Angel Castillo

P FCL Rays

Age 25 RHP ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	24	ROKTB	11	1	14	0.64	1.89	33.3%	12.3%	—	K 22.7% · BB 15.4% · FIP 3.13
2027PROJ	25	MLBTB	8	0	8	4.73	4.73	23.3%	12.6%	-0.0
2028PROJ43% MLB	26	MLBTB	9	0	9	4.67	4.66	23.5%	12.2%	-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 100%

CompsMichael Wuertz (age 25) · Brad Boxberger (age 25) · Brandon Cunniff (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 123115vR 107

ERA4.73

FIP4.73

K%23.3%

BB%12.6%

K-BB%10.7%

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)
2026	24	ROK MLE	FCL Rays	11	1	14	57	19	7	0	9%	1.3	22.7%	15.4%	7.3%	0.0%	0.64	3.13	—
2026	24	ROK MLE	FCL Rays	11	1	14	57	19	7	0	9%	1.3	22.7%	15.4%	7.3%	0.0%	0.64	3.13	—
2026	24	ROK RAW	FCL Rays	11	1	14	57	19	7	0	9%	1.3	33.3%	12.3%	21.1%	0.0%	0.64	1.89	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	TB	8	0	8	34	8	4	1	0%	1.0	23.3%	12.6%	10.7%	3.0%	4.73	4.73	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	TB	19	0	20	84	20	10	2	0%	1.1	23.5%	12.2%	11.3%	3.0%	4.67	4.66	-0.0
2028	26	MLB CTX	TB	9	0	9	38	9	5	1	0%	1.0	23.5%	12.2%	11.3%	3.0%	4.67	4.66	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		8	0	9	36	8	4	1	0%	1.1	23.5%	12.2%	11.3%	3.0%	4.67	4.28	+0.0
/ 200 IP	—	RAW		190	0	200	844	187	94	23	0%	1.1	23.5%	12.2%	11.3%	3.0%	4.67	4.28	+0.6
Career	—	MLE		11	1	14	57	13	9	0	9%	1.3	22.7%	15.4%	7.3%	0.0%	0.64	3.13	-0.0
/ 200 IP	—	MLE		157	14	200	814	185	125	0	9%	1.3	22.7%	15.4%	7.3%	0.0%	0.64	3.13	-0.3

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
Angel Castillo (OGILVIE)	—	—	4.73	23.3%	12.6%	3.0%	—	4.66	23.5%	11.3%	20	-0.07	—	—	—
Michael Wuertz R 2004 · 4.46 FIP	25	SU	4.46	24.2%	12.9%	3.2%	.243	3.39	26.1%	16.6%	189	-1.07	2.27	414	87
Brad Boxberger R 2013 · 4.40 FIP	25	SU	4.40	25.5%	13.8%	3.1%	.296	3.54	32.3%	22.2%	152	-0.86	2.63	478	87
Brandon Cunniff R 2015 · 4.28 FIP	26	SU	4.28	24.5%	13.2%	2.9%	.256	4.32	20.3%	9.0%	115	+0.04	3.89	180	86
Francisco Del Rosario R 2006 · 5.13 FIP	25	SU	5.13	19.4%	13.0%	3.7%	.290	3.93	19.7%	10.3%	26	-1.20	3.93	194	86
Shawn Tolleson R 2012 · 3.86 FIP	24	SU	3.86	24.4%	11.9%	2.4%	.265	3.47	24.4%	18.5%	144	-0.39	3.05	218	85
Maikel Cleto R 2014 · 4.24 FIP	25	SU	4.24	23.2%	15.2%	2.1%	.256	3.45	25.4%	14.5%	106	-0.79	2.59	185	84
Grant Balfour R 2003 · 4.13 FIP	25	SU	4.13	26.1%	10.4%	3.5%	.275	3.79	24.4%	12.8%	39	-0.34	2.04	533	84
Garrett Mock R 2008 · 3.57 FIP	25	SU	3.57	25.6%	11.1%	2.2%	.300	4.06	17.1%	7.4%	91	+0.49	3.57	132	84
Dan Kolb R 2001 · 4.49 FIP	26	SU	4.49	21.4%	12.9%	2.9%	.295	3.61	14.3%	5.5%	131	-0.88	3.00	283	84
Josh Zeid R 2013 · 4.00 FIP	26	SU	4.00	20.3%	9.3%	2.6%	.287	4.75	16.2%	4.8%	183	+0.75	4.00	313	84
Jesus Pirela R 2015 · 3.84 FIP	26	SU	3.84	23.7%	11.6%	2.3%	.305	3.92	17.1%	13.9%	45	+0.08	3.24	161	83
Logan Boyer R 2024 · 3.71 FIP	26	SU	3.71	25.0%	12.3%	2.1%	.267	4.65	17.5%	3.5%	54	+0.94	3.71	121	82
Jason Stoffel R 2015 · 3.61 FIP	26	SU	3.61	23.4%	10.1%	2.2%	.267	3.49	27.2%	19.2%	59	-0.12	3.49	103	82
Manny Acosta R 2007 · 4.05 FIP	26	SU	4.05	23.7%	14.0%	2.1%	.196	4.23	19.0%	9.1%	130	+0.18	3.08	350	82
Chaz Roe R 2013 · 4.02 FIP	26	SU	4.02	25.3%	10.5%	3.1%	.259	2.81	24.6%	16.2%	133	-1.21	1.72	279	82
Tyler Mitzel R 2021 · 4.03 FIP	25	SU	4.03	20.8%	12.0%	2.1%	.323	4.14	23.4%	17.9%	58	+0.11	4.03	142	82
Cameron Gann R 2017 · 4.22 FIP	24	SU	4.22	21.4%	12.4%	2.5%	.296	5.36	21.1%	6.8%	23	+1.14	3.58	146	82
Fernando Salas R 2010 · 4.27 FIP	25	SU	4.27	21.8%	9.8%	3.2%	.276	3.29	23.5%	16.8%	162	-0.98	2.60	539	82
Cayne Ueckert R 2021 · 4.51 FIP	25	SU	4.51	24.6%	12.9%	3.4%	.150	5.52	21.4%	5.1%	124	+1.01	3.95	205	81
Ben Hecht R 2019 · 4.51 FIP	24	SU	4.51	22.7%	12.9%	3.1%	.293	7.98	14.1%	-11.4%	13	+3.47	4.39	155	81