Patricio Aquino

P Biloxi Shuckers

Age 24 RHP 6'0" / 175 lbs AA

Overview

AAPROSPECT

ETA2028MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	22	A+MIL	33	2	67	4.16	3.00	18.8%	8.9%	—	K 14.5% · BB 10.2% · FIP 3.54
2026	23	AAMIL	6	0	11	5.06	4.60	15.2%	21.7%	—	K 15.2% · BB 21.7% · FIP 4.57
2027PROJ	24	MLBMIL	1	0	1	5.25	5.25	13.6%	11.2%	-0.0
2028PROJ44% MLB	25	MLBMIL	20	0	21	5.09	5.04	15.5%	10.8%	-0.1
2029PROJ67% MLB	26	MLBMIL	28	0	29	4.98	4.94	16.7%	10.7%	-0.1

Next 3 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff35Control45Command35

Career WAR0.0 WAR median (P10 -0.4 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsDavid Rodriguez (age 22) · Matt Marsh (age 24) · Jonathan Hughes (age 24)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 133125vR 117

ERA5.25

FIP5.25

K%13.6%

BB%11.2%

K-BB%2.3%

Proj IP67

Value2027 · WAR

Runs saved vs league avg · 67 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL4545

CMD3535

K†3040

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	18	ROK MLE	DSL Brewers 1	11	11	44	190	54	27	0	100%	4.0	19.3%	17.8%	1.6%	0.0%	2.66	3.72	—
2021	18	ROK RAW	DSL Brewers 1	11	11	44	190	54	27	0	100%	4.0	28.4%	14.2%	14.2%	0.0%	2.66	2.49	—
2022	19	ROK MLE	ACL Brewers Gold	8	7	34	152	49	16	3	88%	4.3	21.9%	13.2%	8.8%	2.4%	4.72	4.24	—
2022	19	ROK RAW	ACL Brewers Gold	8	7	34	152	49	16	3	88%	4.3	32.2%	10.5%	21.7%	2.0%	4.72	2.78	—
2023	20	A MLE	Carolina Mudcats	21	19	88	369	86	31	6	90%	4.2	17.2%	9.9%	7.3%	2.0%	2.75	3.98	—
2023	20	A RAW	Carolina Mudcats	21	19	88	369	86	31	6	90%	4.2	23.3%	8.4%	14.9%	1.6%	2.75	3.09	—
2024	21	A+ MLE	Wisconsin Timber Rattlers	20	10	79	330	57	23	6	50%	4.0	13.3%	8.0%	5.3%	2.3%	3.65	4.27	—
2024	21	A+ MLE	Wisconsin Timber Rattlers	20	10	79	330	57	23	6	50%	4.0	13.3%	8.0%	5.3%	2.3%	3.65	4.27	—
2024	21	A+ RAW	Wisconsin Timber Rattlers	20	10	79	330	57	23	6	50%	4.0	17.3%	7.0%	10.3%	1.8%	3.65	3.52	—
2025	22	A+ MLE	Wisconsin Timber Rattlers	33	2	67	303	57	27	2	6%	2.0	14.5%	10.2%	4.2%	0.7%	4.16	3.54	—
2025	22	A+ MLE	Wisconsin Timber Rattlers	33	2	67	303	57	27	2	6%	2.0	14.5%	10.2%	4.2%	0.7%	4.16	3.54	—
2025	22	A+ RAW	Wisconsin Timber Rattlers	33	2	67	303	57	27	2	6%	2.0	18.8%	8.9%	9.9%	0.7%	4.16	3.00	—
2026	23	AA MLE	Biloxi Shuckers	6	0	11	46	7	10	0	0%	1.8	15.2%	21.7%	-6.5%	0.0%	5.06	4.57	—
2026	23	AA MLE	Biloxi Shuckers	6	0	11	46	7	10	0	0%	1.8	15.2%	21.7%	-6.5%	0.0%	5.06	4.57	—
2026	23	AA RAW	Biloxi Shuckers	6	0	11	46	7	10	0	0%	1.8	15.2%	21.7%	-6.5%	0.0%	5.06	4.60	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	24	MLB	MIL	1	0	1	4	1	0	0	0%	1.0	13.6%	11.2%	2.3%	2.7%	5.25	5.25	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	25	MLB MLE	MIL	46	0	49	206	32	22	6	0%	1.1	15.5%	10.8%	4.7%	2.7%	5.09	5.04	-0.3
2029	26	MLB MLE	MIL	41	0	43	181	30	19	5	0%	1.0	16.7%	10.7%	6.0%	2.7%	4.98	4.94	-0.2
2030	27	MLB MLE	MIL	38	0	40	169	29	18	5	0%	1.1	17.0%	10.7%	6.3%	2.8%	4.94	4.94	-0.2
2031	28	MLB MLE	MIL	36	0	38	160	27	17	5	0%	1.0	17.0%	10.8%	6.2%	2.9%	4.98	5.01	-0.2
2028	25	MLB CTX	MIL	20	0	21	89	14	10	2	0%	1.1	15.5%	10.8%	4.7%	2.7%	5.09	5.04	-0.1
2029	26	MLB CTX	MIL	28	0	29	122	20	13	3	0%	1.0	16.7%	10.7%	6.0%	2.7%	4.98	4.94	-0.1
2030	27	MLB CTX	MIL	30	0	31	131	22	14	4	0%	1.0	17.0%	10.7%	6.3%	2.8%	4.94	4.94	-0.1
2031	28	MLB CTX	MIL	30	0	32	135	23	15	4	0%	1.1	17.0%	10.8%	6.2%	2.9%	4.98	5.01	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		108	0	113	477	79	51	13	0%	1.0	16.6%	10.8%	5.9%	2.8%	4.99	4.60	-0.1
/ 200 IP	—	RAW		190	0	200	844	140	90	23	0%	1.1	16.6%	10.8%	5.9%	2.8%	4.99	4.60	-0.1
Career	—	MLE		99	49	323	1390	228	158	21	49%	3.3	16.4%	11.4%	5.1%	1.5%	3.54	3.96	-0.9
/ 200 IP	—	MLE		61	30	200	860	141	98	13	49%	3.3	16.4%	11.4%	5.1%	1.5%	3.54	3.96	-1.0

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 AABiloxi Shuckers · 11 IPFIP 4.57 → 5.09 (+0.52)K% 15.2% → 12.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.22%	—	×0.810	12.33%
BB% (unintentional) /BF	21.74%	—	×1.100	23.91%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 4.57 → 5.09, 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 A+Wisconsin Timber Rattlers · 67 IPFIP 3.00 → 3.54 (+0.54)K% 18.8% → 14.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.81%	—	×0.770	14.49%
BB% (unintentional) /BF	8.91%	—	×1.150	10.25%
HR / BF /BF	0.66%	÷1.246	×1.250	0.66%

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 149).

Result: FIP 3.00 → 3.54, 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+Wisconsin Timber Rattlers · 79 IPFIP 3.52 → 4.27 (+0.74)K% 17.3% → 13.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.27%	—	×0.770	13.30%
BB% (unintentional) /BF	6.97%	—	×1.150	8.02%
HR / BF /BF	1.82%	÷0.979	×1.250	2.32%

Result: FIP 3.52 → 4.27, 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 ACarolina Mudcats · 88 IPFIP 3.09 → 3.98 (+0.89)K% 23.3% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.31%	—	×0.740	17.25%
BB% (unintentional) /BF	8.40%	—	×1.180	9.91%
HR / BF /BF	1.63%	÷1.072	×1.300	1.97%

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 114).

Result: FIP 3.09 → 3.98, 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 ROKACL Brewers Gold · 34 IPFIP 2.79 → 4.24 (+1.45)K% 32.2% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.24%	—	×0.680	21.92%
BB% (unintentional) /BF	10.53%	—	×1.250	13.16%
HR / BF /BF	1.97%	÷1.144	×1.400	2.41%

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 129).

Result: FIP 2.79 → 4.24, 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 ROKDSL Brewers 1 · 44 IPFIP 2.50 → 3.72 (+1.22)K% 28.4% → 19.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.42%	—	×0.680	19.33%
BB% (unintentional) /BF	14.21%	—	×1.250	17.76%
HR / BF /BF	0.00%	÷0.948	×1.400	0.00%

Result: FIP 2.50 → 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).

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
Patricio Aquino (OGILVIE)	—	—	5.25	13.6%	11.2%	2.7%	—	4.98	16.3%	5.6%	132	-0.27	—	—	—
David Rodriguez R 2024 · 4.50 FIP	22	SP-	4.50	13.5%	11.7%	1.9%	.316	3.85	16.9%	9.9%	125	-0.65	3.80	184	87
Matt Marsh R 2015 · 4.14 FIP	24	SW	4.14	15.5%	10.7%	1.8%	.275	3.65	20.5%	11.4%	70	-0.49	3.13	143	87
Jonathan Hughes R 2021 · 4.60 FIP	24	SP-	4.60	12.9%	12.5%	1.8%	.351	3.79	16.5%	6.2%	146	-0.81	3.44	219	87
Marco Camarena R 2016 · 4.49 FIP	25	SW	4.49	11.0%	9.3%	2.1%	.365	3.75	8.4%	0.9%	73	-0.74	3.75	142	85
Hunter Adkins R 2016 · 4.64 FIP	25	SW	4.64	16.2%	10.3%	2.9%	.290	4.82	11.8%	0.5%	58	+0.18	4.64	160	85
Dennis O'Grady R 2015 · 4.95 FIP	26	SW	4.95	13.5%	11.0%	2.9%	.339	—	—	—	—	—	3.62	157	85
Wirkin Estevez R 2016 · 5.39 FIP	24	SW	5.39	10.7%	13.4%	2.7%	.316	4.46	12.3%	3.5%	179	-0.93	4.37	238	84
Jeff Manship R 2009 · 4.69 FIP	24	SW	4.69	14.4%	10.3%	2.7%	.330	4.23	14.9%	9.5%	51	-0.46	2.83	250	84
Tyler Brashears R 2017 · 5.47 FIP	23	SW	5.47	12.1%	13.0%	3.2%	.314	—	—	—	—	—	3.58	156	84
Dakota Hawkins R 2024 · 4.31 FIP	24	SW	4.31	16.3%	8.9%	2.7%	.277	4.32	19.4%	10.4%	102	+0.01	3.50	186	82
LJ Brewster R 2017 · 5.07 FIP	23	SW	5.07	9.4%	11.0%	2.5%	.266	—	—	—	—	—	4.41	143	82
Jorge Sosa R 2002 · 5.77 FIP	25	SW	5.77	11.1%	12.4%	3.7%	.228	4.55	15.7%	5.5%	362	-1.22	4.06	773	82
Zach Miner R 2006 · 4.35 FIP	24	SP-	4.35	14.8%	7.8%	2.8%	.300	4.24	13.8%	4.6%	264	-0.11	3.55	386	82
Chad Bettis R 2013 · 4.38 FIP	24	SP-	4.38	14.4%	8.7%	2.6%	.318	3.81	17.4%	10.4%	365	-0.57	3.67	672	82
Paulshawn Pasqualotto R 2024 · 4.84 FIP	23	SW	4.84	15.6%	9.5%	3.4%	.354	3.77	20.2%	10.8%	111	-1.07	3.73	186	81
Cooper Adams R 2024 · 5.42 FIP	24	SW	5.42	13.0%	12.2%	3.4%	.275	4.32	21.7%	10.4%	141	-1.10	3.05	221	81
Cullen Kafka R 2023 · 4.95 FIP	24	SW	4.95	14.2%	12.1%	2.8%	.330	—	—	—	—	—	3.64	148	81
Kyle Haynes R 2015 · 4.08 FIP	24	SP-	4.08	14.3%	10.3%	1.6%	.302	4.58	15.7%	5.8%	124	+0.50	4.08	240	81
Yaisel Sierra R 2016 · 4.32 FIP	25	SW	4.32	16.9%	8.6%	2.8%	.338	3.04	22.4%	12.3%	71	-1.28	3.04	176	81
Brad Allen R 2015 · 4.25 FIP	26	SW	4.25	14.0%	12.6%	1.3%	.315	5.82	14.7%	1.5%	87	+1.57	4.25	149	80

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	1.2	47	15.7%	10.9%	1.07	5.07
Tom Martin ('07)	1.6	53	15.8%	10.1%	1.02	4.92
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Rodney Myers ('04)	1.2	60	15.0%	10.3%	1.05	5.07
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Mike Munoz ('89-'00, 1 WAR*)	1.8	46	17.6%*	10.2%*	0.93*	4.46*