Gerardo Carrillo

P Reno Aces

Age 28 RHP 6'1" / 170 lbs AAA peak 0.3 · 2027

Overview

AAARP40-MANROOKIE

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	24	AAWSH	2	2	0.00	4.81	14.3%	28.6%	—	K 14.3% · BB 28.6% · FIP 5.51
2025	26	MIX2 levels	42	49	3.88	2.44	26.7%	8.6%	—	K 21.7% · BB 10.0% · FIP 3.22
2026	27	MIX2 levels	50	65	4.04	3.32	30.1%	14.2%	1.0	K 26.9% · BB 13.3% · FIP 3.56
2027PROJ	28	MLBARI	44	46	4.21	4.24	25.9%	12.9%	0.2
2028PROJ78% MLB	29	MLBARI	39	41	4.33	4.41	25.0%	12.7%	0.1
2029PROJ83% MLB	30	MLBARI	35	37	4.49	4.61	24.2%	12.8%	-0.0

Last 3 seasons WAR 1.0 · Next 3 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo84

K%70

xwOBA vs63

Career WAR0.0 WAR median (P10 -0.2 / P90 0.7, comp-based) · star 0% · didn't stick 94%

CompsDaniel Robert (age 28) · Peyton Gray (age 26) · Jason Bulger (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 114106vR 98

ERA4.21

FIP4.24

K%25.9%

BB%12.9%

K-BB%13.0%

Proj IP66

Value2027 · WAR

Runs saved vs league avg · 66 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL4545

CMD5050

K†6060

Statcast Percentiles

FB Velo

p8496.9

Whiff%

p7228.8%

p7025.9%

xwOBA vs

p630.299

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)
2017	18	ROK MLE	DSL Dodgers 2	14	10	48	210	32	14	1	71%	3.5	10.4%	8.3%	2.0%	0.7%	2.79	3.65	—
2017	18	ROK RAW	DSL Dodgers 2	14	10	48	210	32	14	1	71%	3.5	15.2%	6.7%	8.6%	0.5%	2.79	2.91	—
2018	19	MIX MLE	2 levels	13	10	60	237	50	16	3	77%	4.6	14.0%	8.5%	5.6%	1.8%	1.50	3.99	—
2018	19	MIX RAW	2 levels	13	10	60	237	50	16	3	77%	4.6	21.1%	6.8%	14.3%	1.3%	1.50	2.88	—
2019	20	A+ MLE	Rancho Cucamonga Quakes	23	21	86	405	86	51	3	91%	3.7	16.4%	14.5%	1.9%	1.0%	5.44	4.08	—
2019	20	A+ RAW	Rancho Cucamonga Quakes	23	21	86	405	86	51	3	91%	3.7	21.2%	12.6%	8.6%	0.7%	5.44	3.33	—
2021	22	AA MLE	Harrisburg Senators	23	22	96	444	108	50	14	96%	4.2	19.7%	12.4%	7.3%	3.6%	4.76	5.01	—
2021	22	AA RAW	Harrisburg Senators	23	22	96	444	108	50	14	96%	4.2	24.3%	11.3%	13.1%	3.2%	4.76	4.30	—
2022	23	MIX MLE	3 levels	21	1	23	115	28	13	2	5%	1.1	23.7%	15.2%	8.6%	2.1%	6.94	4.18	—
2022	23	MIX RAW	3 levels	21	1	23	115	28	13	2	5%	1.1	24.3%	11.3%	13.0%	1.7%	6.94	3.49	—
2023	24	AA MLE	Harrisburg Senators	2	0	2	7	1	2	0	0%	1.2	14.3%	28.6%	-14.3%	0.0%	0.00	5.51	—
2023	24	AA RAW	Harrisburg Senators	2	0	2	7	1	2	0	0%	1.2	14.3%	28.6%	-14.3%	0.0%	0.00	4.81	—
2025	26	MIX MLE	2 levels	42	0	49	210	56	18	2	0%	1.2	21.7%	10.0%	11.7%	1.2%	3.88	3.22	—
2025	26	MIX MLE	2 levels	42	0	49	210	56	18	2	0%	1.2	21.7%	10.0%	11.7%	1.2%	3.88	3.22	—
2025	26	MIX RAW	2 levels	42	0	49	210	56	18	2	0%	1.2	26.7%	8.6%	18.1%	1.0%	3.88	2.44	—
2026	27	MIX MLE	2 levels	50	0	65	289	87	41	5	0%	1.3	26.9%	13.3%	13.6%	1.9%	4.04	3.56	+0.8
2026	27	MIX MLE	2 levels	50	0	65	289	87	41	5	0%	1.3	26.9%	13.3%	13.6%	1.9%	4.04	3.56	+0.8
2026	27	MIX RAW	2 levels	50	0	65	289	87	41	5	0%	1.3	30.1%	14.2%	15.9%	1.7%	4.04	3.32	+1.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			13	0	17	81	21	15	0	0%	1.3	25.9%	18.5%	7.4%	0.0%	4.15	3.27	+0.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	ARI	44	0	46	194	50	25	5	0%	1.0	25.9%	12.9%	13.0%	2.4%	4.21	4.24	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	ARI	50	0	53	223	56	28	6	0%	1.1	25.0%	12.7%	12.3%	2.6%	4.33	4.41	+0.1
2029	30	MLB MLE	ARI	42	0	44	187	45	24	5	0%	1.1	24.2%	12.8%	11.4%	2.8%	4.49	4.61	-0.0
2028	29	MLB CTX	ARI	39	0	41	173	43	22	5	0%	1.1	25.0%	12.7%	12.3%	2.6%	4.33	4.41	+0.1
2029	30	MLB CTX	ARI	35	0	37	156	38	20	4	0%	1.1	24.2%	12.8%	11.4%	2.8%	4.49	4.61	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		87	0	95	411	102	57	9	0%	1.1	24.9%	13.9%	11.0%	2.2%	4.36	3.95	+0.7
/ 200 IP	—	RAW		183	0	200	861	214	119	19	0%	1.1	24.9%	13.9%	11.0%	2.2%	4.36	3.95	+1.4
Career	—	MLE		188	64	430	1917	360	230	36	34%	2.3	18.8%	12.0%	6.8%	1.9%	4.11	4.07	+0.3
/ 200 IP	—	MLE		88	30	200	892	168	107	17	34%	2.3	18.8%	12.0%	6.8%	1.9%	4.11	4.07	+0.6

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 AAAReno Aces · 47 IPFIP 3.32 → 3.67 (+0.35)K% 31.7% → 27.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.73%	—	×0.860	27.29%
BB% (unintentional) /BF	12.50%	—	×0.900	11.25%
HR / BF /BF	2.40%	÷1.000	×1.100	2.64%

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 3.32 → 3.67, 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 AAFrisco RoughRiders · 46 IPFIP 2.55 → 3.22 (+0.67)K% 26.8% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.77%	—	×0.810	21.68%
BB% (unintentional) /BF	9.09%	—	×1.100	10.00%
HR / BF /BF	1.01%	÷0.976	×1.200	1.24%

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 95).

Result: FIP 2.55 → 3.22, 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).

2022 AAHarrisburg Senators · 10 IPFIP 3.32 → 4.18 (+0.86)K% 29.3% → 23.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.31%	—	×0.810	23.74%
BB% (unintentional) /BF	13.79%	—	×1.100	15.17%
HR / BF /BF	1.72%	÷0.979	×1.200	2.11%

Result: FIP 3.32 → 4.18, 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+Wilmington Blue Rocks · 10 IPFIP 3.89 → 4.71 (+0.83)K% 23.3% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.26%	—	×0.770	17.91%
BB% (unintentional) /BF	11.63%	—	×1.150	13.37%
HR / BF /BF	2.33%	÷1.114	×1.250	2.61%

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 123).

Result: FIP 3.89 → 4.71, 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).

2021 AAHarrisburg Senators · 96 IPFIP 4.20 → 5.01 (+0.80)K% 24.3% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.32%	—	×0.810	19.70%
BB% (unintentional) /BF	11.26%	—	×1.100	12.39%
HR / BF /BF	3.15%	÷1.037	×1.200	3.65%

Result: FIP 4.20 → 5.01, 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+Rancho Cucamonga Quakes · 86 IPFIP 3.31 → 4.08 (+0.77)K% 21.2% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.23%	—	×0.770	16.35%
BB% (unintentional) /BF	12.59%	—	×1.150	14.48%
HR / BF /BF	0.74%	÷0.969	×1.250	0.96%

Result: FIP 3.31 → 4.08, 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).

2018 AGreat Lakes Loons · 49 IPFIP 3.25 → 3.99 (+0.73)K% 19.0% → 14.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.97%	—	×0.740	14.04%
BB% (unintentional) /BF	7.18%	—	×1.180	8.47%
HR / BF /BF	1.54%	÷1.100	×1.300	1.82%

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 120).

Result: FIP 3.25 → 3.99, 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 ROKAZL Dodgers · 11 IPFIP 1.09 → 2.08 (+0.99)K% 31.0% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.95%	—	×0.680	21.05%
BB% (unintentional) /BF	4.76%	—	×1.250	5.95%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

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 1.09 → 2.08, 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).

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
Gerardo Carrillo (OGILVIE)	—	—	4.24	25.9%	12.9%	2.4%	—	4.50	24.6%	11.9%	97	+0.26	—	—	—
Daniel Robert R 2023 · 3.45 FIP	28	SU	3.45	22.7%	10.7%	1.7%	.310	3.02	25.4%	17.1%	87	-0.43	2.32	186	73
Peyton Gray R 2021 · 4.27 FIP	26	SU	4.27	29.2%	14.1%	3.4%	.307	—	—	—	—	—	3.62	160	69
Jason Bulger R 2008 · 4.60 FIP	29	SU	4.60	27.4%	12.3%	4.1%	.293	3.94	25.1%	13.3%	90	-0.66	3.78	106	69
Zach Franklin R 2024 · 3.24 FIP	25	SU	3.24	26.4%	10.9%	1.8%	.301	4.15	27.5%	18.3%	117	+0.91	3.24	158	69
Josh Lueke R 2013 · 4.09 FIP	28	SU	4.09	25.3%	11.1%	3.1%	.333	3.28	24.6%	20.9%	90	-0.81	2.29	191	68
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	68
Spencer Bivens R 2022 · 4.86 FIP	28	SU	4.86	19.8%	13.5%	3.1%	.265	3.85	18.1%	10.3%	272	-1.01	3.52	391	68
Kiko Calero R 2003 · 3.54 FIP	28	SU	3.54	31.5%	11.1%	3.1%	.273	3.11	26.1%	18.9%	159	-0.43	2.27	298	68
Marcos Mateo R 2011 · 3.40 FIP	27	SU	3.40	25.5%	10.2%	2.1%	.361	—	—	—	—	—	3.12	104	68
Matt Ramsey R 2018 · 3.78 FIP	28	SU	3.78	24.9%	8.8%	3.0%	.276	2.42	21.7%	12.6%	34	-1.36	2.42	125	68
Michael Dimock R 2018 · 3.37 FIP	28	SU	3.37	23.5%	10.7%	1.6%	.346	—	—	—	—	—	3.08	166	67
Trevor May R 2018 · 3.74 FIP	28	SU	3.74	26.1%	9.8%	2.9%	.291	3.47	31.9%	23.6%	150	-0.27	3.05	477	67
Joe Colón J R 2017 · 4.25 FIP	27	SU	4.25	20.4%	12.1%	2.4%	.315	—	—	—	—	—	3.27	113	67
Jeff Ames R 2019 · 4.45 FIP	28	SU	4.45	25.6%	16.8%	2.5%	.351	—	—	—	—	—	3.85	272	67
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	67
Jose De La Torre R 2013 · 5.22 FIP	27	SU	5.22	28.3%	18.9%	3.9%	.308	3.87	17.6%	6.6%	110	-1.35	2.64	141	67
Luis Santos R 2019 · 4.31 FIP	28	SU	4.31	22.9%	10.0%	3.4%	.312	—	—	—	—	—	3.53	472	67
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	66
Grant Sides R 2016 · 3.83 FIP	27	SU	3.83	22.4%	11.9%	2.0%	.247	3.31	21.7%	11.9%	47	-0.52	3.31	159	66
Andrew Robinson R 2016 · 3.19 FIP	28	SU	3.19	22.2%	7.9%	1.8%	.247	4.32	23.4%	14.6%	39	+1.13	3.19	160	66

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	60	25.2%	13.5%	0.89	4.31
Chad Fox ('09)	1.1	57	25.8%	13.2%	0.87	3.79
Derrick Turnbow ('08)	1.3	64	23.4%	14.8%	0.87	4.30
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*
Kyle Barraclough ('23)	1.4	56	28.2%	13.9%	0.99	3.86
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*
Dennis Higgins ('66-'72, 1 WAR*)	2.1	82	24.5%*	12.2%*	0.94*	4.34*