Diego Rosal

P DSL Twins

Age 21 RHP 6'1" / 202 lbs ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	19	ROKMIN	6	1	13	11.37	5.47	16.4%	13.1%	—	K 11.1% · BB 16.4% · FIP 6.88
2027PROJ	21	MLBMIN	8	0	8	4.79	4.79	22.1%	12.0%	-0.0
2028PROJ49% MLB	22	MLBMIN	10	0	10	4.61	4.51	23.1%	10.8%	0.0

Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsKyle Zurak (age 22) · Luis Romero (age 23) · Rolddy Muñoz (age 21)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 124116vR 108

ERA4.79

FIP4.79

K%22.1%

BB%12.0%

K-BB%10.1%

Proj IP8

Value2027 · WAR

Runs saved vs league avg · 8 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)
2025	19	ROK MLE	DSL Twins	6	1	13	61	10	8	2	17%	2.1	11.1%	16.4%	-5.2%	4.8%	11.37	6.88	—
2025	19	ROK MLE	DSL Twins	6	1	13	61	10	8	2	17%	2.1	11.1%	16.4%	-5.2%	4.8%	11.37	6.88	—
2025	19	ROK RAW	DSL Twins	6	1	13	61	10	8	2	17%	2.1	16.4%	13.1%	3.3%	3.3%	11.37	5.47	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	21	MLB	MIN	8	0	8	34	7	4	1	0%	1.0	22.1%	12.0%	10.1%	3.0%	4.79	4.79	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	22	MLB MLE	MIN	19	0	20	84	20	9	2	0%	1.1	23.1%	10.8%	12.4%	3.0%	4.61	4.51	+0.0
2028	22	MLB CTX	MIN	10	0	10	42	10	5	1	0%	1.0	23.1%	10.8%	12.4%	3.0%	4.61	4.51	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	0	10	42	10	4	1	0%	1.1	23.1%	10.8%	12.4%	3.0%	4.61	4.13	+0.0
/ 200 IP	—	RAW		190	0	200	844	203	81	20	0%	1.1	23.1%	10.8%	12.4%	3.0%	4.61	4.13	+1.0
Career	—	MLE		6	1	13	61	7	10	3	17%	2.1	11.1%	16.4%	-5.2%	4.8%	11.37	6.88	+0.0
/ 200 IP	—	MLE		95	16	200	963	107	158	46	17%	2.1	11.1%	16.4%	-5.2%	4.8%	11.37	6.88	+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
Diego Rosal (OGILVIE)	—	—	4.79	22.1%	12.0%	3.0%	—	4.51	23.1%	12.4%	20	-0.28	—	—	—
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	86
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	84
Rolddy Muñoz R 2021 · 4.32 FIP	21	SU	4.32	21.4%	13.7%	2.4%	.342	3.54	21.1%	9.8%	149	-0.78	3.18	290	84
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	83
Justin Meis R 2021 · 4.07 FIP	21	SU	4.07	25.6%	13.6%	2.6%	.300	5.14	18.2%	5.5%	261	+1.07	3.68	411	83
Brandyn Sittinger R 2017 · 4.37 FIP	23	SU	4.37	22.2%	13.8%	2.5%	.324	3.97	21.2%	7.2%	72	-0.40	3.58	152	82
Zac Ryan R 2017 · 3.83 FIP	23	SU	3.83	20.5%	10.9%	2.0%	.233	3.93	21.6%	6.9%	124	+0.10	3.83	184	82
Brandon Komar R 2019 · 4.77 FIP	20	SW	4.77	17.7%	11.6%	3.1%	.327	4.93	16.7%	5.7%	198	+0.16	3.00	538	81
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	81
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	81
Reiss Knehr R 2018 · 4.29 FIP	21	SU	4.29	21.3%	12.3%	2.6%	.267	4.86	18.8%	7.2%	171	+0.57	3.36	398	80
Caleb Freeman R 2019 · 3.98 FIP	21	SU	3.98	24.6%	12.9%	2.4%	.267	5.15	21.7%	8.1%	58	+1.17	3.98	225	80
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	80
Cody Palmquist R 2016 · 4.31 FIP	22	SU	4.31	21.9%	9.0%	3.5%	.278	6.02	14.7%	7.1%	62	+1.71	4.31	104	80
Jesus Gamez R 2024 · 3.81 FIP	21	SU	3.81	25.4%	14.0%	2.0%	.321	4.28	27.2%	2.8%	77	+0.47	3.42	105	80
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	80
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	80
Brandon Beckel R 2024 · 3.75 FIP	22	SU	3.75	19.4%	10.3%	1.8%	.250	4.23	19.5%	10.5%	147	+0.48	3.75	194	80
Chris Gau R 2018 · 4.76 FIP	21	SU	4.76	20.0%	8.6%	4.1%	.290	3.19	29.5%	23.5%	37	-1.57	2.96	211	80
Tyler Mitzel R 2019 · 4.34 FIP	23	SU	4.34	24.1%	12.0%	3.2%	.245	4.10	22.4%	14.3%	96	-0.24	4.03	142	80