Samy Natera Jr.

P Los Angeles Angels

Age 27 LHP 6'4" / 230 lbs MLB peak 0.4 · 2027

Overview

MLBRP40-MANROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	A+LAA	5	2	15	0.60	1.10	40.7%	10.2%	—	K 31.3% · BB 11.7% · FIP 1.94
2025	25	MIX2 levels	49	0	57	2.84	3.47	34.3%	16.9%	—	K 27.3% · BB 16.9% · FIP 3.89
2026	26	MIX3 levels	50	0	64	2.97	2.91	35.0%	12.0%	1.3	K 33.1% · BB 11.3% · FIP 3.10
2027PROJ	27	MLBLAA	32	0	34	3.61	3.74	33.3%	13.3%	0.3
2028PROJ79% MLB	28	MLBLAA	35	0	37	3.79	3.88	32.2%	13.0%	0.3
2029PROJ83% MLB	29	MLBLAA	33	0	35	3.97	4.07	30.9%	13.0%	0.2

Last 3 seasons WAR 1.3 · Next 3 projected WAR 0.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%90

xwOBA vs90

FB Velo55

Career WAR0.0 WAR median (P10 -0.3 / P90 2.4, comp-based) · star 0% · didn't stick 89%

CompsJustin King (age 26) · Jack Leathersich (age 27) · Hayden Harris (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 8896vR 104

ERA3.61

FIP3.74

K%33.3%

BB%13.3%

K-BB%20.0%

Proj IP47

Value2027 · WAR

Runs saved vs league avg · 47 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p5594.9

Whiff%

p9035.7%

p9036.6%

xwOBA vs

p900.246

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)
2023	23	MIX MLE	2 levels	22	22	91	397	118	47	14	100%	4.1	22.9%	13.3%	9.6%	4.2%	4.76	5.14	—
2023	23	MIX RAW	2 levels	22	22	91	397	118	47	14	100%	4.1	29.7%	11.8%	17.9%	3.5%	4.76	4.06	—
2024	24	A+ MLE	Tri-City Dust Devils	5	2	15	59	24	6	0	40%	3.0	31.3%	11.7%	19.6%	0.0%	0.60	1.94	—
2024	24	A+ MLE	Tri-City Dust Devils	5	2	15	59	24	6	0	40%	3.0	31.3%	11.7%	19.6%	0.0%	0.60	1.94	—
2024	24	A+ RAW	Tri-City Dust Devils	5	2	15	59	24	6	0	40%	3.0	40.7%	10.2%	30.5%	0.0%	0.60	1.10	—
2025	25	MIX MLE	2 levels	49	0	57	248	85	42	5	0%	1.2	27.3%	16.9%	10.4%	1.7%	2.84	3.89	—
2025	25	MIX MLE	2 levels	49	0	57	248	85	42	5	0%	1.2	27.3%	16.9%	10.4%	1.7%	2.84	3.89	—
2025	25	MIX RAW	2 levels	49	0	57	248	85	42	5	0%	1.2	34.3%	16.9%	17.3%	2.0%	2.84	3.47	—
2026	26	MIX MLE	3 levels	50	0	64	266	93	32	6	0%	1.3	33.1%	11.3%	21.9%	2.5%	2.97	3.10	+1.1
2026	26	MIX MLE	3 levels	50	0	64	266	93	32	6	0%	1.3	33.1%	11.3%	21.9%	2.5%	2.97	3.10	+1.1
2026	26	MIX RAW	3 levels	50	0	64	266	93	32	6	0%	1.3	35.0%	12.0%	22.9%	2.3%	2.97	2.91	+1.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			28	0	32	131	48	13	1	0%	1.1	36.6%	9.9%	26.7%	0.8%	3.13	1.71	+1.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	LAA	32	0	34	144	48	19	4	0%	1.1	33.3%	13.3%	20.0%	2.5%	3.61	3.74	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	LAA	45	0	47	199	64	26	5	0%	1.0	32.2%	13.0%	19.2%	2.7%	3.79	3.88	+0.4
2029	29	MLB MLE	LAA	40	0	42	177	55	23	5	0%	1.1	30.9%	13.0%	18.0%	2.9%	3.97	4.07	+0.2
2028	28	MLB CTX	LAA	35	0	37	156	50	20	4	0%	1.1	32.2%	13.0%	19.2%	2.7%	3.79	3.88	+0.3
2029	29	MLB CTX	LAA	33	0	35	148	46	19	4	0%	1.1	30.9%	13.0%	18.0%	2.9%	3.97	4.07	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		97	0	104	435	144	53	9	0%	1.1	33.1%	12.1%	21.0%	2.2%	3.65	3.02	+1.9
/ 200 IP	—	RAW		186	0	200	839	278	102	17	0%	1.1	33.1%	12.1%	21.0%	2.2%	3.65	3.02	+3.7
Career	—	MLE		126	24	226	970	265	132	28	19%	1.8	27.3%	13.6%	13.8%	2.8%	3.50	4.07	+1.7
/ 200 IP	—	MLE		111	21	200	857	234	116	24	19%	1.8	27.3%	13.6%	13.8%	2.8%	3.50	4.07	+2.8

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 AAASalt Lake Bees · 30 IPFIP 4.12 → 4.57 (+0.44)K% 34.4% → 29.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.38%	—	×0.860	29.56%
BB% (unintentional) /BF	14.06%	—	×0.900	12.66%
HR / BF /BF	3.91%	÷1.000	×1.100	4.30%

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 4.12 → 4.57, 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 AARocket City Trash Pandas · 48 IPFIP 3.02 → 3.89 (+0.87)K% 33.7% → 27.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.66%	—	×0.810	27.27%
BB% (unintentional) /BF	15.35%	—	×1.100	16.88%
HR / BF /BF	1.49%	÷1.028	×1.200	1.73%

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 106).

Result: FIP 3.02 → 3.89, 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 AAASalt Lake Bees · 9 IPFIP 5.39 → 5.80 (+0.40)K% 37.0% → 31.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.96%	—	×0.860	31.78%
BB% (unintentional) /BF	23.91%	—	×0.900	21.52%
HR / BF /BF	4.35%	÷0.989	×1.100	4.83%

Result: FIP 5.39 → 5.80, 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 A+Tri-City Dust Devils · 15 IPFIP 0.95 → 1.94 (+0.98)K% 40.7% → 31.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.68%	—	×0.770	31.32%
BB% (unintentional) /BF	10.17%	—	×1.150	11.69%
HR / BF /BF	0.00%	÷0.916	×1.250	0.00%

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 83).

Result: FIP 0.95 → 1.94, 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+Tri-City Dust Devils · 84 IPFIP 3.87 → 5.14 (+1.28)K% 29.8% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.75%	—	×0.770	22.91%
BB% (unintentional) /BF	11.57%	—	×1.150	13.31%
HR / BF /BF	3.31%	÷0.990	×1.250	4.18%

Result: FIP 3.87 → 5.14, 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).

2023 AARocket City Trash Pandas · 7 IPFIP 5.71 → 7.13 (+1.42)K% 29.4% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.41%	—	×0.810	23.82%
BB% (unintentional) /BF	14.71%	—	×1.100	16.18%
HR / BF /BF	5.88%	÷0.970	×1.200	7.27%

Result: FIP 5.71 → 7.13, 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
Samy Natera Jr. (OGILVIE)	—	—	—	—	—	2.5%	—	3.97	31.6%	18.6%	89	+0.23	—	—	—
Justin King L 2024 · 3.26 FIP	26	SU	3.26	29.5%	11.8%	2.1%	.346	4.16	22.4%	3.6%	65	+0.90	3.26	133	78
Jack Leathersich L 2017 · 3.16 FIP	27	SU	3.16	33.5%	14.4%	1.9%	.250	4.55	21.7%	1.9%	32	+1.39	3.16	101	74
Hayden Harris L 2024 · 3.79 FIP	25	SU	3.79	30.0%	12.7%	3.0%	.398	3.09	29.1%	17.2%	102	-0.70	1.77	196	73
Michael Gonzalez L 2005 · 3.04 FIP	27	SU	3.04	27.4%	13.7%	0.9%	.268	3.04	27.1%	16.4%	105	-0.00	1.45	454	72
Riley Martin L 2024 · 3.73 FIP	26	SU	3.73	28.2%	14.2%	2.2%	.336	3.23	26.4%	14.3%	64	-0.50	3.23	266	70
Ryan O'Rourke L 2015 · 3.85 FIP	27	SU	3.85	27.4%	12.9%	2.6%	.284	3.05	23.4%	16.7%	53	-0.80	3.05	145	70
Jacob Latz L 2023 · 3.06 FIP	27	SU	3.06	28.1%	9.8%	2.0%	.366	3.36	25.0%	15.5%	216	+0.30	2.39	480	70
Amir Garrett L 2019 · 3.62 FIP	27	SU	3.62	31.7%	13.8%	2.6%	.291	3.77	28.5%	15.3%	111	+0.15	3.06	712	70
Jack Sellinger L 2024 · 2.65 FIP	24	SU	2.65	26.4%	9.7%	1.0%	.284	3.24	24.0%	9.1%	114	+0.59	2.65	148	70
Conor Lillis-White L 2018 · 3.48 FIP	26	SU	3.48	26.8%	11.1%	2.3%	.322	—	—	—	—	—	1.80	182	69
Chasen Shreve L 2017 · 4.11 FIP	27	SU	4.11	29.3%	11.1%	3.8%	.245	4.38	26.8%	15.4%	138	+0.27	1.33	483	67
Dale Stanavich L 2024 · 3.99 FIP	25	SU	3.99	27.2%	12.7%	2.9%	.268	5.49	23.2%	7.9%	97	+1.50	3.09	184	67
Yuki Matsui L 2024 · 3.63 FIP	28	SU	3.63	26.8%	8.9%	3.0%	.242	4.25	23.9%	12.6%	140	+0.62	3.63	203	67
Nick Mondak L 2024 · 2.70 FIP	26	SU	2.70	30.9%	6.4%	2.5%	.286	—	—	—	—	—	2.70	153	66
Matt Purke L 2017 · 3.01 FIP	27	SU	3.01	25.1%	10.1%	1.4%	.335	4.29	16.1%	0.1%	47	+1.28	3.01	226	66
C.J. Widger L 2024 · 4.21 FIP	25	SU	4.21	26.0%	16.0%	2.3%	.258	5.75	18.1%	-0.7%	57	+1.54	3.83	105	66
Giovanni Soto L 2017 · 4.18 FIP	26	SU	4.18	25.6%	10.5%	3.5%	.317	—	—	—	—	—	3.30	128	66
Charlie Furbush L 2013 · 2.91 FIP	27	SU	2.91	28.6%	9.6%	1.8%	.256	2.79	26.1%	21.4%	64	-0.12	2.40	261	66
Tommy Vail L 2024 · 3.65 FIP	25	SW	3.65	27.5%	15.3%	1.7%	.237	5.19	19.5%	2.9%	99	+1.54	3.65	168	65
Reagan Todd L 2022 · 3.82 FIP	26	SU	3.82	25.6%	12.0%	2.5%	.325	—	—	—	—	—	2.89	122	65

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	0.8	42	33.0%	12.5%	0.90	3.66
Corey Knebel ('22)	1.5	51	31.7%	11.2%	1.00	3.26
Kyle Barraclough ('23)	1.4	56	28.2%	13.9%	0.99	3.86
Rod Scurry ('80-'88, 5 WAR*)	2.3	58	29.6%*	13.6%*	0.91*	3.67*
Antonio Bastardo ('17)	2.0	56	28.0%	11.4%	1.01	4.01
Victor Cruz ('78-'83, 5 WAR*)	1.4	54	35.3%*	11.5%*	1.30*	3.24*
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*