Felipe Alcazar

P DSL Rays

Age 18 LHP ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	17	ROKTB	12	16	8.27	7.26	17.6%	18.9%	—	K 11.9% · BB 23.6% · FIP 9.24
2027PROJ	18	MLBTB	10	10	5.70	5.70	20.8%	18.0%	-0.1
2028PROJ49% MLB	19	MLBTB	10	10	5.39	5.28	21.4%	15.4%	-0.1

Next 2 projected WAR -0.2Projected 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%

CompsCD Pelham (age 20) · Yensy Bello (age 19) · Yordy Herrera (age 18)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 125133vR 141

ERA5.70

FIP5.70

K%20.8%

BB%18.0%

K-BB%2.8%

Proj IP10

Value2027 · WAR

Runs saved vs league avg · 10 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 Rays	12	0	16	74	13	14	4	0%	1.4	11.9%	23.6%	-11.7%	7.6%	8.27	9.24	—
2026	17	ROK MLE	DSL Rays	12	0	16	74	13	14	4	0%	1.4	11.9%	23.6%	-11.7%	7.6%	8.27	9.24	—
2026	17	ROK RAW	DSL Rays	12	0	16	74	13	14	4	0%	1.4	17.6%	18.9%	-1.4%	5.4%	8.27	7.26	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	18	MLB	TB	10	0	10	42	9	8	1	0%	1.0	20.8%	18.0%	2.8%	3.1%	5.70	5.70	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	19	MLB MLE	TB	19	0	20	84	18	13	3	0%	1.1	21.4%	15.4%	6.1%	3.0%	5.39	5.28	-0.2
2028	19	MLB CTX	TB	10	0	10	42	9	6	1	0%	1.0	21.4%	15.4%	6.1%	3.0%	5.39	5.28	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	0	10	42	9	6	1	0%	1.1	21.4%	15.4%	6.1%	3.0%	5.39	4.90	-0.0
/ 200 IP	—	RAW		190	0	200	844	183	122	20	0%	1.1	21.4%	15.4%	6.1%	3.0%	5.39	4.90	-0.8
Career	—	MLE		12	0	16	74	9	18	6	0%	1.4	11.9%	23.6%	-11.7%	7.6%	8.27	9.24	-0.2
/ 200 IP	—	MLE		147	0	200	906	108	214	69	0%	1.4	11.9%	23.6%	-11.7%	7.6%	8.27	9.24	-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
Felipe Alcazar (OGILVIE)	—	—	5.70	20.8%	18.0%	3.1%	—	5.28	21.4%	6.1%	20	-0.42	—	—	—
CD Pelham L 2015 · 4.77 FIP	20	SU	4.77	18.8%	18.7%	1.6%	.286	4.00	20.4%	7.8%	109	-0.77	3.39	288	84
Yensy Bello L 2022 · 6.82 FIP	19	SU	6.82	19.9%	32.3%	2.4%	.240	3.76	17.4%	4.1%	91	-3.06	2.65	103	83
Yordy Herrera L 2023 · 4.98 FIP	18	SU	4.98	20.6%	23.1%	1.3%	.283	4.88	21.2%	1.8%	117	-0.10	3.87	163	80
Noel Vela L 2017 · 6.62 FIP	18	SU	6.62	20.4%	31.2%	2.3%	.192	5.06	16.3%	-1.5%	45	-1.56	4.48	255	80
Alexander Beltre L 2021 · 6.42 FIP	18	SU	6.42	15.6%	18.2%	4.2%	.351	3.82	17.4%	6.1%	67	-2.60	2.75	106	78
Angel Padron L 2016 · 4.56 FIP	18	SU	4.56	16.4%	17.9%	1.1%	.247	4.14	17.0%	7.0%	222	-0.42	3.05	293	76
Boone Logan L 2006 · 4.69 FIP	21	SU	4.69	16.1%	14.0%	2.1%	.302	4.14	17.2%	10.5%	110	-0.55	2.58	442	76
Nicolo Pinazzi L 2021 · 4.55 FIP	21	SU	4.55	25.7%	21.3%	1.7%	.389	5.41	22.7%	0.2%	76	+0.86	2.58	155	75
Develson Aria L 2019 · 5.19 FIP	18	SU	5.19	15.5%	19.7%	1.6%	.311	4.33	21.7%	3.1%	54	-0.86	4.32	137	75
Wilfred Salaman L 2016 · 6.60 FIP	18	SU	6.60	13.1%	20.8%	3.6%	.333	4.44	13.0%	0.4%	200	-2.16	4.26	218	74
Will Stewart L 2015 · 6.63 FIP	18	SU	6.63	13.6%	18.8%	4.2%	.242	3.57	14.4%	6.8%	158	-3.06	3.38	535	74
Daniel Gonzalez L 2021 · 5.55 FIP	19	SU	5.55	13.6%	19.1%	2.1%	.318	4.98	20.1%	2.0%	100	-0.57	4.34	136	74
Jayvien Sandridge L 2018 · 5.17 FIP	19	SU	5.17	15.5%	19.0%	1.8%	.188	6.78	19.0%	-4.9%	13	+1.61	3.25	223	73
Gregori Louis L 2022 · 5.03 FIP	19	SU	5.03	25.4%	13.1%	4.4%	.364	4.96	19.1%	2.9%	89	-0.07	3.58	149	71
Denny Bentley L 2018 · 4.85 FIP	20	SU	4.85	19.6%	10.3%	3.8%	.318	2.88	25.4%	10.3%	58	-1.97	2.88	175	70
Liu Fuenmayor L 2017 · 5.88 FIP	18	SU	5.88	15.2%	21.1%	2.5%	.214	3.52	11.1%	0.3%	28	-2.36	3.07	130	70
Cleiber Maldonado L 2022 · 5.20 FIP	18	SW	5.20	13.5%	15.1%	2.4%	.267	3.42	14.8%	2.4%	57	-1.78	2.35	109	69
Ignacio Briceno L 2021 · 5.16 FIP	20	SU	5.16	12.7%	12.9%	2.7%	.230	3.33	17.0%	7.2%	82	-1.83	2.39	156	69
Alex Robinson L 2015 · 5.75 FIP	20	SU	5.75	16.2%	31.7%	0.0%	.312	4.45	23.4%	5.2%	123	-1.30	3.69	135	68
Frenny Grant L 2023 · 4.69 FIP	19	SW	4.69	19.4%	25.5%	0.0%	.240	4.18	17.4%	3.9%	120	-0.51	3.92	143	67