JoJo Romero

P Milwaukee Brewers

Age 30 LHP 5'11" / 215 lbs MLB peak 0.3 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MLBSTL	65	0	59	3.36	3.95	21.0%	6.6%	0.4
2025	28	MLBSTL	65	0	61	2.07	2.90	21.6%	9.4%	1.2
2026	29	MIX2 levels	57	1	58	3.24	3.55	23.8%	7.0%	0.7	K 22.7% · BB 6.7% · FIP 3.57
2027PROJ	30	MLBMIL	49	0	51	3.90	4.06	22.3%	7.9%	0.3
2028PROJ95% MLB	31	MLBMIL	33	0	35	4.14	4.29	21.6%	8.3%	0.1
2029PROJ95% MLB	32	MLBMIL	23	0	24	4.38	4.55	20.8%	8.7%	0.0

Last 3 seasons WAR 2.3 · Next 3 projected WAR 0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%53

FB Velo48

xwOBA vs40

CompsRaul Valdes (age 32) · Matt Thornton (age 30) · Andrew Barbosa (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 95103vR 111

ERA3.90

FIP4.06

K%22.3%

BB%7.9%

K-BB%14.4%

Proj IP51

Value2027 · WAR

Runs saved vs league avg · 51 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL4545

CMD4545

K†5555

Statcast Percentiles

FB Velo

p4894.4

Whiff%

p2722.1%

p5322.7%

xwOBA vs

p400.323

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	20	MIX MLE	2 levels	23	23	129	510	128	36	4	100%	5.6	18.9%	8.2%	10.6%	1.1%	2.16	3.13	—
2017	20	MIX RAW	2 levels	23	23	129	510	128	36	4	100%	5.6	25.1%	7.1%	18.0%	0.8%	2.16	2.36	—
2018	21	AA MLE	Reading Fightin Phils	18	18	107	453	100	41	13	100%	5.9	17.9%	10.0%	7.9%	3.0%	3.80	4.48	—
2018	21	AA RAW	Reading Fightin Phils	18	18	107	453	100	41	13	100%	5.9	22.1%	9.1%	13.0%	2.9%	3.80	3.96	—
2019	22	MIX MLE	2 levels	24	24	111	498	92	46	12	100%	4.6	15.5%	9.8%	5.7%	2.9%	5.82	4.60	—
2019	22	MIX RAW	2 levels	24	24	111	498	92	46	12	100%	4.6	18.5%	9.2%	9.2%	2.4%	5.82	4.09	—
2020	23	MLB MLE	Philadelphia Phillies	12	0	11	47	10	2	1	0%	0.9	21.3%	4.3%	17.0%	2.1%	7.59	3.01	+0.2
2020	23	MLB RAW	Philadelphia Phillies	12	0	11	47	10	2	1	0%	0.9	21.3%	4.3%	17.0%	2.1%	7.59	3.01	+0.2
2021	24	MLB MLE	Philadelphia Phillies	11	0	9	44	8	3	4	0%	0.8	18.2%	6.8%	11.4%	9.1%	7.00	7.42	-0.3
2021	24	MLB RAW	Philadelphia Phillies	11	0	9	44	8	3	4	0%	0.8	18.2%	6.8%	11.4%	9.1%	7.00	8.10	-0.4
2022	25	MIX MLE	5 levels	32	3	31	127	37	12	3	9%	1.0	25.4%	14.9%	10.4%	4.8%	3.16	5.49	-0.3
2022	25	MIX RAW	5 levels	32	3	31	127	37	12	3	9%	1.0	29.1%	9.4%	19.7%	2.4%	3.16	3.13	+0.5
2023	26	MIX MLE	2 levels	44	0	58	235	75	19	4	0%	1.3	29.9%	7.7%	22.2%	1.9%	3.43	2.60	+1.3
2023	26	MIX RAW	2 levels	44	0	58	235	75	19	4	0%	1.3	31.9%	8.1%	23.8%	1.7%	3.43	2.39	+1.5
2024	27	MLB MLE	St. Louis Cardinals	65	0	59	243	51	16	8	0%	0.9	21.0%	6.6%	14.4%	3.5%	3.36	4.10	+0.3
2024	27	MLB MLE	St. Louis Cardinals	65	0	59	243	51	16	8	0%	0.9	21.0%	6.6%	14.4%	3.5%	3.36	4.10	+0.3
2024	27	MLB RAW	St. Louis Cardinals	65	0	59	243	51	16	8	0%	0.9	21.0%	6.6%	14.4%	3.3%	3.36	3.95	+0.4
2025	28	MLB MLE	St. Louis Cardinals	65	0	61	255	55	24	2	0%	0.9	21.6%	9.4%	12.2%	0.8%	2.07	2.93	+1.2
2025	28	MLB MLE	St. Louis Cardinals	65	0	61	255	55	24	2	0%	0.9	21.6%	9.4%	12.2%	0.8%	2.07	2.93	+1.2
2025	28	MLB RAW	St. Louis Cardinals	65	0	61	255	55	24	2	0%	0.9	21.6%	9.4%	12.2%	0.8%	2.07	2.90	+1.2
2026	29	MIX MLE	2 levels	57	1	58	244	58	17	7	2%	1.0	22.7%	6.7%	16.0%	2.8%	3.24	3.57	+0.7
2026	29	MIX MLE	2 levels	57	1	58	244	58	17	7	2%	1.0	22.7%	6.7%	16.0%	2.8%	3.24	3.57	+0.7
2026	29	MIX RAW	2 levels	57	1	58	244	58	17	7	2%	1.0	23.8%	7.0%	16.8%	2.9%	3.24	3.55	+0.7
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			252	0	249	1041	237	81	26	0%	1.0	22.8%	7.8%	15.0%	2.5%	3.51	3.53	+3.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	MIL	49	0	51	215	48	17	6	0%	1.0	22.3%	7.9%	14.4%	2.7%	3.90	4.06	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	MIL	35	0	36	154	33	13	4	0%	1.0	21.6%	8.3%	13.3%	2.9%	4.14	4.29	+0.1
2029	32	MLB MLE	MIL	24	0	26	108	22	9	3	0%	1.1	20.8%	8.7%	12.1%	3.1%	4.38	4.55	0.0
2030	33	MLB MLE	MIL	16	0	17	73	14	7	2	0%	1.1	19.9%	9.1%	10.8%	3.4%	4.65	4.83	-0.1
2028	31	MLB CTX	MIL	33	0	35	148	32	12	4	0%	1.1	21.6%	8.3%	13.3%	2.9%	4.14	4.29	+0.1
2029	32	MLB CTX	MIL	23	0	24	101	21	9	3	0%	1.0	20.8%	8.7%	12.1%	3.1%	4.38	4.55	0.0
2030	33	MLB CTX	MIL	15	0	16	68	13	6	2	0%	1.1	19.9%	9.1%	10.8%	3.4%	4.65	4.83	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		324	0	324	1359	304	108	36	0%	1.0	22.3%	8.0%	14.4%	2.6%	3.70	3.67	+3.4
/ 200 IP	—	RAW		200	0	200	838	188	67	22	0%	1.0	22.3%	8.0%	14.4%	2.6%	3.70	3.67	+2.1
Career	—	MLE		351	69	634	2656	536	234	66	20%	1.8	20.2%	8.8%	11.4%	2.5%	3.61	3.88	+3.1
/ 200 IP	—	MLE		111	22	200	838	169	74	21	20%	1.8	20.2%	8.8%	11.4%	2.5%	3.61	3.88	+1.9

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 AAAMemphis Redbirds · 21 IPFIP 3.10 → 3.70 (+0.60)K% 37.5% → 32.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.50%	—	×0.860	32.25%
BB% (unintentional) /BF	10.23%	—	×0.900	9.20%
HR / BF /BF	3.41%	÷0.955	×1.100	3.93%

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 91).

Result: FIP 3.10 → 3.70, 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 AAAMemphis Redbirds · 7 IPFIP 0.40 → 0.72 (+0.32)K% 32.0% → 28.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.00%	—	×0.880	28.16%
BB% (unintentional) /BF	0.00%	—	×1.050	0.00%
HR / BF /BF	0.00%	÷1.048	×1.100	0.00%

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 110).

Result: FIP 0.40 → 0.72, 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 AAALehigh Valley IronPigs · 54 IPFIP 5.14 → 5.83 (+0.69)K% 15.3% → 13.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.33%	—	×0.880	13.49%
BB% (unintentional) /BF	13.03%	—	×1.050	13.68%
HR / BF /BF	3.07%	÷0.866	×1.100	3.89%

Result: FIP 5.14 → 5.83, 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 AAReading Fightin Phils · 58 IPFIP 2.81 → 3.25 (+0.43)K% 21.9% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.94%	—	×0.810	17.77%
BB% (unintentional) /BF	5.06%	—	×1.100	5.57%
HR / BF /BF	1.69%	÷1.182	×1.200	1.71%

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 136).

Result: FIP 2.81 → 3.25, 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).

2018 AAReading Fightin Phils · 107 IPFIP 3.96 → 4.48 (+0.52)K% 22.1% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.08%	—	×0.810	17.88%
BB% (unintentional) /BF	9.05%	—	×1.100	9.96%
HR / BF /BF	2.87%	÷1.164	×1.200	2.96%

Result: FIP 3.96 → 4.48, 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).

2017 ALakewood BlueClaws · 77 IPFIP 2.13 → 3.06 (+0.93)K% 26.3% → 19.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.33%	—	×0.740	19.49%
BB% (unintentional) /BF	7.00%	—	×1.180	8.26%
HR / BF /BF	0.67%	÷0.854	×1.300	1.02%

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 71).

Result: FIP 2.13 → 3.06, 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).

2017 A+Clearwater Threshers · 52 IPFIP 2.56 → 3.24 (+0.68)K% 23.3% → 18.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.33%	—	×0.770	17.97%
BB% (unintentional) /BF	7.14%	—	×1.150	8.21%
HR / BF /BF	0.95%	÷1.058	×1.250	1.13%

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 112).

Result: FIP 2.56 → 3.24, 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
JoJo Romero (OGILVIE)	—	—	4.06	22.3%	7.9%	2.7%	—	4.49	21.0%	12.4%	79	+0.43	—	—	—
Raul Valdes L 2010 · 4.02 FIP	32	SU	4.02	21.4%	9.9%	2.7%	.301	3.14	27.4%	22.5%	78	-0.88	2.29	160	76
Matt Thornton L 2007 · 3.13 FIP	30	SU	3.13	22.1%	8.0%	1.6%	.324	2.19	30.7%	24.4%	200	-0.94	1.71	663	75
Andrew Barbosa L 2017 · 4.67 FIP	29	SU	4.67	20.2%	9.6%	3.8%	.301	—	—	—	—	—	2.70	175	72
Brian Fuentes L 2006 · 3.47 FIP	30	SU	3.47	26.6%	8.0%	2.9%	.246	3.22	24.6%	15.8%	179	-0.25	2.08	602	71
Brian Tallet L 2008 · 3.36 FIP	30	SU	3.36	19.6%	7.9%	1.7%	.282	5.06	16.0%	6.3%	251	+1.70	2.59	443	71
Nick Hagadone L 2015 · 3.65 FIP	29	SU	3.65	22.6%	8.9%	2.4%	.329	3.74	22.6%	13.3%	33	+0.09	2.97	141	71
Armando Almanza L 2003 · 4.95 FIP	30	SU	4.95	21.3%	10.0%	4.3%	.331	5.29	24.1%	14.8%	12	+0.34	2.90	211	70
Tommy Phelps L 2004 · 4.80 FIP	30	SW	4.80	19.4%	8.3%	4.2%	.286	3.98	13.2%	5.7%	23	-0.82	3.39	120	70
Hideki Okajima L 2007 · 3.05 FIP	31	SU	3.05	23.2%	5.5%	2.2%	.234	3.87	20.2%	12.6%	169	+0.82	3.05	238	69
Doug Slaten L 2010 · 3.22 FIP	30	SU	3.22	20.7%	9.8%	1.1%	.269	4.85	13.5%	3.1%	29	+1.63	3.22	139	69
Daniel Rodriguez L 2015 · 2.89 FIP	30	SU	2.89	20.2%	9.4%	0.6%	.256	4.17	16.3%	5.9%	234	+1.28	2.89	391	69
Arturo Barradas L 2017 · 3.42 FIP	29	SU	3.42	18.1%	7.0%	1.8%	.288	3.24	16.1%	9.5%	34	-0.18	3.24	163	69
Jack Taschner L 2008 · 4.09 FIP	30	SU	4.09	17.2%	9.7%	2.2%	.323	4.73	15.2%	3.0%	49	+0.64	3.14	189	68
Pedro Feliciano L 2007 · 3.07 FIP	30	SU	3.07	22.2%	9.8%	1.1%	.239	3.28	21.8%	14.5%	175	+0.21	2.69	378	68
Buddy Boshers L 2018 · 3.22 FIP	30	SU	3.22	22.9%	6.6%	2.2%	.314	3.73	25.3%	14.9%	55	+0.51	2.76	239	68
Yuki Matsui L 2024 · 3.63 FIP	28	SU	3.63	26.8%	8.9%	3.0%	.242	4.25	23.9%	12.6%	140	+0.62	3.63	203	68
Jeff Ibarra L 2017 · 3.64 FIP	29	SU	3.64	18.1%	7.0%	2.1%	.342	2.85	20.6%	17.2%	29	-0.79	2.85	101	68
Sammy Solís L 2019 · 4.05 FIP	30	SU	4.05	26.2%	8.9%	3.7%	.291	—	—	—	—	—	2.51	190	68
Scott Downs L 2006 · 3.97 FIP	30	SU	3.97	18.7%	7.3%	2.8%	.275	2.95	21.5%	14.2%	175	-1.02	2.68	748	68
Brian Moran L 2019 · 3.40 FIP	30	SU	3.40	26.9%	10.0%	2.4%	.269	2.99	25.5%	18.5%	99	-0.41	1.80	421	67

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	1.9	47	22.3%	8.5%	1.02	3.73
Fernando Salas ('19)	2.4	54	23.1%	7.3%	1.05	3.91
Ryan Tepera ('23)	1.8	52	24.3%	8.8%	1.13	3.62
David Carpenter ('19)	1.1	43	23.5%	8.4%	0.92	3.69
Mike Perez ('90-'97, 3 WAR*)	1.7	58	18.5%*	8.2%*	0.88*	3.86*
Carlos Diaz ('82-'86, 2 WAR*)	1.3	52	25.1%*	8.7%*	0.91*	3.84*
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*