Michael King

P San Diego Padres

Age 32 RHP 6'3" / 210 lbs MLB peak 0.4 · 2027

Overview

MLBSP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MLBSD	31	30	174	2.95	3.11	27.7%	8.4%	5.0
2025	30	MIX2 levels	16	16	77	3.99	4.42	25.0%	8.3%	0.9	K 24.7% · BB 8.4% · FIP 4.17
2026	31	MLBSD	32	32	185	3.21	3.92	21.0%	9.2%	3.3
2027PROJ	32	MLBSD	19	19	128	3.98	4.27	22.4%	9.0%	1.7
2028PROJ	33	MLBSD	13	13	85	4.32	4.55	21.5%	9.5%	0.8
2029PROJ	34	MLBSD	8	8	55	4.64	4.86	20.6%	10.0%	0.3

Last 3 seasons WAR 9.1 · Next 3 projected WAR 2.9Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo47

K%42

xwOBA vs41

Form3.10 ERA (proj 3.98) · K 19.8% (proj 22.4%) · BB 8.3% (proj 9.0%) · last 60d · 29 IP through Oct 27

CompsMiguel González (age 32) · Elmer Dessens (age 32) · Mike Fiers (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 114105vR 97

ERA3.98

FIP4.27

K%22.4%

BB%9.0%

K-BB%13.4%

Proj IP128

Value2027 · WAR

Runs saved vs league avg · 128 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p4794.3

Whiff%

p4424.5%

p4221.0%

xwOBA vs

p410.322

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	MIX MLE	2 levels	5	0	9	45	5	3	0	0%	1.9	11.1%	6.7%	4.4%	0.0%	5.79	3.01	—
2016	21	MIX RAW	2 levels	5	0	9	45	5	3	0	0%	1.9	11.1%	6.7%	4.4%	0.0%	5.79	2.99	—
2017	22	A MLE	Greensboro Grasshoppers	26	25	149	597	106	21	14	96%	5.7	13.1%	4.2%	9.0%	2.6%	3.14	3.95	—
2017	22	A RAW	Greensboro Grasshoppers	26	25	149	597	106	21	14	96%	5.7	17.8%	3.5%	14.2%	2.3%	3.14	3.32	—
2018	23	MIX MLE	3 levels	25	24	161	624	152	28	8	96%	6.5	19.8%	5.0%	14.8%	1.4%	1.79	2.84	—
2018	23	MIX RAW	3 levels	25	24	161	624	152	28	8	96%	6.5	24.4%	4.5%	19.9%	1.3%	1.79	2.38	—
2019	24	MIX MLE	4 levels	11	7	44	191	45	10	4	64%	4.0	19.6%	5.3%	14.2%	2.7%	5.73	3.60	+1.0
2019	24	MIX RAW	4 levels	11	7	44	191	45	10	4	64%	4.0	23.6%	5.2%	18.3%	2.1%	5.73	2.92	+1.3
2020	25	MLB MLE	New York Yankees	9	4	27	121	26	11	5	44%	3.0	21.5%	9.1%	12.4%	3.9%	7.76	4.56	-0.0
2020	25	MLB RAW	New York Yankees	9	4	27	121	26	11	5	44%	3.0	21.5%	9.1%	12.4%	4.1%	7.76	4.83	-0.1
2021	26	MIX MLE	2 levels	25	7	69	298	73	23	7	28%	2.8	22.5%	8.4%	14.2%	2.0%	3.65	3.38	+1.0
2021	26	MIX RAW	2 levels	25	7	69	298	73	23	7	28%	2.8	24.5%	7.7%	16.8%	2.3%	3.65	3.30	+1.0
2022	27	MLB MLE	New York Yankees	34	0	51	199	66	14	3	0%	1.5	33.2%	7.0%	26.1%	1.4%	2.29	1.97	+1.6
2022	27	MLB RAW	New York Yankees	34	0	51	199	66	14	3	0%	1.5	33.2%	7.0%	26.1%	1.5%	2.29	2.10	+1.5
2023	28	MLB MLE	New York Yankees	49	9	105	431	127	31	10	18%	2.1	29.5%	7.2%	22.3%	2.2%	2.75	2.72	+2.3
2023	28	MLB RAW	New York Yankees	49	9	105	431	127	31	10	18%	2.1	29.5%	7.2%	22.3%	2.3%	2.75	2.80	+2.2
2024	29	MLB MLE	San Diego Padres	31	30	174	726	201	61	17	97%	5.6	27.7%	8.4%	19.3%	2.3%	2.95	3.08	+5.0
2024	29	MLB MLE	San Diego Padres	31	30	174	726	201	61	17	97%	5.6	27.7%	8.4%	19.3%	2.3%	2.95	3.08	+5.0
2024	29	MLB RAW	San Diego Padres	31	30	174	726	201	61	17	97%	5.6	27.7%	8.4%	19.3%	2.3%	2.95	3.11	+5.0
2025	30	MIX MLE	2 levels	16	16	77	324	81	27	14	100%	4.8	24.7%	8.4%	16.2%	3.8%	3.99	4.17	+1.1
2025	30	MIX MLE	2 levels	16	16	77	324	81	27	14	100%	4.8	24.7%	8.4%	16.2%	3.8%	3.99	4.17	+1.1
2025	30	MIX RAW	2 levels	16	16	77	324	81	27	14	100%	4.8	25.0%	8.3%	16.7%	4.3%	3.99	4.42	+0.9
2026	31	MLB MLE	San Diego Padres	32	32	185	757	159	70	20	100%	5.8	21.0%	9.2%	11.8%	2.6%	3.21	3.91	+3.3
2026	31	MLB MLE	San Diego Padres	32	32	185	757	159	70	20	100%	5.8	21.0%	9.2%	11.8%	2.6%	3.21	3.91	+3.3
2026	31	MLB RAW	San Diego Padres	32	32	185	757	159	70	20	100%	5.8	21.0%	9.2%	11.8%	2.6%	3.21	3.92	+3.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			193	96	680	2826	718	236	73	50%	3.5	25.4%	8.4%	17.1%	2.6%	3.23	3.43	+9.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	SD	19	19	128	540	121	49	15	100%	6.7	22.4%	9.0%	13.4%	2.8%	3.98	4.27	+1.7
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	SD	13	13	85	359	77	34	11	100%	6.5	21.5%	9.5%	12.1%	3.1%	4.32	4.55	+0.8
2029	34	MLB MLE	SD	8	8	55	233	48	23	8	100%	6.9	20.6%	10.0%	10.7%	3.4%	4.64	4.86	+0.3
2028	33	MLB CTX	SD	13	13	85	359	77	34	11	100%	6.5	21.5%	9.5%	12.1%	3.1%	4.32	4.55	+0.8
2029	34	MLB CTX	SD	8	8	55	232	48	23	8	100%	6.9	20.6%	10.0%	10.7%	3.4%	4.64	4.86	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		214	117	820	3419	844	293	92	55%	3.8	24.7%	8.6%	16.1%	2.7%	3.44	3.58	+18.0
/ 200 IP	—	RAW		52	29	200	834	206	71	22	55%	3.8	24.7%	8.6%	16.1%	2.7%	3.44	3.58	+4.4
Career	—	MLE		263	154	1050	4313	970	308	101	59%	4.0	22.5%	7.1%	15.4%	2.3%	3.18	3.39	+17.4
/ 200 IP	—	MLE		50	29	200	821	185	59	19	59%	4.0	22.5%	7.1%	15.4%	2.3%	3.18	3.39	+4.2

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.

2021 AAAScranton/Wilkes-Barre RailRiders · 6 IPFIP 1.45 → 1.83 (+0.38)K% 47.8% → 42.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	47.83%	—	×0.880	42.09%
BB% (unintentional) /BF	0.00%	—	×1.050	0.00%
HR / BF /BF	4.35%	÷1.149	×1.100	4.16%

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 130).

Result: FIP 1.45 → 1.83, 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 AAAScranton/Wilkes-Barre RailRiders · 24 IPFIP 3.14 → 3.49 (+0.35)K% 28.6% → 25.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.57%	—	×0.880	25.14%
BB% (unintentional) /BF	6.12%	—	×1.050	6.43%
HR / BF /BF	3.06%	÷1.087	×1.100	3.10%

Result: FIP 3.14 → 3.49, 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 AATrenton Thunder · 13 IPFIP 3.31 → 3.78 (+0.48)K% 13.1% → 10.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.11%	—	×0.810	10.62%
BB% (unintentional) /BF	3.28%	—	×1.100	3.61%
HR / BF /BF	1.64%	÷0.960	×1.200	2.05%

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 92).

Result: FIP 3.31 → 3.78, 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 ROKGCL Yankees West · 6 IPFIP 1.26 → 2.48 (+1.22)K% 34.8% → 23.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.78%	—	×0.680	23.65%
BB% (unintentional) /BF	8.70%	—	×1.250	10.87%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 1.26 → 2.48, 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 AATrenton Thunder · 82 IPFIP 2.25 → 2.79 (+0.54)K% 23.9% → 19.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.90%	—	×0.810	19.36%
BB% (unintentional) /BF	3.77%	—	×1.100	4.15%
HR / BF /BF	1.26%	÷1.034	×1.200	1.46%

Result: FIP 2.25 → 2.79, 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+Tampa Tarpons · 40 IPFIP 1.89 → 2.55 (+0.66)K% 27.4% → 21.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.44%	—	×0.770	21.13%
BB% (unintentional) /BF	6.10%	—	×1.150	7.01%
HR / BF /BF	0.61%	÷1.205	×1.250	0.63%

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 141).

Result: FIP 1.89 → 2.55, 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 AAAScranton/Wilkes-Barre RailRiders · 39 IPFIP 2.95 → 3.26 (+0.31)K% 21.8% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.83%	—	×0.880	19.21%
BB% (unintentional) /BF	4.23%	—	×1.050	4.44%
HR / BF /BF	2.11%	÷1.046	×1.100	2.22%

Result: FIP 2.95 → 3.26, 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).

2017 AGreensboro Grasshoppers · 149 IPFIP 3.33 → 3.95 (+0.62)K% 17.8% → 13.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.76%	—	×0.740	13.14%
BB% (unintentional) /BF	3.52%	—	×1.180	4.15%
HR / BF /BF	2.35%	÷1.168	×1.300	2.61%

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 134).

Result: FIP 3.33 → 3.95, 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
Michael King (OGILVIE)	—	—	—	—	—	2.8%	—	4.67	21.2%	11.5%	140	+0.40	—	—	—
Miguel González R 2016 · 3.72 FIP	32	SP	3.72	17.8%	5.8%	2.5%	.295	4.71	14.1%	6.3%	168	+0.99	3.72	905	57
Elmer Dessens R 2003 · 4.25 FIP	32	SP	4.25	14.5%	6.5%	2.8%	.319	3.98	15.0%	9.6%	248	-0.27	3.55	1,167	56
Mike Fiers R 2017 · 5.12 FIP	32	SP	5.12	21.8%	9.2%	4.9%	.290	4.88	17.5%	11.5%	416	-0.24	2.83	1,140	53
Rolando Arrojo R 2000 · 4.47 FIP	32	SP	4.47	16.1%	8.0%	3.1%	.291	3.68	16.4%	9.2%	185	-0.79	3.50	700	51
Orlando Hernandez R 2002 · 3.78 FIP	32	SP	3.78	18.6%	5.6%	2.8%	.258	4.26	18.9%	9.8%	213	+0.48	3.35	1,315	49
Jeremy Guthrie R 2011 · 4.18 FIP	32	SP	4.18	14.6%	6.9%	2.6%	.278	4.68	13.2%	7.1%	596	+0.50	4.08	1,834	46
Merrill Kelly R 2021 · 4.00 FIP	32	SP	4.00	19.5%	5.7%	3.3%	.297	3.80	23.4%	15.3%	452	-0.20	3.60	1,170	46
Odrisamer Despaigne R 2019 · 3.77 FIP	32	SP	3.77	19.4%	8.9%	2.2%	.330	—	—	—	—	—	3.13	689	45
Tim Adleman R 2019 · 4.30 FIP	31	SP	4.30	22.8%	7.8%	3.9%	.266	4.71	18.5%	11.1%	90	+0.41	3.63	605	45
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	45
Ryan Franklin R 2005 · 4.89 FIP	32	SP	4.89	11.2%	7.0%	3.4%	.282	4.36	13.7%	7.8%	236	-0.53	3.12	1,201	42
Bruce Billings R 2015 · 3.09 FIP	29	SP-	3.09	15.6%	5.6%	1.1%	.309	—	—	—	—	—	3.09	121	41
Todd Redmond R 2015 · 3.86 FIP	30	SW	3.86	15.4%	7.1%	2.1%	.311	—	—	—	—	—	3.21	247	41
Yohan Pino R 2015 · 4.13 FIP	31	SP-	4.13	17.8%	5.8%	3.3%	.312	5.33	15.2%	11.6%	35	+1.20	3.84	193	39
Steve Parris R 2000 · 4.84 FIP	32	SP	4.84	13.6%	7.7%	3.5%	.304	5.49	10.9%	3.0%	225	+0.65	3.60	753	39
Jose Contreras R 2004 · 5.06 FIP	32	SP	5.06	19.8%	10.9%	4.1%	.273	4.06	15.8%	8.6%	590	-1.00	2.43	1,279	39
Cory Lidle R 2004 · 4.34 FIP	32	SP	4.34	13.8%	6.1%	3.0%	.281	4.16	16.3%	10.6%	355	-0.18	3.48	1,318	39
Jarrett Grube R 2015 · 3.75 FIP	33	SP	3.75	18.7%	4.2%	3.1%	.285	4.57	17.3%	9.6%	253	+0.82	3.75	393	39
Nate Long R 2015 · 4.67 FIP	29	SP	4.67	14.8%	10.6%	2.7%	.285	—	—	—	—	—	4.67	151	38
Pete Walker R 2002 · 4.59 FIP	33	SP-	4.59	13.4%	7.7%	3.0%	.279	5.16	12.0%	2.8%	139	+0.57	4.45	327	36

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	4.7	95	24.3%	8.8%	1.05	3.51
Joe Hesketh ('84-'94, 10 WAR*)	4.8	87	23.2%*	8.8%*	1.07*	3.95*
Andy McGaffigan ('81-'91, 10 WAR*)	4.2	104	22.6%*	8.2%*	0.87*	3.85*
Alejandro Peña ('81-'96, 15 WAR*)	5.3	81	24.7%*	7.5%*	0.96*	3.61*
Carlos Martinez ('21)	4.8	107	22.5%	9.1%	0.75	3.74
Garrett Richards ('22)	4.9	98	20.4%	8.7%	0.85	3.87
Collin McHugh ('23)	5.0	90	23.3%	6.7%	0.96	3.72