Wilkel Hernandez

P Toledo Mud Hens

Age 28 RHP 6'3" / 195 lbs AAA peak 0.6 · 2028

Overview

AAAPROSPECT

ETA2029MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	AADET	28	27	120	4.34	4.40	20.6%	10.5%	—	K 16.7% · BB 11.5% · FIP 5.29
2025	26	AAADET	34	19	114	4.80	4.17	19.3%	8.9%	—	K 16.6% · BB 8.0% · FIP 4.66
2027PROJ	28	MLBDET	1	1	8	5.12	5.12	15.7%	9.4%	0.0
2028PROJ37% MLB	29	MLBDET	4	4	26	4.94	4.89	18.1%	8.6%	0.2
2029PROJ55% MLB	30	MLBDET	6	6	33	4.97	5.02	18.2%	9.0%	0.1

Next 3 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control50Command45

CompsTravis Smith (age 29) · Luke Irvine (age 27) · Fabio Castillo (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 130122vR 114

ERA5.12

FIP5.12

K%15.7%

BB%9.4%

K-BB%6.3%

Proj IP80

Value2027 · WAR

Runs saved vs league avg · 80 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL5050

CMD4545

K†3045

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)
2016	17	ROK MLE	DSL Angels	5	5	15	61	14	6	0	100%	3.0	15.6%	12.3%	3.3%	0.0%	1.20	3.34	—
2016	17	ROK RAW	DSL Angels	5	5	15	61	14	6	0	100%	3.0	23.0%	9.8%	13.1%	0.0%	1.20	2.43	—
2017	18	ROK MLE	Orem Owlz	12	7	44	181	44	22	1	58%	3.7	16.5%	15.2%	1.3%	0.8%	2.64	4.05	—
2017	18	ROK RAW	Orem Owlz	12	7	44	181	44	22	1	58%	3.7	24.3%	12.2%	12.2%	0.6%	2.64	2.90	—
2018	19	A MLE	West Michigan Whitecaps	10	10	42	182	34	16	4	100%	4.2	13.8%	10.4%	3.5%	3.0%	4.71	4.91	—
2018	19	A RAW	West Michigan Whitecaps	10	10	42	182	34	16	4	100%	4.2	18.7%	8.8%	9.9%	2.2%	4.71	3.86	—
2019	20	A MLE	West Michigan Whitecaps	21	21	101	432	90	26	5	100%	4.8	15.4%	7.1%	8.3%	1.7%	3.73	3.62	—
2019	20	A RAW	West Michigan Whitecaps	21	21	101	432	90	26	5	100%	4.8	20.8%	6.0%	14.8%	1.2%	3.73	2.73	—
2022	23	A MLE	Lakeland Flying Tigers	14	13	44	189	51	16	4	93%	3.1	20.0%	10.0%	10.0%	2.2%	4.50	3.86	—
2022	23	A RAW	Lakeland Flying Tigers	14	13	44	189	51	16	4	93%	3.1	27.0%	8.5%	18.5%	2.1%	4.50	3.05	—
2023	24	A+ MLE	West Michigan Whitecaps	26	20	106	440	97	31	11	77%	4.1	17.0%	8.1%	8.9%	3.5%	3.65	4.64	—
2023	24	A+ RAW	West Michigan Whitecaps	26	20	106	440	97	31	11	77%	4.1	22.0%	7.0%	15.0%	2.5%	3.65	3.50	—
2024	25	AA MLE	Erie SeaWolves	28	27	120	524	108	55	16	96%	4.3	16.7%	11.5%	5.1%	3.9%	4.34	5.29	—
2024	25	AA MLE	Erie SeaWolves	28	27	120	524	108	55	16	96%	4.3	16.7%	11.5%	5.1%	3.9%	4.34	5.29	—
2024	25	AA RAW	Erie SeaWolves	28	27	120	524	108	55	16	96%	4.3	20.6%	10.5%	10.1%	3.1%	4.34	4.40	—
2025	26	AAA MLE	Toledo Mud Hens	34	19	114	497	96	44	14	56%	3.4	16.6%	8.0%	8.6%	3.6%	4.80	4.66	—
2025	26	AAA MLE	Toledo Mud Hens	34	19	114	497	96	44	14	56%	3.4	16.6%	8.0%	8.6%	3.6%	4.80	4.66	—
2025	26	AAA RAW	Toledo Mud Hens	34	19	114	497	96	44	14	56%	3.4	19.3%	8.9%	10.5%	2.8%	4.80	4.17	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	DET	1	1	8	34	5	3	1	100%	8.0	15.7%	9.4%	6.3%	3.2%	5.12	5.12	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	DET	12	12	70	294	53	25	10	100%	5.8	18.1%	8.6%	9.5%	3.4%	4.94	4.89	+0.4
2029	30	MLB MLE	DET	10	10	59	250	45	22	9	100%	5.9	18.2%	9.0%	9.2%	3.5%	4.97	5.02	+0.3
2028	29	MLB CTX	DET	4	4	26	110	20	9	4	100%	6.5	18.1%	8.6%	9.5%	3.4%	4.94	4.89	+0.2
2029	30	MLB CTX	DET	6	6	33	139	25	12	5	100%	5.5	18.2%	9.0%	9.2%	3.5%	4.97	5.02	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		10	10	58	246	45	22	8	100%	5.8	18.1%	8.8%	9.3%	3.5%	4.96	4.58	+0.6
/ 200 IP	—	RAW		33	33	200	844	155	76	27	100%	6.0	18.1%	8.8%	9.3%	3.5%	4.96	4.58	+1.9
Career	—	MLE		150	122	587	2506	414	239	72	81%	3.9	16.5%	9.5%	7.0%	2.9%	4.03	4.49	+0.7
/ 200 IP	—	MLE		51	42	200	853	141	81	24	81%	3.9	16.5%	9.5%	7.0%	2.9%	4.03	4.49	+1.0

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.

2025 AAAToledo Mud Hens · 114 IPFIP 4.14 → 4.66 (+0.52)K% 19.3% → 16.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.32%	—	×0.860	16.61%
BB% (unintentional) /BF	8.85%	—	×0.900	7.97%
HR / BF /BF	2.82%	÷0.872	×1.100	3.55%

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 74).

Result: FIP 4.14 → 4.66, 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 AAErie SeaWolves · 120 IPFIP 4.37 → 5.29 (+0.92)K% 20.6% → 16.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.61%	—	×0.810	16.69%
BB% (unintentional) /BF	10.50%	—	×1.100	11.55%
HR / BF /BF	3.05%	÷0.941	×1.200	3.89%

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 88).

Result: FIP 4.37 → 5.29, 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).

2023 A+West Michigan Whitecaps · 106 IPFIP 3.50 → 4.64 (+1.14)K% 22.0% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.05%	—	×0.770	16.98%
BB% (unintentional) /BF	7.05%	—	×1.150	8.10%
HR / BF /BF	2.50%	÷0.882	×1.250	3.54%

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 76).

Result: FIP 3.50 → 4.64, 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 ALakeland Flying Tigers · 44 IPFIP 3.06 → 3.86 (+0.80)K% 27.0% → 20.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.98%	—	×0.740	19.97%
BB% (unintentional) /BF	8.47%	—	×1.180	9.99%
HR / BF /BF	2.12%	÷1.279	×1.300	2.15%

Factors used: pitcher A level factors — K ×0.74, BB ×1.18, HR ×1.30. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 156).

Result: FIP 3.06 → 3.86, 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 AWest Michigan Whitecaps · 101 IPFIP 2.74 → 3.62 (+0.88)K% 20.8% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.83%	—	×0.740	15.42%
BB% (unintentional) /BF	6.02%	—	×1.180	7.10%
HR / BF /BF	1.16%	÷0.895	×1.300	1.68%

Result: FIP 2.74 → 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).

2018 AWest Michigan Whitecaps · 42 IPFIP 3.84 → 4.91 (+1.07)K% 18.7% → 13.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.68%	—	×0.740	13.82%
BB% (unintentional) /BF	8.79%	—	×1.180	10.37%
HR / BF /BF	2.20%	÷0.942	×1.300	3.03%

Result: FIP 3.84 → 4.91, 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).

2017 ROKOrem Owlz · 44 IPFIP 2.89 → 4.05 (+1.16)K% 24.3% → 16.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.31%	—	×0.680	16.53%
BB% (unintentional) /BF	12.15%	—	×1.250	15.19%
HR / BF /BF	0.55%	÷1.000	×1.400	0.77%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. 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 2.89 → 4.05, 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).

2016 ROKDSL Angels · 15 IPFIP 2.41 → 3.34 (+0.93)K% 23.0% → 15.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.95%	—	×0.680	15.61%
BB% (unintentional) /BF	9.84%	—	×1.250	12.30%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Result: FIP 2.41 → 3.34, 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
Wilkel Hernandez (OGILVIE)	—	—	5.12	15.7%	9.4%	3.2%	—	4.95	18.1%	9.3%	129	-0.17	—	—	—
Travis Smith R 2002 · 5.28 FIP	29	SP	5.28	13.1%	8.2%	4.1%	.324	5.71	15.0%	9.0%	51	+0.43	3.67	105	82
Luke Irvine R 2016 · 4.31 FIP	27	SP-	4.31	13.4%	9.8%	2.0%	.302	—	—	—	—	—	4.31	104	81
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	80
Shawn Haviland R 2015 · 3.95 FIP	29	SP-	3.95	14.6%	6.0%	2.4%	.303	4.67	16.1%	8.8%	169	+0.72	3.69	283	79
David Griffin R 2023 · 5.83 FIP	27	SP-	5.83	14.2%	9.2%	5.0%	.306	—	—	—	—	—	4.43	239	78
Frank Batista R 2015 · 4.29 FIP	26	SP-	4.29	12.1%	8.2%	2.1%	.280	—	—	—	—	—	4.29	118	78
Clay Condrey R 2003 · 5.41 FIP	27	SP-	5.41	14.9%	10.1%	4.2%	.303	4.07	13.1%	7.4%	29	-1.34	3.18	250	78
Vanny Valenzuela R 2016 · 4.54 FIP	28	SP	4.54	16.3%	11.3%	2.5%	.380	6.25	10.9%	1.2%	25	+1.71	3.26	118	77
Omar Bencomo R 2017 · 4.50 FIP	28	SP-	4.50	18.9%	6.3%	4.0%	.333	4.48	14.9%	10.1%	186	-0.02	3.70	381	77
Andres Ivan Meza R 2015 · 4.45 FIP	28	SP	4.45	10.9%	5.6%	2.9%	.322	4.14	12.5%	4.0%	85	-0.31	4.14	275	77
Scott McGregor R 2015 · 4.37 FIP	28	SP-	4.37	11.8%	7.6%	2.4%	.293	—	—	—	—	—	4.37	107	77
Miguel Ruiz R 2015 · 5.77 FIP	29	SP-	5.77	8.8%	8.0%	4.4%	.346	5.60	10.6%	-0.4%	53	-0.17	5.60	117	76
Travis Driskill R 2002 · 4.95 FIP	30	SP-	4.95	13.2%	8.0%	3.6%	.291	4.26	15.3%	12.0%	48	-0.69	4.26	181	75
Robert Ellis R 2001 · 4.84 FIP	30	SP	4.84	9.9%	7.7%	2.9%	.287	8.08	9.0%	-2.2%	18	+3.24	4.84	110	75
Tim Corcoran R 2006 · 4.67 FIP	28	SP-	4.67	14.9%	11.4%	2.5%	.291	5.29	7.6%	-3.8%	17	+0.62	4.10	130	74
Daniel Guerrero R 2016 · 4.81 FIP	31	SP	4.81	12.4%	11.6%	2.3%	.328	4.93	11.7%	2.0%	175	+0.12	4.61	269	74
Edgar Alberto Garcia R 2016 · 4.37 FIP	28	SP-	4.37	14.6%	9.8%	2.3%	.311	4.01	17.3%	6.4%	44	-0.36	4.01	272	74
Zach Stewart R 2015 · 4.43 FIP	28	SP-	4.43	14.4%	8.3%	2.7%	.322	5.17	11.7%	2.1%	51	+0.74	4.27	194	74
David Fletcher R 2024 · 5.67 FIP	30	SP-	5.67	7.5%	10.3%	3.5%	.294	—	—	—	—	—	5.67	100	74
Juan Omar Espinoza R 2015 · 4.81 FIP	31	SP-	4.81	8.9%	6.6%	3.0%	.346	4.84	8.4%	-0.8%	52	+0.03	4.81	104	74

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,234 reliever careers (754 from 1990-2025 + 480 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	1.0	70	17.2%	9.0%	1.30	5.02
Jose Cabrera ('02)	1.4	68	16.2%	7.9%	1.39	4.95
Buddy Carlyle ('15)	1.5	58	18.5%	8.5%	1.32	5.14
J. C. Ramirez ('13-'19, -0 WAR*)	1.4	72	15.1%*	8.7%*	1.30*	4.83*
Paul Reuschel ('75-'79, 1 WAR*)	2.0	79	16.8%*	7.6%*	1.29*	4.76*
John Morris ('66-'74, -0 WAR*)	1.2	58	18.3%*	8.2%*	1.00*	4.74*
Paul Gibson ('88-'96, 2 WAR*)	2.8	80	19.0%*	9.5%*	1.18*	4.37*