Julian Aguiar

P Louisville Bats

Age 26 RHP 6'3" / 180 lbs AAA peak 0.1 · 2027

Overview

AAARP40-MANROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	22	MIX2 levels	25	25	125	2.95	2.61	26.8%	7.2%	—	K 21.1% · BB 8.1% · FIP 3.38
2024	23	MIX3 levels	29	29	148	4.32	4.21	18.3%	6.4%	2.1	K 15.8% · BB 6.4% · FIP 4.44
2026	25	MIX3 levels	17	16	61	6.05	4.85	21.2%	11.4%	0.4	K 18.2% · BB 11.8% · FIP 5.33
2027PROJ	26	MLBCIN	7	7	41	4.80	5.18	17.6%	9.5%	0.1
2028PROJ82% MLB	27	MLBCIN	6	6	39	4.97	5.13	18.2%	9.6%	0.1
2029PROJ87% MLB	28	MLBCIN	6	6	38	5.06	5.16	18.5%	9.7%	0.1

Last 3 seasons WAR 2.5 · Next 3 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2024

FB Velo48

xwOBA vs26

K%10

Career WAR0.0 WAR median (P10 -0.5 / P90 1.2, comp-based) · star 0% · didn't stick 92%

CompsJake Walters (age 26) · Hiram Burgos (age 25) · Ramon Ramirez (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 132123vR 115

ERA4.80

FIP5.18

K%17.6%

BB%9.5%

K-BB%8.1%

Proj IP55

Value2027 · WAR

Runs saved vs league avg · 55 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p4894.4

Whiff%

p1018.6%

p1013.6%

xwOBA vs

p260.340

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)
2021	20	ROK MLE	ACL Reds	5	0	9	38	14	0	1	0%	1.7	36.8%	0.0%	36.8%	2.6%	3.12	1.43	—
2021	20	ROK RAW	ACL Reds	5	0	9	38	14	0	1	0%	1.7	36.8%	0.0%	36.8%	2.6%	3.12	1.37	—
2022	21	MIX MLE	2 levels	25	17	96	410	113	27	13	68%	3.9	20.4%	6.9%	13.4%	4.7%	3.46	4.85	—
2022	21	MIX RAW	2 levels	25	17	96	410	113	27	13	68%	3.9	27.6%	6.6%	21.0%	3.2%	3.46	3.35	—
2023	22	MIX MLE	2 levels	25	25	125	515	138	37	8	100%	5.0	21.1%	8.1%	13.0%	1.9%	2.95	3.38	—
2023	22	MIX RAW	2 levels	25	25	125	515	138	37	8	100%	5.0	26.8%	7.2%	19.6%	1.6%	2.95	2.61	—
2024	23	MIX MLE	3 levels	29	29	148	622	114	40	21	100%	5.1	15.8%	6.4%	9.4%	3.4%	4.32	4.44	+1.7
2024	23	MIX MLE	3 levels	29	29	148	622	114	40	21	100%	5.1	15.8%	6.4%	9.4%	3.4%	4.32	4.44	+1.7
2024	23	MIX RAW	3 levels	29	29	148	622	114	40	21	100%	5.1	18.3%	6.4%	11.9%	3.4%	4.32	4.21	+2.1
2026	25	MIX MLE	3 levels	17	16	61	273	58	31	10	94%	3.6	18.2%	11.8%	6.3%	4.1%	6.05	5.33	+0.0
2026	25	MIX MLE	3 levels	17	16	61	273	58	31	10	94%	3.6	18.2%	11.8%	6.3%	4.1%	6.05	5.33	+0.0
2026	25	MIX RAW	3 levels	17	16	61	273	58	31	10	94%	3.6	21.2%	11.4%	9.9%	3.7%	6.05	4.85	+0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			8	7	35	154	21	12	8	88%	4.3	13.6%	7.8%	5.8%	5.2%	6.23	5.93	-0.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	CIN	7	7	41	173	31	16	6	100%	5.9	17.6%	9.5%	8.1%	3.6%	4.80	5.18	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	CIN	8	8	48	201	37	19	7	100%	6.0	18.2%	9.6%	8.7%	3.6%	4.97	5.13	+0.1
2029	28	MLB MLE	CIN	7	7	43	182	34	18	7	100%	6.2	18.5%	9.7%	8.8%	3.7%	5.06	5.16	+0.1
2028	27	MLB CTX	CIN	6	6	39	165	30	16	6	100%	6.5	18.2%	9.6%	8.7%	3.6%	4.97	5.13	+0.1
2029	28	MLB CTX	CIN	6	6	38	160	30	16	6	100%	6.3	18.5%	9.7%	8.8%	3.7%	5.06	5.16	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		21	20	111	478	80	43	20	95%	5.3	16.8%	9.0%	7.8%	4.1%	5.39	5.09	+0.4
/ 200 IP	—	RAW		37	36	200	858	144	77	36	95%	5.4	16.8%	9.0%	7.8%	4.1%	5.39	5.09	+0.7
Career	—	MLE		101	87	439	1858	354	142	62	86%	4.3	19.0%	7.7%	11.4%	3.4%	3.96	4.31	+0.1
/ 200 IP	—	MLE		46	40	200	846	161	65	28	86%	4.3	19.0%	7.7%	11.4%	3.4%	3.96	4.31	+0.1

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.

2026 AAALouisville Bats · 47 IPFIP 5.04 → 5.33 (+0.29)K% 21.1% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.13%	—	×0.860	18.17%
BB% (unintentional) /BF	13.15%	—	×0.900	11.83%
HR / BF /BF	3.76%	÷1.000	×1.100	4.13%

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 5.04 → 5.33, 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).

2026 A+Dayton Dragons · 11 IPFIP 4.02 → 5.16 (+1.14)K% 23.9% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.91%	—	×0.770	18.41%
BB% (unintentional) /BF	4.35%	—	×1.150	5.00%
HR / BF /BF	4.35%	÷1.000	×1.250	5.43%

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 100).

Result: FIP 4.02 → 5.16, 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 AAChattanooga Lookouts · 69 IPFIP 3.43 → 3.93 (+0.50)K% 19.1% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.08%	—	×0.810	15.46%
BB% (unintentional) /BF	4.59%	—	×1.100	5.05%
HR / BF /BF	2.47%	÷1.089	×1.200	2.73%

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 118).

Result: FIP 3.43 → 3.93, 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 AAALouisville Bats · 47 IPFIP 4.03 → 4.16 (+0.13)K% 20.6% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.60%	—	×0.860	17.72%
BB% (unintentional) /BF	8.04%	—	×0.900	7.24%
HR / BF /BF	3.02%	÷1.111	×1.100	2.99%

Result: FIP 4.03 → 4.16, 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+Dayton Dragons · 70 IPFIP 2.26 → 3.08 (+0.81)K% 27.2% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.21%	—	×0.770	20.95%
BB% (unintentional) /BF	8.48%	—	×1.150	9.75%
HR / BF /BF	0.71%	÷0.951	×1.250	0.93%

Result: FIP 2.26 → 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).

2023 AAChattanooga Lookouts · 55 IPFIP 3.01 → 3.76 (+0.75)K% 26.3% → 21.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.29%	—	×0.810	21.30%
BB% (unintentional) /BF	5.60%	—	×1.100	6.16%
HR / BF /BF	2.59%	÷1.017	×1.200	3.05%

Result: FIP 3.01 → 3.76, 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 ADaytona Tortugas · 88 IPFIP 3.28 → 4.85 (+1.57)K% 27.5% → 20.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.54%	—	×0.740	20.38%
BB% (unintentional) /BF	5.88%	—	×1.180	6.94%
HR / BF /BF	3.21%	÷0.883	×1.300	4.73%

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 77).

Result: FIP 3.28 → 4.85, 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).

2022 A+Dayton Dragons · 8 IPFIP 4.04 → 5.12 (+1.08)K% 27.8% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.78%	—	×0.770	21.39%
BB% (unintentional) /BF	13.89%	—	×1.150	15.97%
HR / BF /BF	2.78%	÷1.058	×1.250	3.28%

Result: FIP 4.04 → 5.12, 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
Julian Aguiar (OGILVIE)	—	—	—	—	—	3.6%	—	5.14	18.3%	8.7%	91	-0.04	—	—	—
Jake Walters R 2022 · 4.03 FIP	26	SP-	4.03	17.0%	9.4%	2.1%	.316	5.85	15.2%	1.3%	72	+1.82	3.51	261	75
Hiram Burgos R 2013 · 4.89 FIP	25	SP	4.89	12.9%	7.9%	3.4%	.314	3.73	18.0%	8.7%	293	-1.16	3.40	384	74
Ramon Ramirez R 2008 · 4.31 FIP	25	SP-	4.31	20.0%	10.5%	2.9%	.200	—	—	—	—	—	3.65	182	74
Brian Stokes R 2006 · 3.98 FIP	26	SP-	3.98	13.6%	8.2%	1.8%	.345	4.51	14.3%	6.3%	166	+0.53	3.96	207	74
Carlos Torres R 2009 · 5.24 FIP	26	SP-	5.24	16.9%	11.5%	3.9%	.284	3.59	18.2%	7.3%	67	-1.65	2.89	604	74
Justin Topa R 2018 · 4.15 FIP	27	SP-	4.15	15.1%	7.9%	2.4%	.374	2.69	19.2%	12.6%	40	-1.46	2.67	284	74
Britt Reames R 2000 · 4.49 FIP	26	SP	4.49	18.2%	12.9%	2.4%	.230	4.35	21.9%	11.5%	163	-0.14	3.76	204	73
Darrell Rasner R 2007 · 5.15 FIP	26	SP	5.15	9.9%	7.2%	3.6%	.284	4.43	13.1%	5.7%	113	-0.72	4.07	158	72
Travis Smith R 2002 · 5.28 FIP	29	SP	5.28	13.1%	8.2%	4.1%	.324	5.71	15.0%	9.0%	51	+0.43	3.67	105	71
Seth Shuman R 2024 · 5.47 FIP	26	SP	5.47	14.1%	8.0%	4.7%	.273	4.61	17.0%	11.3%	157	-0.86	3.16	357	71
Ricky Castro R 2024 · 3.99 FIP	24	SP-	3.99	20.4%	8.6%	2.8%	.287	5.11	19.0%	10.6%	178	+1.12	3.99	241	70
Denny Bautista R 2006 · 4.71 FIP	25	SP-	4.71	13.9%	10.8%	2.6%	.298	4.58	17.5%	3.3%	74	-0.13	3.38	238	69
Shane McCarthy R 2021 · 5.47 FIP	25	SP	5.47	18.9%	11.9%	4.5%	.240	8.32	14.3%	3.9%	18	+2.85	2.07	117	69
Cha Seung Baek R 2006 · 5.24 FIP	26	SP	5.24	16.4%	9.3%	4.3%	.204	3.97	15.3%	9.6%	214	-1.27	3.35	280	69
Nick Payero R 2024 · 4.21 FIP	24	SP-	4.21	16.5%	6.3%	3.1%	.285	5.81	16.6%	4.6%	107	+1.60	4.21	178	68
Spencer Jones R 2019 · 5.49 FIP	24	SP	5.49	14.9%	8.9%	4.6%	.331	—	—	—	—	—	2.48	171	68
Zach Haake R 2023 · 4.45 FIP	26	SP	4.45	16.8%	9.0%	3.0%	.291	4.69	20.6%	6.5%	49	+0.24	3.44	272	67
Wirkin Estevez R 2018 · 4.68 FIP	26	SP	4.68	14.8%	7.3%	3.5%	.276	—	—	—	—	—	4.37	238	67
Alejandro Martinez R 2015 · 4.46 FIP	26	SP-	4.46	17.5%	10.9%	2.7%	.393	4.24	9.2%	3.9%	53	-0.22	4.24	166	67
Kohei Arihara R 2021 · 6.04 FIP	28	SP	6.04	13.5%	7.3%	5.8%	.262	4.58	16.4%	9.2%	94	-1.46	4.58	135	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	0.9	45	17.2%	9.4%	1.52	5.18
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
Lance Painter ('03)	2.2	56	16.7%	9.0%	1.32	5.24
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Chuck Hartenstein ('66-'77, -1 WAR*)	1.5	59	13.7%*	7.2%*	1.50*	5.28*