Jose Melo

P DSL Blue Jays Red

Age 22 RHP ROK peak 0.1 · 2028

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	21	ROKDSL Blue Jays…	15	31	1.72	2.59	23.5%	7.6%	—	K 16.0% · BB 9.5% · FIP 3.59
2027PROJ	22	MLB—	18	19	4.51	4.51	21.0%	9.4%	0.0
2028PROJ49% MLB	23	MLB—	13	14	4.40	4.34	22.0%	8.9%	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) · Heath Holder (age 23) · Addison Russ (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 119111vR 103

ERA4.51

FIP4.51

K%21.0%

BB%9.4%

K-BB%11.6%

Proj IP19

Value2027 · WAR

Runs saved vs league avg · 19 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	21	ROK MLE	DSL Blue Jays Red	15	0	31	119	28	9	1	0%	2.1	16.0%	9.5%	6.5%	1.2%	1.72	3.59	—
2026	21	ROK MLE	DSL Blue Jays Red	15	0	31	119	28	9	1	0%	2.1	16.0%	9.5%	6.5%	1.2%	1.72	3.59	—
2026	21	ROK RAW	DSL Blue Jays Red	15	0	31	119	28	9	1	0%	2.1	23.5%	7.6%	16.0%	0.8%	1.72	2.59	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	22	MLB	—	18	0	19	80	17	8	2	0%	1.1	21.0%	9.4%	11.6%	2.9%	4.51	4.51	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	23	MLB MLE	—	28	0	29	124	27	11	4	0%	1.0	22.0%	8.9%	13.1%	2.9%	4.40	4.34	+0.1
2028	23	MLB CTX	—	13	0	14	59	13	5	2	0%	1.1	22.0%	8.9%	13.1%	2.9%	4.40	4.34	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		14	0	14	61	13	5	2	0%	1.0	22.0%	8.9%	13.1%	2.9%	4.40	3.96	+0.1
/ 200 IP	—	RAW		190	0	200	844	180	69	28	0%	1.1	22.0%	8.9%	13.1%	2.9%	4.40	3.96	+1.4
Career	—	MLE		15	0	31	119	19	11	1	0%	2.1	16.0%	9.5%	6.5%	1.2%	1.72	3.59	+0.1
/ 200 IP	—	MLE		96	0	200	760	122	72	9	0%	2.1	16.0%	9.5%	6.5%	1.2%	1.72	3.59	+0.5

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
Jose Melo (OGILVIE)	—	—	4.51	21.0%	9.4%	2.9%	—	4.34	22.0%	13.1%	29	-0.17	—	—	—
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	92
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	91
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	90
Michael Gomez R 2019 · 3.32 FIP	22	SU	3.32	22.6%	9.2%	1.8%	.283	3.81	17.9%	8.3%	110	+0.49	3.27	286	90
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	89
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	89
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	88
David Garner R 2015 · 3.81 FIP	22	SU	3.81	21.7%	10.0%	2.3%	.282	4.52	19.8%	5.2%	98	+0.71	3.81	154	87
Tyler Bray R 2015 · 4.07 FIP	23	SU	4.07	22.3%	9.1%	3.1%	.356	3.21	17.9%	7.6%	114	-0.86	2.82	152	87
Reece Karalus R 2016 · 4.80 FIP	22	SU	4.80	18.5%	8.6%	4.0%	.298	4.81	14.8%	4.1%	103	+0.01	4.73	149	87
Corey Copping R 2016 · 4.13 FIP	22	SU	4.13	21.4%	8.7%	3.1%	.265	4.55	19.6%	6.7%	179	+0.42	3.38	214	86
Matt Pidich R 2018 · 4.42 FIP	23	SU	4.42	17.1%	8.3%	3.1%	.303	4.08	20.8%	13.3%	115	-0.34	4.05	196	86
Devon Roedahl R 2019 · 3.94 FIP	22	SU	3.94	19.7%	6.7%	3.0%	.305	4.64	16.5%	9.2%	100	+0.70	3.94	122	86
Luke Bell R 2024 · 3.62 FIP	23	SU	3.62	20.4%	9.9%	1.8%	.295	5.69	13.1%	1.3%	66	+2.07	3.62	110	86
Ricardo Velez R 2023 · 4.44 FIP	24	SU	4.44	22.4%	10.9%	3.4%	.261	4.09	18.8%	8.1%	138	-0.35	3.83	166	86
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	85
Peyton Williams R 2021 · 3.69 FIP	23	SU	3.69	22.3%	10.3%	2.1%	.311	4.82	22.2%	10.2%	100	+1.13	3.69	123	85
Collin Kober R 2017 · 3.39 FIP	22	SU	3.39	21.3%	7.5%	2.1%	.268	2.76	24.0%	17.9%	128	-0.63	2.38	294	85
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	85
Josh Advocate R 2018 · 3.78 FIP	24	SU	3.78	18.8%	7.3%	2.4%	.291	3.71	20.4%	10.1%	75	-0.07	3.71	118	85