Javier Martínez

P DSL Cardinals

Age 18 RHP ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	17	ROKSTL	11	17	9.87	7.02	14.0%	10.5%	—	K 9.5% · BB 13.1% · FIP 8.42
2027PROJ	18	MLBSTL	10	10	5.00	5.00	19.8%	11.7%	-0.1
2028PROJ49% MLB	19	MLBSTL	10	10	4.83	4.76	20.7%	10.7%	-0.0

Next 2 projected WAR -0.1Projected 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 100%

CompsHarold Cortijo (age 18) · Yordin Chalas (age 19) · Kevin Tejada (age 18)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 128120vR 112

ERA5.00

FIP5.00

K%19.8%

BB%11.7%

K-BB%8.1%

Proj IP10

Value2027 · WAR

Runs saved vs league avg · 10 IP

Grades · Contract

Scouting Grades

K†4550

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 Cardinals	11	0	17	86	12	9	5	0%	1.6	9.5%	13.1%	-3.6%	8.1%	9.87	8.42	—
2026	17	ROK MLE	DSL Cardinals	11	0	17	86	12	9	5	0%	1.6	9.5%	13.1%	-3.6%	8.1%	9.87	8.42	—
2026	17	ROK RAW	DSL Cardinals	11	0	17	86	12	9	5	0%	1.6	14.0%	10.5%	3.5%	5.8%	9.87	7.02	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	18	MLB	STL	10	0	10	42	8	5	1	0%	1.0	19.8%	11.7%	8.1%	3.1%	5.00	5.00	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	19	MLB MLE	STL	19	0	20	84	18	9	3	0%	1.1	20.7%	10.7%	10.0%	3.1%	4.83	4.76	-0.0
2028	19	MLB CTX	STL	10	0	10	42	9	5	1	0%	1.0	20.7%	10.7%	10.0%	3.1%	4.83	4.76	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	0	10	42	9	4	1	0%	1.1	20.7%	10.7%	10.0%	3.1%	4.83	4.38	+0.0
/ 200 IP	—	RAW		190	0	200	844	183	81	20	0%	1.1	20.7%	10.7%	10.0%	3.1%	4.83	4.38	+0.4
Career	—	MLE		11	0	17	86	8	11	7	0%	1.6	9.5%	13.1%	-3.6%	8.1%	9.87	8.42	-0.0
/ 200 IP	—	MLE		127	0	200	992	94	130	81	0%	1.6	9.5%	13.1%	-3.6%	8.1%	9.87	8.42	-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
Javier Martínez (OGILVIE)	—	—	5.00	19.8%	11.7%	3.1%	—	4.76	20.7%	10.0%	20	-0.24	—	—	—
Harold Cortijo R 2017 · 4.46 FIP	18	SU	4.46	19.1%	9.8%	3.1%	.309	5.64	13.5%	2.2%	73	+1.18	4.15	179	90
Yordin Chalas R 2023 · 4.56 FIP	19	SU	4.56	17.3%	10.6%	2.9%	.294	3.92	19.9%	7.8%	116	-0.64	3.67	140	88
Kevin Tejada R 2023 · 3.97 FIP	18	SU	3.97	17.4%	10.0%	1.9%	.284	5.53	13.1%	2.7%	78	+1.56	3.97	108	86
David Matoma R 2024 · 3.81 FIP	18	SU	3.81	20.7%	12.2%	1.7%	.259	5.70	15.7%	-5.9%	79	+1.89	3.58	118	86
Blake Workman R 2018 · 4.00 FIP	20	SU	4.00	18.9%	9.5%	2.4%	.307	3.98	23.8%	19.5%	105	-0.02	3.09	213	86
Kevin Rodriguez R 2019 · 4.37 FIP	18	SU	4.37	17.4%	12.8%	2.0%	.279	4.14	16.7%	7.6%	41	-0.23	2.34	188	85
Francisco Frias R 2023 · 5.74 FIP	18	SU	5.74	20.8%	14.1%	4.8%	.294	4.83	19.2%	2.2%	134	-0.91	4.00	148	84
Greiber Mendez R 2022 · 4.92 FIP	18	SU	4.92	15.7%	11.5%	3.1%	.330	4.78	16.7%	2.5%	152	-0.14	3.64	247	84
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	83
Audry Lugo R 2019 · 4.05 FIP	20	SU	4.05	18.5%	11.4%	2.0%	.247	5.30	15.6%	-0.4%	77	+1.25	4.05	113	83
Devon Fisher R 2016 · 4.39 FIP	20	SU	4.39	16.5%	12.5%	2.0%	.333	5.76	15.1%	0.9%	88	+1.37	4.39	102	83
Troy Bacon R 2017 · 3.92 FIP	20	SU	3.92	19.9%	11.7%	1.9%	.222	4.06	19.7%	10.8%	102	+0.14	3.34	203	83
José Cruz R 2018 · 5.53 FIP	18	SU	5.53	15.3%	11.8%	4.1%	.256	3.65	18.8%	3.8%	70	-1.88	2.18	227	83
Max Gieg R 2022 · 5.10 FIP	21	SU	5.10	21.1%	11.8%	4.2%	.317	4.65	20.4%	2.3%	92	-0.45	3.98	149	82
Joangel Gonzalez R 2024 · 4.23 FIP	20	SU	4.23	18.3%	11.7%	2.1%	.312	5.15	18.3%	2.5%	116	+0.92	3.93	151	82
Augusto Mendieta R 2023 · 5.24 FIP	18	SU	5.24	19.4%	12.5%	4.0%	.439	3.82	21.0%	10.4%	118	-1.42	2.29	133	82
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	82
Angel Guillen R 2015 · 3.92 FIP	18	SU	3.92	20.6%	10.2%	2.3%	.411	3.44	15.7%	8.6%	78	-0.48	3.37	181	82
José Geraldo R 2018 · 4.15 FIP	19	SU	4.15	15.3%	10.9%	1.8%	.296	4.15	18.0%	7.8%	46	-0.00	3.50	192	81
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	81