Alix Hernandez

P San Jose Giants

Age 23 RHP 6'2" / 182 lbs A

Overview

APROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	20	MIX2 levels	21	1	50	4.71	3.58	29.1%	13.5%	—	K 21.7% · BB 13.7% · FIP 4.44
2025	21	ROKSF	12	0	14	2.51	1.91	42.9%	10.7%	—	K 29.1% · BB 13.4% · FIP 3.55
2026	22	MIX2 levels	35	0	63	4.26	4.09	28.9%	9.5%	—	K 21.6% · BB 11.2% · FIP 5.53
2027PROJ	23	MLBSF	30	0	32	4.87	4.87	22.1%	11.3%	-0.1
2028PROJ43% MLB	24	MLBSF	24	0	25	4.72	4.66	22.7%	10.4%	-0.0
2029PROJ66% MLB	25	MLBSF	37	0	39	4.60	4.54	23.2%	9.8%	0.0

Next 3 projected WAR -0.1Projected 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 95%

CompsHeath Holder (age 23) · Tyler Mitzel (age 23) · Colby Morris (age 24)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 126118vR 109

ERA4.87

FIP4.87

K%22.1%

BB%11.3%

K-BB%10.8%

Proj IP32

Value2027 · WAR

Runs saved vs league avg · 32 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)
2023	19	ROK MLE	ACL Giants Orange	14	5	51	216	69	27	6	36%	3.7	21.7%	15.6%	6.1%	2.8%	4.73	4.80	—
2023	19	ROK RAW	ACL Giants Orange	14	5	51	216	69	27	6	36%	3.7	31.9%	12.5%	19.4%	2.8%	4.73	3.51	—
2024	20	MIX MLE	2 levels	21	1	50	230	67	31	5	5%	2.4	21.7%	13.7%	7.9%	2.6%	4.71	4.44	—
2024	20	MIX MLE	2 levels	21	1	50	230	67	31	5	5%	2.4	21.7%	13.7%	7.9%	2.6%	4.71	4.44	—
2024	20	MIX RAW	2 levels	21	1	50	230	67	31	5	5%	2.4	29.1%	13.5%	15.7%	2.2%	4.71	3.58	—
2025	21	ROK MLE	ACL Giants	12	0	14	56	24	6	1	0%	1.2	29.1%	13.4%	15.8%	2.2%	2.51	3.55	—
2025	21	ROK MLE	ACL Giants	12	0	14	56	24	6	1	0%	1.2	29.1%	13.4%	15.8%	2.2%	2.51	3.55	—
2025	21	ROK RAW	ACL Giants	12	0	14	56	24	6	1	0%	1.2	42.9%	10.7%	32.1%	1.8%	2.51	1.91	—
2026	22	MIX MLE	2 levels	35	0	63	273	79	26	11	0%	1.8	21.6%	11.2%	10.5%	5.2%	4.26	5.53	—
2026	22	MIX MLE	2 levels	35	0	63	273	79	26	11	0%	1.8	21.6%	11.2%	10.5%	5.2%	4.26	5.53	—
2026	22	MIX RAW	2 levels	35	0	63	273	79	26	11	0%	1.8	28.9%	9.5%	19.4%	4.0%	4.26	4.09	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	23	MLB	SF	30	0	32	135	30	15	4	0%	1.1	22.1%	11.3%	10.8%	3.3%	4.87	4.87	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	24	MLB MLE	SF	56	0	58	247	56	26	8	0%	1.0	22.7%	10.4%	12.3%	3.3%	4.72	4.66	-0.1
2029	25	MLB MLE	SF	56	0	59	250	58	25	8	0%	1.1	23.2%	9.8%	13.3%	3.2%	4.60	4.54	+0.0
2030	26	MLB MLE	SF	56	0	59	250	58	24	8	0%	1.1	23.4%	9.8%	13.6%	3.2%	4.54	4.51	+0.0
2031	27	MLB MLE	SF	55	0	58	246	57	24	8	0%	1.1	23.4%	9.8%	13.5%	3.3%	4.54	4.54	+0.0
2028	24	MLB CTX	SF	24	0	25	106	24	11	3	0%	1.0	22.7%	10.4%	12.3%	3.3%	4.72	4.66	-0.0
2029	25	MLB CTX	SF	37	0	39	165	38	16	5	0%	1.1	23.2%	9.8%	13.3%	3.2%	4.60	4.54	+0.0
2030	26	MLB CTX	SF	45	0	47	198	46	19	6	0%	1.0	23.4%	9.8%	13.6%	3.2%	4.54	4.51	+0.0
2031	27	MLB CTX	SF	48	0	50	211	49	21	7	0%	1.0	23.4%	9.8%	13.5%	3.3%	4.54	4.54	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		153	0	161	678	157	67	22	0%	1.0	23.2%	9.9%	13.3%	3.2%	4.58	4.17	+0.7
/ 200 IP	—	RAW		190	0	200	844	196	83	27	0%	1.1	23.2%	9.9%	13.3%	3.2%	4.58	4.17	+0.9
Career	—	MLE		82	6	179	775	172	103	28	7%	2.2	22.2%	13.3%	8.9%	3.5%	4.38	4.86	-0.0
/ 200 IP	—	MLE		92	7	200	868	193	116	31	7%	2.2	22.2%	13.3%	8.9%	3.5%	4.38	4.86	-0.0

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
Alix Hernandez (OGILVIE)	—	—	4.87	22.1%	11.3%	3.3%	—	4.57	23.1%	13.1%	177	-0.30	—	—	—
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	90
Tyler Mitzel R 2019 · 4.34 FIP	23	SU	4.34	24.1%	12.0%	3.2%	.245	4.10	22.4%	14.3%	96	-0.24	4.03	142	89
Colby Morris R 2021 · 4.11 FIP	24	SU	4.11	20.4%	10.7%	2.5%	.291	5.76	16.2%	4.4%	54	+1.65	4.11	105	89
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	88
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	87
Ryan Conroy R 2021 · 4.01 FIP	24	SU	4.01	22.2%	9.8%	2.8%	.353	4.75	19.3%	6.7%	54	+0.74	4.01	106	86
Kyle Marman R 2019 · 3.97 FIP	22	SU	3.97	22.2%	12.8%	2.0%	.270	5.16	22.5%	8.4%	71	+1.19	3.97	117	86
Kyle Schepel R 2015 · 4.63 FIP	24	SU	4.63	23.1%	10.7%	3.9%	.233	3.64	22.1%	10.4%	120	-0.99	3.54	156	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	86
Luis Romero R 2017 · 5.00 FIP	23	SU	5.00	22.1%	11.9%	4.1%	.367	4.26	21.6%	12.5%	132	-0.74	4.00	293	86
Harrison Cohen R 2023 · 4.56 FIP	24	SU	4.56	22.4%	13.4%	3.0%	.282	4.18	22.3%	9.0%	119	-0.38	2.12	165	86
Cole Gordon R 2019 · 4.09 FIP	23	SU	4.09	22.0%	12.7%	2.3%	.243	5.19	20.9%	9.5%	83	+1.10	4.09	112	86
Brandyn Sittinger R 2017 · 4.37 FIP	23	SU	4.37	22.2%	13.8%	2.5%	.324	3.97	21.2%	7.2%	72	-0.40	3.58	152	86
Luis Eusebio R 2019 · 4.92 FIP	23	SU	4.92	18.2%	10.6%	3.7%	.295	—	—	—	—	—	4.79	131	85
Austin Ross R 2019 · 4.41 FIP	24	SU	4.41	20.7%	9.6%	3.4%	.281	5.19	21.2%	5.7%	55	+0.78	4.41	121	85
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	85
Sean Isaac R 2016 · 4.27 FIP	23	SU	4.27	19.5%	12.3%	2.3%	.342	3.76	25.0%	10.7%	128	-0.51	3.27	155	85
Jacob Dorris R 2016 · 4.16 FIP	23	SU	4.16	26.9%	12.4%	3.2%	.295	4.58	19.2%	8.8%	88	+0.42	4.16	130	85
Shane Broyles R 2015 · 3.91 FIP	23	SU	3.91	21.9%	11.5%	2.2%	.338	3.75	25.7%	14.5%	159	-0.16	3.34	218	85
Jonathan Papelbon R 2005 · 3.93 FIP	24	SW	3.93	23.0%	10.1%	2.7%	.305	1.90	31.3%	26.8%	196	-2.03	1.33	726	85

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,474 reliever careers (754 from 1990-2025 + 720 historical, 1901-2023), also matched on career-to-date at the same age. * Historical (Lahman) careers: rates era-adjusted to 2001-24 league levels; WAR is an OGILVIE proxy.

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	1.3	53	23.0%	10.1%	1.26	4.63
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
José Ruiz ('25)	1.4	57	22.3%	10.4%	1.44	4.62
Josias Manzanillo ('04)	1.7	57	20.0%	10.2%	1.21	4.71
Bill Scherrer ('82-'88, 1 WAR*)	1.6	62	20.7%*	10.2%*	1.19*	4.44*
Bill Pleis ('61-'66, -0 WAR*)	1.4	56	19.7%*	9.8%*	1.15*	4.53*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*