Jean Henriquez

P Chesapeake Baysox

Age 34 RHP 6'3" / 231 lbs AA

Overview

AAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2015	22	ROKTB	15	0	28	3.90	3.53	13.7%	8.9%	—	K 9.3% · BB 11.1% · FIP 4.34
2026	33	AABAL	7	0	9	14.46	5.03	26.0%	12.0%	—	K 21.1% · BB 13.2% · FIP 5.63
2027PROJ	34	MLBBAL	5	0	5	4.73	4.73	22.3%	11.2%	-0.0
2028PROJ0% MLB	35	MLBBAL	—	—	0	4.87	4.99	21.8%	11.6%	—

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%

CompsDiego Moreno (age 34) · Leo Rosales (age 34) · Keiichi Yabu (age 36)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 123115vR 107

ERA4.73

FIP4.73

K%22.3%

BB%11.2%

K-BB%11.0%

Proj IP5

Value2027 · WAR

Runs saved vs league avg · 5 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)
2015	22	ROK MLE	DSL Rays	15	0	28	124	17	11	1	0%	1.8	9.3%	11.1%	-1.8%	1.1%	3.90	4.34	—
2015	22	ROK RAW	DSL Rays	15	0	28	124	17	11	1	0%	1.8	13.7%	8.9%	4.8%	0.8%	3.90	3.53	—
2026	33	AA MLE	Chesapeake Baysox	7	0	9	50	13	6	2	0%	1.3	21.1%	13.2%	7.9%	4.8%	14.46	5.63	—
2026	33	AA MLE	Chesapeake Baysox	7	0	9	50	13	6	2	0%	1.3	21.1%	13.2%	7.9%	4.8%	14.46	5.63	—
2026	33	AA RAW	Chesapeake Baysox	7	0	9	50	13	6	2	0%	1.3	26.0%	12.0%	14.0%	4.0%	14.46	5.03	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	BAL	5	0	5	21	5	2	1	0%	1.0	22.3%	11.2%	11.0%	3.1%	4.73	4.73	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	BAL	19	0	20	84	18	10	3	0%	1.1	21.8%	11.6%	10.2%	3.4%	4.87	4.99	-0.1
2028	35	MLB CTX	BAL	—	—	0	—	—	—	—	—	—	21.8%	11.6%	10.2%	3.4%	4.87	4.99	—
▸ Career totals — MLB only (actual + projected)
Career	—	MLE		22	0	37	174	22	20	4	0%	1.7	12.7%	11.7%	1.0%	2.2%	6.57	4.71	-0.1
/ 200 IP	—	MLE		119	0	200	941	119	110	21	0%	1.7	12.7%	11.7%	1.0%	2.2%	6.57	4.71	-1.0

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
Jean Henriquez (OGILVIE)	—	—	4.73	22.3%	11.2%	3.1%	—	4.99	21.8%	10.2%	20	+0.26	—	—	—
Diego Moreno R 2021 · 4.75 FIP	34	SU	4.75	18.6%	9.4%	3.7%	.232	—	—	—	—	—	2.29	187	80
Leo Rosales R 2015 · 3.99 FIP	34	SU	3.99	18.1%	10.8%	1.9%	.261	4.24	7.8%	-0.4%	22	+0.25	3.85	130	76
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	75
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	74
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	74
Jim Miller R 2016 · 5.43 FIP	34	SU	5.43	20.4%	14.1%	4.1%	.347	—	—	—	—	—	3.95	140	72
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	72
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	71
Carlos Fisher R 2017 · 3.91 FIP	34	SU	3.91	18.1%	12.9%	1.3%	.333	—	—	—	—	—	2.48	245	69
Juan Sandoval R 2015 · 3.82 FIP	34	SU	3.82	15.4%	6.0%	2.3%	.294	3.33	17.4%	8.8%	116	-0.49	3.24	225	68
Josh Lueke R 2019 · 4.11 FIP	34	SU	4.11	20.4%	6.4%	3.5%	.311	—	—	—	—	—	2.29	191	68
Austin Adams R 2019 · 5.80 FIP	32	SU	5.80	20.8%	10.6%	5.7%	.280	—	—	—	—	—	3.40	162	68
Hector Navarro R 2015 · 4.35 FIP	35	SU	4.35	15.0%	5.4%	3.3%	.281	3.00	15.2%	9.0%	81	-1.35	2.30	126	68
Rudy Gonzalez R 2015 · 4.52 FIP	34	SW	4.52	13.5%	9.6%	2.4%	.347	3.84	14.0%	6.5%	79	-0.68	3.31	119	67
Jean Machi R 2016 · 4.36 FIP	34	SU	4.36	18.3%	6.6%	3.6%	.282	4.12	18.6%	12.0%	67	-0.24	2.16	306	67
Willie Eyre R 2011 · 4.18 FIP	33	SU	4.18	13.9%	6.9%	2.5%	.182	—	—	—	—	—	2.87	164	66
Matt Bush R 2018 · 4.72 FIP	32	SU	4.72	17.6%	13.0%	2.7%	.278	—	—	—	—	—	2.87	249	66
Scott McGough R 2024 · 4.56 FIP	34	SU	4.56	18.6%	12.2%	2.7%	.289	3.82	20.3%	13.1%	57	-0.74	3.55	429	65
Rafael Dolis R 2022 · 3.61 FIP	34	SU	3.61	19.9%	11.9%	1.2%	.275	—	—	—	—	—	2.80	200	65
Fernando Rodriguez Jr. R 2018 · 4.07 FIP	34	SW	4.07	23.7%	9.9%	3.1%	.253	5.11	25.0%	13.8%	32	+1.04	3.34	335	65