Jesús García

P Palm Beach Cardinals

Age 21 RHP 5'11" / 141 lbs A peak 0.2 · 2031

Overview

APROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	18	ROKSTL	18	34	5.24	2.02	23.9%	8.2%	—	K 16.3% · BB 10.2% · FIP 3.02
2025	19	ROKSTL	14	23	2.78	2.53	32.3%	7.5%	—	K 21.9% · BB 9.4% · FIP 4.02
2026	20	MIX2 levels	32	51	3.53	3.90	19.9%	7.3%	—	K 13.7% · BB 9.3% · FIP 5.52
2027PROJ	21	MLBSTL	20	21	4.86	4.86	17.9%	9.4%	-0.1
2028PROJ49% MLB	22	MLBSTL	23	24	4.67	4.58	19.9%	8.8%	-0.0
2029PROJ73% MLB	23	MLBSTL	34	36	4.51	4.42	21.0%	8.5%	0.1

Next 3 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0 WAR median (P10 0 / P90 0, comp-based) · star 0% · didn't stick 96%

CompsMike Morrison (age 22) · Logan Lombana (age 21) · Matt Pidich (age 23)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 125117vR 109

ERA4.86

FIP4.86

K%17.9%

BB%9.4%

K-BB%8.6%

Proj IP21

Value2027 · WAR

Runs saved vs league avg · 21 IP

Grades · Contract

Scouting Grades

K†4055

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 industry-standard fWAR.

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)
2024	18	ROK MLE	DSL Cardinals	18	0	34	159	38	13	0	0%	1.9	16.3%	10.2%	6.0%	0.0%	5.24	3.02	—
2024	18	ROK MLE	DSL Cardinals	18	0	34	159	38	13	0	0%	1.9	16.3%	10.2%	6.0%	0.0%	5.24	3.02	—
2024	18	ROK RAW	DSL Cardinals	18	0	34	159	38	13	0	0%	1.9	23.9%	8.2%	15.7%	0.0%	5.24	2.02	—
2025	19	ROK MLE	DSL Cardinals	14	0	23	93	30	7	2	0%	1.6	21.9%	9.4%	12.5%	2.9%	2.78	4.02	—
2025	19	ROK MLE	DSL Cardinals	14	0	23	93	30	7	2	0%	1.6	21.9%	9.4%	12.5%	2.9%	2.78	4.02	—
2025	19	ROK RAW	DSL Cardinals	14	0	23	93	30	7	2	0%	1.6	32.3%	7.5%	24.7%	2.2%	2.78	2.53	—
2026	20	MIX MLE	2 levels	32	0	51	206	41	15	6	0%	1.6	13.7%	9.3%	4.4%	4.4%	3.53	5.52	—
2026	20	MIX MLE	2 levels	32	0	51	206	41	15	6	0%	1.6	13.7%	9.3%	4.4%	4.4%	3.53	5.52	—
2026	20	MIX RAW	2 levels	32	0	51	206	41	15	6	0%	1.6	19.9%	7.3%	12.6%	2.9%	3.53	3.90	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	21	MLB	STL	20	0	21	89	16	8	3	0%	1.1	17.9%	9.4%	8.6%	3.1%	4.86	4.86	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	22	MLB MLE	STL	46	0	48	204	40	18	6	0%	1.0	19.9%	8.8%	11.1%	3.0%	4.67	4.58	-0.0
2029	23	MLB MLE	STL	48	0	50	211	44	18	6	0%	1.0	21.0%	8.5%	12.5%	3.0%	4.51	4.42	+0.1
2030	24	MLB MLE	STL	49	0	51	216	47	18	6	0%	1.0	21.7%	8.3%	13.4%	3.0%	4.39	4.32	+0.1
2031	25	MLB MLE	STL	49	0	52	219	48	18	6	0%	1.1	22.1%	8.2%	13.9%	2.9%	4.32	4.27	+0.2
2032	26	MLB MLE	STL	49	0	52	219	49	18	6	0%	1.1	22.3%	8.1%	14.2%	2.9%	4.27	4.24	+0.2
2033	27	MLB MLE	STL	49	0	51	215	48	18	6	0%	1.0	22.3%	8.2%	14.1%	3.0%	4.28	4.28	+0.2
2028	22	MLB CTX	STL	23	0	24	101	20	9	3	0%	1.0	19.9%	8.8%	11.1%	3.0%	4.67	4.58	-0.0
2029	23	MLB CTX	STL	34	0	36	152	32	13	5	0%	1.1	21.0%	8.5%	12.5%	3.0%	4.51	4.42	+0.1
2030	24	MLB CTX	STL	40	0	42	177	38	15	5	0%	1.1	21.7%	8.3%	13.4%	3.0%	4.39	4.32	+0.1
2031	25	MLB CTX	STL	44	0	46	194	43	16	6	0%	1.0	22.1%	8.2%	13.9%	2.9%	4.32	4.27	+0.2
2032	26	MLB CTX	STL	45	0	47	198	44	16	6	0%	1.0	22.3%	8.1%	14.2%	2.9%	4.27	4.24	+0.2
2033	27	MLB CTX	STL	45	0	47	198	44	16	6	0%	1.0	22.3%	8.2%	14.1%	3.0%	4.28	4.28	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		231	0	243	1026	223	85	30	0%	1.1	21.7%	8.3%	13.4%	3.0%	4.38	3.95	+1.7
/ 200 IP	—	RAW		190	0	200	844	184	70	25	0%	1.0	21.7%	8.3%	13.4%	3.0%	4.38	3.95	+1.4
Career	—	MLE		64	0	108	458	75	44	12	0%	1.7	16.3%	9.6%	6.6%	2.6%	3.92	4.35	+0.7
/ 200 IP	—	MLE		119	0	200	848	138	82	22	0%	1.7	16.3%	9.6%	6.6%	2.6%	3.92	4.35	+0.5

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
Jesús García (OGILVIE)	—	—	4.86	17.9%	9.4%	3.1%	—	4.44	20.9%	12.4%	149	-0.42	—	—	—
Mike Morrison R 2016 · 4.86 FIP	22	SU	4.86	17.3%	10.7%	3.4%	.280	4.02	19.0%	7.1%	128	-0.84	3.36	145	92
Logan Lombana R 2015 · 4.63 FIP	21	SU	4.63	16.9%	10.0%	3.1%	.315	4.02	15.7%	8.1%	123	-0.61	3.80	155	91
Matt Pidich R 2018 · 4.42 FIP	23	SU	4.42	17.1%	8.3%	3.1%	.303	4.08	20.8%	13.3%	115	-0.34	4.05	196	89
Chris Gau R 2018 · 4.76 FIP	21	SU	4.76	20.0%	8.6%	4.1%	.290	3.19	29.5%	23.5%	37	-1.57	2.96	211	89
Andrew Bash R 2019 · 3.87 FIP	22	SU	3.87	18.0%	9.2%	2.1%	.273	4.21	14.9%	4.8%	146	+0.34	3.46	483	88
Josnier Parra R 2023 · 4.56 FIP	21	SU	4.56	15.9%	9.8%	2.9%	.319	5.01	12.1%	2.9%	118	+0.45	3.76	150	88
Tyler Zombro R 2017 · 4.37 FIP	22	SU	4.37	14.6%	8.9%	2.5%	.295	2.67	15.7%	12.7%	134	-1.70	2.22	172	88
Mike Foltynewicz R 2014 · 4.76 FIP	22	SU	4.76	16.7%	8.3%	3.7%	.333	4.20	20.8%	12.6%	448	-0.56	3.17	957	88
Sandy Lugo R 2015 · 3.86 FIP	21	SU	3.86	20.7%	9.5%	2.4%	.352	3.98	23.6%	12.5%	119	+0.12	3.48	146	87
Joseilyn Gonzalez R 2022 · 4.98 FIP	20	SU	4.98	14.5%	8.5%	3.7%	.321	5.20	14.5%	-3.2%	107	+0.22	4.98	168	87
Geoff Hartlieb R 2016 · 4.87 FIP	22	SU	4.87	15.9%	9.4%	3.5%	.287	3.68	20.7%	11.7%	197	-1.19	3.03	570	87
Heath Holder R 2016 · 4.16 FIP	23	SU	4.16	21.1%	10.1%	2.8%	.287	3.30	22.3%	13.1%	247	-0.86	2.94	367	87
Reece Karalus R 2016 · 4.80 FIP	22	SU	4.80	18.5%	8.6%	4.0%	.298	4.81	14.8%	4.1%	103	+0.01	4.73	149	86
Jeremy Beasley R 2017 · 4.71 FIP	21	SU	4.71	19.5%	11.6%	3.3%	.273	4.10	17.7%	8.7%	234	-0.61	3.17	337	86
Austin Mason R 2015 · 4.41 FIP	21	SU	4.41	17.1%	11.6%	2.4%	.289	4.06	16.2%	6.5%	151	-0.35	3.60	179	86
Anyelo Leclerc R 2015 · 5.00 FIP	23	SU	5.00	16.2%	9.8%	3.7%	.326	4.65	15.9%	6.1%	96	-0.35	4.65	140	86
Alex Burnett R 2010 · 4.37 FIP	23	SU	4.37	17.5%	9.5%	2.8%	.311	3.80	12.9%	5.3%	122	-0.57	3.68	170	86
Brooks Wilson R 2018 · 5.17 FIP	22	SU	5.17	15.8%	10.3%	3.8%	.229	3.11	21.3%	12.5%	131	-2.06	2.92	194	86
Luis Alvarado R 2018 · 5.24 FIP	21	SU	5.24	20.2%	12.4%	4.2%	.276	5.16	18.7%	4.4%	140	-0.08	4.89	162	86
Miles Mikolas R 2012 · 4.56 FIP	23	SU	4.56	16.0%	10.4%	2.7%	.275	4.29	14.9%	8.6%	57	-0.27	3.13	1,386	86

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,474 reliever careers (754 from 1990-2025 + 720 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	46	21.3%	8.4%	1.15	4.43
Jacob Barnes ('25)	1.7	48	22.0%	9.2%	1.15	4.79
Tyler Walker ('10)	1.5	50	18.9%	8.5%	1.11	4.23
Ian Krol ('21)	1.0	42	21.2%	8.8%	1.25	4.49
Bill Pleis ('61-'66, -0 WAR*)	1.4	56	19.7%*	9.8%*	1.15*	4.53*
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*