.8%	6.1%	1.3%	.268	4.07	12.8%	5.9%	115	+0.66	2.57	284	76
Mark Serrano R 2017 · 3.56 FIP	31	SU	3.56	21.9%	6.4%	2.7%	.240	5.25	20.2%	12.3%	42	+1.69	3.16	120	76
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	74
Scott Atchison R 2007 · 4.55 FIP	31	SU	4.55	19.1%	7.6%	3.8%	.297	4.59	16.2%	9.5%	60	+0.04	2.52	340	74
Santiago Casilla R 2012 · 3.98 FIP	32	SU	3.98	20.2%	6.6%	3.2%	.246	3.23	21.6%	13.7%	166	-0.75	2.76	647	74
Jumbo Diaz R 2016 · 3.85 FIP	32	SU	3.85	22.3%	9.2%	2.7%	.247	3.28	23.0%	13.8%	141	-0.57	2.80	319	74
Jared Hughes R 2017 · 3.28 FIP	32	SU	3.28	19.7%	7.8%	1.6%	.260	3.99	19.3%	10.9%	172	+0.71	3.00	530	73

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,234 reliever careers (754 from 1990-2025 + 480 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	1.1	46	16.8%	6.7%	1.29	5.08
Steve Kealey ('68-'73, -1 WAR*)	1.1	54	18.5%*	7.2%*	1.32*	5.26*
Carlos Almánzar ('05)	1.2	60	16.3%	7.9%	1.32	4.82
Jose Cabrera ('02)	1.4	68	16.2%	7.9%	1.39	4.95
Brandon Maurer ('18)	1.9	62	19.9%	7.8%	1.14	5.36
Chuck Hartenstein ('66-'77, -1 WAR*)	1.5	59	13.7%*	7.2%*	1.50*	5.28*
Larry Casian ('90-'98, 0 WAR*)	1.2	40	14.7%*	6.8%*	1.25*	4.37*