Diego Palacios

P DSL Rays

Age 21 RHP 6'0" / 174 lbs ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	19	ROKTB	3	3	11	5.56	1.78	28.3%	9.4%	—	K 19.2% · BB 11.8% · FIP 2.97
2026	20	ROKTB	11	0	20	4.12	3.56	22.6%	8.3%	—	K 15.4% · BB 10.4% · FIP 4.95
2027PROJ	21	MLBTB	10	0	10	4.63	4.63	21.2%	10.3%	-0.0
2028PROJ49% MLB	22	MLBTB	10	0	10	4.48	4.40	22.4%	9.5%	0.0

Next 2 projected WAR 0.0Projected 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 99%

CompsKyle Zurak (age 22) · Chris Gau (age 21) · Cody Palmquist (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 121113vR 105

ERA4.63

FIP4.63

K%21.2%

BB%10.3%

K-BB%10.9%

Proj IP10

Value2027 · WAR

Runs saved vs league avg · 10 IP

Grades · Contract

Scouting Grades

K†5055

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 Rays	3	3	11	53	15	5	0	100%	3.8	19.2%	11.8%	7.5%	0.0%	5.56	2.97	—
2025	19	ROK MLE	DSL Rays	3	3	11	53	15	5	0	100%	3.8	19.2%	11.8%	7.5%	0.0%	5.56	2.97	—
2025	19	ROK RAW	DSL Rays	3	3	11	53	15	5	0	100%	3.8	28.3%	9.4%	18.9%	0.0%	5.56	1.78	—
2026	20	ROK MLE	DSL Rays	11	0	20	84	19	7	2	0%	1.8	15.4%	10.4%	5.0%	3.3%	4.12	4.95	—
2026	20	ROK MLE	DSL Rays	11	0	20	84	19	7	2	0%	1.8	15.4%	10.4%	5.0%	3.3%	4.12	4.95	—
2026	20	ROK RAW	DSL Rays	11	0	20	84	19	7	2	0%	1.8	22.6%	8.3%	14.3%	2.4%	4.12	3.56	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	21	MLB	TB	10	0	10	42	9	4	1	0%	1.0	21.2%	10.3%	10.9%	3.0%	4.63	4.63	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	22	MLB MLE	TB	19	0	20	84	19	8	2	0%	1.1	22.4%	9.5%	12.9%	2.9%	4.48	4.40	+0.0
2028	22	MLB CTX	TB	10	0	10	42	9	4	1	0%	1.0	22.4%	9.5%	12.9%	2.9%	4.48	4.40	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	0	10	42	9	4	1	0%	1.1	22.3%	9.5%	12.9%	2.9%	4.48	4.02	+0.1
/ 200 IP	—	RAW		190	0	200	844	183	81	20	0%	1.1	22.3%	9.5%	12.9%	2.9%	4.48	4.02	+1.3
Career	—	MLE		14	3	31	137	23	15	3	21%	2.2	16.9%	10.9%	5.9%	2.0%	4.65	4.18	+0.0
/ 200 IP	—	MLE		90	19	200	884	149	97	18	21%	2.2	16.9%	10.9%	5.9%	2.0%	4.65	4.18	+0.4

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 Palacios (OGILVIE)	—	—	4.63	21.2%	10.3%	3.0%	—	4.40	22.3%	12.9%	20	-0.23	—	—	—
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	91
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	85
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	85
Sandy Lugo R 2015 · 3.86 FIP	21	SU	3.86	20.7%	9.5%	2.4%	.352	3.98	23.6%	12.5%	119	+0.12	3.48	146	84
Heath Holder R 2016 · 4.16 FIP	23	SU	4.16	21.1%	10.1%	2.8%	.287	3.30	22.3%	13.1%	247	-0.86	2.94	367	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	84
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	84
Addison Russ R 2017 · 3.62 FIP	22	SU	3.62	22.2%	7.9%	2.5%	.324	3.09	25.6%	17.5%	121	-0.53	3.08	194	83
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	83
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	83
Justin Lasko R 2019 · 3.66 FIP	22	SU	3.66	17.1%	8.6%	1.7%	.286	4.62	15.8%	8.1%	152	+0.96	3.66	173	83
Jake Elliott R 2016 · 3.82 FIP	21	SU	3.82	19.2%	7.1%	2.6%	.353	3.81	18.1%	10.0%	202	-0.01	2.91	354	83
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	83
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	83
Gerlin Rosario R 2023 · 3.79 FIP	21	SU	3.79	20.3%	9.1%	2.3%	.294	4.94	18.1%	5.4%	153	+1.15	3.02	248	82
Mike Morrison R 2016 · 4.86 FIP	22	SU	4.86	17.3%	10.7%	3.4%	.280	4.02	19.0%	7.1%	128	-0.84	3.36	145	82
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	82
Josnier Parra R 2023 · 4.56 FIP	21	SU	4.56	15.9%	9.8%	2.9%	.319	5.01	12.1%	2.9%	118	+0.45	3.76	150	82
Nick Lockhart R 2022 · 4.44 FIP	21	SU	4.44	22.0%	9.9%	3.5%	.275	4.63	16.1%	5.5%	43	+0.19	4.44	140	82
Owen Holt R 2022 · 3.72 FIP	23	SU	3.72	20.7%	10.2%	2.0%	.258	4.51	18.7%	6.4%	107	+0.79	3.72	145	82