Victor Garcia

P Rancho Cucamonga Quakes

Age 23 RHP 6'1" / 194 lbs A

Overview

APROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	20	MIX2 levels	31	3	68	4.66	2.80	23.6%	9.1%	—	K 16.5% · BB 11.1% · FIP 3.98
2025	21	ASEA	40	0	66	3.39	2.48	26.0%	8.2%	—	K 19.3% · BB 9.7% · FIP 3.41
2026	22	MIX2 levels	25	0	39	4.89	4.81	30.9%	13.5%	—	K 22.7% · BB 15.6% · FIP 6.60
2027PROJ	23	MLBLAA	50	0	52	5.11	5.11	20.4%	13.0%	-0.3
2028PROJ43% MLB	24	MLBLAA	25	0	26	4.93	4.86	21.2%	11.8%	-0.1
2029PROJ66% MLB	25	MLBLAA	39	0	41	4.79	4.71	21.8%	11.0%	-0.1

Next 3 projected WAR -0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff45Control45Command45

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

CompsHayden Snelsire (age 23) · Max Alba (age 24) · Josh Harlow (age 23)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 130122vR 114

ERA5.11

FIP5.11

K%20.4%

BB%13.0%

K-BB%7.4%

Proj IP52

Value2027 · WAR

Runs saved vs league avg · 52 IP

Grades · Contract

Scouting Grades

STUF4545

CTRL4545

CMD4545

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 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	20	MIX MLE	2 levels	31	3	68	297	70	27	3	10%	2.2	16.5%	11.1%	5.4%	1.6%	4.66	3.98	—
2024	20	MIX MLE	2 levels	31	3	68	297	70	27	3	10%	2.2	16.5%	11.1%	5.4%	1.6%	4.66	3.98	—
2024	20	MIX RAW	2 levels	31	3	68	297	70	27	3	10%	2.2	23.6%	9.1%	14.5%	1.0%	4.66	2.80	—
2025	21	A MLE	Inland Empire 66ers	40	0	66	292	76	24	3	0%	1.7	19.3%	9.7%	9.6%	1.3%	3.39	3.41	—
2025	21	A MLE	Inland Empire 66ers	40	0	66	292	76	24	3	0%	1.7	19.3%	9.7%	9.6%	1.3%	3.39	3.41	—
2025	21	A RAW	Inland Empire 66ers	40	0	66	292	76	24	3	0%	1.7	26.0%	8.2%	17.8%	1.0%	3.39	2.48	—
2026	22	MIX MLE	2 levels	25	0	39	178	55	24	8	0%	1.5	22.7%	15.6%	7.1%	6.3%	4.89	6.60	—
2026	22	MIX MLE	2 levels	25	0	39	178	55	24	8	0%	1.5	22.7%	15.6%	7.1%	6.3%	4.89	6.60	—
2026	22	MIX RAW	2 levels	25	0	39	178	55	24	8	0%	1.5	30.9%	13.5%	17.4%	4.5%	4.89	4.81	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	23	MLB	LAA	50	0	52	220	45	28	7	0%	1.0	20.4%	13.0%	7.4%	3.1%	5.11	5.11	-0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	24	MLB MLE	LAA	58	0	61	258	55	30	8	0%	1.1	21.2%	11.8%	9.5%	3.1%	4.93	4.86	-0.2
2029	25	MLB MLE	LAA	59	0	62	262	57	29	8	0%	1.1	21.8%	11.0%	10.7%	3.0%	4.79	4.71	-0.1
2028	24	MLB CTX	LAA	25	0	26	110	23	13	3	0%	1.0	21.2%	11.8%	9.5%	3.1%	4.93	4.86	-0.1
2029	25	MLB CTX	LAA	39	0	41	173	38	19	5	0%	1.1	21.8%	11.0%	10.7%	3.0%	4.79	4.71	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		64	0	67	284	61	32	9	0%	1.1	21.5%	11.3%	10.2%	3.1%	4.84	4.39	+0.1
/ 200 IP	—	RAW		190	0	200	844	181	95	27	0%	1.1	21.5%	11.3%	10.2%	3.1%	4.84	4.39	+0.4
Career	—	MLE		96	3	173	767	146	89	20	3%	1.8	19.0%	11.6%	7.4%	2.6%	4.22	4.37	-0.3
/ 200 IP	—	MLE		111	3	200	888	169	103	23	3%	1.8	19.0%	11.6%	7.4%	2.6%	4.22	4.37	-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
Victor Garcia (OGILVIE)	—	—	5.11	20.4%	13.0%	3.1%	—	4.78	21.5%	10.1%	123	-0.33	—	—	—
Hayden Snelsire R 2024 · 5.10 FIP	23	SU	5.10	18.9%	13.8%	3.4%	.272	4.28	20.0%	13.7%	135	-0.82	3.83	178	91
Max Alba R 2023 · 4.47 FIP	24	SU	4.47	20.6%	12.6%	2.7%	.290	5.29	16.7%	9.8%	248	+0.82	4.47	303	91
Josh Harlow R 2024 · 5.17 FIP	23	SU	5.17	18.5%	13.5%	3.5%	.266	5.73	17.1%	-4.2%	51	+0.56	5.17	107	91
Harrison Cohen R 2023 · 4.56 FIP	24	SU	4.56	22.4%	13.4%	3.0%	.282	4.18	22.3%	9.0%	119	-0.38	2.12	165	91
Alaska Abney R 2023 · 4.92 FIP	23	SU	4.92	18.8%	13.8%	3.0%	.301	3.89	17.4%	7.9%	104	-1.03	3.38	207	91
Bailey Dees R 2022 · 4.26 FIP	23	SU	4.26	21.3%	13.2%	2.4%	.248	4.35	21.4%	9.7%	278	+0.09	3.41	330	91
Easton Sikorski R 2023 · 4.85 FIP	23	SU	4.85	20.9%	14.1%	3.1%	.254	4.62	17.5%	6.3%	154	-0.23	4.23	183	90
Brandon Johnson R 2023 · 4.94 FIP	24	SU	4.94	22.4%	14.2%	3.5%	.327	4.47	22.1%	12.1%	189	-0.47	3.35	250	90
Colby Morris R 2021 · 4.11 FIP	24	SU	4.11	20.4%	10.7%	2.5%	.291	5.76	16.2%	4.4%	54	+1.65	4.11	105	89
Tanner Jacobson R 2023 · 4.09 FIP	23	SU	4.09	22.8%	13.8%	2.1%	.313	4.89	21.1%	5.4%	115	+0.80	4.09	168	89
Kieran Lovegrove R 2017 · 4.92 FIP	23	SU	4.92	17.9%	12.6%	3.2%	.273	4.46	19.3%	4.5%	76	-0.46	3.79	215	89
Grayson Thurman R 2023 · 4.63 FIP	24	SU	4.63	19.5%	14.1%	2.5%	.319	4.85	19.9%	10.5%	87	+0.22	4.58	132	89
Brett Standlee R 2022 · 4.13 FIP	23	SU	4.13	19.7%	11.1%	2.4%	.322	4.45	17.0%	8.9%	75	+0.32	4.13	128	89
Kyle Marman R 2019 · 3.97 FIP	22	SU	3.97	22.2%	12.8%	2.0%	.270	5.16	22.5%	8.4%	71	+1.19	3.97	117	89
Sean Isaac R 2016 · 4.27 FIP	23	SU	4.27	19.5%	12.3%	2.3%	.342	3.76	25.0%	10.7%	128	-0.51	3.27	155	88
Tyler Schoff R 2022 · 4.25 FIP	23	SU	4.25	19.6%	10.8%	2.6%	.350	3.72	23.8%	15.7%	93	-0.53	3.69	190	88
Jayson McKinley R 2017 · 4.39 FIP	23	SU	4.39	17.5%	11.4%	2.4%	.308	3.60	20.4%	11.3%	134	-0.79	2.35	173	88
David Trexler R 2015 · 4.62 FIP	24	SU	4.62	17.7%	13.4%	2.4%	.313	4.44	18.3%	4.8%	31	-0.18	4.44	100	88
Junior Rincon R 2015 · 4.93 FIP	23	SU	4.93	17.8%	13.8%	2.9%	.318	3.75	17.6%	5.1%	82	-1.18	3.52	113	87
Bladimir Matos R 2017 · 5.02 FIP	23	SU	5.02	18.8%	13.7%	3.2%	.301	6.99	14.4%	-7.0%	13	+1.97	3.88	143	87

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	0.9	59	21.1%	11.9%	1.19	4.93
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Tyler Yates ('09)	1.2	62	19.7%	12.0%	0.94	5.12
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57
Josias Manzanillo ('04)	1.7	57	20.0%	10.2%	1.21	4.71
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*