Jose A. Ferrer

P Seattle Mariners

Age 27 LHP 6'1" / 233 lbs MLB peak 0.5 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	MIX3 levels	39	41	3.10	2.49	21.2%	6.2%	1.0	K 19.4% · BB 4.7% · FIP 2.48
2025	25	MLBWSH	72	76	4.48	2.68	21.9%	4.6%	1.7
2026	26	MLBSEA	73	65	4.18	3.67	18.3%	6.1%	0.7
2027PROJ	27	MLBSEA	56	59	3.85	3.64	21.4%	5.2%	0.7
2028PROJ95% MLB	28	MLBSEA	42	44	3.77	3.72	21.2%	5.3%	0.4
2029PROJ95% MLB	29	MLBSEA	33	35	3.84	3.88	20.6%	5.5%	0.3

Last 3 seasons WAR 3.4 · Next 3 projected WAR 1.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo90

xwOBA vs51

K%23

Form7.40 ERA (proj 3.85) · K 17.5% (proj 21.4%) · BB 6.8% (proj 5.2%) ▼ last 90d · 21 IP through Oct 27

CompsAaron Fultz (age 27) · James Pazos (age 27) · Jose Mijares (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 8795vR 103

ERA3.85

FIP3.64

K%21.4%

BB%5.2%

K-BB%16.2%

Proj IP59

Value2027 · WAR

Runs saved vs league avg · 59 IP

Grades · Statcast · Contract

Scouting Grades

STUF4545

CTRL6565

CMD5555

K†5050

Statcast Percentiles

FB Velo

p9098.0

Whiff%

p1019.6%

p2318.3%

xwOBA vs

p510.311

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)
2018	18	ROK MLE	DSL Nationals	14	0	30	139	53	11	0	0%	2.1	25.9%	9.9%	16.0%	0.0%	3.60	2.16	—
2018	18	ROK RAW	DSL Nationals	14	0	30	139	53	11	0	0%	2.1	38.1%	7.9%	30.2%	0.0%	3.60	0.67	—
2019	19	ROK MLE	GCL Nationals	9	2	22	94	24	13	0	22%	2.4	17.4%	17.3%	0.1%	0.0%	2.91	3.82	—
2019	19	ROK RAW	GCL Nationals	9	2	22	94	24	13	0	22%	2.4	25.5%	13.8%	11.7%	0.0%	2.91	2.68	—
2021	21	ROK MLE	FCL Nationals	17	0	36	153	47	9	1	0%	2.1	20.9%	7.4%	13.5%	0.9%	2.78	2.76	—
2021	21	ROK RAW	FCL Nationals	17	0	36	153	47	9	1	0%	2.1	30.7%	5.9%	24.8%	0.7%	2.78	1.59	—
2022	22	MIX MLE	3 levels	48	0	65	256	78	11	8	0%	1.4	22.8%	5.2%	17.6%	3.6%	2.48	3.78	—
2022	22	MIX RAW	3 levels	48	0	65	256	78	11	8	0%	1.4	30.5%	4.3%	26.2%	3.1%	2.48	2.81	—
2023	23	MIX MLE	2 levels	73	0	74	321	58	30	8	0%	1.0	16.6%	8.8%	7.9%	2.5%	4.38	4.20	+0.3
2023	23	MIX RAW	2 levels	73	0	74	321	58	30	8	0%	1.0	18.1%	9.3%	8.7%	2.5%	4.38	4.15	+0.3
2024	24	MIX MLE	3 levels	39	0	41	160	34	10	1	0%	1.0	19.4%	4.7%	14.7%	0.8%	3.10	2.48	+1.0
2024	24	MIX MLE	3 levels	39	0	41	160	34	10	1	0%	1.0	19.4%	4.7%	14.7%	0.8%	3.10	2.48	+1.0
2024	24	MIX RAW	3 levels	39	0	41	160	34	10	1	0%	1.0	21.2%	6.2%	15.0%	0.6%	3.10	2.49	+1.0
2025	25	MLB MLE	Washington Nationals	72	0	76	324	71	15	5	0%	1.1	21.9%	4.6%	17.3%	1.5%	4.48	2.68	+1.7
2025	25	MLB MLE	Washington Nationals	72	0	76	324	71	15	5	0%	1.1	21.9%	4.6%	17.3%	1.5%	4.48	2.68	+1.7
2025	25	MLB RAW	Washington Nationals	72	0	76	324	71	15	5	0%	1.1	21.9%	4.6%	17.3%	1.5%	4.48	2.68	+1.7
2026	26	MLB MLE	Seattle Mariners	73	0	65	295	54	18	7	0%	0.9	18.3%	6.1%	12.2%	2.4%	4.18	3.66	+0.7
2026	26	MLB MLE	Seattle Mariners	73	0	65	295	54	18	7	0%	0.9	18.3%	6.1%	12.2%	2.4%	4.18	3.66	+0.7
2026	26	MLB RAW	Seattle Mariners	73	0	65	295	54	18	7	0%	0.9	18.3%	6.1%	12.2%	2.4%	4.18	3.67	+0.7
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			215	0	207	890	175	50	17	0%	1.0	19.7%	5.6%	14.0%	1.9%	4.30	3.20	+3.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	SEA	56	0	59	249	53	13	6	0%	1.1	21.4%	5.2%	16.2%	2.4%	3.85	3.64	+0.7
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	SEA	44	0	46	195	42	10	5	0%	1.1	21.2%	5.3%	15.9%	2.5%	3.77	3.72	+0.5
2029	29	MLB MLE	SEA	35	0	37	156	32	9	4	0%	1.1	20.6%	5.5%	15.1%	2.6%	3.84	3.88	+0.3
2028	28	MLB CTX	SEA	42	0	44	186	39	10	5	0%	1.0	21.2%	5.3%	15.9%	2.5%	3.77	3.72	+0.4
2029	29	MLB CTX	SEA	33	0	35	148	31	8	4	0%	1.1	20.6%	5.5%	15.1%	2.6%	3.84	3.88	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		290	0	286	1224	245	68	26	0%	1.0	20.0%	5.6%	14.5%	2.1%	4.17	3.26	+4.4
/ 200 IP	—	RAW		203	0	200	856	171	48	18	0%	1.0	20.0%	5.6%	14.5%	2.1%	4.17	3.26	+3.1
Career	—	MLE		345	2	408	1742	352	123	32	1%	1.2	20.2%	7.1%	13.2%	1.8%	3.66	3.30	+4.1
/ 200 IP	—	MLE		169	1	200	853	172	60	16	1%	1.2	20.2%	7.1%	13.2%	1.8%	3.66	3.30	+2.8

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 AAARochester Red Wings · 40 IPFIP 4.11 → 4.25 (+0.13)K% 18.4% → 15.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.44%	—	×0.860	15.85%
BB% (unintentional) /BF	10.61%	—	×0.900	9.55%
HR / BF /BF	2.23%	÷1.058	×1.100	2.32%

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 4.11 → 4.25, 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 A+Wilmington Blue Rocks · 39 IPFIP 3.63 → 4.55 (+0.93)K% 28.3% → 21.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.29%	—	×0.770	21.78%
BB% (unintentional) /BF	5.92%	—	×1.150	6.81%
HR / BF /BF	3.95%	÷1.114	×1.250	4.43%

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 123).

Result: FIP 3.63 → 4.55, 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).

2022 AFredericksburg Nationals · 19 IPFIP 1.20 → 2.13 (+0.94)K% 33.8% → 25.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.80%	—	×0.740	25.01%
BB% (unintentional) /BF	1.41%	—	×1.180	1.66%
HR / BF /BF	1.41%	÷1.074	×1.300	1.71%

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 115).

Result: FIP 1.20 → 2.13, 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 AAHarrisburg Senators · 8 IPFIP 2.33 → 3.28 (+0.95)K% 33.3% → 27.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.810	27.00%
BB% (unintentional) /BF	3.03%	—	×1.100	3.33%
HR / BF /BF	3.03%	÷0.979	×1.200	3.71%

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 96).

Result: FIP 2.33 → 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).

2021 ROKFCL Nationals · 36 IPFIP 1.61 → 2.76 (+1.15)K% 30.7% → 20.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.72%	—	×0.680	20.89%
BB% (unintentional) /BF	5.88%	—	×1.250	7.35%
HR / BF /BF	0.65%	÷1.017	×1.400	0.90%

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 103).

Result: FIP 1.61 → 2.76, 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 ROKGCL Nationals · 22 IPFIP 2.70 → 3.82 (+1.13)K% 25.5% → 17.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.53%	—	×0.680	17.36%
BB% (unintentional) /BF	13.83%	—	×1.250	17.29%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Result: FIP 2.70 → 3.82, 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 ROKDSL Nationals · 30 IPFIP 0.88 → 2.16 (+1.28)K% 38.1% → 25.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.13%	—	×0.680	25.93%
BB% (unintentional) /BF	7.91%	—	×1.250	9.89%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Result: FIP 0.88 → 2.16, 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
Jose A. Ferrer (OGILVIE)	—	—	3.64	21.4%	5.2%	2.4%	—	3.79	21.0%	15.6%	83	+0.15	—	—	—
Aaron Fultz L 2001 · 3.62 FIP	27	SU	3.62	22.3%	6.0%	3.0%	.296	4.09	17.4%	9.2%	159	+0.47	3.46	480	73
James Pazos L 2018 · 3.21 FIP	27	SU	3.21	21.3%	6.6%	1.9%	.291	4.60	20.6%	9.4%	97	+1.39	2.55	261	71
Jose Mijares L 2012 · 2.79 FIP	27	SU	2.79	23.6%	7.4%	1.3%	.287	2.78	22.9%	16.1%	49	-0.01	2.78	249	69
Jesse Carlson L 2008 · 3.28 FIP	27	SU	3.28	23.2%	5.9%	2.5%	.216	4.00	16.8%	10.8%	81	+0.72	3.28	141	68
Steve Kline L 2000 · 3.72 FIP	27	SU	3.72	18.3%	7.2%	2.3%	.317	3.55	15.5%	7.4%	197	-0.17	3.06	682	67
John Grabow L 2006 · 3.66 FIP	27	SU	3.66	21.8%	8.9%	2.3%	.300	4.10	18.7%	8.3%	200	+0.44	3.66	471	66
Williams Jerez L 2019 · 3.58 FIP	27	SU	3.58	22.8%	7.1%	2.7%	.263	7.03	18.7%	7.0%	21	+3.45	3.58	364	65
Fernando Abad L 2013 · 3.23 FIP	27	SU	3.23	19.3%	6.0%	1.8%	.322	3.99	22.2%	14.5%	152	+0.76	2.37	486	65
Jeff Malm L 2016 · 3.13 FIP	25	SU	3.13	22.0%	7.2%	1.8%	.354	—	—	—	—	—	3.13	101	65
Adam Liberatore L 2015 · 3.64 FIP	28	SU	3.64	21.1%	7.3%	2.5%	.267	3.17	23.3%	15.2%	73	-0.47	2.38	124	65
Fabian Williamson L 2016 · 3.39 FIP	27	SU	3.39	23.8%	9.0%	2.1%	.259	5.26	16.5%	-3.3%	54	+1.87	3.39	154	64
Scott Stewart L 2003 · 3.87 FIP	27	SU	3.87	15.6%	4.8%	2.7%	.329	4.20	20.0%	14.6%	26	+0.33	2.60	181	64
Keegan Akin L 2022 · 3.57 FIP	27	SU	3.57	23.4%	6.1%	3.1%	.266	3.49	26.6%	18.7%	166	-0.08	2.62	743	64
Wesley Wright L 2012 · 3.03 FIP	27	SU	3.03	24.2%	7.6%	1.8%	.277	3.51	19.8%	11.6%	126	+0.48	3.03	375	64
Darin Downs L 2012 · 2.83 FIP	27	SU	2.83	23.3%	8.1%	1.2%	.293	3.64	19.8%	11.9%	86	+0.81	2.83	107	64
Jordan Jess L 2018 · 3.64 FIP	25	SU	3.64	19.3%	5.3%	2.7%	.315	—	—	—	—	—	3.39	136	64
Sean Burnett L 2010 · 2.50 FIP	27	SU	2.50	23.8%	6.1%	1.1%	.272	3.34	18.7%	13.3%	113	+0.84	2.48	430	63
Justin Wilson L 2015 · 2.49 FIP	27	SU	2.49	27.0%	8.2%	1.1%	.297	3.28	29.1%	18.1%	171	+0.79	2.49	554	63
Jason Gurka L 2015 · 3.15 FIP	27	SU	3.15	17.5%	7.0%	1.2%	.303	3.25	23.4%	17.6%	95	+0.10	2.82	183	63
Luis Perez L 2012 · 3.32 FIP	27	SU	3.32	22.3%	9.1%	1.7%	.299	4.00	15.2%	2.6%	66	+0.68	3.32	173	63

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	1.7	50	20.3%	5.8%	0.83	4.11
Mike Morin ('20)	1.1	46	20.3%	6.3%	0.83	4.57
Casey Janssen ('15)	2.7	59	17.7%	5.8%	0.88	3.63
Manny Corpas ('13)	1.9	53	16.6%	7.0%	0.91	4.14
Tony Castillo ('88-'98, 4 WAR*)	2.6	59	18.5%*	7.3%*	0.98*	3.76*
Donnie Moore ('75-'88, 7 WAR*)	3.3	60	20.7%*	6.6%*	1.00*	3.83*
Mike Perez ('90-'97, 3 WAR*)	1.7	58	18.5%*	8.2%*	0.88*	3.86*