Michael Castillo

P DSL Pirates Black

Age 22 RHP ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	21	ROKDSL Pirates B…	18	22	2.42	5.03	26.0%	26.9%	—	K 17.7% · BB 33.7% · FIP 6.61
2027PROJ	22	MLBPIT	12	13	5.80	5.80	21.7%	20.0%	-0.2
2028PROJ49% MLB	23	MLBPIT	10	10	5.43	5.29	22.6%	16.7%	-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 99%

CompsHudson Leach (age 22) · Andrew Schultz (age 22) · Saul Teran (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 143135vR 127

ERA5.80

FIP5.80

K%21.7%

BB%20.0%

K-BB%1.7%

Proj IP13

Value2027 · WAR

Runs saved vs league avg · 13 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)
2026	21	ROK MLE	DSL Pirates Black	18	0	22	104	27	28	1	0%	1.2	17.7%	33.7%	-16.0%	1.3%	2.42	6.61	—
2026	21	ROK MLE	DSL Pirates Black	18	0	22	104	27	28	1	0%	1.2	17.7%	33.7%	-16.0%	1.3%	2.42	6.61	—
2026	21	ROK RAW	DSL Pirates Black	18	0	22	104	27	28	1	0%	1.2	26.0%	26.9%	-1.0%	1.0%	2.42	5.03	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	22	MLB	PIT	12	0	13	55	12	11	2	0%	1.1	21.7%	20.0%	1.7%	3.0%	5.80	5.80	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	23	MLB MLE	PIT	20	0	21	88	20	15	3	0%	1.0	22.6%	16.7%	5.9%	2.9%	5.43	5.29	-0.2
2028	23	MLB CTX	PIT	10	0	10	42	10	7	1	0%	1.0	22.6%	16.7%	5.9%	2.9%	5.43	5.29	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		10	0	10	43	10	7	1	0%	1.0	22.6%	16.7%	5.9%	2.9%	5.43	4.91	-0.0
/ 200 IP	—	RAW		190	0	200	844	195	136	19	0%	1.0	22.6%	16.7%	5.9%	2.9%	5.43	4.91	-0.8
Career	—	MLE		18	0	22	104	18	35	1	0%	1.2	17.7%	33.7%	-16.0%	1.3%	2.42	6.61	-0.2
/ 200 IP	—	MLE		161	0	200	931	164	313	13	0%	1.2	17.7%	33.7%	-16.0%	1.3%	2.42	6.61	-1.7

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
Michael Castillo (OGILVIE)	—	—	5.80	21.7%	20.0%	3.0%	—	5.29	22.6%	5.9%	21	-0.51	—	—	—
Hudson Leach R 2024 · 5.37 FIP	22	SU	5.37	20.5%	20.0%	2.7%	.261	4.54	20.9%	3.1%	71	-0.83	2.77	101	92
Andrew Schultz R 2019 · 5.25 FIP	22	SU	5.25	20.9%	17.8%	3.0%	.345	4.59	23.0%	4.7%	45	-0.66	3.56	176	91
Saul Teran R 2024 · 5.21 FIP	22	SU	5.21	22.4%	18.8%	2.9%	.279	4.40	20.1%	10.7%	84	-0.81	2.28	166	90
Carlos Contreras R 2014 · 4.77 FIP	23	SU	4.77	20.2%	18.1%	2.0%	.304	4.35	18.4%	5.0%	107	-0.42	4.29	127	89
Marcus Crescentini R 2015 · 5.80 FIP	22	SU	5.80	21.8%	21.9%	3.2%	.365	3.95	23.3%	11.6%	123	-1.85	2.74	150	89
Paul Gervase R 2022 · 4.91 FIP	22	SU	4.91	20.3%	16.2%	2.7%	.345	3.76	29.3%	16.0%	152	-1.15	3.38	211	88
Jackson Rose R 2018 · 5.32 FIP	22	SU	5.32	17.3%	17.2%	2.8%	.267	4.77	23.5%	16.5%	56	-0.55	3.33	147	88
Michael Perez R 2024 · 5.44 FIP	21	SU	5.44	18.3%	16.1%	3.4%	.296	4.65	23.4%	7.7%	132	-0.79	4.38	153	88
Christian Ruebeck R 2024 · 6.03 FIP	23	SU	6.03	20.6%	24.4%	2.9%	.265	4.57	21.6%	1.9%	70	-1.46	4.35	104	87
Brandon Dufault R 2021 · 5.32 FIP	22	SU	5.32	22.1%	15.9%	3.8%	.278	4.83	21.0%	4.2%	66	-0.49	4.38	152	87
Morgan McSweeney R 2021 · 5.36 FIP	23	SU	5.36	21.9%	16.3%	3.7%	.295	5.15	18.5%	5.3%	93	-0.21	3.20	213	86
James Acuna R 2021 · 5.12 FIP	23	SU	5.12	21.3%	17.0%	3.0%	.302	4.33	19.4%	4.6%	60	-0.79	4.33	107	86
Zane Russell R 2024 · 4.95 FIP	24	SU	4.95	22.7%	18.3%	2.6%	.314	5.36	18.2%	6.7%	71	+0.41	4.63	108	86
Will Varmette R 2024 · 5.06 FIP	21	SU	5.06	22.8%	19.3%	2.6%	.302	5.13	16.1%	2.3%	135	+0.07	4.69	182	86
Kasey Ford R 2021 · 4.89 FIP	23	SU	4.89	20.3%	14.5%	3.0%	.310	4.26	21.9%	5.8%	98	-0.63	2.53	114	85
Franklyn German R 2003 · 5.17 FIP	23	SU	5.17	18.5%	18.9%	2.2%	.313	5.27	13.1%	0.1%	86	+0.10	3.37	152	85
Roberto Espinosa R 2015 · 4.92 FIP	23	SU	4.92	18.9%	18.6%	1.9%	.273	4.43	14.8%	2.2%	77	-0.49	4.32	117	85
Greg Weissert R 2016 · 5.22 FIP	21	SU	5.22	19.4%	19.3%	2.4%	.382	3.80	23.0%	10.3%	126	-1.42	2.57	487	85
Jonathan Teaney R 2018 · 4.77 FIP	22	SU	4.77	22.5%	19.8%	1.9%	.328	5.65	16.4%	0.7%	55	+0.88	4.77	108	85
Miguel Alfonseca R 2022 · 4.78 FIP	22	SU	4.78	20.1%	16.4%	2.4%	.354	5.73	11.6%	-3.8%	56	+0.95	4.19	123	84