Aaron Ashby

P Milwaukee Brewers

Age 29 LHP 6'0" / 194 lbs MLB peak 0.8 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MIX2 levels	39	16	112	6.73	3.90	23.2%	15.4%	0.9	K 20.8% · BB 14.1% · FIP 3.93
2025	27	MIX3 levels	48	2	74	2.43	2.69	26.6%	10.2%	1.7	K 28.1% · BB 8.9% · FIP 2.43
2026	28	MLBMIL	75	1	89	3.12	3.01	30.3%	10.4%	1.6
2027PROJ	29	MLBMIL	63	0	66	3.40	3.48	29.6%	10.6%	0.9
2028PROJ95% MLB	30	MLBMIL	49	0	51	3.57	3.68	28.9%	10.9%	0.5
2029PROJ95% MLB	31	MLBMIL	40	0	42	3.78	3.91	28.2%	11.2%	0.3

Last 3 seasons WAR 4.2 · Next 3 projected WAR 1.7Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo90

K%90

xwOBA vs90

Form1.57 ERA (proj 3.40) · K 28.9% (proj 29.6%) · BB 8.8% (proj 10.6%) · last 90d · 29 IP through Oct 27

CompsJustin Wilson (age 29) · Scott Sauerbeck (age 29) · A.J. Puk (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 7583vR 91

ERA3.40

FIP3.48

K%29.6%

BB%10.6%

K-BB%19.1%

Proj IP66

Value2027 · WAR

Runs saved vs league avg · 66 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p9097.3

Whiff%

p9032.1%

p9030.3%

xwOBA vs

p900.268

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)
2018	20	MIX MLE	2 levels	13	10	58	242	66	17	4	77%	4.4	19.7%	8.5%	11.2%	2.3%	3.59	3.76	—
2018	20	MIX RAW	2 levels	13	10	58	242	66	17	4	77%	4.4	27.3%	7.0%	20.2%	1.7%	3.59	2.60	—
2019	21	MIX MLE	2 levels	24	23	126	530	135	60	5	96%	5.2	19.2%	13.2%	6.0%	1.2%	3.50	3.80	—
2019	21	MIX RAW	2 levels	24	23	126	530	135	60	5	96%	5.2	25.5%	11.3%	14.2%	0.9%	3.50	2.90	—
2021	23	MIX MLE	2 levels	34	16	95	409	139	44	8	47%	2.8	31.1%	11.1%	19.9%	2.1%	4.45	3.05	+1.7
2021	23	MIX RAW	2 levels	34	16	95	409	139	44	8	47%	2.8	34.0%	10.8%	23.2%	2.0%	4.45	2.66	+2.2
2022	24	MLB MLE	Milwaukee Brewers	27	19	107	475	126	47	15	70%	4.0	26.5%	9.9%	16.6%	3.0%	4.44	3.76	+2.1
2022	24	MLB RAW	Milwaukee Brewers	27	19	107	475	126	47	15	70%	4.0	26.5%	9.9%	16.6%	3.2%	4.44	3.88	+1.9
2023	25	MIX MLE	3 levels	7	6	7	42	7	14	1	86%	1.0	16.7%	33.3%	-16.7%	2.4%	15.43	7.22	—
2023	25	MIX RAW	3 levels	7	6	7	42	7	14	1	86%	1.0	16.7%	33.3%	-16.7%	2.4%	15.43	8.96	—
2024	26	MIX MLE	2 levels	39	16	112	538	125	83	7	41%	2.9	20.8%	14.1%	6.8%	1.5%	6.73	3.93	+0.8
2024	26	MIX MLE	2 levels	39	16	112	538	125	83	7	41%	2.9	20.8%	14.1%	6.8%	1.5%	6.73	3.93	+0.8
2024	26	MIX RAW	2 levels	39	16	112	538	125	83	7	41%	2.9	23.2%	15.4%	7.8%	1.3%	6.73	3.90	+0.9
2025	27	MIX MLE	3 levels	48	2	74	304	81	31	3	4%	1.5	28.1%	8.9%	19.3%	1.1%	2.43	2.43	+1.9
2025	27	MIX MLE	3 levels	48	2	74	304	81	31	3	4%	1.5	28.1%	8.9%	19.3%	1.1%	2.43	2.43	+1.9
2025	27	MIX RAW	3 levels	48	2	74	304	81	31	3	4%	1.5	26.6%	10.2%	16.4%	1.0%	2.43	2.69	+1.7
2026	28	MLB MLE	Milwaukee Brewers	75	1	89	383	116	40	8	1%	1.2	30.3%	10.4%	19.8%	2.0%	3.12	2.96	+1.7
2026	28	MLB MLE	Milwaukee Brewers	75	1	89	383	116	40	8	1%	1.2	30.3%	10.4%	19.8%	2.0%	3.12	2.96	+1.7
2026	28	MLB RAW	Milwaukee Brewers	75	1	89	383	116	40	8	1%	1.2	30.3%	10.4%	19.8%	2.1%	3.12	3.01	+1.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			172	27	323	1380	390	133	32	16%	1.9	28.3%	9.6%	18.6%	2.3%	3.48	3.21	+5.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	MIL	63	0	66	279	83	29	6	0%	1.0	29.6%	10.6%	19.1%	2.1%	3.40	3.48	+0.9
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	MIL	51	0	54	227	66	25	5	0%	1.1	28.9%	10.9%	18.1%	2.3%	3.57	3.68	+0.6
2029	31	MLB MLE	MIL	42	0	44	185	52	21	5	0%	1.0	28.2%	11.2%	17.0%	2.5%	3.78	3.91	+0.3
2028	30	MLB CTX	MIL	49	0	51	215	62	23	5	0%	1.0	28.9%	10.9%	18.1%	2.3%	3.57	3.68	+0.5
2029	31	MLB CTX	MIL	40	0	42	177	50	20	5	0%	1.1	28.2%	11.2%	17.0%	2.5%	3.78	3.91	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		260	27	416	1771	502	176	41	10%	1.6	28.3%	9.9%	18.4%	2.3%	3.52	3.25	+6.5
/ 200 IP	—	RAW		125	13	200	852	241	85	20	10%	1.6	28.3%	9.9%	18.4%	2.3%	3.52	3.25	+3.1
Career	—	MLE		267	93	669	2923	723	340	54	35%	2.5	24.7%	11.6%	13.1%	1.9%	4.29	3.51	+6.1
/ 200 IP	—	MLE		80	28	200	874	216	102	16	35%	2.5	24.7%	11.6%	13.1%	1.9%	4.29	3.51	+2.9

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 AAANashville Sounds · 6 IPFIP 4.28 → 4.22 (−0.06)K% 16.0% → 13.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.00%	—	×0.860	13.76%
BB% (unintentional) /BF	20.00%	—	×0.900	18.00%
HR / BF /BF	0.00%	÷1.111	×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 122).

Result: FIP 4.28 → 4.22, 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 AAANashville Sounds · 84 IPFIP 4.11 → 4.28 (+0.18)K% 22.0% → 18.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.96%	—	×0.860	18.88%
BB% (unintentional) /BF	17.42%	—	×0.900	15.68%
HR / BF /BF	1.19%	÷0.909	×1.100	1.44%

Result: FIP 4.11 → 4.28, 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 AAANashville Sounds · 63 IPFIP 2.30 → 2.91 (+0.60)K% 36.2% → 31.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.23%	—	×0.880	31.88%
BB% (unintentional) /BF	11.59%	—	×1.050	12.17%
HR / BF /BF	1.45%	÷0.915	×1.100	1.74%

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 83).

Result: FIP 2.30 → 2.91, 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).

2019 A+Carolina Mudcats · 65 IPFIP 3.08 → 3.72 (+0.63)K% 19.8% → 15.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.78%	—	×0.770	15.23%
BB% (unintentional) /BF	11.51%	—	×1.150	13.24%
HR / BF /BF	0.36%	÷1.082	×1.250	0.42%

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 116).

Result: FIP 3.08 → 3.72, 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 AWisconsin Timber Rattlers · 61 IPFIP 2.70 → 3.88 (+1.19)K% 31.7% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.75%	—	×0.740	23.49%
BB% (unintentional) /BF	11.11%	—	×1.180	13.11%
HR / BF /BF	1.59%	÷1.022	×1.300	2.02%

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 104).

Result: FIP 2.70 → 3.88, 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 AWisconsin Timber Rattlers · 37 IPFIP 1.63 → 2.52 (+0.90)K% 30.3% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.32%	—	×0.740	22.44%
BB% (unintentional) /BF	5.81%	—	×1.180	6.85%
HR / BF /BF	0.65%	÷1.019	×1.300	0.82%

Result: FIP 1.63 → 2.52, 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).

2018 ROKHelena Brewers · 20 IPFIP 4.31 → 5.95 (+1.64)K% 21.8% → 14.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.84%	—	×0.680	14.85%
BB% (unintentional) /BF	9.20%	—	×1.250	11.49%
HR / BF /BF	3.45%	÷1.000	×1.400	4.83%

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 4.31 → 5.95, 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
Aaron Ashby (OGILVIE)	—	—	—	—	—	2.1%	—	3.78	28.6%	17.6%	98	+0.30	—	—	—
Justin Wilson L 2017 · 3.26 FIP	29	SU	3.26	32.3%	13.7%	2.1%	.271	3.40	27.8%	15.9%	113	+0.14	2.49	554	61
Scott Sauerbeck L 2001 · 3.04 FIP	29	SU	3.04	28.1%	12.1%	1.4%	.348	3.64	23.6%	11.9%	119	+0.60	2.79	386	60
A.J. Puk L 2024 · 2.68 FIP	29	SU	2.68	29.9%	8.8%	1.8%	.263	—	—	—	—	—	2.46	381	59
Jake Diekman L 2016 · 3.23 FIP	29	SU	3.23	26.7%	11.3%	1.7%	.241	3.09	28.6%	15.8%	115	-0.14	2.27	592	59
Zach Phillips L 2016 · 3.01 FIP	29	SU	3.01	27.4%	11.9%	1.3%	.370	3.20	19.2%	10.6%	86	+0.19	2.33	202	58
Kyle Regnault L 2018 · 3.82 FIP	29	SU	3.82	27.6%	9.7%	3.3%	.367	—	—	—	—	—	2.88	204	57
Brian Fuentes L 2005 · 2.92 FIP	29	SU	2.92	28.3%	9.3%	1.9%	.273	3.08	26.9%	18.5%	189	+0.16	2.08	602	56
Raul Valdes L 2010 · 4.02 FIP	32	SU	4.02	21.4%	9.9%	2.7%	.301	3.14	27.4%	22.5%	78	-0.88	2.29	160	56
Armando Almanza L 2002 · 4.34 FIP	29	SU	4.34	30.0%	11.6%	4.2%	.272	5.01	21.8%	12.0%	62	+0.67	2.90	211	56
Damaso Marte L 2004 · 4.27 FIP	29	SU	4.27	22.4%	9.9%	3.3%	.236	3.28	25.9%	15.1%	149	-0.99	2.41	495	55
Jesse Biddle L 2021 · 3.35 FIP	29	SU	3.35	30.2%	12.6%	2.2%	.330	—	—	—	—	—	3.35	311	55
Ryan Buchter L 2016 · 2.74 FIP	29	SU	2.74	31.6%	11.3%	1.6%	.219	4.30	24.8%	15.3%	150	+1.56	2.37	296	55
Matt Whitehouse L 2019 · 4.07 FIP	28	SW	4.07	20.1%	10.9%	2.3%	.339	—	—	—	—	—	3.37	353	55
Ryan Verdugo L 2015 · 3.61 FIP	28	SU	3.61	19.8%	10.8%	1.5%	.281	3.36	22.7%	17.3%	82	-0.25	3.36	153	55
Andrew Barbosa L 2017 · 4.67 FIP	29	SU	4.67	20.2%	9.6%	3.8%	.301	—	—	—	—	—	2.70	175	54
Josh Smoker L 2018 · 3.66 FIP	29	SU	3.66	22.1%	8.4%	2.5%	.318	6.58	14.2%	3.4%	14	+2.92	2.71	230	54
Mike Dunn L 2014 · 2.82 FIP	29	SU	2.82	27.3%	8.6%	1.7%	.281	3.92	25.3%	14.8%	147	+1.10	2.82	432	54
Matt Thornton L 2006 · 3.43 FIP	29	SU	3.43	21.6%	7.5%	2.2%	.263	2.61	27.2%	20.5%	196	-0.82	1.71	663	53
Chasen Shreve L 2019 · 3.95 FIP	29	SU	3.95	24.4%	11.1%	2.7%	.269	4.59	23.9%	13.0%	108	+0.64	1.33	483	53
Adam Liberatore L 2016 · 2.38 FIP	29	SU	2.38	26.7%	7.4%	1.1%	.281	4.28	18.6%	9.5%	30	+1.90	2.38	124	52

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	2.4	61	28.5%	10.1%	0.89	3.51
Mychal Givens ('23)	2.3	58	28.2%	10.0%	1.05	3.47
Al Hrabosky ('70-'82, 10 WAR*)	3.6	72	26.7%*	10.1%*	0.98*	3.50*
Norm Charlton ('88-'01, 10 WAR*)	4.5	75	26.3%*	10.3%*	0.87*	3.83*
Antonio Osuna ('05)	2.4	61	24.0%	10.0%	0.81	3.68
Randy Myers ('85-'98, 16 WAR*)	4.4	74	29.4%*	10.4%*	0.92*	3.47*
Ugueth Urbina ('05)	3.5	70	27.9%	10.5%	1.11	3.45