Jordany Ventura

P Somerset Patriots

Age 27 RHP 6'0" / 195 lbs AA

Overview

AAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	23	MIX2 levels	25	23	103	4.81	4.09	22.5%	17.6%	—	K 16.9% · BB 20.5% · FIP 4.89
2024	24	MIX3 levels	22	4	49	2.96	3.41	27.0%	9.8%	—	K 20.3% · BB 11.6% · FIP 4.46
2025	25	MIX2 levels	30	0	34	3.93	4.15	24.6%	21.0%	—	K 19.5% · BB 23.5% · FIP 4.82
2026	26	No MLB games played
2027PROJ	27	MLBNYY	—	—	0	5.43	5.43	21.0%	17.2%	—
2028PROJ38% MLB	28	MLBNYY	6	0	6	5.37	5.40	21.1%	16.5%	-0.1

Next 2 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsGrant Black (age 27) · Brian Keller (age 27) · Ben Gross (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 136128vR 120

ERA5.43

FIP5.43

K%21.0%

BB%17.2%

K-BB%3.8%

Proj IP21

Value2027 · WAR

Runs saved vs league avg · 21 IP

Grades · Contract

Scouting Grades

K†5050

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 Mets 2	3	1	7	32	3	6	0	33%	2.2	9.4%	18.8%	-9.4%	0.0%	0.00	4.68	—
2018	18	ROK RAW	DSL Mets 2	3	1	7	32	3	6	0	33%	2.2	9.4%	18.8%	-9.4%	0.0%	0.00	4.90	—
2019	19	ROK MLE	GCL Mets	13	11	44	182	45	13	3	85%	3.4	16.8%	8.9%	7.9%	2.3%	4.26	4.08	—
2019	19	ROK RAW	GCL Mets	13	11	44	182	45	13	3	85%	3.4	24.7%	7.1%	17.6%	1.6%	4.26	2.83	—
2022	22	MIX MLE	2 levels	4	4	9	35	13	2	0	100%	2.2	37.1%	5.7%	31.4%	0.0%	4.15	0.69	—
2022	22	MIX RAW	2 levels	4	4	9	35	13	2	0	100%	2.2	37.1%	5.7%	31.4%	0.0%	4.15	0.79	—
2023	23	MIX MLE	2 levels	25	23	103	472	106	83	5	92%	4.1	16.9%	20.5%	-3.6%	1.1%	4.81	4.89	—
2023	23	MIX RAW	2 levels	25	23	103	472	106	83	5	92%	4.1	22.5%	17.6%	4.9%	1.1%	4.81	4.09	—
2024	24	MIX MLE	3 levels	22	4	49	204	55	20	5	18%	2.2	20.3%	11.6%	8.8%	2.9%	2.96	4.46	—
2024	24	MIX MLE	3 levels	22	4	49	204	55	20	5	18%	2.2	20.3%	11.6%	8.8%	2.9%	2.96	4.46	—
2024	24	MIX RAW	3 levels	22	4	49	204	55	20	5	18%	2.2	27.0%	9.8%	17.2%	2.5%	2.96	3.41	—
2025	25	MIX MLE	2 levels	30	0	34	167	41	35	1	0%	1.1	19.5%	23.5%	-4.1%	0.7%	3.93	4.82	—
2025	25	MIX MLE	2 levels	30	0	34	167	41	35	1	0%	1.1	19.5%	23.5%	-4.1%	0.7%	3.93	4.82	—
2025	25	MIX RAW	2 levels	30	0	34	167	41	35	1	0%	1.1	24.6%	21.0%	3.6%	0.6%	3.93	4.15	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	NYY	—	—	0	—	—	—	—	—	—	21.0%	17.2%	3.8%	2.8%	5.43	5.43	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	NYY	14	0	15	64	14	11	2	0%	1.1	21.1%	16.5%	4.6%	2.9%	5.37	5.40	-0.1
2028	28	MLB CTX	NYY	6	0	6	25	5	4	1	0%	1.0	21.1%	16.5%	4.6%	2.9%	5.37	5.40	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		5	0	6	24	5	4	1	0%	1.1	21.1%	16.5%	4.6%	2.9%	5.37	5.02	-0.0
/ 200 IP	—	RAW		190	0	200	844	175	140	35	0%	1.1	21.1%	16.5%	4.6%	2.9%	5.37	5.02	-1.1
Career	—	MLE		97	43	246	1092	200	184	17	44%	2.5	18.4%	16.9%	1.5%	1.5%	4.07	4.52	-0.1
/ 200 IP	—	MLE		79	35	200	889	163	150	14	44%	2.5	18.4%	16.9%	1.5%	1.5%	4.07	4.52	-2.0

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 AASomerset Patriots · 21 IPFIP 4.12 → 4.83 (+0.71)K% 23.2% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.23%	—	×0.810	18.82%
BB% (unintentional) /BF	19.19%	—	×1.100	21.11%
HR / BF /BF	1.01%	÷1.030	×1.200	1.18%

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 106).

Result: FIP 4.12 → 4.83, 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).

2025 A+Hudson Valley Renegades · 14 IPFIP 3.85 → 4.81 (+0.96)K% 26.5% → 20.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.47%	—	×0.770	20.38%
BB% (unintentional) /BF	23.53%	—	×1.150	27.06%
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 3.85 → 4.81, 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 A+Brooklyn Cyclones · 37 IPFIP 3.87 → 4.46 (+0.59)K% 26.4% → 20.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.42%	—	×0.770	20.34%
BB% (unintentional) /BF	10.06%	—	×1.150	11.57%
HR / BF /BF	3.14%	÷1.341	×1.250	2.93%

Result: FIP 3.87 → 4.46, 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 AABinghamton Rumble Ponies · 9 IPFIP 1.89 → 2.54 (+0.65)K% 31.4% → 25.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.43%	—	×0.810	25.46%
BB% (unintentional) /BF	11.43%	—	×1.100	12.57%
HR / BF /BF	0.00%	÷0.834	×1.200	0.00%

Result: FIP 1.89 → 2.54, 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 ASt. Lucie Mets · 54 IPFIP 4.43 → 5.39 (+0.96)K% 23.1% → 17.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.08%	—	×0.740	17.08%
BB% (unintentional) /BF	19.23%	—	×1.180	22.69%
HR / BF /BF	1.54%	÷1.274	×1.300	1.57%

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 155).

Result: FIP 4.43 → 5.39, 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+Brooklyn Cyclones · 49 IPFIP 3.50 → 4.26 (+0.77)K% 21.7% → 16.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.70%	—	×0.770	16.71%
BB% (unintentional) /BF	15.57%	—	×1.150	17.90%
HR / BF /BF	0.47%	÷1.054	×1.250	0.56%

Result: FIP 3.50 → 4.26, 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 ASt. Lucie Mets · 7 IPFIP 1.06 → 1.98 (+0.91)K% 34.5% → 25.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.48%	—	×0.740	25.52%
BB% (unintentional) /BF	6.90%	—	×1.180	8.14%
HR / BF /BF	0.00%	÷0.949	×1.300	0.00%

Result: FIP 1.06 → 1.98, 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 Mets · 44 IPFIP 2.82 → 4.08 (+1.26)K% 24.7% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.73%	—	×0.680	16.81%
BB% (unintentional) /BF	7.14%	—	×1.250	8.93%
HR / BF /BF	1.65%	÷1.000	×1.400	2.31%

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 2.82 → 4.08, 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
Jordany Ventura (OGILVIE)	—	—	5.43	21.0%	17.2%	2.8%	—	5.40	21.1%	4.6%	15	-0.03	—	—	—
Grant Black R 2021 · 4.46 FIP	27	SW	4.46	19.0%	13.9%	2.2%	.327	5.35	15.0%	3.8%	156	+0.89	4.46	215	74
Brian Keller R 2021 · 4.23 FIP	27	SW	4.23	22.6%	19.1%	1.1%	.288	3.67	23.6%	12.0%	113	-0.56	1.89	613	71
Ben Gross R 2022 · 4.85 FIP	25	SW	4.85	17.6%	15.6%	2.3%	.303	—	—	—	—	—	4.05	118	71
Shawn Dubin R 2023 · 4.87 FIP	27	SP-	4.87	20.0%	12.9%	3.3%	.292	3.97	21.8%	11.4%	79	-0.90	3.02	341	70
Colby Morris R 2022 · 5.76 FIP	25	SW	5.76	16.2%	11.8%	4.6%	.268	—	—	—	—	—	4.11	105	69
Dustin Antolin R 2017 · 4.35 FIP	27	SW	4.35	16.2%	14.4%	1.4%	.368	—	—	—	—	—	2.95	159	69
Jeremy Guthrie R 2006 · 4.92 FIP	27	SU	4.92	15.1%	15.1%	2.1%	.349	4.57	14.8%	8.1%	566	-0.35	4.08	1,834	68
Cameron Foster R 2024 · 4.83 FIP	25	SW	4.83	17.4%	11.5%	3.2%	.321	3.09	25.5%	17.5%	60	-1.74	2.50	213	68
Tyler Yates R 2004 · 4.47 FIP	26	SW	4.47	15.4%	9.6%	2.6%	.333	3.64	22.5%	13.5%	116	-0.83	3.23	248	68
Paul Clemens R 2015 · 5.37 FIP	27	SP-	5.37	14.3%	14.1%	3.1%	.310	4.62	16.9%	7.3%	200	-0.75	4.58	345	68
Keyvius Sampson R 2017 · 5.08 FIP	26	SP-	5.08	19.6%	16.4%	2.8%	.333	—	—	—	—	—	4.10	316	67
Noah Denoyer R 2023 · 5.24 FIP	25	SW	5.24	22.2%	14.0%	4.1%	.306	—	—	—	—	—	3.26	181	67
Ariel Peña R 2016 · 6.26 FIP	27	SW	6.26	16.2%	17.7%	4.2%	.379	4.57	21.8%	6.0%	75	-1.69	3.74	223	66
Deylen Miley R 2023 · 5.34 FIP	25	SP-	5.34	22.3%	17.5%	3.5%	.336	—	—	—	—	—	2.07	185	66
Carlos Torres R 2010 · 4.50 FIP	27	SW	4.50	18.3%	11.3%	2.8%	.438	3.89	20.1%	13.2%	139	-0.61	2.89	604	66
Tyler Davis R 2024 · 6.02 FIP	25	SU	6.02	21.0%	18.8%	4.2%	.317	3.78	21.9%	10.2%	111	-2.24	3.20	137	66
Fernando Baez R 2017 · 5.37 FIP	25	SU	5.37	24.3%	21.2%	3.0%	.271	—	—	—	—	—	3.45	129	65
Jake Stinnett R 2019 · 4.23 FIP	27	SW	4.23	21.1%	12.2%	2.5%	.301	—	—	—	—	—	2.88	356	65
Taylor Grover R 2017 · 4.93 FIP	26	SW	4.93	20.0%	10.9%	3.9%	.320	4.89	16.2%	8.9%	14	-0.04	3.68	239	65
Brian Glowicki R 2022 · 5.39 FIP	27	SU	5.39	18.2%	15.9%	3.3%	.229	—	—	—	—	—	2.31	189	65