Roberto Mendoza

P DSL Tampa Bay

Age 20 RHP ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	19	ROKDSL Tampa Bay	18	24	4.56	3.78	14.7%	14.7%	—	K 10.0% · BB 18.3% · FIP 4.58
2027PROJ	20	MLB—	13	14	5.42	5.42	19.3%	15.6%	-0.1
2028PROJ49% MLB	21	MLB—	10	11	5.15	5.05	20.4%	13.6%	-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%

CompsMichael Perez (age 21) · Drew Pestka (age 20) · Tim Naughton (age 21)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 136128vR 120

ERA5.42

FIP5.42

K%19.3%

BB%15.6%

K-BB%3.8%

Proj IP14

Value2027 · WAR

Runs saved vs league avg · 14 IP

Grades · Contract

Scouting Grades

K†4550

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	19	ROK MLE	DSL Tampa Bay	18	0	24	109	16	16	0	0%	1.3	10.0%	18.3%	-8.4%	0.0%	4.56	4.58	—
2026	19	ROK MLE	DSL Tampa Bay	18	0	24	109	16	16	0	0%	1.3	10.0%	18.3%	-8.4%	0.0%	4.56	4.58	—
2026	19	ROK RAW	DSL Tampa Bay	18	0	24	109	16	16	0	0%	1.3	14.7%	14.7%	0.0%	0.0%	4.56	3.78	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	20	MLB	—	13	0	14	59	11	9	2	0%	1.1	19.3%	15.6%	3.8%	2.9%	5.42	5.42	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	21	MLB MLE	—	21	0	22	95	19	13	3	0%	1.1	20.4%	13.6%	6.8%	2.9%	5.15	5.05	-0.1
2028	21	MLB CTX	—	10	0	11	46	9	6	1	0%	1.1	20.4%	13.6%	6.8%	2.9%	5.15	5.05	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		10	0	11	46	9	6	1	0%	1.1	20.4%	13.6%	6.8%	2.9%	5.15	4.67	-0.0
/ 200 IP	—	RAW		190	0	200	844	163	109	18	0%	1.1	20.4%	13.6%	6.8%	2.9%	5.15	4.67	-0.3
Career	—	MLE		18	0	24	109	11	20	0	0%	1.3	10.0%	18.3%	-8.4%	0.0%	4.56	4.58	-0.1
/ 200 IP	—	MLE		152	0	200	921	92	169	0	0%	1.3	10.0%	18.3%	-8.4%	0.0%	4.56	4.58	-1.2

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
Roberto Mendoza (OGILVIE)	—	—	5.42	19.3%	15.6%	2.9%	—	5.05	20.4%	6.8%	22	-0.37	—	—	—
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	92
Drew Pestka R 2024 · 4.26 FIP	20	SU	4.26	19.0%	15.1%	1.6%	.298	4.55	18.1%	0.7%	83	+0.29	3.42	100	89
Tim Naughton R 2017 · 4.53 FIP	21	SU	4.53	17.9%	15.6%	1.8%	.312	3.58	20.7%	6.4%	83	-0.95	2.93	305	88
Tommy DeJuneas R 2017 · 4.72 FIP	21	SU	4.72	19.1%	15.5%	2.3%	.357	4.59	20.8%	4.9%	100	-0.13	3.93	178	88
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	87
Nick Kuzia R 2017 · 5.18 FIP	21	SU	5.18	16.5%	15.2%	2.8%	.361	5.35	17.6%	6.6%	60	+0.17	4.54	231	87
Tyler Smith R 2018 · 5.30 FIP	22	SU	5.30	17.8%	14.3%	3.4%	.329	4.35	19.8%	7.8%	94	-0.95	3.44	121	87
Gerson Moreno R 2016 · 4.48 FIP	20	SU	4.48	18.6%	14.8%	2.0%	.278	4.13	23.0%	9.1%	67	-0.35	3.37	349	86
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	86
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	85
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
Devon Fisher R 2016 · 4.39 FIP	20	SU	4.39	16.5%	12.5%	2.0%	.333	5.76	15.1%	0.9%	88	+1.37	4.39	102	85
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	85
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	85
Michael Brewer R 2021 · 4.30 FIP	20	SU	4.30	23.7%	16.2%	2.1%	.303	4.69	19.7%	6.3%	114	+0.39	3.14	144	85
Isaac Gallegos R 2024 · 4.40 FIP	21	SU	4.40	22.9%	17.8%	1.8%	.267	3.09	19.9%	10.5%	106	-1.31	2.89	125	85
Efrailin Ramos R 2024 · 4.31 FIP	18	SU	4.31	21.0%	15.7%	1.8%	.284	3.35	17.0%	6.4%	106	-0.96	3.11	142	84
Elison Joseph R 2021 · 5.31 FIP	20	SU	5.31	17.4%	19.2%	2.3%	.254	4.55	23.5%	6.8%	133	-0.76	3.32	217	84
Zack Hess R 2019 · 5.00 FIP	22	SU	5.00	18.1%	13.1%	3.2%	.232	5.47	22.9%	6.3%	50	+0.47	5.00	101	84
Adam Ravenelle R 2015 · 4.32 FIP	22	SU	4.32	19.6%	14.8%	1.8%	.322	5.06	17.1%	4.3%	130	+0.74	4.32	165	84