Oscar Montero

P DSL Mets Blue

Age 18 RHP ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	17	ROKDSL Mets Blue	11	11	24	7.61	5.34	23.0%	26.2%	—	K 15.6% · BB 32.8% · FIP 6.56
2027PROJ	18	MLBNYM	3	3	14	5.87	5.87	20.8%	20.0%	-0.2
2028PROJ49% MLB	19	MLBNYM	2	2	11	5.51	5.38	21.5%	16.8%	-0.1

Next 2 projected WAR -0.2Projected 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 97%

CompsJared Kelley (age 19) · Randry De Leon (age 18) · Omar Gonzalez (age 18)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 145137vR 128

ERA5.87

FIP5.87

K%20.8%

BB%20.0%

K-BB%0.8%

Proj IP14

Value2027 · WAR

Runs saved vs league avg · 14 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 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)
2026	17	ROK MLE	DSL Mets Blue	11	11	24	122	28	32	1	100%	2.2	15.6%	32.8%	-17.2%	1.1%	7.61	6.56	—
2026	17	ROK MLE	DSL Mets Blue	11	11	24	122	28	32	1	100%	2.2	15.6%	32.8%	-17.2%	1.1%	7.61	6.56	—
2026	17	ROK RAW	DSL Mets Blue	11	11	24	122	28	32	1	100%	2.2	23.0%	26.2%	-3.3%	0.8%	7.61	5.34	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	18	MLB	NYM	3	3	14	59	12	12	2	100%	4.7	20.8%	20.0%	0.8%	2.9%	5.87	5.87	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	19	MLB MLE	NYM	4	4	22	95	20	16	3	100%	5.6	21.5%	16.8%	4.7%	2.9%	5.51	5.38	-0.1
2028	19	MLB CTX	NYM	2	2	11	46	10	8	1	100%	5.5	21.5%	16.8%	4.7%	2.9%	5.51	5.38	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		3	3	11	46	10	8	1	100%	3.7	21.5%	16.8%	4.7%	2.9%	5.51	5.00	-0.0
/ 200 IP	—	RAW		46	46	200	844	182	145	18	100%	4.3	21.5%	16.8%	4.7%	2.9%	5.51	5.00	-0.2
Career	—	MLE		11	11	24	122	19	40	1	100%	2.2	15.6%	32.8%	-17.2%	1.1%	7.61	6.56	-0.1
/ 200 IP	—	MLE		93	93	200	1031	161	338	12	100%	2.2	15.6%	32.8%	-17.2%	1.1%	7.61	6.56	-1.1

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
Oscar Montero (OGILVIE)	—	—	5.87	20.8%	20.0%	2.9%	—	5.38	21.5%	4.7%	22	-0.49	—	—	—
Jared Kelley R 2021 · 5.33 FIP	19	SP	5.33	16.5%	23.2%	1.2%	.312	5.14	16.5%	-1.2%	174	-0.19	4.25	250	80
Randry De Leon R 2023 · 6.45 FIP	18	SP-	6.45	17.7%	20.2%	4.2%	.308	4.83	18.4%	3.3%	123	-1.62	4.37	153	80
Omar Gonzalez R 2023 · 5.10 FIP	18	SP	5.10	24.3%	24.6%	1.7%	.375	5.69	15.1%	-2.0%	106	+0.59	2.25	137	80
Gio Arriera R 2017 · 5.41 FIP	19	SP	5.41	15.1%	13.9%	3.3%	.333	4.34	15.5%	2.0%	79	-1.07	4.34	185	78
Michell Miliano R 2018 · 4.93 FIP	18	SP	4.93	16.3%	16.7%	2.0%	.379	5.90	24.3%	-1.8%	71	+0.97	4.42	205	78
Alexander Almonte R 2024 · 5.69 FIP	17	SP	5.69	16.2%	13.8%	4.0%	.250	4.82	12.6%	-2.8%	75	-0.87	4.27	100	78
Waylin Santana R 2021 · 5.12 FIP	18	SP	5.12	15.1%	15.0%	2.5%	.377	6.18	13.5%	1.0%	94	+1.06	4.88	117	78
Jharold Clemente R 2023 · 4.97 FIP	20	SP	4.97	17.5%	13.6%	3.0%	.258	5.11	13.3%	4.3%	92	+0.14	4.09	116	76
Chen-Wei Lin R 2023 · 6.48 FIP	21	SP	6.48	21.3%	22.0%	4.4%	.379	3.81	20.5%	8.4%	257	-2.67	3.05	269	76
Peter Heubeck R 2022 · 6.70 FIP	20	SP	6.70	21.9%	20.8%	5.1%	.221	4.52	22.2%	6.6%	243	-2.18	4.08	294	75
Ryan Harbin R 2021 · 4.79 FIP	19	SP	4.79	15.8%	15.4%	2.0%	.391	4.57	21.8%	6.2%	107	-0.22	3.82	185	75
Tanner McDougal R 2023 · 4.96 FIP	20	SP	4.96	19.7%	16.9%	2.5%	.285	4.81	21.3%	8.0%	253	-0.15	3.82	323	75
Jeter Martinez R 2024 · 4.72 FIP	18	SP	4.72	18.1%	21.1%	0.9%	.282	4.90	15.6%	-0.4%	129	+0.18	3.52	216	74
Tony Santillan R 2015 · 4.77 FIP	18	SP	4.77	15.2%	16.2%	1.7%	.259	4.29	17.8%	7.0%	346	-0.48	2.96	784	74
Luis Ghisays R 2024 · 5.74 FIP	18	SP	5.74	13.8%	15.0%	3.5%	.291	5.08	16.2%	5.4%	75	-0.66	4.58	110	74
Kenyi Perez R 2021 · 6.09 FIP	19	SP	6.09	15.6%	27.4%	1.5%	.349	6.38	21.0%	-13.4%	77	+0.29	4.30	194	74
Jose Pena Jr. R 2022 · 5.48 FIP	19	SP-	5.48	15.0%	18.7%	2.3%	.269	4.62	19.2%	3.1%	124	-0.86	3.48	176	74
Chris Viall R 2016 · 5.86 FIP	20	SP-	5.86	18.9%	21.9%	2.9%	.314	5.06	21.3%	5.8%	88	-0.80	4.89	108	74
Victor Mederos R 2022 · 4.69 FIP	21	SP	4.69	15.6%	14.0%	2.1%	.286	5.19	16.4%	5.7%	301	+0.50	3.73	394	74
Wikelman González R 2019 · 4.97 FIP	17	SP	4.97	15.7%	15.7%	2.2%	.258	3.45	21.2%	8.4%	151	-1.52	3.20	498	73