Elieser Hernández

P Gwinnett Stripers

Age 32 RHP 6'1" / 214 lbs AAA

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MIX2 levels	15	6	44	4.06	4.14	23.6%	7.3%	0.2	K 20.9% · BB 6.9% · FIP 4.43
2025	30	AAATOR	4	4	19	7.91	3.31	18.5%	8.6%	—	K 15.9% · BB 7.8% · FIP 3.62
2026	31	MIX2 levels	30	12	97	4.35	4.64	21.5%	7.7%	-0.1	K 19.0% · BB 7.0% · FIP 4.95
2027PROJ	32	MLBATL	25	25	150	4.63	4.92	18.7%	7.2%	0.8
2028PROJ95% MLB	33	MLBATL	18	18	105	4.97	5.20	17.9%	7.6%	0.2
2029PROJ90% MLB	34	MLBATL	13	13	78	5.29	5.50	17.0%	8.1%	-0.1

Last 3 seasons WAR 0.1 · Next 3 projected WAR 1.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs90

K%62

FB Velo18

CompsElian Leyva (age 30) · Mike Burns (age 31) · Zack Segovia (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 127119vR 110

ERA4.63

FIP4.92

K%18.7%

BB%7.2%

K-BB%11.6%

Proj IP150

Value2027 · WAR

Runs saved vs league avg · 150 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1892.2

Whiff%

p7629.3%

p6224.5%

xwOBA vs

p900.259

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 the standard WAR scale.

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	20	A MLE	Quad Cities River Bandits	10	7	46	199	46	11	3	70%	4.6	17.1%	6.5%	10.6%	1.9%	3.94	3.52	—
2015	20	A RAW	Quad Cities River Bandits	10	7	46	199	46	11	3	70%	4.6	23.1%	5.5%	17.6%	1.5%	3.94	2.66	—
2016	21	MIX MLE	2 levels	24	19	108	473	107	35	14	79%	4.5	17.0%	8.6%	8.4%	3.2%	4.51	4.52	—
2016	21	MIX RAW	2 levels	24	19	108	473	107	35	14	79%	4.5	22.6%	7.4%	15.2%	3.0%	4.51	3.78	—
2017	22	MIX MLE	2 levels	18	13	73	300	88	22	6	72%	4.1	21.6%	9.1%	12.4%	2.8%	3.68	3.99	—
2017	22	MIX RAW	2 levels	18	13	73	300	88	22	6	72%	4.1	29.3%	7.3%	22.0%	2.0%	3.68	2.66	—
2018	23	MIX MLE	4 levels	37	11	83	364	62	32	17	30%	2.3	15.8%	8.5%	7.4%	4.1%	5.18	5.07	-0.5
2018	23	MIX RAW	4 levels	37	11	83	364	62	32	17	30%	2.3	17.0%	8.8%	8.2%	4.7%	5.18	5.42	-0.8
2019	24	MIX MLE	2 levels	30	24	130	554	154	39	20	80%	4.3	26.3%	7.2%	19.1%	3.8%	3.59	3.87	+2.4
2019	24	MIX RAW	2 levels	30	24	130	554	154	39	20	80%	4.3	27.8%	7.0%	20.8%	3.6%	3.59	3.63	+2.8
2020	25	MLB MLE	Miami Marlins	6	6	26	106	34	5	5	100%	4.3	32.1%	4.7%	27.4%	5.0%	3.16	3.71	+0.5
2020	25	MLB RAW	Miami Marlins	6	6	26	106	34	5	5	100%	4.3	32.1%	4.7%	27.4%	4.7%	3.16	3.57	+0.6
2021	26	MIX MLE	3 levels	17	17	76	312	88	15	16	100%	4.5	26.9%	5.0%	21.9%	5.8%	3.69	4.63	+0.7
2021	26	MIX RAW	3 levels	17	17	76	312	88	15	16	100%	4.5	28.2%	4.8%	23.4%	5.1%	3.69	4.12	+1.1
2022	27	MIX MLE	4 levels	34	23	121	521	131	38	27	68%	3.6	23.3%	7.6%	15.8%	5.6%	5.19	5.14	+0.4
2022	27	MIX RAW	4 levels	34	23	121	521	131	38	27	68%	3.6	25.1%	7.3%	17.9%	5.2%	5.19	4.77	+0.9
2023	28	MIX MLE	3 levels	8	4	9	42	12	4	2	50%	1.2	28.6%	9.5%	19.0%	4.8%	2.89	4.51	—
2023	28	MIX RAW	3 levels	8	4	9	42	12	4	2	50%	1.2	28.6%	9.5%	19.0%	4.8%	2.89	4.60	—
2024	29	MIX MLE	2 levels	15	6	44	178	42	13	7	40%	3.0	20.9%	6.9%	14.1%	4.1%	4.06	4.43	+0.1
2024	29	MIX MLE	2 levels	15	6	44	178	42	13	7	40%	3.0	20.9%	6.9%	14.1%	4.1%	4.06	4.43	+0.1
2024	29	MIX RAW	2 levels	15	6	44	178	42	13	7	40%	3.0	23.6%	7.3%	16.3%	3.9%	4.06	4.14	+0.2
2025	30	AAA MLE	Buffalo Bisons	4	4	19	81	15	7	1	100%	4.8	15.9%	7.8%	8.1%	1.6%	7.91	3.62	—
2025	30	AAA MLE	Buffalo Bisons	4	4	19	81	15	7	1	100%	4.8	15.9%	7.8%	8.1%	1.6%	7.91	3.62	—
2025	30	AAA RAW	Buffalo Bisons	4	4	19	81	15	7	1	100%	4.8	18.5%	8.6%	9.9%	1.2%	7.91	3.31	—
2026	31	MIX MLE	2 levels	30	12	97	418	90	32	18	40%	3.2	19.0%	7.0%	11.9%	4.7%	4.35	4.95	-0.4
2026	31	MIX MLE	2 levels	30	12	97	418	90	32	18	40%	3.2	19.0%	7.0%	11.9%	4.7%	4.35	4.95	-0.4
2026	31	MIX RAW	2 levels	30	12	97	418	90	32	18	40%	3.2	21.5%	7.7%	13.9%	4.3%	4.35	4.64	-0.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			104	49	315	1363	298	97	76	47%	3.0	21.9%	7.1%	14.7%	5.6%	4.99	5.27	-2.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	ATL	25	25	150	633	119	45	24	100%	6.0	18.7%	7.2%	11.6%	3.8%	4.63	4.92	+0.8
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	ATL	18	18	110	465	83	35	19	100%	6.1	17.9%	7.6%	10.3%	4.1%	4.97	5.20	+0.2
2029	34	MLB MLE	ATL	14	14	86	364	62	30	16	100%	6.2	17.0%	8.1%	8.9%	4.4%	5.29	5.50	-0.1
2028	33	MLB CTX	ATL	18	18	105	443	79	34	18	100%	5.8	17.9%	7.6%	10.3%	4.1%	4.97	5.20	+0.2
2029	34	MLB CTX	ATL	13	13	78	329	56	27	15	100%	6.0	17.0%	8.1%	8.9%	4.4%	5.29	5.50	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		134	79	498	2134	433	157	109	59%	3.7	20.3%	7.4%	12.9%	5.1%	5.04	5.12	+1.6
/ 200 IP	—	RAW		54	32	200	857	174	63	44	59%	3.7	20.3%	7.4%	12.9%	5.1%	5.04	5.12	+0.6
Career	—	MLE		233	146	833	3548	763	263	146	63%	3.6	21.5%	7.4%	14.1%	4.1%	4.33	4.48	+0.6
/ 200 IP	—	MLE		56	35	200	852	183	63	35	63%	3.6	21.5%	7.4%	14.1%	4.1%	4.33	4.48	+0.2

How the minor-league lines were translated

One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.

2026 AAAGwinnett Stripers · 85 IPFIP 4.51 → 4.89 (+0.38)K% 21.1% → 18.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.10%	—	×0.860	18.14%
BB% (unintentional) /BF	7.40%	—	×0.900	6.66%
HR / BF /BF	4.11%	÷1.000	×1.100	4.52%

Factors used: pitcher AAA level factors (Triple-A 2023+ robo-zone set: walks improve on promotion) — K ×0.86, BB ×0.90, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 100).

Result: FIP 4.51 → 4.89, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2025 AAABuffalo Bisons · 19 IPFIP 3.31 → 3.62 (+0.31)K% 18.5% → 15.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.52%	—	×0.860	15.93%
BB% (unintentional) /BF	8.64%	—	×0.900	7.78%
HR / BF /BF	1.23%	÷0.847	×1.100	1.60%

Result: FIP 3.31 → 3.62, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2024 AAAOklahoma City Baseball Club · 29 IPFIP 2.43 → 2.92 (+0.48)K% 29.8% → 25.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.82%	—	×0.860	25.65%
BB% (unintentional) /BF	7.02%	—	×0.900	6.32%
HR / BF /BF	1.75%	÷0.896	×1.100	2.15%

Result: FIP 2.43 → 2.92, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2022 AAAJacksonville Jumbo Shrimp · 57 IPFIP 3.44 → 3.90 (+0.46)K% 28.8% → 25.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.81%	—	×0.880	25.36%
BB% (unintentional) /BF	7.20%	—	×1.050	7.56%
HR / BF /BF	3.39%	÷1.032	×1.100	3.61%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 106).

Result: FIP 3.44 → 3.90, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2021 AAAJacksonville Jumbo Shrimp · 21 IPFIP 2.22 → 3.18 (+0.96)K% 41.6% → 36.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.56%	—	×0.880	36.57%
BB% (unintentional) /BF	3.90%	—	×1.050	4.09%
HR / BF /BF	3.90%	÷0.886	×1.100	4.84%

Result: FIP 2.22 → 3.18, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2019 AAANew Orleans Baby Cakes · 48 IPFIP 1.08 → 1.48 (+0.39)K% 34.3% → 30.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.33%	—	×0.880	30.21%
BB% (unintentional) /BF	6.97%	—	×1.050	7.31%
HR / BF /BF	0.00%	÷1.100	×1.100	0.00%

Result: FIP 1.08 → 1.48, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2018 AAJacksonville Jumbo Shrimp · 9 IPFIP 6.74 → 8.02 (+1.28)K% 27.8% → 22.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.78%	—	×0.810	22.50%
BB% (unintentional) /BF	11.11%	—	×1.100	12.22%
HR / BF /BF	8.33%	÷1.041	×1.200	9.60%

Factors used: pitcher AA level factors — K ×0.81, BB ×1.10, HR ×1.20. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 108).

Result: FIP 6.74 → 8.02, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2018 A+Jupiter Hammerheads · 6 IPFIP 6.91 → 9.14 (+2.23)K% 16.1% → 12.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.13%	—	×0.770	12.42%
BB% (unintentional) /BF	12.90%	—	×1.150	14.84%
HR / BF /BF	6.45%	÷0.850	×1.250	9.49%

Factors used: pitcher A+ level factors — K ×0.77, BB ×1.15, HR ×1.25. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 70).

Result: FIP 6.91 → 9.14, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

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
Elieser Hernández (OGILVIE)	—	—	—	—	—	3.8%	—	5.33	17.5%	9.7%	196	+0.41	—	—	—
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	72
Mike Burns R 2009 · 4.90 FIP	31	SP-	4.90	17.2%	6.6%	4.4%	.307	—	—	—	—	—	3.10	104	69
Zack Segovia R 2015 · 4.78 FIP	32	SP	4.78	15.0%	8.3%	3.4%	.314	3.33	20.2%	14.3%	39	-1.45	3.33	144	67
Marco Quevedo R 2019 · 5.17 FIP	32	SP-	5.17	13.6%	11.4%	3.2%	.344	—	—	—	—	—	4.13	300	65
Thad Weber R 2017 · 5.25 FIP	32	SP-	5.25	13.2%	4.4%	4.9%	.398	—	—	—	—	—	4.40	378	62
Yohan Pino R 2015 · 4.13 FIP	31	SP-	4.13	17.8%	5.8%	3.3%	.312	5.33	15.2%	11.6%	35	+1.20	3.84	193	60
Reinier Roibal R 2019 · 4.91 FIP	30	SP	4.91	17.5%	11.8%	3.3%	.426	—	—	—	—	—	3.11	133	60
Juan Omar Espinoza R 2016 · 4.84 FIP	32	SP-	4.84	8.4%	9.2%	2.4%	.348	—	—	—	—	—	4.81	104	60
Elih Villanueva R 2017 · 5.48 FIP	31	SP	5.48	14.1%	6.0%	5.1%	.365	—	—	—	—	—	3.83	225	60
Jesus Adrian Castillo R 2016 · 3.88 FIP	32	SP	3.88	12.8%	6.0%	2.0%	.245	4.27	13.6%	7.2%	58	+0.39	2.23	173	59
Danny Gutierrez R 2017 · 4.11 FIP	30	SP	4.11	15.1%	6.1%	2.8%	.362	—	—	—	—	—	3.34	239	58
Sergio Valenzuela R 2017 · 5.66 FIP	32	SP	5.66	10.6%	6.5%	4.8%	.355	—	—	—	—	—	3.66	244	57
Miguel Ruiz R 2017 · 5.60 FIP	31	SP	5.60	10.6%	11.0%	3.6%	.279	—	—	—	—	—	5.60	117	57
Todd Redmond R 2015 · 3.86 FIP	30	SW	3.86	15.4%	7.1%	2.1%	.311	—	—	—	—	—	3.21	247	57
Osvaldo Fernandez R 2001 · 4.53 FIP	32	SP-	4.53	9.6%	8.2%	2.2%	.324	—	—	—	—	—	4.25	387	56
Brandon Beachy R 2019 · 4.19 FIP	32	SP	4.19	17.4%	9.5%	2.5%	.315	—	—	—	—	—	1.97	364	55
Aaron Brooks R 2022 · 4.38 FIP	32	SP	4.38	15.8%	7.0%	3.1%	.332	4.45	14.2%	7.5%	245	+0.07	3.71	879	54
Tyler Cloyd R 2019 · 5.21 FIP	32	SP	5.21	18.9%	9.5%	4.6%	.388	—	—	—	—	—	3.89	343	53
Bryan Evans R 2019 · 3.89 FIP	32	SP	3.89	18.7%	10.4%	1.9%	.450	—	—	—	—	—	3.89	231	53
Rob Wooten R 2017 · 5.15 FIP	32	SP	5.15	21.2%	4.9%	5.9%	.394	4.38	15.5%	12.5%	43	-0.77	2.48	253	53

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	3.3	83	19.9%	7.6%	1.85	4.95
Bill Faul ('62-'70, -1 WAR*)	1.3	87	18.8%*	9.1%*	1.82*	5.41*
Sergio Valdez ('86-'95, -2 WAR*)	1.5	61	18.1%*	8.0%*	1.79*	5.46*
Jackson Todd ('77-'81, 1 WAR*)	1.4	72	17.5%*	7.1%*	1.69*	4.65*
Sam Gaviglio ('20)	1.5	99	19.1%	7.2%	1.67	4.88
Luke Prokopec ('02)	1.2	77	14.1%	7.3%	1.87	5.30
Alec Mills ('23)	1.3	86	19.3%	7.2%	1.50	5.00