Enyel De Los Santos

P Houston Astros

Age 31 RHP 6'3" / 235 lbs MLB peak 0.1 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	28	MLBCWS	64	64	5.20	5.62	23.7%	8.6%	-0.8
2025	29	MLBHOU	65	66	4.36	3.60	22.1%	7.9%	0.7
2026	30	MIX3 levels	70	76	4.52	3.89	22.2%	6.0%	0.6	K 22.3% · BB 6.3% · FIP 4.08
2027PROJ	31	MLBHOU	56	59	4.42	4.32	23.2%	7.1%	0.2
2028PROJ	32	MLBHOU	42	44	4.51	4.57	22.4%	7.5%	-0.0
2029PROJ	33	MLBHOU	30	31	4.71	4.85	21.5%	8.0%	-0.1

Last 3 seasons WAR 0.5 · Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs77

FB Velo58

K%51

Form5.91 ERA (proj 4.42) · K 18.8% (proj 23.2%) · BB 8.3% (proj 7.1%) ▼ last 90d · 21 IP through Oct 27

CompsPedro Báez (age 31) · Chris Hatcher (age 31) · Carlos Torres (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10698vR 89

ERA4.42

FIP4.32

K%23.2%

BB%7.1%

K-BB%16.1%

Proj IP59

Value2027 · WAR

Runs saved vs league avg · 59 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p5895.1

Whiff%

p6227.1%

p5122.3%

xwOBA vs

p770.286

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	19	ROK MLE	AZL Mariners	5	5	25	103	29	5	1	100%	4.9	19.1%	6.1%	13.1%	1.4%	2.55	3.00	—
2015	19	ROK RAW	AZL Mariners	5	5	25	103	29	5	1	100%	4.9	28.2%	4.9%	23.3%	1.0%	2.55	1.88	—
2016	20	MIX MLE	2 levels	26	22	121	508	97	38	13	85%	4.7	14.4%	8.7%	5.8%	3.5%	3.72	4.90	—
2016	20	MIX RAW	2 levels	26	22	121	508	97	38	13	85%	4.7	19.1%	7.5%	11.6%	2.6%	3.72	3.84	—
2017	21	AA MLE	San Antonio Missions	26	24	150	617	138	47	12	92%	5.8	18.1%	8.4%	9.7%	2.5%	3.78	3.99	—
2017	21	AA RAW	San Antonio Missions	26	24	150	617	138	47	12	92%	5.8	22.4%	7.6%	14.7%	1.9%	3.78	3.24	—
2018	22	MIX MLE	2 levels	29	24	146	602	125	51	14	83%	5.0	18.6%	8.8%	9.7%	2.6%	2.90	4.08	+2.3
2018	22	MIX RAW	2 levels	29	24	146	602	125	51	14	83%	5.0	20.8%	8.5%	12.3%	2.3%	2.90	3.68	+3.0
2019	23	MIX MLE	2 levels	24	20	105	442	92	37	20	83%	4.4	18.4%	8.5%	10.0%	5.1%	4.71	5.43	-0.0
2019	23	MIX RAW	2 levels	24	20	105	442	92	37	20	83%	4.4	20.8%	8.4%	12.4%	4.5%	4.71	4.88	+0.6
2021	25	MIX MLE	2 levels	43	0	49	220	72	18	9	0%	1.1	27.7%	8.1%	19.7%	5.0%	5.36	4.53	+0.0
2021	25	MIX RAW	2 levels	43	0	49	220	72	18	9	0%	1.1	32.7%	8.2%	24.5%	4.1%	5.36	3.65	+0.5
2022	26	MIX MLE	2 levels	54	0	57	231	69	18	4	0%	1.1	28.4%	7.4%	20.9%	1.4%	3.16	2.41	+1.5
2022	26	MIX RAW	2 levels	54	0	57	231	69	18	4	0%	1.1	29.9%	7.8%	22.1%	1.7%	3.16	2.54	+1.4
2023	27	MLB MLE	Cleveland Guardians	70	0	66	262	62	24	4	0%	0.9	23.7%	9.2%	14.5%	1.5%	3.29	3.10	+1.1
2023	27	MLB RAW	Cleveland Guardians	70	0	66	262	62	24	4	0%	0.9	23.7%	9.2%	14.5%	1.5%	3.29	3.10	+1.1
2024	28	MLB MLE	Chicago White Sox	64	0	64	278	66	24	17	0%	1.0	23.7%	8.6%	15.1%	6.0%	5.20	5.49	-0.7
2024	28	MLB MLE	Chicago White Sox	64	0	64	278	66	24	17	0%	1.0	23.7%	8.6%	15.1%	6.0%	5.20	5.49	-0.7
2024	28	MLB RAW	Chicago White Sox	64	0	64	278	66	24	17	0%	1.0	23.7%	8.6%	15.1%	6.1%	5.20	5.62	-0.8
2025	29	MLB MLE	Houston Astros	65	0	66	280	62	22	7	0%	1.0	22.1%	7.9%	14.3%	2.6%	4.36	3.64	+0.7
2025	29	MLB MLE	Houston Astros	65	0	66	280	62	22	7	0%	1.0	22.1%	7.9%	14.3%	2.6%	4.36	3.64	+0.7
2025	29	MLB RAW	Houston Astros	65	0	66	280	62	22	7	0%	1.0	22.1%	7.9%	14.3%	2.5%	4.36	3.60	+0.7
2026	30	MIX MLE	3 levels	70	0	76	315	70	19	11	0%	1.1	22.3%	6.3%	15.9%	3.8%	4.52	4.08	+0.4
2026	30	MIX MLE	3 levels	70	0	76	315	70	19	11	0%	1.1	22.3%	6.3%	15.9%	3.8%	4.52	4.08	+0.4
2026	30	MIX RAW	3 levels	70	0	76	315	70	19	11	0%	1.1	22.2%	6.0%	16.2%	3.5%	4.52	3.89	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			360	3	386	1636	390	132	56	1%	1.1	23.8%	8.1%	15.8%	3.4%	4.50	3.99	+2.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	HOU	56	0	59	249	58	18	9	0%	1.1	23.2%	7.1%	16.1%	3.4%	4.42	4.32	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	HOU	42	0	44	185	41	14	7	0%	1.0	22.4%	7.5%	14.9%	3.7%	4.51	4.57	-0.0
2029	33	MLB MLE	HOU	30	0	31	132	28	11	5	0%	1.0	21.5%	8.0%	13.6%	4.0%	4.71	4.85	-0.1
2028	32	MLB CTX	HOU	42	0	44	186	42	14	7	0%	1.0	22.4%	7.5%	14.9%	3.7%	4.51	4.57	-0.0
2029	33	MLB CTX	HOU	30	0	31	131	28	10	5	0%	1.0	21.5%	8.0%	13.6%	4.0%	4.71	4.85	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		431	3	461	1953	460	156	68	1%	1.1	23.5%	8.0%	15.5%	3.5%	4.52	4.04	+2.8
/ 200 IP	—	RAW		187	1	200	848	200	68	30	1%	1.1	23.5%	8.0%	15.5%	3.5%	4.52	4.04	+1.2
Career	—	MLE		476	95	923	3858	785	318	127	20%	1.9	20.3%	8.2%	12.1%	3.3%	3.92	4.23	+2.4
/ 200 IP	—	MLE		103	21	200	836	170	69	27	20%	1.9	20.3%	8.2%	12.1%	3.3%	3.92	4.23	+1.1

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.

2021 AAALehigh Valley IronPigs · 13 IPFIP 1.03 → 1.78 (+0.75)K% 51.1% → 44.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	51.06%	—	×0.880	44.94%
BB% (unintentional) /BF	8.51%	—	×1.050	8.94%
HR / BF /BF	2.13%	÷0.957	×1.100	2.45%

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 91).

Result: FIP 1.03 → 1.78, 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 AAALehigh Valley IronPigs · 94 IPFIP 4.57 → 5.43 (+0.86)K% 21.0% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.96%	—	×0.880	18.44%
BB% (unintentional) /BF	8.08%	—	×1.050	8.48%
HR / BF /BF	4.04%	÷0.866	×1.100	5.13%

Result: FIP 4.57 → 5.43, 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 AAALehigh Valley IronPigs · 127 IPFIP 3.63 → 4.09 (+0.46)K% 21.1% → 18.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.11%	—	×0.880	18.58%
BB% (unintentional) /BF	8.25%	—	×1.050	8.67%
HR / BF /BF	2.30%	÷0.954	×1.100	2.66%

Result: FIP 3.63 → 4.09, 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 AASan Antonio Missions · 150 IPFIP 3.24 → 3.99 (+0.75)K% 22.4% → 18.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.37%	—	×0.810	18.12%
BB% (unintentional) /BF	7.62%	—	×1.100	8.38%
HR / BF /BF	1.94%	÷0.940	×1.200	2.48%

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 3.24 → 3.99, 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 A+Lake Elsinore Storm · 68 IPFIP 4.69 → 5.91 (+1.22)K% 17.6% → 13.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.63%	—	×0.770	13.57%
BB% (unintentional) /BF	8.14%	—	×1.150	9.36%
HR / BF /BF	3.73%	÷0.925	×1.250	5.04%

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 85).

Result: FIP 4.69 → 5.91, 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).

2016 AFort Wayne TinCaps · 53 IPFIP 2.66 → 3.52 (+0.85)K% 21.1% → 15.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.13%	—	×0.740	15.63%
BB% (unintentional) /BF	6.57%	—	×1.180	7.76%
HR / BF /BF	0.94%	÷0.888	×1.300	1.37%

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 78).

Result: FIP 2.66 → 3.52, 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).

2015 ROKAZL Mariners · 25 IPFIP 1.87 → 3.00 (+1.13)K% 28.2% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.16%	—	×0.680	19.15%
BB% (unintentional) /BF	4.85%	—	×1.250	6.07%
HR / BF /BF	0.97%	÷1.000	×1.400	1.36%

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 1.87 → 3.00, 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
Enyel De Los Santos (OGILVIE)	—	—	—	—	—	3.4%	—	4.69	22.0%	14.3%	75	+0.37	—	—	—
Pedro Báez R 2019 · 3.14 FIP	31	SU	3.14	25.0%	8.0%	2.1%	.207	4.30	18.6%	8.6%	17	+1.16	2.29	356	69
Chris Hatcher R 2016 · 4.61 FIP	31	SU	4.61	23.8%	9.4%	4.2%	.283	4.69	22.0%	13.8%	96	+0.08	2.51	246	68
Carlos Torres R 2014 · 3.66 FIP	31	SU	3.66	23.7%	8.4%	2.7%	.295	3.72	20.2%	12.4%	213	+0.06	2.89	604	67
Brad Brach R 2017 · 3.36 FIP	31	SU	3.36	25.5%	9.1%	2.3%	.254	3.68	22.8%	11.1%	129	+0.32	2.69	570	67
Guillermo Mota R 2004 · 3.39 FIP	31	SU	3.39	21.6%	7.9%	2.0%	.249	4.11	19.3%	11.6%	182	+0.72	2.68	857	67
Spencer Bivens R 2024 · 4.07 FIP	30	SU	4.07	18.0%	5.8%	3.2%	.265	3.88	18.2%	10.9%	157	-0.19	3.52	391	67
Matt Bush R 2017 · 3.60 FIP	31	SU	3.60	24.2%	7.9%	2.8%	.321	4.72	17.6%	4.6%	23	+1.12	2.87	249	67
Fernando Rodriguez Jr. R 2015 · 3.34 FIP	31	SU	3.34	26.5%	9.6%	2.3%	.241	3.89	23.3%	13.2%	105	+0.55	3.34	335	66
Josh Fields R 2017 · 3.98 FIP	31	SU	3.98	26.9%	6.3%	4.3%	.216	5.01	20.5%	12.9%	66	+1.03	1.80	330	66
Mike Broadway R 2018 · 4.65 FIP	31	SU	4.65	23.0%	10.6%	3.9%	.282	—	—	—	—	—	1.74	195	66
Matt Herges R 2001 · 3.62 FIP	31	SU	3.62	17.5%	7.8%	1.8%	.281	3.73	17.0%	10.3%	209	+0.11	2.90	691	65
Ryan Brasier R 2019 · 4.12 FIP	31	SU	4.12	25.3%	8.3%	3.8%	.278	3.56	24.3%	18.2%	99	-0.56	2.31	426	65
Mike DeJean R 2002 · 3.80 FIP	31	SU	3.80	19.9%	9.5%	2.1%	.265	3.66	19.6%	10.5%	206	-0.14	2.82	622	65
Gregory Infante R 2018 · 4.07 FIP	31	SU	4.07	22.0%	4.6%	4.1%	.291	—	—	—	—	—	2.97	230	64
Frank Francisco R 2011 · 3.74 FIP	31	SU	3.74	24.3%	7.3%	3.2%	.296	3.77	23.9%	13.7%	42	+0.03	2.92	369	64
Manny Acosta R 2012 · 4.49 FIP	31	SU	4.49	21.3%	11.1%	3.2%	.295	—	—	—	—	—	3.08	350	64
Alex Wilson R 2018 · 4.16 FIP	31	SU	4.16	17.6%	5.3%	3.4%	.232	5.06	19.4%	13.4%	62	+0.90	2.93	382	63
Tommy Nance R 2022 · 3.28 FIP	31	SU	3.28	29.1%	9.2%	2.7%	.345	2.75	23.4%	18.0%	118	-0.53	2.08	360	63
Mark Serrano R 2017 · 3.56 FIP	31	SU	3.56	21.9%	6.4%	2.7%	.240	5.25	20.2%	12.3%	42	+1.69	3.16	120	63
Brian Sanches R 2010 · 4.24 FIP	31	SU	4.24	21.3%	10.6%	2.9%	.217	4.35	19.6%	8.5%	62	+0.11	3.39	229	63

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	2.6	58	23.5%	8.4%	1.35	4.51
David Hernandez ('19)	3.2	65	23.9%	9.1%	1.22	4.12
Shane Greene ('23)	2.4	59	21.7%	8.6%	1.12	4.50
Justin Speier ('09)	3.4	56	20.4%	8.0%	1.44	4.11
Pete Ladd ('79-'86, 0 WAR*)	1.4	72	24.6%*	7.8%*	1.53*	4.42*
Xavier Hernandez ('89-'98, 3 WAR*)	3.4	67	23.9%*	9.1%*	1.12*	4.20*
Ed Nunez ('82-'94, 2 WAR*)	3.3	54	24.5%*	9.5%*	1.24*	4.37*