Antonio Senzatela

P Milwaukee Brewers

Age 32 RHP 6'1" / 235 lbs MLB peak 0.5 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MIX3 levels	8	8	29	5.83	5.28	20.0%	9.6%	0.0	K 13.0% · BB 14.8% · FIP 6.59
2025	30	MLBCOL	30	23	130	6.65	5.22	11.8%	7.3%	0.3
2026	31	MLBMIL	57	0	73	4.05	3.51	19.3%	7.7%	0.9
2027PROJ	32	MLBMIL	8	8	49	4.94	4.57	16.3%	7.8%	0.5
2028PROJ	33	MLBMIL	6	6	39	4.97	4.93	15.5%	8.3%	0.2
2029PROJ	34	MLBMIL	4	4	26	5.14	5.25	14.6%	8.8%	0.1

Last 3 seasons WAR 1.2 · 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

FB Velo90

xwOBA vs52

K%30

Form4.98 ERA (proj 4.94) · K 15.8% (proj 16.3%) · BB 9.5% (proj 7.8%) · last 90d · 22 IP through Oct 27

CompsElian Leyva (age 30) · Jared Fernandez (age 31) · Osvaldo Fernandez (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 114106vR 98

ERA4.94

FIP4.57

K%16.3%

BB%7.8%

K-BB%8.5%

Proj IP49

Value2027 · WAR

Runs saved vs league avg · 49 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p9097.3

Whiff%

p3723.5%

p3019.3%

xwOBA vs

p520.310

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	Modesto Nuts	26	26	154	623	143	33	10	100%	5.9	17.7%	6.1%	11.6%	2.4%	2.51	3.71	—
2015	20	A+ RAW	Modesto Nuts	26	26	154	623	143	33	10	100%	5.9	23.0%	5.3%	17.7%	1.6%	2.51	2.73	—
2016	21	AA MLE	Hartford Yard Goats	7	7	35	137	27	9	1	100%	5.0	16.0%	7.2%	8.7%	0.8%	1.82	3.11	—
2016	21	AA RAW	Hartford Yard Goats	7	7	35	137	27	9	1	100%	5.0	19.7%	6.6%	13.1%	0.7%	1.82	2.70	—
2017	22	MIX MLE	2 levels	37	21	138	579	104	47	18	57%	3.7	18.1%	8.2%	9.9%	2.8%	4.63	4.16	+2.0
2017	22	MIX RAW	2 levels	37	21	138	579	104	47	18	57%	3.7	18.0%	8.1%	9.8%	3.1%	4.63	4.31	+1.8
2018	23	MIX MLE	2 levels	31	21	128	540	111	41	11	68%	4.1	19.6%	7.7%	11.9%	1.8%	3.73	3.42	+3.1
2018	23	MIX RAW	2 levels	31	21	128	540	111	41	11	68%	4.1	20.6%	7.6%	13.0%	2.0%	3.73	3.44	+3.0
2019	24	MIX MLE	2 levels	32	32	159	733	88	62	26	100%	5.0	11.8%	8.5%	3.3%	3.2%	6.51	4.95	+0.8
2019	24	MIX RAW	2 levels	32	32	159	733	88	62	26	100%	5.0	12.0%	8.5%	3.5%	3.5%	6.51	5.29	+0.2
2020	25	MLB MLE	Colorado Rockies	12	12	73	303	41	18	9	100%	6.1	13.5%	5.9%	7.6%	2.6%	3.44	4.16	+1.1
2020	25	MLB RAW	Colorado Rockies	12	12	73	303	41	18	9	100%	6.1	13.5%	5.9%	7.6%	3.0%	3.44	4.31	+0.9
2021	26	MIX MLE	2 levels	29	29	161	683	108	31	12	100%	5.5	15.7%	4.6%	11.0%	1.6%	4.31	3.23	+4.3
2021	26	MIX RAW	2 levels	29	29	161	683	108	31	12	100%	5.5	15.8%	4.5%	11.3%	1.8%	4.31	3.31	+4.2
2022	27	MIX MLE	2 levels	21	21	101	451	54	25	11	100%	4.8	13.1%	5.6%	7.5%	1.9%	5.06	3.76	+2.0
2022	27	MIX RAW	2 levels	21	21	101	451	54	25	11	100%	4.8	12.0%	5.5%	6.4%	2.4%	5.06	4.19	+1.5
2023	28	MIX MLE	2 levels	4	4	14	68	11	5	3	100%	3.5	16.2%	7.4%	8.8%	4.4%	7.07	5.09	+0.1
2023	28	MIX RAW	2 levels	4	4	14	68	11	5	3	100%	3.5	16.2%	7.4%	8.8%	4.4%	7.07	5.39	+0.0
2024	29	MIX MLE	3 levels	8	8	29	125	25	12	6	100%	3.7	13.0%	14.8%	-1.9%	4.9%	5.83	6.59	-0.4
2024	29	MIX MLE	3 levels	8	8	29	125	25	12	6	100%	3.7	13.0%	14.8%	-1.9%	4.9%	5.83	6.59	-0.4
2024	29	MIX RAW	3 levels	8	8	29	125	25	12	6	100%	3.7	20.0%	9.6%	10.4%	4.8%	5.83	5.28	+0.0
2025	30	MLB MLE	Colorado Rockies	30	23	130	618	73	45	22	77%	4.3	11.8%	7.3%	4.5%	3.2%	6.65	4.76	+1.0
2025	30	MLB MLE	Colorado Rockies	30	23	130	618	73	45	22	77%	4.3	11.8%	7.3%	4.5%	3.2%	6.65	4.76	+1.0
2025	30	MLB RAW	Colorado Rockies	30	23	130	618	73	45	22	77%	4.3	11.8%	7.3%	4.5%	3.6%	6.65	5.22	+0.3
2026	31	MLB MLE	Milwaukee Brewers	57	0	73	311	60	24	6	0%	1.3	19.3%	7.7%	11.6%	1.8%	4.05	3.46	+1.0
2026	31	MLB MLE	Milwaukee Brewers	57	0	73	311	60	24	6	0%	1.3	19.3%	7.7%	11.6%	1.8%	4.05	3.46	+1.0
2026	31	MLB RAW	Milwaukee Brewers	57	0	73	311	60	24	6	0%	1.3	19.3%	7.7%	11.6%	1.9%	4.05	3.51	+0.9
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			235	145	895	3935	591	278	111	62%	3.8	15.0%	7.1%	8.0%	2.8%	5.09	4.32	+11.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	MIL	8	8	49	207	34	16	6	100%	6.1	16.3%	7.8%	8.5%	2.7%	4.94	4.57	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	MIL	6	6	39	166	26	14	5	100%	6.5	15.5%	8.3%	7.2%	3.0%	4.89	4.85	+0.2
2029	34	MLB MLE	MIL	4	4	26	110	16	10	4	100%	6.5	14.6%	8.8%	5.8%	3.3%	5.05	5.16	+0.1
2028	33	MLB CTX	MIL	6	6	39	165	25	14	5	100%	6.5	15.5%	8.3%	7.2%	3.1%	4.97	4.93	+0.2
2029	34	MLB CTX	MIL	4	4	26	110	16	10	4	100%	6.5	14.6%	8.8%	5.8%	3.4%	5.14	5.25	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		246	156	961	4211	633	301	120	63%	3.9	15.0%	7.2%	7.9%	2.8%	5.08	4.30	+12.4
/ 200 IP	—	RAW		51	32	200	877	132	63	25	63%	3.9	15.0%	7.2%	7.9%	2.8%	5.08	4.30	+2.6
Career	—	MLE		294	204	1196	5171	796	366	128	69%	4.1	15.4%	7.1%	8.3%	2.5%	4.59	4.06	+11.6
/ 200 IP	—	MLE		49	34	200	865	133	61	21	69%	4.1	15.4%	7.1%	8.3%	2.5%	4.59	4.06	+2.4

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 AAHartford Yard Goats · 12 IPFIP 3.62 → 4.79 (+1.17)K% 26.5% → 21.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.53%	—	×0.810	21.49%
BB% (unintentional) /BF	4.08%	—	×1.100	4.49%
HR / BF /BF	4.08%	÷0.916	×1.200	5.35%

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 83).

Result: FIP 3.62 → 4.79, 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+Spokane Indians · 5 IPFIP 4.83 → 5.82 (+0.99)K% 22.7% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.73%	—	×0.770	17.50%
BB% (unintentional) /BF	9.09%	—	×1.150	10.45%
HR / BF /BF	4.55%	÷1.086	×1.250	5.23%

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 117).

Result: FIP 4.83 → 5.82, 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 AAAAlbuquerque Isotopes · 6 IPFIP 2.54 → 2.66 (+0.12)K% 18.4% → 15.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.42%	—	×0.860	15.84%
BB% (unintentional) /BF	7.89%	—	×0.900	7.11%
HR / BF /BF	0.00%	÷1.062	×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 112).

Result: FIP 2.54 → 2.66, 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).

2022 AAAAlbuquerque Isotopes · 9 IPFIP 6.66 → 6.79 (+0.14)K% 0.0% → 0.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	0.00%	—	×0.880	0.00%
BB% (unintentional) /BF	5.26%	—	×1.050	5.53%
HR / BF /BF	5.26%	÷1.061	×1.100	5.46%

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 112).

Result: FIP 6.66 → 6.79, 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 AAAAlbuquerque Isotopes · 34 IPFIP 5.81 → 5.85 (+0.04)K% 7.9% → 7.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	7.95%	—	×0.880	6.99%
BB% (unintentional) /BF	6.62%	—	×1.050	6.95%
HR / BF /BF	4.64%	÷1.136	×1.100	4.49%

Result: FIP 5.81 → 5.85, 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 AAAAlbuquerque Isotopes · 38 IPFIP 2.11 → 2.43 (+0.31)K% 28.0% → 24.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.00%	—	×0.880	24.64%
BB% (unintentional) /BF	8.00%	—	×1.050	8.40%
HR / BF /BF	0.67%	÷1.162	×1.100	0.63%

Result: FIP 2.11 → 2.43, 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).

2016 AAHartford Yard Goats · 35 IPFIP 2.67 → 3.11 (+0.44)K% 19.7% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.71%	—	×0.810	15.96%
BB% (unintentional) /BF	6.57%	—	×1.100	7.23%
HR / BF /BF	0.73%	÷1.094	×1.200	0.80%

Result: FIP 2.67 → 3.11, 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 A+Modesto Nuts · 154 IPFIP 2.71 → 3.71 (+1.00)K% 23.0% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.95%	—	×0.770	17.67%
BB% (unintentional) /BF	5.30%	—	×1.150	6.09%
HR / BF /BF	1.61%	÷0.827	×1.250	2.43%

Result: FIP 2.71 → 3.71, 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
Antonio Senzatela (OGILVIE)	—	—	—	—	—	2.7%	—	4.97	15.1%	6.6%	65	+0.40	—	—	—
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	72
Jared Fernandez R 2003 · 3.57 FIP	31	SP-	3.57	11.8%	6.2%	1.2%	.269	—	—	—	—	—	3.57	101	69
Osvaldo Fernandez R 2001 · 4.53 FIP	32	SP-	4.53	9.6%	8.2%	2.2%	.324	—	—	—	—	—	4.25	387	69
Mitch Lively R 2017 · 3.47 FIP	31	SP-	3.47	17.0%	6.4%	1.8%	.304	—	—	—	—	—	2.39	158	67
Marco Quevedo R 2019 · 5.17 FIP	32	SP-	5.17	13.6%	11.4%	3.2%	.344	—	—	—	—	—	4.13	300	65
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	64
Todd Redmond R 2015 · 3.86 FIP	30	SW	3.86	15.4%	7.1%	2.1%	.311	—	—	—	—	—	3.21	247	63
Juan Omar Espinoza R 2016 · 4.84 FIP	32	SP-	4.84	8.4%	9.2%	2.4%	.348	—	—	—	—	—	4.81	104	63
Mike Burns R 2009 · 4.90 FIP	31	SP-	4.90	17.2%	6.6%	4.4%	.307	—	—	—	—	—	3.10	104	62
Jason Berken R 2016 · 4.54 FIP	32	SW	4.54	11.5%	8.3%	2.5%	.308	—	—	—	—	—	3.37	468	61
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	61
Junior Guerra R 2017 · 5.24 FIP	32	SP-	5.24	19.4%	12.8%	3.9%	.255	3.99	22.2%	12.5%	248	-1.25	3.18	646	60
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	59
Miguel Ruiz R 2017 · 5.60 FIP	31	SP	5.60	10.6%	11.0%	3.6%	.279	—	—	—	—	—	5.60	117	59
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	59
Danny Gutierrez R 2017 · 4.11 FIP	30	SP	4.11	15.1%	6.1%	2.8%	.362	—	—	—	—	—	3.34	239	59
Hector Galvan R 2019 · 4.84 FIP	31	SP-	4.84	14.3%	12.2%	2.6%	.357	—	—	—	—	—	3.59	406	59
Sergio Valenzuela R 2017 · 5.66 FIP	32	SP	5.66	10.6%	6.5%	4.8%	.355	—	—	—	—	—	3.66	244	58
David Fletcher R 2024 · 5.67 FIP	30	SP-	5.67	7.5%	10.3%	3.5%	.294	—	—	—	—	—	5.67	100	57
Kenshin Kawakami R 2009 · 3.97 FIP	34	SP-	3.97	15.7%	7.6%	2.2%	.277	4.06	15.1%	9.5%	87	+0.09	3.97	244	57

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	5.0	92	15.1%	7.5%	1.10	5.07
John O'Donoghue ('63-'71, 1 WAR*)	3.8	107	14.5%*	7.9%*	1.19*	4.86*
Jerry Augustine ('75-'84, 2 WAR*)	4.7	105	13.5%*	8.3%*	1.15*	4.73*
Luke Hochevar ('16)	4.6	116	17.7%	7.5%	1.12	4.98
Chad Bettis ('19)	3.0	86	16.2%	7.9%	1.18	5.12
Dickie Noles ('79-'90, 1 WAR*)	4.3	96	16.8%*	9.0%*	0.96*	4.96*
Ross Detwiler ('22)	3.8	68	15.3%	8.2%	1.11	4.56