Marcus Stroman

P New York Yankees

Age 36 RHP 5'7" / 180 lbs MLB peak 0.2 · 2027

Overview

MLBSP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	32	MLBCHC	27	25	137	3.95	3.36	20.7%	9.0%	3.4
2024	33	MLBNYY	30	29	155	4.31	4.40	16.7%	8.9%	1.8
2025	34	MIX2 levels	12	12	49	6.39	4.54	15.8%	9.5%	0.5	K 14.9% · BB 9.1% · FIP 4.77
2026	35	No MLB games played
2027PROJ	36	MLBNYY	7	7	42	4.80	4.97	15.2%	9.2%	0.2
2028PROJ	37	MLBNYY	3	3	20	5.14	5.37	14.1%	9.8%	0.0

Last 3 seasons WAR 5.7 · Next 2 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

FB Velo10

K%10

xwOBA vs10

CompsKenshin Kawakami (age 35) · Francisco Rodriguez (age 36) · Jonathan Castellanos (age 35)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 133125vR 117

ERA4.80

FIP4.97

K%15.2%

BB%9.2%

K-BB%6.1%

Proj IP42

Value2027 · WAR

Runs saved vs league avg · 42 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1089.5

Whiff%

p1019.2%

p1014.9%

xwOBA vs

p100.368

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)
2014	23	MLB MLE	Toronto Blue Jays	26	20	131	534	111	27	7	77%	5.0	20.8%	5.1%	15.7%	1.3%	3.65	2.70	+4.5
2014	23	MLB RAW	Toronto Blue Jays	26	20	131	534	111	27	7	77%	5.0	20.8%	5.1%	15.7%	1.3%	3.65	2.72	+4.4
2015	24	MIX MLE	3 levels	6	6	35	139	30	11	2	100%	5.8	17.5%	5.8%	11.7%	1.9%	2.34	3.43	+0.8
2015	24	MIX RAW	3 levels	6	6	35	139	30	11	2	100%	5.8	21.6%	7.9%	13.7%	1.4%	2.34	3.07	+1.0
2016	25	MLB MLE	Toronto Blue Jays	32	32	204	855	166	54	21	100%	6.4	19.4%	6.3%	13.1%	2.5%	4.37	3.61	+4.5
2016	25	MLB RAW	Toronto Blue Jays	32	32	204	855	166	54	21	100%	6.4	19.4%	6.3%	13.1%	2.5%	4.37	3.60	+4.5
2017	26	MLB MLE	Toronto Blue Jays	33	33	201	834	164	61	21	100%	6.1	19.7%	7.3%	12.4%	2.5%	3.09	3.75	+4.0
2017	26	MLB RAW	Toronto Blue Jays	33	33	201	834	164	61	21	100%	6.1	19.7%	7.3%	12.4%	2.5%	3.09	3.74	+4.0
2018	27	MIX MLE	2 levels	20	20	107	466	80	40	10	100%	5.3	17.1%	8.0%	9.1%	2.0%	5.48	3.77	+2.1
2018	27	MIX RAW	2 levels	20	20	107	466	80	40	10	100%	5.3	17.2%	8.6%	8.6%	2.1%	5.48	3.94	+1.9
2019	28	MLB MLE	New York Mets	32	32	184	774	159	57	18	100%	5.8	20.5%	7.4%	13.2%	2.3%	3.22	3.58	+4.1
2019	28	MLB RAW	New York Mets	32	32	184	774	159	57	18	100%	5.8	20.5%	7.4%	13.2%	2.3%	3.22	3.57	+4.1
2021	30	MLB MLE	New York Mets	33	33	179	730	158	42	17	100%	5.4	21.6%	5.8%	15.9%	2.3%	3.02	3.28	+4.7
2021	30	MLB RAW	New York Mets	33	33	179	730	158	42	17	100%	5.4	21.6%	5.8%	15.9%	2.3%	3.02	3.27	+4.7
2022	31	MIX MLE	2 levels	26	26	141	585	121	37	16	100%	5.4	20.9%	6.3%	14.6%	2.9%	3.76	3.74	+2.8
2022	31	MIX RAW	2 levels	26	26	141	585	121	37	16	100%	5.4	20.7%	6.3%	14.4%	2.7%	3.76	3.64	+3.0
2023	32	MLB MLE	Chicago Cubs	27	25	137	575	119	52	9	93%	5.1	20.7%	9.0%	11.7%	1.6%	3.95	3.39	+3.4
2023	32	MLB RAW	Chicago Cubs	27	25	137	575	119	52	9	93%	5.1	20.7%	9.0%	11.7%	1.6%	3.95	3.36	+3.4
2024	33	MLB MLE	New York Yankees	30	29	155	675	113	60	19	97%	5.2	16.7%	8.9%	7.9%	2.6%	4.31	4.26	+2.1
2024	33	MLB MLE	New York Yankees	30	29	155	675	113	60	19	97%	5.2	16.7%	8.9%	7.9%	2.6%	4.31	4.26	+2.1
2024	33	MLB RAW	New York Yankees	30	29	155	675	113	60	19	97%	5.2	16.7%	8.9%	7.9%	2.8%	4.31	4.40	+1.8
2025	34	MIX MLE	2 levels	12	12	49	221	35	21	6	100%	4.1	14.9%	9.1%	5.7%	3.2%	6.39	4.77	+0.4
2025	34	MIX MLE	2 levels	12	12	49	221	35	21	6	100%	4.1	14.9%	9.1%	5.7%	3.2%	6.39	4.77	+0.4
2025	34	MIX RAW	2 levels	12	12	49	221	35	21	6	100%	4.1	15.8%	9.5%	6.3%	2.7%	6.39	4.54	+0.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			270	261	1497	6273	1230	447	145	97%	5.5	19.6%	7.1%	12.5%	2.3%	3.79	3.61	+32.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	NYY	7	7	42	177	27	16	5	100%	6.0	15.2%	9.2%	6.1%	2.9%	4.80	4.97	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	NYY	3	3	20	86	12	8	3	100%	6.8	14.1%	9.8%	4.3%	3.4%	5.14	5.37	+0.0
2028	37	MLB CTX	NYY	3	3	20	84	12	8	3	100%	6.7	14.1%	9.8%	4.3%	3.4%	5.14	5.37	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		273	264	1518	6359	1242	455	148	97%	5.6	19.5%	7.2%	12.4%	2.3%	3.80	3.63	+32.5
/ 200 IP	—	RAW		36	35	200	838	164	60	20	97%	5.6	19.5%	7.2%	12.4%	2.3%	3.80	3.63	+4.3
Career	—	MLE		277	268	1522	6388	1249	456	147	97%	5.5	19.6%	7.1%	12.4%	2.3%	3.84	3.62	+32.5
/ 200 IP	—	MLE		36	35	200	839	164	60	19	97%	5.5	19.6%	7.1%	12.4%	2.3%	3.84	3.62	+4.3

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 AASomerset Patriots · 10 IPFIP 2.82 → 3.28 (+0.45)K% 19.6% → 15.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.57%	—	×0.810	15.85%
BB% (unintentional) /BF	10.87%	—	×1.100	11.96%
HR / BF /BF	0.00%	÷1.030	×1.200	0.00%

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 106).

Result: FIP 2.82 → 3.28, 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 AAABuffalo Bisons · 3 IPFIP 3.52 → 3.90 (+0.38)K% 25.0% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.880	22.00%
BB% (unintentional) /BF	20.00%	—	×1.050	21.00%
HR / BF /BF	0.00%	÷0.966	×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 93).

Result: FIP 3.52 → 3.90, 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
Marcus Stroman (OGILVIE)	—	—	—	—	—	2.9%	—	5.37	14.1%	4.3%	20	+0.40	—	—	—
Kenshin Kawakami R 2010 · 4.06 FIP	35	SP	4.06	15.1%	5.6%	2.8%	.293	—	—	—	—	—	3.97	244	62
Francisco Rodriguez R 2019 · 5.18 FIP	36	SP	5.18	10.7%	9.3%	3.3%	.339	—	—	—	—	—	3.16	334	61
Jonathan Castellanos R 2017 · 4.91 FIP	35	SP	4.91	8.4%	9.2%	2.5%	.314	5.24	11.0%	2.0%	67	+0.33	3.40	394	60
Walter Silva R 2015 · 4.15 FIP	38	SP	4.15	14.8%	7.4%	2.5%	.311	3.91	10.4%	3.7%	209	-0.24	3.67	453	58
Juan Delgadillo R 2017 · 4.47 FIP	34	SP	4.47	10.9%	6.2%	2.7%	.311	—	—	—	—	—	4.47	143	57
Pablo Ortega R 2015 · 4.52 FIP	38	SP	4.52	8.6%	7.3%	2.2%	.291	4.24	11.5%	6.0%	236	-0.28	4.01	375	56
Jarrett Grube R 2017 · 4.41 FIP	35	SP	4.41	15.8%	8.1%	3.0%	.296	—	—	—	—	—	3.75	393	56
Jose Oyervides R 2017 · 5.38 FIP	35	SP	5.38	18.0%	6.3%	5.5%	.254	5.66	16.3%	5.1%	115	+0.28	3.01	407	55
Ivan Maldonado R 2016 · 5.41 FIP	36	SP	5.41	6.4%	9.7%	3.0%	.325	—	—	—	—	—	4.60	172	53
Jesse Estrada R 2019 · 4.34 FIP	35	SP-	4.34	14.4%	6.6%	2.9%	.312	—	—	—	—	—	3.80	257	53
Frankie De La Cruz R 2019 · 4.38 FIP	35	SP-	4.38	16.2%	8.0%	3.0%	.322	—	—	—	—	—	2.87	262	53
J.D. Martin R 2019 · 5.89 FIP	36	SP	5.89	13.9%	12.8%	4.3%	.282	—	—	—	—	—	4.79	414	52
Austin Bibens-Dirkx R 2021 · 4.20 FIP	36	SP-	4.20	15.8%	5.6%	3.1%	.333	—	—	—	—	—	3.97	567	51
Yoanner Negrin R 2019 · 3.87 FIP	35	SP	3.87	17.5%	8.1%	2.2%	.280	—	—	—	—	—	3.15	485	49
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	48
Chris Smith R 2017 · 5.08 FIP	36	SP-	5.08	15.6%	7.5%	4.3%	.286	—	—	—	—	—	3.79	477	46
Yasutomo Kubo R 2019 · 3.98 FIP	38	SP	3.98	20.4%	4.7%	3.6%	.327	—	—	—	—	—	3.98	152	42
Jose Contreras R 2008 · 4.08 FIP	36	SP	4.08	13.4%	6.7%	2.3%	.291	3.52	20.1%	12.1%	202	-0.56	2.43	1,279	40
Francisley Bueno L 2017 · 4.44 FIP	36	SP	4.44	11.7%	8.4%	2.3%	.351	—	—	—	—	—	2.43	188	35
Jorge Castillo L 2017 · 4.97 FIP	35	SP	4.97	11.2%	6.7%	3.6%	.337	4.91	19.6%	11.5%	119	-0.06	4.50	408	31

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	7.8	120	19.4%	7.3%	0.91	3.83
Alex Wood ('24)	6.3	114	22.1%	7.1%	0.91	3.78
Jaime García ('18)	5.7	126	19.2%	7.7%	0.87	3.85
Bob Moose ('67-'76, 14 WAR*)	6.5	145	20.0%*	7.0%*	0.80*	4.31*
Roger Nelson ('67-'76, 10 WAR*)	3.2	106	19.5%*	7.1%*	0.98*	3.88*
Bryn Smith ('81-'93, 21 WAR*)	9.0	149	17.9%*	5.8%*	1.07*	4.08*
Danny Duffy ('21)	5.9	107	21.1%	8.7%	1.11	3.95