Jose Quintana

P Colorado Rockies

Age 38 LHP 6'2" / 224 lbs MLB

Overview

MLBSP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	35	MLBNYM	31	31	170	3.75	4.30	18.8%	8.8%	2.2
2025	36	MIX2 levels	25	25	136	4.05	4.60	16.0%	8.9%	1.3	K 16.0% · BB 9.0% · FIP 4.58
2026	37	MIX3 levels	13	13	52	5.50	5.70	11.6%	8.6%	-0.2	K 11.8% · BB 9.0% · FIP 5.54
2027PROJ	38	MLBCOL	4	4	27	4.81	5.26	14.1%	9.0%	0.0
2028PROJ	39	MLBCOL	2	2	13	5.66	6.02	12.9%	9.7%	-0.0
2029PROJ	40	MLBCOL	1	1	7	6.16	6.48	11.8%	10.4%	-0.1

Last 3 seasons WAR 3.3 · 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

xwOBA vs12

FB Velo10

K%10

CompsOscar Rivera (age 36) · Juan Antonio Pena (age 37) · Jorge Castillo (age 37)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 118126vR 134

ERA4.81

FIP5.26

K%14.1%

BB%9.0%

K-BB%5.1%

Proj IP27

Value2027 · WAR

Runs saved vs league avg · 27 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1089.7

Whiff%

p1920.9%

p1011.8%

xwOBA vs

p120.357

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)
2012	23	MLB MLE	Chicago White Sox	25	22	136	568	81	38	14	88%	5.5	14.3%	6.7%	7.6%	2.4%	3.76	4.07	+2.1
2012	23	MLB RAW	Chicago White Sox	25	22	136	568	81	38	14	88%	5.5	14.3%	6.7%	7.6%	2.5%	3.76	4.08	+2.1
2013	24	MLB MLE	Chicago White Sox	33	33	200	832	164	54	23	100%	6.1	19.7%	6.5%	13.2%	2.7%	3.51	3.75	+4.0
2013	24	MLB RAW	Chicago White Sox	33	33	200	832	164	54	23	100%	6.1	19.7%	6.5%	13.2%	2.8%	3.51	3.77	+3.9
2014	25	MLB MLE	Chicago White Sox	32	32	200	830	178	49	10	100%	6.3	21.4%	5.9%	15.5%	1.2%	3.32	2.69	+7.0
2014	25	MLB RAW	Chicago White Sox	32	32	200	830	178	49	10	100%	6.3	21.4%	5.9%	15.5%	1.2%	3.32	2.71	+6.9
2015	26	MLB MLE	Chicago White Sox	32	32	206	862	177	40	16	100%	6.4	20.5%	4.6%	15.9%	1.8%	3.36	2.96	+6.4
2015	26	MLB RAW	Chicago White Sox	32	32	206	862	177	40	16	100%	6.4	20.5%	4.6%	15.9%	1.9%	3.36	2.97	+6.3
2016	27	MLB MLE	Chicago White Sox	32	32	208	837	181	49	22	100%	6.5	21.6%	5.9%	15.8%	2.6%	3.20	3.43	+5.0
2016	27	MLB RAW	Chicago White Sox	32	32	208	837	181	49	22	100%	6.5	21.6%	5.9%	15.8%	2.6%	3.20	3.44	+5.0
2017	28	MLB MLE	Chicago Cubs	32	32	189	790	207	57	23	100%	5.9	26.2%	7.2%	19.0%	3.0%	4.15	3.46	+4.5
2017	28	MLB RAW	Chicago Cubs	32	32	189	790	207	57	23	100%	5.9	26.2%	7.2%	19.0%	2.9%	4.15	3.40	+4.7
2018	29	MLB MLE	Chicago Cubs	32	32	174	739	158	65	25	100%	5.4	21.4%	8.8%	12.6%	3.5%	4.03	4.34	+2.2
2018	29	MLB RAW	Chicago Cubs	32	32	174	739	158	65	25	100%	5.4	21.4%	8.8%	12.6%	3.4%	4.03	4.27	+2.3
2019	30	MLB MLE	Chicago Cubs	32	31	171	745	152	46	20	97%	5.3	20.4%	6.2%	14.2%	2.8%	4.68	3.69	+3.5
2019	30	MLB RAW	Chicago Cubs	32	31	171	745	152	46	20	97%	5.3	20.4%	6.2%	14.2%	2.7%	4.68	3.65	+3.6
2020	31	MLB MLE	Chicago Cubs	4	1	10	41	12	3	1	25%	2.5	29.3%	7.3%	22.0%	2.4%	4.50	2.89	+0.2
2020	31	MLB RAW	Chicago Cubs	4	1	10	41	12	3	1	25%	2.5	29.3%	7.3%	22.0%	2.4%	4.50	2.90	+0.2
2021	32	MLB MLE	San Francisco Giants	29	10	63	297	85	34	12	34%	2.2	28.6%	11.4%	17.2%	4.4%	6.43	4.53	+0.0
2021	32	MLB RAW	San Francisco Giants	29	10	63	297	85	34	12	34%	2.2	28.6%	11.4%	17.2%	4.0%	6.43	4.50	+0.0
2022	33	MLB MLE	St. Louis Cardinals	32	32	166	679	137	46	8	100%	5.2	20.2%	6.8%	13.4%	1.3%	2.93	2.95	+5.1
2022	33	MLB RAW	St. Louis Cardinals	32	32	166	679	137	46	8	100%	5.2	20.2%	6.8%	13.4%	1.2%	2.93	2.91	+5.2
2023	34	MIX MLE	4 levels	18	17	91	386	76	32	7	94%	5.1	18.8%	7.5%	11.3%	1.6%	3.74	3.33	+2.3
2023	34	MIX RAW	4 levels	18	17	91	386	76	32	7	94%	5.1	19.7%	8.3%	11.4%	1.8%	3.74	3.48	+2.1
2024	35	MLB MLE	New York Mets	31	31	170	717	135	63	22	100%	5.5	18.8%	8.8%	10.0%	3.1%	3.75	4.31	+2.2
2024	35	MLB MLE	New York Mets	31	31	170	717	135	63	22	100%	5.5	18.8%	8.8%	10.0%	3.1%	3.75	4.31	+2.2
2024	35	MLB RAW	New York Mets	31	31	170	717	135	63	22	100%	5.5	18.8%	8.8%	10.0%	3.1%	3.75	4.30	+2.2
2025	36	MIX MLE	2 levels	25	25	136	574	92	51	18	100%	5.4	16.0%	9.0%	7.0%	3.1%	4.05	4.58	+1.3
2025	36	MIX MLE	2 levels	25	25	136	574	92	51	18	100%	5.4	16.0%	9.0%	7.0%	3.1%	4.05	4.58	+1.3
2025	36	MIX RAW	2 levels	25	25	136	574	92	51	18	100%	5.4	16.0%	8.9%	7.1%	3.1%	4.05	4.60	+1.3
2026	37	MIX MLE	3 levels	13	13	52	232	27	20	10	100%	4.0	11.8%	9.0%	2.8%	4.2%	5.50	5.54	-0.1
2026	37	MIX MLE	3 levels	13	13	52	232	27	20	10	100%	4.0	11.8%	9.0%	2.8%	4.2%	5.50	5.54	-0.1
2026	37	MIX RAW	3 levels	13	13	52	232	27	20	10	100%	4.0	11.6%	8.6%	3.0%	4.3%	5.50	5.70	-0.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			394	368	2149	9024	1841	637	229	93%	5.5	20.4%	7.1%	13.3%	2.5%	3.79	3.66	+45.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	38	MLB	COL	4	4	27	114	16	10	4	100%	6.8	14.1%	9.0%	5.1%	3.3%	4.81	5.26	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	39	MLB MLE	COL	2	2	13	56	7	5	2	100%	6.7	12.9%	9.7%	3.2%	3.8%	5.34	5.70	-0.0
2029	40	MLB MLE	COL	1	1	7	29	3	3	1	100%	6.9	11.8%	10.4%	1.4%	4.2%	5.81	6.13	-0.1
2028	39	MLB CTX	COL	2	2	13	55	7	5	2	100%	6.5	12.9%	9.7%	3.2%	4.4%	5.66	6.02	-0.0
2029	40	MLB CTX	COL	1	1	7	30	3	3	1	100%	7.0	11.8%	10.4%	1.4%	4.9%	6.16	6.48	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		397	371	2170	9109	1852	645	233	93%	5.5	20.3%	7.1%	13.2%	2.6%	3.81	3.68	+45.0
/ 200 IP	—	RAW		37	34	200	840	171	59	21	93%	5.5	20.3%	7.1%	13.2%	2.6%	3.81	3.68	+4.2
Career	—	MLE		402	375	2173	9129	1859	645	232	93%	5.4	20.4%	7.1%	13.3%	2.5%	3.81	3.67	+45.1
/ 200 IP	—	MLE		37	35	200	840	171	59	21	93%	5.4	20.4%	7.1%	13.3%	2.5%	3.81	3.67	+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.

2023 AAASyracuse Mets · 7 IPFIP 5.21 → 5.39 (+0.18)K% 20.6% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.59%	—	×0.860	17.71%
BB% (unintentional) /BF	17.65%	—	×0.900	15.88%
HR / BF /BF	2.94%	÷1.003	×1.100	3.23%

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 101).

Result: FIP 5.21 → 5.39, 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).

	Profile at Match Age	Next 3 Yrs	Career
Jose Quintana (OGILVIE)	—	—	—	—	—	3.3%	—	5.70	12.9%	3.2%	13	+0.44	—	—	—
Oscar Rivera L 2017 · 5.80 FIP	36	SP	5.80	9.8%	7.8%	4.6%	.252	—	—	—	—	—	3.68	237	47
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	46
Jorge Castillo L 2019 · 4.91 FIP	37	SP	4.91	19.6%	8.1%	4.5%	.316	—	—	—	—	—	4.50	408	41
Jason Lane L 2015 · 5.56 FIP	38	SP	5.56	8.4%	6.2%	4.3%	.307	—	—	—	—	—	5.56	164	37
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	22
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	22
Ivan Maldonado R 2016 · 5.41 FIP	36	SP	5.41	6.4%	9.7%	3.0%	.325	—	—	—	—	—	4.60	172	21
Jose Oyervides R 2019 · 5.66 FIP	37	SP	5.66	16.3%	11.2%	4.6%	.320	—	—	—	—	—	3.01	407	20
Jonathan Castellanos R 2019 · 5.24 FIP	37	SW	5.24	11.0%	9.0%	3.5%	.348	—	—	—	—	—	3.40	394	8

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	11.0	129	20.2%	7.4%	0.99	3.82
Aníbal Sánchez ('22)	10.1	126	20.6%	8.0%	1.06	4.06
Bob Ojeda ('80-'94, 22 WAR*)	9.4	135	19.1%*	8.5%*	0.97*	4.08*
Bruce Kison ('71-'85, 16 WAR*)	9.0	121	20.4%*	8.5%*	1.10*	4.16*
Mike Flanagan ('75-'92, 32 WAR*)	13.8	163	19.0%*	7.6%*	1.06*	4.25*
Charlie Morton ('25)	11.3	133	22.5%	8.8%	0.90	4.13
Marcus Stroman ('25)	7.5	136	19.6%	7.2%	0.87	3.79

			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
Jose Quintana (OGILVIE)	—	—	—	—	—	3.3%	—	5.70	12.9%	3.2%	13	+0.44	—	—	—
Oscar Rivera L 2017 · 5.80 FIP	36	SP	5.80	9.8%	7.8%	4.6%	.252	—	—	—	—	—	3.68	237	47
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	46
Jorge Castillo L 2019 · 4.91 FIP	37	SP	4.91	19.6%	8.1%	4.5%	.316	—	—	—	—	—	4.50	408	41
Jason Lane L 2015 · 5.56 FIP	38	SP	5.56	8.4%	6.2%	4.3%	.307	—	—	—	—	—	5.56	164	37
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	22
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	22
Ivan Maldonado R 2016 · 5.41 FIP	36	SP	5.41	6.4%	9.7%	3.0%	.325	—	—	—	—	—	4.60	172	21
Jose Oyervides R 2019 · 5.66 FIP	37	SP	5.66	16.3%	11.2%	4.6%	.320	—	—	—	—	—	3.01	407	20
Jonathan Castellanos R 2019 · 5.24 FIP	37	SW	5.24	11.0%	9.0%	3.5%	.348	—	—	—	—	—	3.40	394	8

Jose Quintana

Contract

Career Stats + Projections

How the minor-league lines were translated

Career Path Comps

Career Comps