José Buttó

P San Francisco Giants

Age 29 RHP 6'0" / 208 lbs MLB peak 0.2 · 2027 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MIX2 levels	38	15	118	2.74	3.64	24.4%	11.7%	1.3	K 23.3% · BB 11.3% · FIP 3.73
2025	27	MIX3 levels	58	2	70	3.73	3.39	20.7%	10.2%	1.0	K 20.4% · BB 10.6% · FIP 3.55
2026	28	MLBSF	3	0	2	22.50	17.10	31.2%	25.0%	-0.3
2027PROJ	29	MLBSF	7	7	41	4.22	4.43	23.0%	11.8%	0.5
2028PROJ95% MLB	30	MLBSF	6	6	37	4.47	4.64	22.3%	12.1%	0.3
2029PROJ95% MLB	31	MLBSF	4	4	23	4.71	4.87	21.6%	12.5%	0.1

Last 3 seasons WAR 2.0 · Next 3 projected WAR 0.9Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

FB Velo60

K%38

xwOBA vs36

CompsEdgar Alberto Garcia (age 29) · Carlos Frías (age 29) · Ross Ohlendorf (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 117109vR 101

ERA4.22

FIP4.43

K%23.0%

BB%11.8%

K-BB%11.2%

Proj IP41

Value2027 · WAR

Runs saved vs league avg · 41 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p6095.2

Whiff%

p7228.8%

p3820.4%

xwOBA vs

p360.328

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)
2017	19	ROK MLE	DSL Mets 2	15	8	50	199	41	9	0	53%	3.3	14.0%	5.7%	8.4%	0.0%	1.44	2.63	—
2017	19	ROK RAW	DSL Mets 2	15	8	50	199	41	9	0	53%	3.3	20.6%	4.5%	16.1%	0.0%	1.44	2.00	—
2018	20	ROK MLE	Kingsport Mets	6	6	33	133	31	11	3	100%	5.4	15.8%	10.3%	5.5%	3.2%	1.93	4.80	—
2018	20	ROK RAW	Kingsport Mets	6	6	33	133	31	11	3	100%	5.4	23.3%	8.3%	15.0%	2.3%	1.93	3.41	—
2019	21	A MLE	Columbia Fireflies	27	25	112	467	109	31	8	93%	4.1	17.3%	7.8%	9.4%	2.3%	3.62	3.92	—
2019	21	A RAW	Columbia Fireflies	27	25	112	467	109	31	8	93%	4.1	23.3%	6.6%	16.7%	1.7%	3.62	2.91	—
2021	23	MIX MLE	2 levels	20	20	99	406	110	24	17	100%	4.9	21.4%	6.7%	14.7%	5.4%	3.83	5.13	—
2021	23	MIX RAW	2 levels	20	20	99	406	110	24	17	100%	4.9	27.1%	5.9%	21.2%	4.2%	3.83	3.84	—
2022	24	MIX MLE	3 levels	29	26	133	563	143	46	19	90%	4.6	21.1%	8.9%	12.2%	4.1%	3.92	4.68	+1.1
2022	24	MIX RAW	3 levels	29	26	133	563	143	46	19	90%	4.6	25.4%	8.2%	17.2%	3.4%	3.92	3.84	+2.5
2023	25	MIX MLE	2 levels	28	26	133	593	120	72	20	93%	4.8	18.3%	11.3%	7.0%	3.7%	5.21	4.99	+0.6
2023	25	MIX RAW	2 levels	28	26	133	593	120	72	20	93%	4.8	20.2%	12.1%	8.1%	3.4%	5.21	4.87	+0.8
2024	26	MIX MLE	2 levels	38	15	118	479	117	56	10	39%	3.1	23.3%	11.3%	12.0%	2.1%	2.74	3.73	+1.2
2024	26	MIX MLE	2 levels	38	15	118	479	117	56	10	39%	3.1	23.3%	11.3%	12.0%	2.1%	2.74	3.73	+1.2
2024	26	MIX RAW	2 levels	38	15	118	479	117	56	10	39%	3.1	24.4%	11.7%	12.7%	2.1%	2.74	3.64	+1.3
2025	27	MIX MLE	3 levels	58	2	70	295	61	30	4	3%	1.2	20.4%	10.6%	9.9%	1.5%	3.73	3.55	+0.8
2025	27	MIX MLE	3 levels	58	2	70	295	61	30	4	3%	1.2	20.4%	10.6%	9.9%	1.5%	3.73	3.55	+0.8
2025	27	MIX RAW	3 levels	58	2	70	295	61	30	4	3%	1.2	20.7%	10.2%	10.5%	1.4%	3.73	3.39	+1.0
2026	28	MLB MLE	San Francisco Giants	3	0	2	16	5	4	2	0%	0.7	31.2%	25.0%	6.2%	12.5%	22.50	10.49	-0.1
2026	28	MLB MLE	San Francisco Giants	3	0	2	16	5	4	2	0%	0.7	31.2%	25.0%	6.2%	12.5%	22.50	10.49	-0.1
2026	28	MLB RAW	San Francisco Giants	3	0	2	16	5	4	2	0%	0.7	31.2%	25.0%	6.2%	12.5%	22.50	17.10	-0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			98	15	189	796	185	97	17	15%	1.9	23.2%	12.2%	11.1%	2.1%	3.76	3.85	+1.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	SF	7	7	41	173	40	20	4	100%	5.9	23.0%	11.8%	11.2%	2.5%	4.22	4.43	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	SF	6	6	39	165	37	20	5	100%	6.5	22.3%	12.1%	10.2%	2.7%	4.47	4.64	+0.3
2029	31	MLB MLE	SF	4	4	24	103	22	13	3	100%	6.1	21.6%	12.5%	9.1%	3.0%	4.71	4.87	+0.1
2028	30	MLB CTX	SF	6	6	37	156	35	19	4	100%	6.2	22.3%	12.1%	10.2%	2.7%	4.47	4.64	+0.3
2029	31	MLB CTX	SF	4	4	23	97	21	12	3	100%	5.8	21.6%	12.5%	9.1%	3.0%	4.71	4.87	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		108	25	249	1050	241	128	24	23%	2.3	22.9%	12.2%	10.7%	2.3%	3.96	3.97	+1.7
/ 200 IP	—	RAW		87	20	200	843	193	103	19	23%	2.3	22.9%	12.2%	10.7%	2.3%	3.96	3.97	+1.4
Career	—	MLE		224	128	750	3151	620	295	99	57%	3.3	19.7%	9.4%	10.3%	3.1%	3.69	4.34	+4.0
/ 200 IP	—	MLE		60	34	200	841	166	79	26	57%	3.3	19.7%	9.4%	10.3%	3.1%	3.69	4.34	+3.1

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.

2024 AAASyracuse Mets · 44 IPFIP 3.78 → 3.95 (+0.17)K% 20.5% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.54%	—	×0.860	17.66%
BB% (unintentional) /BF	9.73%	—	×0.900	8.76%
HR / BF /BF	2.16%	÷1.059	×1.100	2.25%

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 112).

Result: FIP 3.78 → 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).

2023 AAASyracuse Mets · 91 IPFIP 5.18 → 5.48 (+0.30)K% 19.8% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.81%	—	×0.860	17.03%
BB% (unintentional) /BF	11.84%	—	×0.900	10.65%
HR / BF /BF	4.11%	÷1.003	×1.100	4.50%

Result: FIP 5.18 → 5.48, 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).

2022 AABinghamton Rumble Ponies · 92 IPFIP 3.86 → 5.06 (+1.21)K% 27.2% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.20%	—	×0.810	22.04%
BB% (unintentional) /BF	8.82%	—	×1.100	9.70%
HR / BF /BF	3.53%	÷0.895	×1.200	4.73%

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 79).

Result: FIP 3.86 → 5.06, 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 AAASyracuse Mets · 37 IPFIP 3.28 → 3.60 (+0.33)K% 21.0% → 18.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.98%	—	×0.880	18.46%
BB% (unintentional) /BF	6.29%	—	×1.050	6.61%
HR / BF /BF	2.10%	÷1.033	×1.100	2.23%

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 107).

Result: FIP 3.28 → 3.60, 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 A+Brooklyn Cyclones · 58 IPFIP 4.30 → 5.80 (+1.50)K% 25.1% → 19.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.10%	—	×0.770	19.33%
BB% (unintentional) /BF	6.28%	—	×1.150	7.22%
HR / BF /BF	4.60%	÷0.925	×1.250	6.22%

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 85).

Result: FIP 4.30 → 5.80, 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 AABinghamton Rumble Ponies · 40 IPFIP 3.23 → 4.18 (+0.96)K% 29.9% → 24.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.94%	—	×0.810	24.25%
BB% (unintentional) /BF	5.39%	—	×1.100	5.93%
HR / BF /BF	3.59%	÷0.995	×1.200	4.34%

Result: FIP 3.23 → 4.18, 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 AColumbia Fireflies · 112 IPFIP 2.91 → 3.92 (+1.01)K% 23.3% → 17.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.34%	—	×0.740	17.27%
BB% (unintentional) /BF	6.64%	—	×1.180	7.83%
HR / BF /BF	1.71%	÷0.949	×1.300	2.35%

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 90).

Result: FIP 2.91 → 3.92, 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 ROKKingsport Mets · 33 IPFIP 3.42 → 4.80 (+1.39)K% 23.3% → 15.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.31%	—	×0.680	15.85%
BB% (unintentional) /BF	8.27%	—	×1.250	10.34%
HR / BF /BF	2.26%	÷1.000	×1.400	3.16%

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 3.42 → 4.80, 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
José Buttó (OGILVIE)	—	—	—	—	—	2.5%	—	4.73	22.0%	9.8%	63	+0.30	—	—	—
Edgar Alberto Garcia R 2017 · 4.01 FIP	29	SP-	4.01	17.3%	10.9%	1.8%	.305	—	—	—	—	—	4.01	272	64
Carlos Frías R 2019 · 4.42 FIP	29	SP-	4.42	16.9%	11.1%	2.4%	.369	—	—	—	—	—	3.40	236	64
Ross Ohlendorf R 2012 · 4.60 FIP	29	SP-	4.60	16.7%	10.3%	2.9%	.337	3.67	20.8%	14.6%	116	-0.93	3.30	617	62
Zach Stewart R 2015 · 4.43 FIP	28	SP-	4.43	14.4%	8.3%	2.7%	.322	5.17	11.7%	2.1%	51	+0.74	4.27	194	62
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	61
Derek Eitel R 2017 · 4.72 FIP	29	SP-	4.72	17.2%	16.0%	1.9%	.273	—	—	—	—	—	3.96	138	61
Ryan Jensen R 2005 · 4.35 FIP	29	SW	4.35	15.7%	5.2%	3.5%	.310	—	—	—	—	—	4.35	253	59
Dinelson Lamet R 2021 · 3.67 FIP	29	SW	3.67	27.3%	10.5%	2.8%	.339	4.61	20.7%	8.6%	176	+0.94	2.11	778	58
Anthony Bass R 2017 · 3.42 FIP	29	SP-	3.42	23.6%	9.1%	2.1%	.356	3.43	20.7%	14.2%	141	+0.01	2.93	647	58
Lisalverto Bonilla R 2019 · 4.70 FIP	29	SP-	4.70	15.8%	12.6%	2.5%	.265	—	—	—	—	—	3.22	242	58
Paul Clemens R 2017 · 4.72 FIP	29	SW	4.72	14.9%	11.0%	2.7%	.264	—	—	—	—	—	4.58	345	58
Reinier Roibal R 2019 · 4.91 FIP	30	SP	4.91	17.5%	11.8%	3.3%	.426	—	—	—	—	—	3.11	133	57
Orlando Rodriguez R 2023 · 4.67 FIP	27	SW	4.67	13.7%	10.6%	2.5%	.252	—	—	—	—	—	4.40	119	57
Bradin Hagens R 2018 · 4.92 FIP	29	SP-	4.92	14.9%	9.9%	3.3%	.341	5.46	13.2%	0.6%	66	+0.54	3.79	254	57
Dustin McGowan R 2011 · 5.34 FIP	29	SP-	5.34	20.8%	13.5%	4.2%	.271	4.46	18.5%	9.4%	108	-0.88	3.36	690	56
Mickey Callaway R 2004 · 5.21 FIP	29	SP-	5.21	15.5%	12.1%	3.5%	.400	—	—	—	—	—	4.22	126	56
Mike Wright Jr. R 2019 · 3.76 FIP	29	SW	3.76	19.9%	7.2%	2.6%	.347	4.19	17.6%	7.3%	169	+0.43	3.76	725	56
Jon Leicester R 2007 · 4.44 FIP	28	SP-	4.44	11.0%	9.0%	2.1%	.292	—	—	—	—	—	3.76	113	56
Mitch Neunborn R 2024 · 4.25 FIP	27	SP-	4.25	19.0%	12.0%	2.2%	.285	5.80	16.4%	6.5%	114	+1.55	3.65	248	56
Markus Solbach R 2021 · 3.63 FIP	29	SP-	3.63	15.4%	8.3%	1.4%	.383	5.37	18.3%	10.7%	63	+1.74	3.34	391	55

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	1.5	50	22.9%	12.3%	0.91	4.00
Dave Geisel ('78-'85, 2 WAR*)	1.0	42	23.5%*	10.6%*	0.84*	4.12*
Daniel Bard ('23)	2.3	57	24.2%	12.3%	0.85	3.74
David Aardsma ('15)	1.7	48	23.1%	12.4%	1.09	4.27
Tyler Matzek ('25)	1.5	58	22.2%	11.7%	0.65	3.73
Horacio Pina ('68-'78, 2 WAR*)	2.2	62	20.7%*	11.2%*	0.84*	4.01*
Bill Kelso ('64-'68, 1 WAR*)	1.0	67	23.1%*	11.6%*	1.09*	4.19*