Jose Rosal

P DSL Marlins

Age 18 RHP ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	17	ROKMIA	16	8	32	4.55	3.83	23.6%	17.8%	—	K 16.0% · BB 22.3% · FIP 5.06
2027PROJ	18	MLBMIA	3	3	19	5.78	5.78	20.6%	19.2%	-0.2
2028PROJ49% MLB	19	MLBMIA	3	3	15	5.44	5.32	21.3%	16.3%	-0.1

Next 2 projected WAR -0.3Projected 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%

CompsEdinzo Marquez (age 17) · Ernesto Jaquez (age 18) · Keegan Zinn (age 19)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 143135vR 127

ERA5.78

FIP5.78

K%20.6%

BB%19.2%

K-BB%1.3%

Proj IP19

Value2027 · WAR

Runs saved vs league avg · 19 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 Marlins	16	8	32	157	37	28	1	50%	2.0	16.0%	22.3%	-6.3%	0.9%	4.55	5.06	—
2026	17	ROK MLE	DSL Marlins	16	8	32	157	37	28	1	50%	2.0	16.0%	22.3%	-6.3%	0.9%	4.55	5.06	—
2026	17	ROK RAW	DSL Marlins	16	8	32	157	37	28	1	50%	2.0	23.6%	17.8%	5.7%	0.6%	4.55	3.83	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	18	MLB	MIA	3	3	19	80	16	15	2	100%	6.3	20.6%	19.2%	1.3%	2.9%	5.78	5.78	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	19	MLB MLE	MIA	5	5	30	126	27	21	4	100%	6.0	21.3%	16.3%	5.0%	2.9%	5.44	5.32	-0.1
2028	19	MLB CTX	MIA	3	3	15	63	13	10	2	100%	5.0	21.3%	16.3%	5.0%	2.9%	5.44	5.32	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		3	3	15	62	13	10	2	100%	4.9	21.3%	16.3%	5.0%	2.9%	5.44	4.94	-0.0
/ 200 IP	—	RAW		46	46	200	844	177	136	27	100%	4.3	21.3%	16.3%	5.0%	2.9%	5.44	4.94	-0.1
Career	—	MLE		16	8	32	157	25	35	1	50%	2.0	16.0%	22.3%	-6.3%	0.9%	4.55	5.06	-0.1
/ 200 IP	—	MLE		101	51	200	992	159	221	9	50%	2.0	16.0%	22.3%	-6.3%	0.9%	4.55	5.06	-1.0

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
Jose Rosal (OGILVIE)	—	—	5.78	20.6%	19.2%	2.9%	—	5.32	21.3%	5.0%	30	-0.46	—	—	—
Edinzo Marquez R 2022 · 4.97 FIP	17	SW	4.97	20.5%	18.9%	2.2%	.250	3.90	13.2%	0.4%	119	-1.07	3.26	188	88
Ernesto Jaquez R 2017 · 4.99 FIP	18	SW	4.99	18.4%	16.9%	2.4%	.265	2.56	24.8%	15.7%	53	-2.43	2.56	239	86
Keegan Zinn R 2024 · 6.40 FIP	19	SP-	6.40	19.1%	19.5%	4.4%	.318	5.80	19.0%	-1.9%	112	-0.60	4.88	145	84
Jesus Rivero R 2021 · 5.42 FIP	18	SP-	5.42	21.7%	22.1%	2.5%	.224	4.35	21.7%	1.5%	117	-1.07	4.09	146	83
Janser Lara R 2016 · 5.61 FIP	19	SP-	5.61	20.1%	17.3%	3.7%	.354	5.04	17.9%	4.8%	118	-0.57	2.84	220	83
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	83
Ben Peoples R 2019 · 6.28 FIP	18	SW	6.28	21.8%	27.5%	2.8%	.227	4.51	23.0%	9.1%	103	-1.77	3.56	365	82
Miguel Ullola R 2021 · 4.90 FIP	19	SP-	4.90	24.4%	24.8%	1.3%	.239	4.54	24.8%	7.6%	290	-0.36	3.87	511	81
Joseph Hernandez R 2018 · 5.37 FIP	18	SW	5.37	15.6%	15.0%	3.1%	.296	4.39	24.7%	8.0%	31	-0.98	4.39	260	80
Cesar Espinal R 2024 · 5.75 FIP	18	SW	5.75	16.8%	25.5%	1.5%	.300	6.38	15.7%	-1.8%	36	+0.63	4.28	109	79
Yosber Sanchez R 2019 · 5.58 FIP	18	SP-	5.58	14.6%	14.9%	3.3%	.315	4.61	20.2%	-5.2%	13	-0.97	3.21	200	79
Jace Beck R 2021 · 5.13 FIP	21	SP-	5.13	21.1%	23.7%	1.5%	.347	5.32	25.7%	2.8%	50	+0.19	4.03	216	79
Sandy Gaston R 2019 · 5.63 FIP	17	SP-	5.63	16.3%	26.2%	1.1%	.314	5.05	22.9%	-0.2%	105	-0.58	4.17	310	79
Wilmer Blanco R 2022 · 5.15 FIP	18	SP-	5.15	15.0%	19.9%	1.5%	.348	4.81	16.3%	1.5%	92	-0.34	3.81	163	78
Jaydenn Estanista R 2021 · 4.72 FIP	19	SP-	4.72	18.1%	19.2%	1.3%	.254	5.35	21.0%	2.6%	109	+0.63	4.59	230	78
Yimi Presinal R 2023 · 4.75 FIP	18	SW	4.75	20.2%	15.0%	2.7%	.326	4.71	20.8%	4.6%	92	-0.04	3.62	157	78
Eliazar Dishmey R 2023 · 6.05 FIP	18	SW	6.05	17.9%	15.1%	4.6%	.302	3.83	21.9%	9.2%	268	-2.22	3.40	311	78
Luis Rujano R 2023 · 4.68 FIP	20	SW	4.68	17.1%	16.6%	1.7%	.309	4.71	17.6%	1.2%	150	+0.03	4.54	203	78
Sunayro Martina R 2023 · 4.79 FIP	19	SP-	4.79	17.6%	21.9%	0.7%	.247	5.46	14.4%	-4.0%	90	+0.67	4.57	118	78
Andry Cuevas R 2017 · 4.68 FIP	18	SW	4.68	18.2%	17.1%	1.7%	.223	4.21	20.7%	2.6%	71	-0.47	3.71	108	78