Jeyson Bautista

P DSL Rangers Red

Age 20 RHP ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	19	ROKDSL Rangers R…	14	20	11.44	6.00	18.8%	17.9%	—	K 12.8% · BB 22.3% · FIP 6.91
2027PROJ	20	MLB—	11	12	5.77	5.77	20.1%	18.4%	-0.2
2028PROJ49% MLB	21	MLB—	10	10	5.44	5.32	20.9%	15.7%	-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) · Elison Joseph (age 20) · Hudson Leach (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 143135vR 126

ERA5.77

FIP5.77

K%20.1%

BB%18.4%

K-BB%1.7%

Proj IP12

Value2027 · WAR

Runs saved vs league avg · 12 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	19	ROK MLE	DSL Rangers Red	14	0	20	112	21	20	3	0%	1.4	12.8%	22.3%	-9.6%	3.8%	11.44	6.91	—
2026	19	ROK MLE	DSL Rangers Red	14	0	20	112	21	20	3	0%	1.4	12.8%	22.3%	-9.6%	3.8%	11.44	6.91	—
2026	19	ROK RAW	DSL Rangers Red	14	0	20	112	21	20	3	0%	1.4	18.8%	17.9%	0.9%	2.7%	11.44	6.00	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	20	MLB	—	11	0	12	51	10	9	2	0%	1.1	20.1%	18.4%	1.7%	3.0%	5.77	5.77	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	21	MLB MLE	—	19	0	20	84	18	13	3	0%	1.1	20.9%	15.7%	5.3%	3.0%	5.44	5.32	-0.2
2028	21	MLB CTX	—	10	0	10	42	9	7	1	0%	1.0	20.9%	15.7%	5.3%	3.0%	5.44	5.32	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	0	10	42	9	7	1	0%	1.1	20.9%	15.7%	5.3%	3.0%	5.44	4.94	-0.0
/ 200 IP	—	RAW		190	0	200	844	183	142	20	0%	1.1	20.9%	15.7%	5.3%	3.0%	5.44	4.94	-0.9
Career	—	MLE		14	0	20	112	14	25	4	0%	1.4	12.8%	22.3%	-9.6%	3.8%	11.44	6.91	-0.2
/ 200 IP	—	MLE		142	0	200	1139	145	254	43	0%	1.4	12.8%	22.3%	-9.6%	3.8%	11.44	6.91	-1.8

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
Jeyson Bautista (OGILVIE)	—	—	5.77	20.1%	18.4%	3.0%	—	5.32	20.9%	5.3%	20	-0.45	—	—	—
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	89
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	87
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	87
Daniel Lloyd R 2021 · 5.40 FIP	20	SU	5.40	20.4%	22.4%	2.2%	.367	4.15	18.0%	8.5%	226	-1.25	3.59	319	86
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	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	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
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	85
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	85
Jordy Luciano R 2022 · 4.97 FIP	21	SU	4.97	24.9%	22.3%	2.1%	.306	5.33	17.1%	-4.8%	80	+0.36	4.97	104	85
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	84
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	84
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	84
Adrian Rodriguez R 2021 · 6.92 FIP	20	SU	6.92	23.1%	34.0%	2.7%	.368	5.46	23.1%	-1.6%	93	-1.46	2.43	148	83
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	83
Adonis Villavicencio R 2022 · 4.65 FIP	21	SU	4.65	21.5%	21.9%	1.1%	.316	3.93	18.0%	3.9%	90	-0.72	3.21	115	83
Conor Grady R 2021 · 5.28 FIP	22	SU	5.28	17.2%	19.0%	2.2%	.242	4.62	16.9%	5.1%	96	-0.66	4.62	108	82
José Mesa Jr. R 2016 · 5.41 FIP	22	SU	5.41	22.4%	17.2%	3.7%	.311	4.00	22.8%	9.6%	113	-1.41	3.33	176	82
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	82
Johan Quezada R 2015 · 4.65 FIP	20	SU	4.65	18.0%	17.2%	1.6%	.255	4.39	14.1%	-3.0%	53	-0.26	3.78	234	82