Yadiel Batista

P Palm Beach Cardinals

Age 23 LHP 6'3" / 170 lbs A peak 0.1 · 2030

Overview

APROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	20	ROKSTL	11	10	46	3.88	3.32	22.8%	8.1%	—	K 15.5% · BB 10.2% · FIP 4.67
2025	21	MIX2 levels	19	5	75	4.22	3.34	20.0%	7.0%	—	K 14.0% · BB 8.4% · FIP 4.30
2026	22	ASTL	33	1	65	4.71	3.59	19.6%	7.7%	—	K 14.5% · BB 9.1% · FIP 4.53
2027PROJ	23	MLBSTL	—	—	0	5.12	5.12	13.4%	9.2%	—
2028PROJ43% MLB	24	MLBSTL	25	0	26	4.95	4.89	15.6%	8.9%	-0.1
2029PROJ66% MLB	25	MLBSTL	29	0	30	4.82	4.76	16.9%	8.8%	-0.1

Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff35Control55Command45

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsEstevan Gonzalez (age 23) · Matt Crouse (age 25) · Jake Drehoff (age 23)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 114122vR 130

ERA5.12

FIP5.12

K%13.4%

BB%9.2%

K-BB%4.2%

Proj IP62

Value2027 · WAR

Runs saved vs league avg · 62 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL5555

CMD4545

K†3040

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)
2023	19	ROK MLE	DSL Cardinals	10	9	39	152	37	2	2	90%	3.9	16.6%	1.6%	14.9%	2.0%	3.96	3.00	—
2023	19	ROK RAW	DSL Cardinals	10	9	39	152	37	2	2	90%	3.9	24.3%	1.3%	23.0%	1.3%	3.96	2.01	—
2024	20	ROK MLE	FCL Cardinals	11	10	46	197	45	16	4	91%	4.2	15.5%	10.2%	5.4%	2.9%	3.88	4.67	—
2024	20	ROK MLE	FCL Cardinals	11	10	46	197	45	16	4	91%	4.2	15.5%	10.2%	5.4%	2.9%	3.88	4.67	—
2024	20	ROK RAW	FCL Cardinals	11	10	46	197	45	16	4	91%	4.2	22.8%	8.1%	14.7%	2.0%	3.88	3.32	—
2025	21	MIX MLE	2 levels	19	5	75	315	63	22	6	26%	3.9	14.0%	8.4%	5.6%	2.4%	4.22	4.30	—
2025	21	MIX MLE	2 levels	19	5	75	315	63	22	6	26%	3.9	14.0%	8.4%	5.6%	2.4%	4.22	4.30	—
2025	21	MIX RAW	2 levels	19	5	75	315	63	22	6	26%	3.9	20.0%	7.0%	13.0%	1.9%	4.22	3.34	—
2026	22	A MLE	Palm Beach Cardinals	33	1	65	285	56	22	6	3%	2.0	14.5%	9.1%	5.4%	2.7%	4.71	4.53	—
2026	22	A MLE	Palm Beach Cardinals	33	1	65	285	56	22	6	3%	2.0	14.5%	9.1%	5.4%	2.7%	4.71	4.53	—
2026	22	A RAW	Palm Beach Cardinals	33	1	65	285	56	22	6	3%	2.0	19.6%	7.7%	11.9%	2.1%	4.71	3.59	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	23	MLB	STL	—	—	0	—	—	—	—	—	—	13.4%	9.2%	4.2%	2.9%	5.12	5.12	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	24	MLB MLE	STL	59	0	62	260	41	23	8	0%	1.0	15.6%	8.9%	6.7%	2.9%	4.95	4.89	-0.2
2029	25	MLB MLE	STL	43	0	45	189	32	17	5	0%	1.0	16.9%	8.8%	8.1%	2.9%	4.82	4.76	-0.1
2030	26	MLB MLE	STL	41	0	43	182	32	16	5	0%	1.0	17.6%	8.8%	8.8%	2.9%	4.74	4.71	-0.1
2031	27	MLB MLE	STL	40	0	42	175	31	16	5	0%	1.0	17.7%	8.9%	8.8%	3.0%	4.73	4.73	-0.1
2032	28	MLB MLE	STL	38	0	39	166	29	15	5	0%	1.0	17.6%	9.0%	8.5%	3.1%	4.78	4.82	-0.1
2033	29	MLB MLE	STL	35	0	37	155	27	14	5	0%	1.0	17.3%	9.3%	8.1%	3.2%	4.88	4.95	-0.2
2028	24	MLB CTX	STL	25	0	26	110	17	10	3	0%	1.0	15.6%	8.9%	6.7%	2.9%	4.95	4.89	-0.1
2029	25	MLB CTX	STL	29	0	30	127	21	11	4	0%	1.0	16.9%	8.8%	8.1%	2.9%	4.82	4.76	-0.1
2030	26	MLB CTX	STL	32	0	34	144	25	13	4	0%	1.1	17.6%	8.8%	8.8%	2.9%	4.74	4.71	-0.1
2031	27	MLB CTX	STL	33	0	35	148	26	13	4	0%	1.1	17.7%	8.9%	8.8%	3.0%	4.73	4.73	-0.1
2032	28	MLB CTX	STL	33	0	35	148	26	13	5	0%	1.1	17.6%	9.0%	8.5%	3.1%	4.78	4.82	-0.1
2033	29	MLB CTX	STL	31	0	33	139	24	13	4	0%	1.1	17.3%	9.3%	8.1%	3.2%	4.88	4.95	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		185	0	194	818	141	73	24	0%	1.0	17.2%	9.0%	8.2%	3.0%	4.81	4.43	+0.3
/ 200 IP	—	RAW		190	0	200	844	146	75	25	0%	1.1	17.2%	9.0%	8.2%	3.0%	4.81	4.43	+0.3
Career	—	MLE		73	25	225	949	141	75	24	34%	3.1	14.9%	7.9%	7.0%	2.5%	4.25	4.24	-0.8
/ 200 IP	—	MLE		65	22	200	845	126	67	21	34%	3.1	14.9%	7.9%	7.0%	2.5%	4.25	4.24	-0.6

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 APalm Beach Cardinals · 65 IPFIP 3.57 → 4.53 (+0.95)K% 19.6% → 14.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.65%	—	×0.740	14.54%
BB% (unintentional) /BF	7.72%	—	×1.180	9.11%
HR / BF /BF	2.11%	÷1.000	×1.300	2.74%

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 100).

Result: FIP 3.57 → 4.53, 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 ROKFCL Cardinals · 47 IPFIP 2.99 → 4.00 (+1.02)K% 22.5% → 15.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.46%	—	×0.680	15.27%
BB% (unintentional) /BF	4.81%	—	×1.250	6.02%
HR / BF /BF	2.14%	÷1.149	×1.400	2.61%

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 130).

Result: FIP 2.99 → 4.00, 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 APalm Beach Cardinals · 28 IPFIP 3.86 → 4.74 (+0.88)K% 16.4% → 12.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.41%	—	×0.740	12.14%
BB% (unintentional) /BF	10.16%	—	×1.180	11.98%
HR / BF /BF	1.56%	÷0.973	×1.300	2.09%

Result: FIP 3.86 → 4.74, 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 ROKFCL Cardinals · 46 IPFIP 3.31 → 4.67 (+1.36)K% 22.8% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.84%	—	×0.680	15.53%
BB% (unintentional) /BF	8.12%	—	×1.250	10.15%
HR / BF /BF	2.03%	÷0.975	×1.400	2.91%

Result: FIP 3.31 → 4.67, 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 ROKDSL Cardinals · 39 IPFIP 1.93 → 3.00 (+1.06)K% 24.3% → 16.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.34%	—	×0.680	16.55%
BB% (unintentional) /BF	1.32%	—	×1.250	1.64%
HR / BF /BF	1.32%	÷0.932	×1.400	1.98%

Result: FIP 1.93 → 3.00, 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
Yadiel Batista (OGILVIE)	—	—	5.12	13.4%	9.2%	2.9%	—	4.80	16.6%	7.7%	149	-0.32	—	—	—
Estevan Gonzalez L 2015 · 4.77 FIP	23	SW	4.77	14.1%	10.7%	2.8%	.322	4.86	14.7%	0.1%	130	+0.09	4.58	195	89
Matt Crouse L 2015 · 3.99 FIP	25	SW	3.99	12.0%	6.3%	2.0%	.276	4.40	12.2%	4.3%	268	+0.41	3.99	342	83
Jake Drehoff L 2015 · 3.95 FIP	23	SW	3.95	16.0%	5.9%	2.6%	.326	4.83	17.8%	6.8%	81	+0.88	3.95	153	81
Hayden Howard L 2017 · 4.16 FIP	23	SU	4.16	16.4%	8.1%	2.6%	.307	3.80	17.7%	8.7%	123	-0.36	3.76	200	81
Connor Oliver L 2024 · 4.34 FIP	23	SW	4.34	17.3%	12.1%	2.1%	.314	6.07	19.2%	3.4%	165	+1.73	4.34	244	81
Steve Ascher L 2016 · 4.14 FIP	22	SU	4.14	13.3%	9.5%	1.8%	.288	—	—	—	—	—	3.62	151	80
Edwin Escobar L 2015 · 5.96 FIP	23	SW	5.96	9.6%	11.9%	3.9%	.268	4.28	13.7%	4.9%	122	-1.68	4.28	218	80
Irwin Delgado L 2015 · 4.77 FIP	26	SW	4.77	14.4%	9.6%	3.0%	.349	3.53	16.2%	7.6%	237	-1.24	3.52	383	80
C.J. Wilson L 2005 · 4.17 FIP	24	SW	4.17	13.6%	7.7%	2.3%	.345	4.14	21.4%	10.7%	159	-0.03	2.55	1,430	79
Matt Walker L 2021 · 4.21 FIP	23	SU	4.21	16.7%	13.3%	1.5%	.324	4.62	15.5%	4.0%	94	+0.41	4.21	156	79
Matt Tracy L 2015 · 3.96 FIP	26	SW	3.96	14.4%	9.8%	1.5%	.306	4.10	14.7%	5.5%	208	+0.14	3.24	298	79
Doug Davis L 2000 · 5.12 FIP	24	SW	5.12	14.7%	12.2%	3.1%	.302	4.41	13.0%	4.1%	355	-0.71	3.47	1,713	78
Steven Moyers L 2017 · 4.84 FIP	23	SU	4.84	11.7%	6.4%	3.5%	.301	3.71	15.6%	10.8%	239	-1.13	3.52	464	78
Jaime Arias L 2022 · 5.00 FIP	23	SP-	5.00	15.6%	9.9%	3.6%	.332	5.53	15.8%	4.8%	77	+0.53	4.38	243	78
Cameron Roegner L 2016 · 4.16 FIP	23	SW	4.16	11.1%	12.1%	0.9%	.273	3.96	15.1%	6.5%	278	-0.20	3.77	319	77
Riley Cooper L 2024 · 4.22 FIP	22	SW	4.22	16.6%	12.0%	1.8%	.287	4.46	18.9%	7.7%	51	+0.24	4.14	139	77
Graeme Stinson L 2021 · 5.66 FIP	23	SU	5.66	12.6%	12.6%	3.7%	.266	4.14	21.4%	8.7%	101	-1.52	3.56	146	77
Luis De Paula L 2015 · 4.35 FIP	23	SW	4.35	14.8%	14.2%	1.3%	.285	5.37	16.4%	0.2%	47	+1.02	4.35	125	77
Jackson Stoeckinger L 2019 · 4.57 FIP	23	SW	4.57	13.5%	6.9%	3.2%	.303	—	—	—	—	—	3.19	184	77
Tom Windle L 2015 · 4.63 FIP	23	SW	4.63	12.3%	13.0%	1.7%	.304	4.33	18.0%	6.8%	159	-0.30	3.68	330	77

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	1.6	47	16.3%	9.0%	1.15	4.88
Vic Darensbourg ('05)	1.5	50	17.0%	9.3%	1.01	4.96
Tom Martin ('07)	1.6	53	15.8%	10.1%	1.02	4.92
Jeff Manship ('16)	1.1	32	16.5%	9.3%	1.05	4.82
Dave Leiper ('84-'96, 0 WAR*)	1.4	46	15.6%*	9.1%*	0.94*	4.28*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*