Noah Syndergaard

P ACL White Sox

Age 34 RHP 6'6" / 242 lbs ROK peak 0.6 · 2027

Overview

ROKSP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	29	MLBPHI	25	24	135	3.94	3.73	16.8%	5.5%	2.7
2023	30	MIX2 levels	20	20	99	6.39	5.41	14.9%	4.4%	-0.0	K 14.3% · BB 4.9% · FIP 5.60
2025	32	MIX2 levels	6	6	23	5.40	4.94	14.7%	2.1%	—	K 13.6% · BB 2.1% · FIP 2.22
2026	33	No MLB games played
2027PROJ	34	MLBCWS	—	—	0	4.28	4.27	23.5%	9.0%	—
2028PROJ	35	MLBCWS	3	3	20	4.51	4.64	22.6%	9.6%	0.2

Last 3 seasons WAR 2.7 · Next 2 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2023

FB Velo18

K%10

xwOBA vs10

CompsJose Oyervides (age 34) · Manuel Flores (age 33) · Kenshin Kawakami (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 128119vR 111

ERA4.28

FIP4.27

K%23.5%

BB%9.0%

K-BB%14.5%

Proj IP7

Value2027 · WAR

Runs saved vs league avg · 7 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1892.2

Whiff%

p1017.9%

p1014.3%

xwOBA vs

p100.381

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	MIX MLE	2 levels	29	29	180	716	200	37	21	100%	6.2	27.4%	5.2%	22.1%	2.9%	3.01	3.06	+5.3
2015	22	MIX RAW	2 levels	29	29	180	716	200	37	21	100%	6.2	27.9%	5.2%	22.8%	2.9%	3.01	3.01	+5.4
2016	23	MLB MLE	New York Mets	31	30	184	744	218	41	11	97%	5.9	29.3%	5.5%	23.8%	1.5%	2.60	2.14	+7.9
2016	23	MLB RAW	New York Mets	31	30	184	744	218	41	11	97%	5.9	29.3%	5.5%	23.8%	1.5%	2.60	2.17	+7.8
2017	24	MIX MLE	2 levels	8	8	31	130	36	2	0	100%	3.9	27.4%	1.6%	25.8%	0.0%	2.87	0.99	+1.8
2017	24	MIX RAW	2 levels	8	8	31	130	36	2	0	100%	3.9	27.7%	1.5%	26.2%	0.0%	2.87	0.99	+1.8
2018	25	MLB MLE	New York Mets	25	25	154	644	155	37	9	100%	6.2	24.1%	5.7%	18.3%	1.4%	3.03	2.56	+5.7
2018	25	MLB RAW	New York Mets	25	25	154	644	155	37	9	100%	6.2	24.1%	5.7%	18.3%	1.4%	3.03	2.57	+5.7
2019	26	MLB MLE	New York Mets	32	32	198	825	202	48	24	100%	6.2	24.5%	5.8%	18.7%	2.9%	4.28	3.37	+5.0
2019	26	MLB RAW	New York Mets	32	32	198	825	202	48	24	100%	6.2	24.5%	5.8%	18.7%	2.9%	4.28	3.36	+5.0
2021	28	MIX MLE	4 levels	7	7	10	38	11	1	2	100%	1.4	28.9%	2.6%	26.3%	5.3%	2.70	3.88	+0.2
2021	28	MIX RAW	4 levels	7	7	10	38	11	1	2	100%	1.4	28.9%	2.6%	26.3%	5.3%	2.70	3.80	+0.2
2022	29	MLB MLE	Philadelphia Phillies	25	24	135	565	95	31	14	96%	5.4	16.8%	5.5%	11.3%	2.3%	3.94	3.64	+2.9
2022	29	MLB RAW	Philadelphia Phillies	25	24	135	565	95	31	14	96%	5.4	16.8%	5.5%	11.3%	2.5%	3.94	3.73	+2.7
2023	30	MIX MLE	2 levels	20	20	99	430	64	19	23	100%	4.9	14.3%	4.9%	9.5%	5.6%	6.39	5.60	-0.2
2023	30	MIX RAW	2 levels	20	20	99	430	64	19	23	100%	4.9	14.9%	4.4%	10.5%	5.3%	6.39	5.41	-0.0
2025	32	MIX MLE	2 levels	6	6	23	95	14	2	5	100%	3.9	13.6%	2.1%	11.5%	0.0%	5.40	2.22	—
2025	32	MIX MLE	2 levels	6	6	23	95	14	2	5	100%	3.9	13.6%	2.1%	11.5%	0.0%	5.40	2.22	—
2025	32	MIX RAW	2 levels	6	6	23	95	14	2	5	100%	3.9	14.7%	2.1%	12.6%	5.3%	5.40	4.94	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			164	162	941	3904	928	207	100	99%	5.7	23.8%	5.3%	18.5%	2.6%	3.71	3.17	+26.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	CWS	—	—	0	—	—	—	—	—	—	23.5%	9.0%	14.5%	3.0%	4.28	4.27	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	CWS	3	3	20	84	19	8	3	100%	6.7	22.6%	9.6%	13.0%	3.3%	4.48	4.61	+0.2
2028	35	MLB CTX	CWS	3	3	20	84	19	8	3	100%	6.7	22.6%	9.6%	13.0%	3.4%	4.51	4.64	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		167	165	961	3988	947	215	103	99%	5.8	23.7%	5.4%	18.4%	2.6%	3.73	3.19	+26.4
/ 200 IP	—	RAW		35	34	200	830	197	45	21	99%	5.7	23.7%	5.4%	18.4%	2.6%	3.73	3.19	+5.5
Career	—	MLE		183	181	1013	4187	987	220	104	99%	5.5	23.6%	5.3%	18.3%	2.5%	3.69	3.15	+26.2
/ 200 IP	—	MLE		36	36	200	826	195	43	21	99%	5.5	23.6%	5.3%	18.3%	2.5%	3.69	3.15	+5.5

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 ROKACL White Sox · 15 IPFIP 1.62 → 2.22 (+0.59)K% 20.0% → 13.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.680	13.60%
BB% (unintentional) /BF	1.67%	—	×1.250	2.08%
HR / BF /BF	0.00%	÷1.128	×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 126).

Result: FIP 1.62 → 2.22, 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 AAACharlotte Knights · 8 IPFIP 10.82 → 9.55 (−1.27)K% 5.7% → 4.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	5.71%	—	×0.860	4.91%
BB% (unintentional) /BF	2.86%	—	×0.900	2.57%
HR / BF /BF	14.29%	÷1.320	×1.100	11.91%

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 164).

Result: FIP 10.82 → 9.55, 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).

2023 AAAOklahoma City Dodgers · 10 IPFIP 2.78 → 3.15 (+0.37)K% 20.5% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.51%	—	×0.860	17.64%
BB% (unintentional) /BF	0.00%	—	×0.900	0.00%
HR / BF /BF	2.56%	÷1.006	×1.100	2.80%

Result: FIP 2.78 → 3.15, 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 AAALas Vegas 51s · 30 IPFIP 2.43 → 2.78 (+0.35)K% 30.1% → 26.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.09%	—	×0.880	26.48%
BB% (unintentional) /BF	7.08%	—	×1.050	7.43%
HR / BF /BF	1.77%	÷1.099	×1.100	1.77%

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 120).

Result: FIP 2.43 → 2.78, 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).

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
Noah Syndergaard (OGILVIE)	—	—	—	—	—	3.0%	—	4.61	22.6%	13.0%	20	+0.34	—	—	—
Jose Oyervides R 2016 · 3.09 FIP	34	SP	3.09	24.9%	8.2%	1.9%	.318	5.55	17.0%	7.8%	195	+2.46	3.01	407	80
Manuel Flores R 2019 · 4.32 FIP	33	SP	4.32	17.1%	7.4%	3.1%	.291	—	—	—	—	—	3.46	515	76
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	69
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	67
Yoanner Negrin R 2017 · 3.15 FIP	33	SP	3.15	15.6%	6.0%	1.1%	.277	3.87	17.5%	9.4%	148	+0.72	3.15	485	67
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	67
Jorge Martinez R 2019 · 3.71 FIP	34	SP	3.71	16.3%	5.7%	2.3%	.348	—	—	—	—	—	3.53	214	64
Matt Buschmann R 2016 · 4.84 FIP	32	SP	4.84	12.8%	8.4%	3.2%	.325	—	—	—	—	—	4.03	277	63
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	61
Josh Lowey R 2019 · 3.45 FIP	34	SP	3.45	22.4%	6.8%	2.5%	.303	—	—	—	—	—	2.22	426	60
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	59
Angel Castro R 2017 · 3.51 FIP	34	SP	3.51	14.5%	7.4%	1.3%	.332	—	—	—	—	—	3.51	292	59
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	59
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	58
Leo Medrano R 2016 · 4.34 FIP	33	SP	4.34	11.0%	7.3%	2.3%	.312	—	—	—	—	—	3.76	222	57
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	56
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	56
Michael Nix R 2016 · 4.60 FIP	33	SP	4.60	11.9%	11.6%	1.9%	.322	—	—	—	—	—	3.82	234	56
Frankie De La Cruz R 2017 · 3.77 FIP	33	SP	3.77	15.2%	8.0%	1.7%	.262	4.38	16.2%	8.2%	114	+0.61	2.87	262	54
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	53

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	4.8	108	23.7%	5.6%	1.00	3.73
Pablo López ('25)	4.8	121	24.9%	6.3%	1.07	3.81
Hyun Jin Ryu ('23)	5.3	117	21.5%	5.4%	0.99	3.27
James Paxton ('24)	4.8	95	25.3%	7.9%	1.05	3.77
Roger Nelson ('67-'76, 10 WAR*)	3.2	106	19.5%*	7.1%*	0.98*	3.88*
Ed Halicki ('74-'80, 11 WAR*)	5.3	152	22.9%*	7.2%*	1.10*	4.18*
Chris Bosio ('86-'96, 24 WAR*)	8.6	155	19.4%*	6.3%*	1.04*	3.97*