Jeremiah Estrada

P San Diego Padres

Age 28 RHP 6'1" / 185 lbs MLB peak 0.5 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	70	70	2.84	1.65	40.0%	8.8%	2.4	K 37.3% · BB 8.7% · FIP 1.91
2025	26	MLBSD	77	73	3.45	3.31	35.5%	8.2%	1.1
2026	27	MIX4 levels	39	36	3.03	3.10	29.7%	13.8%	0.6	K 30.2% · BB 12.7% · FIP 3.01
2027PROJ	28	MLBSD	40	42	3.11	3.19	35.3%	8.9%	0.7
2028PROJ95% MLB	29	MLBSD	42	44	3.25	3.35	34.7%	9.1%	0.7
2029PROJ95% MLB	30	MLBSD	40	42	3.44	3.56	34.0%	9.4%	0.5

Last 3 seasons WAR 4.1 · Next 3 projected WAR 1.9Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%90

xwOBA vs77

FB Velo70

CompsJoel Hanrahan (age 28) · Ken Giles (age 28) · Sergio Santos (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9486vR 78

ERA3.11

FIP3.19

K%35.3%

BB%8.9%

K-BB%26.4%

Proj IP42

Value2027 · WAR

Runs saved vs league avg · 42 IP

Grades · Statcast · Contract

Scouting Grades

STUF7070

CTRL4545

CMD7575

K†8080

Statcast Percentiles

FB Velo

p7095.9

Whiff%

p9031.7%

p9030.2%

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)
2017	18	ROK MLE	AZL Cubs	4	0	6	29	6	6	0	0%	1.6	20.7%	20.7%	0.0%	0.0%	1.42	3.97	—
2017	18	ROK RAW	AZL Cubs	4	0	6	29	6	6	0	0%	1.6	20.7%	20.7%	0.0%	0.0%	1.42	4.05	—
2021	22	A MLE	Myrtle Beach Pelicans	11	2	23	93	38	6	2	18%	2.1	30.2%	7.6%	22.6%	2.9%	1.57	3.08	—
2021	22	A RAW	Myrtle Beach Pelicans	11	2	23	93	38	6	2	18%	2.1	40.9%	6.5%	34.4%	2.2%	1.57	1.71	—
2022	23	MIX MLE	4 levels	39	0	54	218	86	21	2	0%	1.4	30.9%	11.4%	19.5%	0.8%	1.50	2.37	+1.4
2022	23	MIX RAW	4 levels	39	0	54	218	86	21	2	0%	1.4	39.4%	9.6%	29.8%	0.9%	1.50	1.56	+2.0
2023	24	MIX MLE	2 levels	38	0	39	194	56	37	12	0%	1.0	25.8%	17.7%	8.0%	6.8%	6.18	6.93	-1.1
2023	24	MIX RAW	2 levels	38	0	39	194	56	37	12	0%	1.0	28.9%	19.1%	9.8%	6.2%	6.18	7.04	-1.1
2024	25	MIX MLE	2 levels	70	0	70	285	114	25	4	0%	1.0	37.3%	8.7%	28.6%	1.5%	2.84	1.91	+2.2
2024	25	MIX MLE	2 levels	70	0	70	285	114	25	4	0%	1.0	37.3%	8.7%	28.6%	1.5%	2.84	1.91	+2.2
2024	25	MIX RAW	2 levels	70	0	70	285	114	25	4	0%	1.0	40.0%	8.8%	31.2%	1.4%	2.84	1.65	+2.4
2025	26	MLB MLE	San Diego Padres	77	0	73	304	108	25	12	0%	0.9	35.5%	8.2%	27.3%	3.9%	3.45	3.26	+1.1
2025	26	MLB MLE	San Diego Padres	77	0	73	304	108	25	12	0%	0.9	35.5%	8.2%	27.3%	3.9%	3.45	3.26	+1.1
2025	26	MLB RAW	San Diego Padres	77	0	73	304	108	25	12	0%	0.9	35.5%	8.2%	27.3%	3.9%	3.45	3.31	+1.1
2026	27	MIX MLE	4 levels	39	0	36	145	43	20	2	0%	0.9	30.2%	12.7%	17.5%	1.5%	3.03	3.01	+0.7
2026	27	MIX MLE	4 levels	39	0	36	145	43	20	2	0%	0.9	30.2%	12.7%	17.5%	1.5%	3.03	3.01	+0.7
2026	27	MIX RAW	4 levels	39	0	36	145	43	20	2	0%	0.9	29.7%	13.8%	15.9%	1.4%	3.03	3.10	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			189	0	181	763	261	77	23	0%	1.0	34.2%	10.1%	24.1%	3.0%	3.47	3.14	+3.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	SD	40	0	42	177	63	16	5	0%	1.1	35.3%	8.9%	26.4%	2.9%	3.11	3.19	+0.7
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	SD	44	0	47	197	68	18	6	0%	1.1	34.7%	9.1%	25.6%	3.0%	3.25	3.35	+0.7
2029	30	MLB MLE	SD	42	0	44	187	64	18	6	0%	1.1	34.0%	9.4%	24.6%	3.2%	3.44	3.56	+0.5
2028	29	MLB CTX	SD	42	0	44	186	64	17	6	0%	1.0	34.7%	9.1%	25.6%	3.0%	3.25	3.35	+0.7
2029	30	MLB CTX	SD	40	0	42	177	60	17	6	0%	1.1	34.0%	9.4%	24.6%	3.2%	3.44	3.56	+0.5
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		271	0	268	1128	386	111	34	0%	1.0	34.2%	9.8%	24.4%	3.0%	3.43	3.12	+4.6
/ 200 IP	—	RAW		203	0	200	842	288	83	25	0%	1.0	34.2%	9.8%	24.4%	3.0%	3.43	3.12	+3.4
Career	—	MLE		278	2	301	1268	409	141	36	1%	1.1	32.3%	11.1%	21.2%	2.8%	3.08	3.34	+4.2
/ 200 IP	—	MLE		185	1	200	843	272	93	24	1%	1.1	32.3%	11.1%	21.2%	2.8%	3.08	3.34	+3.1

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.

2024 AAAEl Paso Chihuahuas · 9 IPFIP -0.87 → -0.26 (+0.60)K% 60.6% → 52.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	60.61%	—	×0.860	52.12%
BB% (unintentional) /BF	9.09%	—	×0.900	8.18%
HR / BF /BF	0.00%	÷1.078	×1.100	0.00%

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 116).

Result: FIP -0.87 → -0.26, 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 AAAIowa Cubs · 29 IPFIP 6.04 → 6.61 (+0.57)K% 31.2% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.16%	—	×0.860	26.80%
BB% (unintentional) /BF	18.84%	—	×0.900	16.96%
HR / BF /BF	5.80%	÷0.965	×1.100	6.61%

Result: FIP 6.04 → 6.61, 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 A+South Bend Cubs · 23 IPFIP 1.34 → 2.56 (+1.22)K% 42.9% → 33.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	42.86%	—	×0.770	33.00%
BB% (unintentional) /BF	9.89%	—	×1.150	11.37%
HR / BF /BF	1.10%	÷0.938	×1.250	1.46%

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 88).

Result: FIP 1.34 → 2.56, 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 AATennessee Smokies · 19 IPFIP 1.45 → 2.15 (+0.69)K% 35.1% → 28.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.06%	—	×0.810	28.40%
BB% (unintentional) /BF	10.39%	—	×1.100	11.43%
HR / BF /BF	0.00%	÷1.010	×1.200	0.00%

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 102).

Result: FIP 1.45 → 2.15, 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 AAAIowa Cubs · 6 IPFIP -0.45 → 0.07 (+0.51)K% 48.0% → 42.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	48.00%	—	×0.880	42.24%
BB% (unintentional) /BF	4.00%	—	×1.050	4.20%
HR / BF /BF	0.00%	÷0.996	×1.100	0.00%

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 99).

Result: FIP -0.45 → 0.07, 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 AMyrtle Beach Pelicans · 23 IPFIP 1.65 → 3.08 (+1.43)K% 40.9% → 30.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.86%	—	×0.740	30.24%
BB% (unintentional) /BF	6.45%	—	×1.180	7.61%
HR / BF /BF	2.15%	÷0.977	×1.300	2.86%

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 95).

Result: FIP 1.65 → 3.08, 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 ROKAZL Cubs · 6 IPFIP 3.97 → 5.19 (+1.21)K% 20.7% → 14.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.69%	—	×0.680	14.07%
BB% (unintentional) /BF	20.69%	—	×1.250	25.86%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

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 3.97 → 5.19, 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
Jeremiah Estrada (OGILVIE)	—	—	3.19	35.3%	8.9%	2.9%	—	3.45	34.3%	25.1%	91	+0.26	—	—	—
Joel Hanrahan R 2010 · 2.56 FIP	28	SU	2.56	34.0%	8.8%	2.2%	.321	3.22	24.2%	14.9%	128	+0.66	2.08	397	76
Ken Giles R 2019 · 2.02 FIP	28	SU	2.02	39.9%	7.7%	2.4%	.298	—	—	—	—	—	0.92	414	76
Sergio Santos R 2011 · 2.53 FIP	28	SU	2.53	35.4%	9.2%	2.3%	.254	3.13	29.4%	21.4%	47	+0.60	1.36	178	74
Jose Valverde R 2006 · 3.04 FIP	28	SU	3.04	30.9%	8.5%	2.7%	.341	3.30	27.6%	19.7%	190	+0.26	2.21	752	73
Kiko Calero R 2003 · 3.54 FIP	28	SU	3.54	31.5%	11.1%	3.1%	.273	3.11	26.1%	18.9%	159	-0.43	2.27	298	71
Frank Francisco R 2008 · 3.05 FIP	28	SU	3.05	31.4%	9.1%	2.6%	.267	3.29	26.5%	19.4%	153	+0.24	2.92	369	71
Brad Lidge R 2005 · 2.01 FIP	28	SU	2.01	35.4%	7.6%	1.7%	.329	2.96	30.9%	21.2%	211	+0.95	1.56	595	70
Steve Delabar R 2012 · 3.82 FIP	29	SU	3.82	33.6%	9.1%	4.4%	.234	3.44	26.9%	15.9%	139	-0.38	2.43	229	70
Cody Allen R 2017 · 3.04 FIP	28	SU	3.04	32.6%	7.4%	3.2%	.300	5.02	27.0%	14.6%	90	+1.98	1.58	464	70
Austin Adams R 2019 · 2.12 FIP	28	SU	2.12	41.7%	10.4%	2.2%	.296	2.39	31.5%	17.8%	53	+0.27	1.79	392	70
Ernesto Frieri R 2013 · 3.55 FIP	28	SU	3.55	33.6%	9.9%	3.7%	.286	5.63	23.6%	15.4%	65	+2.08	2.62	334	70
Ray Black R 2018 · 2.95 FIP	28	SU	2.95	38.1%	9.5%	3.4%	.289	4.89	30.8%	17.6%	45	+1.94	2.95	150	70
Robert Coello R 2013 · 2.56 FIP	28	SU	2.56	31.5%	11.0%	1.3%	.317	4.31	13.4%	2.8%	95	+1.75	2.56	112	69
Will Vest R 2023 · 3.66 FIP	28	SU	3.66	28.4%	7.8%	3.6%	.281	2.69	23.9%	17.2%	166	-0.97	2.56	448	68
Nate Jones R 2013 · 2.58 FIP	27	SU	2.58	28.3%	7.9%	1.6%	.327	3.03	31.0%	25.7%	90	+0.45	2.57	307	68
John Brebbia R 2018 · 3.20 FIP	28	SU	3.20	30.0%	6.4%	3.3%	.317	3.09	29.3%	22.2%	106	-0.11	2.89	576	68
Matt Barnes R 2018 · 2.54 FIP	28	SU	2.54	36.2%	11.3%	1.9%	.313	3.21	37.0%	26.1%	142	+0.67	2.54	495	68
Jon Edwards R 2015 · 3.40 FIP	27	SU	3.40	31.7%	13.1%	2.4%	.264	2.40	30.3%	22.6%	30	-1.00	2.40	132	68
Jason Motte R 2010 · 3.24 FIP	28	SU	3.24	26.0%	7.2%	2.6%	.269	2.69	27.3%	21.8%	140	-0.55	2.22	387	67
Brian Wilson R 2010 · 2.00 FIP	28	SU	2.00	29.9%	6.8%	1.0%	.304	3.33	22.2%	9.4%	55	+1.33	2.00	366	67

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	1.6	52	34.4%	10.0%	1.17	3.39
Corey Knebel ('22)	1.5	51	31.7%	11.2%	1.00	3.26
Ernesto Frieri ('17)	1.5	51	30.1%	11.1%	1.25	3.59
Keone Kela ('21)	1.1	45	29.9%	9.2%	1.03	3.33
Victor Cruz ('78-'83, 5 WAR*)	1.4	54	35.3%*	11.5%*	1.30*	3.24*
Bryan Harvey ('87-'94, 12 WAR*)	1.9	64	37.8%*	8.9%*	0.94*	2.59*
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*