Raudy Gomez

P FCL Blue Jays

Age 22 RHP 5'10" / 160 lbs ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	18	ROKTOR	12	7	31	9.77	3.20	15.4%	10.9%	—	K 10.5% · BB 13.6% · FIP 3.94
2024	19	ROKTOR	15	0	27	7.24	4.78	17.2%	16.4%	—	K 11.7% · BB 20.5% · FIP 5.95
2027PROJ	22	MLBTOR	15	0	16	4.85	4.85	22.4%	12.8%	-0.1
2028PROJ49% MLB	23	MLBTOR	10	0	10	4.67	4.58	23.3%	11.4%	-0.0

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

Contract

No contract data on file.

CompsJuan Mendez (age 22) · Alec Barger (age 23) · Joey Matulovich (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 125117vR 109

ERA4.85

FIP4.85

K%22.4%

BB%12.8%

K-BB%9.6%

Proj IP16

Value2027 · WAR

Runs saved vs league avg · 16 IP

Grades · Contract

Scouting Grades

K†5555

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)
2022	17	ROK MLE	DSL Blue Jays	5	5	7	37	4	7	0	100%	1.5	10.8%	18.9%	-8.1%	0.0%	8.59	4.58	—
2022	17	ROK RAW	DSL Blue Jays	5	5	7	37	4	7	0	100%	1.5	10.8%	18.9%	-8.1%	0.0%	8.59	4.87	—
2023	18	ROK MLE	DSL Blue Jays	12	7	31	156	24	17	0	58%	2.6	10.5%	13.6%	-3.2%	0.0%	9.77	3.94	—
2023	18	ROK RAW	DSL Blue Jays	12	7	31	156	24	17	0	58%	2.6	15.4%	10.9%	4.5%	0.0%	9.77	3.20	—
2024	19	ROK MLE	FCL Blue Jays	15	0	27	134	23	22	2	0%	1.8	11.7%	20.5%	-8.9%	2.3%	7.24	5.95	—
2024	19	ROK MLE	FCL Blue Jays	15	0	27	134	23	22	2	0%	1.8	11.7%	20.5%	-8.9%	2.3%	7.24	5.95	—
2024	19	ROK RAW	FCL Blue Jays	15	0	27	134	23	22	2	0%	1.8	17.2%	16.4%	0.7%	1.5%	7.24	4.78	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	22	MLB	TOR	15	0	16	68	15	9	2	0%	1.1	22.4%	12.8%	9.6%	3.0%	4.85	4.85	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	23	MLB MLE	TOR	19	0	20	84	20	10	2	0%	1.1	23.3%	11.4%	11.8%	3.0%	4.67	4.58	-0.0
2028	23	MLB CTX	TOR	10	0	10	42	10	5	1	0%	1.0	23.3%	11.4%	11.8%	3.0%	4.67	4.58	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	0	10	42	10	5	1	0%	1.1	23.3%	11.4%	11.8%	3.0%	4.67	4.20	+0.0
/ 200 IP	—	RAW		190	0	200	844	203	102	20	0%	1.1	23.3%	11.4%	11.8%	3.0%	4.67	4.20	+0.8
Career	—	MLE		32	12	66	327	36	56	3	38%	2.1	11.0%	17.0%	-6.1%	0.9%	8.59	4.84	-0.0
/ 200 IP	—	MLE		97	36	200	991	109	169	9	37%	2.1	11.0%	17.0%	-6.1%	0.9%	8.59	4.84	-0.1

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
Raudy Gomez (OGILVIE)	—	—	4.85	22.4%	12.8%	3.0%	—	4.58	23.3%	11.8%	20	-0.27	—	—	—
Juan Mendez R 2021 · 4.45 FIP	22	SW	4.45	20.5%	14.2%	2.3%	.271	5.07	21.9%	6.1%	128	+0.62	3.69	156	89
Alec Barger R 2021 · 4.55 FIP	23	SW	4.55	21.7%	13.6%	2.8%	.289	4.17	21.3%	9.4%	148	-0.38	3.85	242	81
Joey Matulovich R 2019 · 5.52 FIP	22	SW	5.52	19.8%	14.6%	4.1%	.378	5.04	20.5%	8.9%	133	-0.48	3.22	201	80
Brendan Collins R 2022 · 3.67 FIP	22	SW	3.67	21.8%	10.3%	2.0%	.294	3.86	20.2%	5.1%	54	+0.19	3.67	122	79
Trayson Kubo R 2019 · 5.01 FIP	21	SW	5.01	19.8%	15.6%	2.9%	.450	4.82	17.7%	1.4%	66	-0.19	4.48	107	78
Victor Simeon R 2023 · 5.53 FIP	22	SW	5.53	20.3%	15.7%	3.9%	.333	3.87	25.6%	5.4%	81	-1.66	3.22	180	78
Jonathan Papelbon R 2005 · 3.93 FIP	24	SW	3.93	23.0%	10.1%	2.7%	.305	1.90	31.3%	26.8%	196	-2.03	1.33	726	78
Luis Romero R 2017 · 5.00 FIP	23	SU	5.00	22.1%	11.9%	4.1%	.367	4.26	21.6%	12.5%	132	-0.74	4.00	293	77
Blake Holub R 2022 · 4.55 FIP	23	SU	4.55	21.7%	15.3%	2.4%	.339	3.73	23.4%	12.7%	156	-0.82	3.22	258	77
Todd Peterson R 2021 · 5.11 FIP	23	SW	5.11	18.4%	10.3%	4.1%	.279	4.83	15.0%	4.3%	124	-0.28	4.45	175	77
Luimy Munoz R 2024 · 3.83 FIP	22	SW	3.83	20.1%	14.3%	1.1%	.380	4.18	16.4%	2.0%	54	+0.35	3.05	115	77
Billy Corcoran R 2023 · 4.20 FIP	23	SW	4.20	19.5%	10.0%	2.7%	.308	5.26	16.4%	8.7%	208	+1.06	4.20	277	77
Nick Lockhart R 2023 · 4.63 FIP	22	SW	4.63	16.1%	10.6%	2.8%	.274	—	—	—	—	—	4.44	140	76
Josh White R 2023 · 5.12 FIP	22	SW	5.12	17.7%	13.9%	3.2%	.244	3.15	27.7%	17.2%	182	-1.97	1.84	247	76
Eiberson Castellano R 2023 · 4.25 FIP	22	SW	4.25	18.3%	14.1%	1.7%	.359	4.06	20.9%	10.6%	251	-0.19	3.67	386	76
Brad Deppermann R 2021 · 4.51 FIP	25	SW	4.51	17.1%	9.6%	3.0%	.289	3.52	20.0%	7.8%	45	-0.99	1.94	143	76
Kyle Zurak R 2017 · 3.96 FIP	22	SU	3.96	21.2%	9.4%	2.6%	.302	3.42	16.7%	7.5%	121	-0.54	3.20	181	76
Tyler Santana R 2021 · 4.28 FIP	23	SU	4.28	20.3%	15.1%	1.8%	.333	4.37	16.0%	5.7%	259	+0.09	3.37	401	76
Yunior Montero R 2015 · 4.82 FIP	22	SW	4.82	16.9%	14.1%	2.5%	.276	4.58	21.5%	6.2%	91	-0.24	3.65	127	76
Kyle Zimmer R 2015 · 3.74 FIP	23	SW	3.74	21.8%	8.6%	2.5%	.293	4.55	20.4%	9.0%	33	+0.81	2.08	276	76