Yohan Ramírez

P Pittsburgh Pirates

Age 32 RHP 6'3" / 205 lbs MLB peak 0.7 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MIX2 levels	53	0	66	4.93	3.37	23.2%	8.7%	0.9	K 22.0% · BB 8.4% · FIP 3.46
2025	30	MIX2 levels	51	0	64	4.34	2.90	29.2%	9.2%	1.3	K 27.2% · BB 8.7% · FIP 3.16
2026	31	MLBPIT	66	1	85	2.86	2.55	28.2%	9.7%	2.0
2027PROJ	32	MLBPIT	55	0	58	3.74	3.50	27.7%	9.4%	0.7
2028PROJ95% MLB	33	MLBPIT	41	0	43	3.76	3.78	26.8%	9.8%	0.4
2029PROJ90% MLB	34	MLBPIT	29	0	30	3.95	4.08	25.9%	10.3%	0.2

Last 3 seasons WAR 4.2 · Next 3 projected WAR 1.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%82

xwOBA vs81

FB Velo79

Form2.17 ERA (proj 3.74) · K 35.1% (proj 27.7%) · BB 9.6% (proj 9.4%) ▲▲ last 90d · 29 IP through Oct 27

CompsJumbo Diaz (age 32) · Jose Veras (age 32) · Scot Shields (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9586vR 78

ERA3.74

FIP3.50

K%27.7%

BB%9.4%

K-BB%18.3%

Proj IP58

Value2027 · WAR

Runs saved vs league avg · 58 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p7996.6

Whiff%

p6727.9%

p8228.2%

xwOBA vs

p810.282

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	GCL Astros	12	4	30	135	18	14	0	33%	2.5	9.1%	13.0%	-3.9%	0.0%	2.37	3.98	—
2016	21	ROK RAW	GCL Astros	12	4	30	135	18	14	0	33%	2.5	13.3%	10.4%	3.0%	0.0%	2.37	3.30	—
2017	22	MIX MLE	3 levels	20	11	75	333	65	46	5	55%	3.8	13.2%	17.5%	-4.3%	1.5%	4.66	5.04	—
2017	22	MIX RAW	3 levels	20	11	75	333	65	46	5	55%	3.8	19.5%	13.8%	5.7%	1.5%	4.66	4.07	—
2018	23	MIX MLE	2 levels	29	10	78	336	82	42	6	34%	2.7	18.2%	14.6%	3.6%	2.4%	3.00	4.72	—
2018	23	MIX RAW	2 levels	29	10	78	336	82	42	6	34%	2.7	24.4%	12.5%	11.9%	1.8%	3.00	3.61	—
2019	24	MIX MLE	2 levels	27	15	106	467	158	74	5	56%	3.9	26.8%	17.7%	9.1%	1.2%	3.99	3.73	—
2019	24	MIX RAW	2 levels	27	15	106	467	158	74	5	56%	3.9	33.8%	15.8%	18.0%	1.1%	3.99	2.83	—
2020	25	MLB MLE	Seattle Mariners	16	0	21	94	26	19	3	0%	1.3	27.7%	20.2%	7.4%	3.3%	2.61	5.12	-0.1
2020	25	MLB RAW	Seattle Mariners	16	0	21	94	26	19	3	0%	1.3	27.7%	20.2%	7.4%	3.2%	2.61	5.23	-0.2
2021	26	MIX MLE	2 levels	40	0	45	190	59	25	8	0%	1.1	29.5%	13.5%	16.0%	4.4%	4.00	4.75	-0.1
2021	26	MIX RAW	2 levels	40	0	45	190	59	25	8	0%	1.1	31.1%	13.2%	17.9%	4.2%	4.00	4.46	+0.1
2022	27	MIX MLE	2 levels	50	0	59	257	56	31	6	0%	1.2	20.7%	12.3%	8.4%	2.5%	4.58	4.30	+0.2
2022	27	MIX RAW	2 levels	50	0	59	257	56	31	6	0%	1.2	21.8%	12.1%	9.7%	2.3%	4.58	4.10	+0.3
2023	28	MIX MLE	2 levels	53	1	65	298	74	30	5	2%	1.2	23.0%	9.6%	13.4%	1.6%	4.55	3.27	+1.0
2023	28	MIX RAW	2 levels	53	1	65	298	74	30	5	2%	1.2	24.8%	10.1%	14.8%	1.7%	4.55	3.21	+1.0
2024	29	MIX MLE	2 levels	53	0	66	298	69	26	6	0%	1.2	22.0%	8.4%	13.7%	2.1%	4.93	3.46	+0.9
2024	29	MIX MLE	2 levels	53	0	66	298	69	26	6	0%	1.2	22.0%	8.4%	13.7%	2.1%	4.93	3.46	+0.9
2024	29	MIX RAW	2 levels	53	0	66	298	69	26	6	0%	1.2	23.2%	8.7%	14.4%	2.0%	4.93	3.37	+0.9
2025	30	MIX MLE	2 levels	51	0	64	295	86	27	6	0%	1.3	27.2%	8.7%	18.5%	2.3%	4.34	3.16	+1.1
2025	30	MIX MLE	2 levels	51	0	64	295	86	27	6	0%	1.3	27.2%	8.7%	18.5%	2.3%	4.34	3.16	+1.1
2025	30	MIX RAW	2 levels	51	0	64	295	86	27	6	0%	1.3	29.2%	9.2%	20.0%	2.0%	4.34	2.90	+1.3
2026	31	MLB MLE	Pittsburgh Pirates	66	1	85	362	102	35	4	2%	1.3	28.2%	9.7%	18.5%	1.2%	2.86	2.60	+2.0
2026	31	MLB MLE	Pittsburgh Pirates	66	1	85	362	102	35	4	2%	1.3	28.2%	9.7%	18.5%	1.2%	2.86	2.60	+2.0
2026	31	MLB RAW	Pittsburgh Pirates	66	1	85	362	102	35	4	2%	1.3	28.2%	9.7%	18.5%	1.1%	2.86	2.55	+2.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			230	1	287	1276	320	131	28	0%	1.2	25.1%	10.3%	14.8%	2.2%	4.17	3.51	+3.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	PIT	55	0	58	245	68	23	5	0%	1.1	27.7%	9.4%	18.3%	2.1%	3.74	3.50	+0.7
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	PIT	43	0	45	190	51	19	5	0%	1.0	26.8%	9.8%	17.0%	2.4%	3.76	3.78	+0.4
2029	34	MLB MLE	PIT	32	0	33	140	36	14	4	0%	1.0	25.9%	10.3%	15.6%	2.7%	3.95	4.08	+0.2
2030	35	MLB MLE	PIT	21	0	22	94	23	10	3	0%	1.1	24.9%	10.9%	14.1%	3.0%	4.23	4.42	+0.0
2028	33	MLB CTX	PIT	41	0	43	182	49	18	4	0%	1.0	26.8%	9.8%	17.0%	2.4%	3.76	3.78	+0.4
2029	34	MLB CTX	PIT	29	0	30	127	33	13	3	0%	1.0	25.9%	10.3%	15.6%	2.7%	3.95	4.08	+0.2
2030	35	MLB CTX	PIT	18	0	19	80	20	9	2	0%	1.1	24.9%	10.9%	14.1%	3.0%	4.23	4.42	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		317	1	379	1664	421	171	38	0%	1.2	25.3%	10.2%	15.1%	2.3%	4.11	3.52	+4.6
/ 200 IP	—	RAW		167	1	200	878	222	90	20	0%	1.2	25.3%	10.2%	15.1%	2.3%	4.11	3.52	+2.4
Career	—	MLE		417	42	695	3065	695	398	59	10%	1.7	22.7%	13.0%	9.7%	1.9%	3.93	3.89	+4.2
/ 200 IP	—	MLE		120	12	200	882	200	115	17	10%	1.7	22.7%	13.0%	9.7%	1.9%	3.93	3.89	+2.2

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.

2025 AAAIndianapolis Indians · 31 IPFIP 2.50 → 2.89 (+0.40)K% 29.3% → 25.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.29%	—	×0.860	25.19%
BB% (unintentional) /BF	8.57%	—	×0.900	7.71%
HR / BF /BF	1.43%	÷0.915	×1.100	1.72%

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 83).

Result: FIP 2.50 → 2.89, 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 AAAWorcester Red Sox · 21 IPFIP 3.62 → 3.90 (+0.29)K% 26.7% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.67%	—	×0.860	22.93%
BB% (unintentional) /BF	12.22%	—	×0.900	11.00%
HR / BF /BF	2.22%	÷0.996	×1.100	2.45%

Result: FIP 3.62 → 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).

2023 AAACharlotte Knights · 27 IPFIP 2.75 → 2.95 (+0.19)K% 32.0% → 27.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.97%	—	×0.860	27.49%
BB% (unintentional) /BF	11.48%	—	×0.900	10.33%
HR / BF /BF	1.64%	÷1.152	×1.100	1.56%

Result: FIP 2.75 → 2.95, 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).

2022 AAAIndianapolis Indians · 22 IPFIP 3.76 → 4.22 (+0.46)K% 26.7% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.67%	—	×0.880	23.47%
BB% (unintentional) /BF	13.33%	—	×1.050	14.00%
HR / BF /BF	2.22%	÷1.013	×1.100	2.41%

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 103).

Result: FIP 3.76 → 4.22, 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).

2021 AAATacoma Rainiers · 17 IPFIP 4.04 → 4.67 (+0.62)K% 31.6% → 27.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.58%	—	×0.880	27.79%
BB% (unintentional) /BF	17.11%	—	×1.050	17.96%
HR / BF /BF	2.63%	÷0.970	×1.100	2.98%

Result: FIP 4.04 → 4.67, 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 AACorpus Christi Hooks · 62 IPFIP 3.74 → 4.59 (+0.85)K% 31.3% → 25.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.34%	—	×0.810	25.38%
BB% (unintentional) /BF	18.31%	—	×1.100	20.14%
HR / BF /BF	1.76%	÷1.067	×1.200	1.98%

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 113).

Result: FIP 3.74 → 4.59, 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 A+Fayetteville Woodpeckers · 44 IPFIP 1.44 → 2.40 (+0.96)K% 37.7% → 29.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.70%	—	×0.770	29.03%
BB% (unintentional) /BF	12.02%	—	×1.150	13.83%
HR / BF /BF	0.00%	÷0.969	×1.250	0.00%

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 94).

Result: FIP 1.44 → 2.40, 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 AQuad Cities River Bandits · 58 IPFIP 3.75 → 5.01 (+1.26)K% 25.1% → 18.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.10%	—	×0.740	18.57%
BB% (unintentional) /BF	11.34%	—	×1.180	13.38%
HR / BF /BF	2.43%	÷0.973	×1.300	3.24%

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 95).

Result: FIP 3.75 → 5.01, 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
Yohan Ramírez (OGILVIE)	—	—	—	—	—	2.1%	—	4.02	26.1%	15.9%	100	+0.52	—	—	—
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	75
Jose Veras R 2013 · 3.51 FIP	32	SU	3.51	23.6%	8.3%	2.5%	.234	4.28	21.9%	10.2%	65	+0.77	3.37	422	75
Scot Shields R 2007 · 3.58 FIP	32	SU	3.58	24.1%	10.3%	2.2%	.271	4.26	20.3%	7.3%	127	+0.68	2.77	686	73
Akinori Otsuka R 2004 · 2.61 FIP	32	SU	2.61	27.9%	6.4%	1.9%	.251	2.78	20.3%	13.4%	155	+0.17	2.39	232	73
Dale Thayer R 2013 · 3.62 FIP	32	SU	3.62	23.7%	7.4%	2.9%	.287	3.85	20.6%	15.0%	103	+0.23	2.75	239	72
Kazuhiro Sasaki R 2000 · 3.93 FIP	32	SU	3.93	29.4%	9.8%	3.8%	.212	2.88	24.9%	19.3%	161	-1.05	2.76	223	71
Chris Hatcher R 2017 · 4.31 FIP	32	SU	4.31	24.5%	7.4%	4.3%	.291	5.32	18.0%	8.4%	36	+1.01	2.51	246	70
Steve Delabar R 2015 · 3.74 FIP	32	SU	3.74	25.0%	9.9%	2.7%	.246	4.62	20.4%	4.8%	24	+0.88	2.43	229	70
Mike Broadway R 2018 · 4.65 FIP	31	SU	4.65	23.0%	10.6%	3.9%	.282	—	—	—	—	—	1.74	195	69
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	69
Grant Balfour R 2010 · 2.59 FIP	32	SU	2.59	25.2%	6.8%	1.4%	.270	3.50	25.6%	16.7%	199	+0.91	2.04	533	69
Jared Burton R 2013 · 3.20 FIP	32	SU	3.20	21.7%	6.0%	2.1%	.279	3.92	18.4%	10.0%	78	+0.72	3.09	367	68
Hirokazu Sawamura R 2021 · 4.48 FIP	33	SU	4.48	26.2%	11.2%	4.0%	.263	4.02	18.1%	6.8%	51	-0.46	4.02	104	67
George Kontos R 2017 · 3.71 FIP	32	SU	3.71	25.2%	6.5%	3.5%	.287	4.41	14.7%	8.6%	97	+0.70	2.56	421	67
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	67
Huascar Brazobán R 2022 · 3.77 FIP	32	SU	3.77	28.5%	11.4%	3.0%	.275	3.49	23.3%	12.9%	187	-0.28	3.08	370	67
Ryan Brasier R 2020 · 2.97 FIP	32	SU	2.97	27.3%	9.1%	1.9%	.324	3.30	23.4%	17.1%	134	+0.33	2.31	426	66
Jay Jackson R 2019 · 2.80 FIP	31	SU	2.80	32.4%	9.1%	2.3%	.272	3.59	29.4%	19.9%	41	+0.79	2.36	261	66
Brian Sanches R 2011 · 4.35 FIP	32	SU	4.35	19.6%	11.1%	2.7%	.250	—	—	—	—	—	3.39	229	66
Matt Lindstrom R 2012 · 2.71 FIP	32	SU	2.71	20.0%	6.0%	1.0%	.295	3.34	15.4%	7.9%	117	+0.63	2.40	443	66

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	2.2	40	25.6%	10.9%	0.88	4.06
Rudy Seanez ('08)	2.8	43	23.1%	11.4%	0.93	4.11
Jason Grilli ('17)	3.4	53	23.4%	9.8%	1.00	4.22
John Axford ('21)	2.6	58	25.6%	11.3%	0.86	3.90
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Dave Geisel ('78-'85, 2 WAR*)	1.0	42	23.5%*	10.6%*	0.84*	4.12*
Tim Stoddard ('75-'89, 4 WAR*)	3.6	66	26.2%*	11.2%*	1.14*	4.24*