Orlando Ribalta

P Washington Nationals

Age 29 RHP 6'7" / 245 lbs MLB

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MIX3 levels	55	58	3.43	3.22	31.9%	13.5%	0.9	K 28.3% · BB 13.3% · FIP 3.76
2025	27	MIX3 levels	31	33	5.67	5.80	20.8%	13.6%	-0.5	K 20.8% · BB 14.2% · FIP 5.88
2026	28	MIX2 levels	54	51	3.53	3.69	23.6%	10.1%	0.5	K 23.6% · BB 10.1% · FIP 3.93
2027PROJ	29	MLBWSH	31	33	4.77	4.88	24.6%	13.3%	-0.1
2028PROJ86% MLB	30	MLBWSH	24	25	4.90	5.03	23.8%	13.2%	-0.1
2029PROJ89% MLB	31	MLBWSH	18	19	5.06	5.21	23.0%	13.2%	-0.1

Last 3 seasons WAR 0.9 · 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

FB Velo84

xwOBA vs66

K%58

CompsShintaro Fujinami (age 29) · Pedro Báez (age 29) · Jake Cousins (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 115107vR 99

ERA4.77

FIP4.88

K%24.6%

BB%13.3%

K-BB%11.3%

Proj IP40

Value2027 · WAR

Runs saved vs league avg · 40 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL2525

CMD3535

K†6060

Statcast Percentiles

FB Velo

p8496.9

Whiff%

p5926.7%

p5823.6%

xwOBA vs

p660.296

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)
2019	21	ROK MLE	GCL Nationals	9	0	17	75	19	13	1	0%	1.9	17.2%	21.7%	-4.4%	1.9%	3.18	5.41	—
2019	21	ROK RAW	GCL Nationals	9	0	17	75	19	13	1	0%	1.9	25.3%	17.3%	8.0%	1.3%	3.18	3.92	—
2021	23	ROK MLE	FCL Nationals	11	0	17	73	17	7	1	0%	1.5	15.8%	12.0%	3.8%	1.9%	4.24	4.32	—
2021	23	ROK RAW	FCL Nationals	11	0	17	73	17	7	1	0%	1.5	23.3%	9.6%	13.7%	1.4%	4.24	3.10	—
2022	24	MIX MLE	2 levels	36	0	50	215	54	27	5	0%	1.4	18.9%	14.7%	4.2%	2.8%	3.40	4.89	—
2022	24	MIX RAW	2 levels	36	0	50	215	54	27	5	0%	1.4	25.1%	12.6%	12.6%	2.3%	3.40	3.85	—
2023	25	MIX MLE	5 levels	27	0	35	147	36	12	2	0%	1.3	16.7%	9.6%	7.2%	2.3%	3.89	4.18	—
2023	25	MIX RAW	5 levels	27	0	35	147	36	12	2	0%	1.3	24.5%	8.2%	16.3%	1.4%	3.89	2.81	—
2024	26	MIX MLE	3 levels	55	0	58	251	80	34	5	0%	1.0	28.3%	13.3%	15.0%	2.5%	3.43	3.76	+0.5
2024	26	MIX MLE	3 levels	55	0	58	251	80	34	5	0%	1.0	28.3%	13.3%	15.0%	2.5%	3.43	3.76	+0.5
2024	26	MIX RAW	3 levels	55	0	58	251	80	34	5	0%	1.0	31.9%	13.5%	18.3%	2.0%	3.43	3.22	+0.9
2025	27	MIX MLE	3 levels	31	0	33	154	32	21	7	0%	1.1	20.8%	14.2%	6.7%	5.0%	5.67	5.88	-0.5
2025	27	MIX MLE	3 levels	31	0	33	154	32	21	7	0%	1.1	20.8%	14.2%	6.7%	5.0%	5.67	5.88	-0.5
2025	27	MIX RAW	3 levels	31	0	33	154	32	21	7	0%	1.1	20.8%	13.6%	7.1%	4.5%	5.67	5.80	-0.5
2026	28	MIX MLE	2 levels	54	0	51	208	49	21	5	0%	0.9	23.6%	10.1%	13.5%	2.8%	3.53	3.93	+0.4
2026	28	MIX MLE	2 levels	54	0	51	208	49	21	5	0%	0.9	23.6%	10.1%	13.5%	2.8%	3.53	3.93	+0.4
2026	28	MIX RAW	2 levels	54	0	51	208	49	21	5	0%	0.9	23.6%	10.1%	13.5%	2.4%	3.53	3.69	+0.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			71	0	71	321	70	37	11	0%	1.0	21.8%	11.5%	10.3%	3.4%	5.35	4.71	-0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	WSH	31	0	33	139	34	18	5	0%	1.1	24.6%	13.3%	11.3%	3.3%	4.77	4.88	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	WSH	28	0	30	125	30	16	4	0%	1.1	23.8%	13.2%	10.6%	3.4%	4.90	5.03	-0.2
2029	31	MLB MLE	WSH	20	0	21	89	20	12	3	0%	1.1	23.0%	13.2%	9.8%	3.6%	5.06	5.21	-0.2
2028	30	MLB CTX	WSH	24	0	25	106	25	14	4	0%	1.0	23.8%	13.2%	10.6%	3.4%	4.90	5.03	-0.1
2029	31	MLB CTX	WSH	18	0	19	80	18	11	3	0%	1.1	23.0%	13.2%	9.8%	3.6%	5.06	5.21	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		113	0	115	507	114	62	18	0%	1.0	22.4%	12.1%	10.3%	3.5%	5.20	4.65	-0.1
/ 200 IP	—	RAW		197	0	200	884	199	108	31	0%	1.0	22.4%	12.1%	10.3%	3.5%	5.20	4.65	-0.2
Career	—	MLE		223	0	261	1123	242	147	32	0%	1.2	21.5%	13.1%	8.5%	2.8%	3.83	4.50	-0.5
/ 200 IP	—	MLE		171	0	200	861	185	113	24	0%	1.2	21.5%	13.1%	8.5%	2.8%	3.83	4.50	-0.8

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.

2026 AAARochester Red Wings · 8 IPFIP 2.40 → 2.55 (+0.15)K% 23.3% → 20.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.33%	—	×0.860	20.07%
BB% (unintentional) /BF	10.00%	—	×0.900	9.00%
HR / BF /BF	0.00%	÷1.000	×1.100	0.00%

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 100).

Result: FIP 2.40 → 2.55, 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).

2025 AAARochester Red Wings · 7 IPFIP 4.19 → 4.66 (+0.47)K% 22.2% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.22%	—	×0.860	19.11%
BB% (unintentional) /BF	7.41%	—	×0.900	6.67%
HR / BF /BF	3.70%	÷0.960	×1.100	4.25%

Result: FIP 4.19 → 4.66, 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 AAARochester Red Wings · 36 IPFIP 4.01 → 4.32 (+0.31)K% 28.7% → 24.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.66%	—	×0.860	24.65%
BB% (unintentional) /BF	15.29%	—	×0.900	13.76%
HR / BF /BF	2.55%	÷0.986	×1.100	2.84%

Result: FIP 4.01 → 4.32, 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 AAHarrisburg Senators · 18 IPFIP 1.49 → 2.52 (+1.03)K% 45.1% → 36.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	45.07%	—	×0.810	36.51%
BB% (unintentional) /BF	11.27%	—	×1.100	12.39%
HR / BF /BF	1.41%	÷0.990	×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 98).

Result: FIP 1.49 → 2.52, 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 AAHarrisburg Senators · 21 IPFIP 3.65 → 4.18 (+0.53)K% 20.7% → 16.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.65%	—	×0.810	16.73%
BB% (unintentional) /BF	8.70%	—	×1.100	9.57%
HR / BF /BF	2.17%	÷1.115	×1.200	2.34%

Result: FIP 3.65 → 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).

2023 A+Wilmington Blue Rocks · 6 IPFIP 1.09 → 2.01 (+0.92)K% 38.1% → 29.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.10%	—	×0.770	29.33%
BB% (unintentional) /BF	9.52%	—	×1.150	10.95%
HR / BF /BF	0.00%	÷0.913	×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 83).

Result: FIP 1.09 → 2.01, 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).

2022 AFredericksburg Nationals · 34 IPFIP 4.34 → 5.45 (+1.11)K% 22.6% → 16.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.60%	—	×0.740	16.73%
BB% (unintentional) /BF	13.01%	—	×1.180	15.36%
HR / BF /BF	2.74%	÷1.074	×1.300	3.32%

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 4.34 → 5.45, 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 · 16 IPFIP 2.79 → 3.70 (+0.91)K% 30.4% → 23.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.43%	—	×0.770	23.43%
BB% (unintentional) /BF	11.59%	—	×1.150	13.33%
HR / BF /BF	1.45%	÷1.114	×1.250	1.63%

Result: FIP 2.79 → 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).

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
Orlando Ribalta (OGILVIE)	—	—	4.88	24.6%	13.3%	3.3%	—	5.11	23.5%	10.3%	51	+0.23	—	—	—
Shintaro Fujinami R 2023 · 4.09 FIP	29	SU	4.09	23.2%	12.3%	2.5%	.290	4.49	22.0%	0.2%	51	+0.40	4.09	130	82
Pedro Báez R 2017 · 4.08 FIP	29	SU	4.08	22.9%	9.6%	3.1%	.261	3.18	24.7%	16.1%	143	-0.90	2.29	356	76
Jake Cousins R 2023 · 4.38 FIP	29	SU	4.38	27.3%	11.4%	3.9%	.379	3.42	34.2%	21.9%	38	-0.96	1.11	160	74
Jose Veras R 2010 · 4.10 FIP	29	SU	4.10	26.9%	14.4%	2.6%	.239	3.42	25.3%	14.8%	201	-0.68	3.37	422	74
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	73
Jason Bulger R 2008 · 4.60 FIP	29	SU	4.60	27.4%	12.3%	4.1%	.293	3.94	25.1%	13.3%	90	-0.66	3.78	106	73
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	73
Coleman Huntley III R 2022 · 4.05 FIP	29	SU	4.05	24.4%	10.9%	3.0%	.311	2.38	20.9%	12.6%	25	-1.67	2.38	160	71
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	71
Jacob Barnes R 2019 · 5.09 FIP	29	SU	5.09	21.9%	10.0%	4.7%	.303	3.54	23.1%	15.1%	101	-1.55	1.84	551	70
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	70
Joe Colón J R 2017 · 4.25 FIP	27	SU	4.25	20.4%	12.1%	2.4%	.315	—	—	—	—	—	3.27	113	70
Brandon Cunniff R 2017 · 4.79 FIP	28	SU	4.79	20.1%	11.6%	3.5%	.275	6.80	13.9%	-1.9%	30	+2.01	3.89	180	70
Ray Black R 2019 · 4.89 FIP	29	SU	4.89	30.8%	13.2%	5.0%	.275	—	—	—	—	—	2.95	150	70
Cody Hall R 2017 · 4.03 FIP	29	SU	4.03	26.8%	10.0%	3.5%	.299	3.92	25.9%	8.4%	19	-0.11	3.51	134	70
Gregory Infante R 2016 · 4.47 FIP	29	SU	4.47	19.0%	12.3%	2.6%	.333	3.43	22.5%	15.8%	120	-1.04	2.97	230	69
Cole McDonald R 2024 · 5.01 FIP	27	SU	5.01	20.9%	12.7%	3.8%	.281	—	—	—	—	—	2.81	153	69
Hunter Strickland R 2018 · 4.22 FIP	29	SU	4.22	18.4%	9.5%	2.7%	.271	4.48	22.0%	13.3%	83	+0.26	2.30	523	69
Jose Cuas R 2023 · 4.13 FIP	29	SU	4.13	24.3%	12.0%	2.9%	.309	3.75	21.7%	9.4%	133	-0.38	2.71	345	69
José Ramírez R 2017 · 4.56 FIP	27	SU	4.56	21.7%	10.9%	3.5%	.218	—	—	—	—	—	3.36	206	69

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	0.8	32	23.0%	12.5%	1.32	5.09
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*
Tim Byrdak ('13)	1.7	42	21.4%	13.3%	1.22	4.35
Amir Garrett ('24)	1.7	55	26.7%	13.3%	1.52	4.95
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*