Juan Burgos

P Reno Aces

Age 27 RHP 6'0" / 185 lbs AAA

Overview

AAARP40-MANROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	A+SEA	38	3	61	3.38	3.00	27.1%	8.9%	—	K 20.9% · BB 10.3% · FIP 3.77
2025	25	MIX3 levels	42	0	49	2.96	3.10	23.1%	9.1%	0.8	K 22.1% · BB 8.6% · FIP 3.50
2026	26	MIX2 levels	50	0	53	6.45	4.67	17.8%	10.7%	-0.1	K 16.4% · BB 10.4% · FIP 4.91
2027PROJ	27	MLBARI	19	0	20	4.65	4.85	18.4%	9.9%	-0.1
2028PROJ80% MLB	28	MLBARI	17	0	18	4.77	4.89	18.7%	10.0%	-0.1

Last 3 seasons WAR 0.8 · Next 2 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

FB Velo68

K%45

xwOBA vs10

Career WAR0.0 WAR median (P10 -0.2 / P90 0.9, comp-based) · star 0% · didn't stick 95%

CompsJoe Colón J (age 27) · Scott Proctor (age 27) · Chris Hatcher (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 125117vR 109

ERA4.65

FIP4.85

K%18.4%

BB%9.9%

K-BB%8.5%

Proj IP28

Value2027 · WAR

Runs saved vs league avg · 28 IP

Grades · Statcast · Contract

Scouting Grades

K†4545

Statcast Percentiles

FB Velo

p6895.8

Whiff%

p6026.9%

p4521.5%

xwOBA vs

p100.364

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)
2019	19	ROK MLE	DSL Mariners	17	4	42	185	42	20	3	24%	2.5	15.4%	13.5%	1.9%	2.3%	3.19	4.75	—
2019	19	ROK RAW	DSL Mariners	17	4	42	185	42	20	3	24%	2.5	22.7%	10.8%	11.9%	1.6%	3.19	3.45	—
2021	21	MIX MLE	2 levels	14	0	16	78	19	11	1	0%	1.2	17.7%	18.1%	-0.4%	0.0%	4.41	3.90	—
2021	21	MIX RAW	2 levels	14	0	16	78	19	11	1	0%	1.2	24.4%	14.1%	10.3%	1.3%	4.41	3.59	—
2022	22	MIX MLE	2 levels	26	3	43	187	46	26	2	12%	1.7	17.7%	16.5%	1.2%	1.5%	2.70	4.54	—
2022	22	MIX RAW	2 levels	26	3	43	187	46	26	2	12%	1.7	24.6%	13.9%	10.7%	1.1%	2.70	3.38	—
2023	23	A MLE	Modesto Nuts	30	0	32	146	39	17	1	0%	1.1	19.8%	13.7%	6.0%	1.0%	2.53	3.72	—
2023	23	A RAW	Modesto Nuts	30	0	32	146	39	17	1	0%	1.1	26.7%	11.6%	15.1%	0.7%	2.53	2.66	—
2024	24	A+ MLE	Everett AquaSox	38	3	61	258	70	23	5	8%	1.6	20.9%	10.3%	10.6%	2.1%	3.38	3.77	—
2024	24	A+ MLE	Everett AquaSox	38	3	61	258	70	23	5	8%	1.6	20.9%	10.3%	10.6%	2.1%	3.38	3.77	—
2024	24	A+ RAW	Everett AquaSox	38	3	61	258	70	23	5	8%	1.6	27.1%	8.9%	18.2%	1.9%	3.38	3.00	—
2025	25	MIX MLE	3 levels	42	0	49	208	48	19	3	0%	1.2	22.1%	8.6%	13.4%	2.1%	2.96	3.50	+0.6
2025	25	MIX MLE	3 levels	42	0	49	208	48	19	3	0%	1.2	22.1%	8.6%	13.4%	2.1%	2.96	3.50	+0.6
2025	25	MIX RAW	3 levels	42	0	49	208	48	19	3	0%	1.2	23.1%	9.1%	13.9%	1.4%	2.96	3.10	+0.8
2026	26	MIX MLE	2 levels	50	0	53	242	43	26	7	0%	1.1	16.4%	10.4%	6.0%	3.4%	6.45	4.91	-0.2
2026	26	MIX MLE	2 levels	50	0	53	242	43	26	7	0%	1.1	16.4%	10.4%	6.0%	3.4%	6.45	4.91	-0.2
2026	26	MIX RAW	2 levels	50	0	53	242	43	26	7	0%	1.1	17.8%	10.7%	7.0%	2.9%	6.45	4.67	-0.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			17	0	18	82	14	7	2	0%	1.0	17.1%	8.5%	8.5%	2.4%	5.09	4.18	+0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	ARI	19	0	20	84	16	8	3	0%	1.1	18.4%	9.9%	8.5%	3.0%	4.65	4.85	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	ARI	21	0	22	93	17	9	3	0%	1.1	18.7%	10.0%	8.8%	3.1%	4.77	4.89	-0.1
2028	28	MLB CTX	ARI	17	0	18	76	14	8	2	0%	1.1	18.7%	10.0%	8.8%	3.1%	4.77	4.89	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		34	0	35	156	28	14	4	0%	1.0	17.9%	9.2%	8.6%	2.8%	4.93	4.28	+0.1
/ 200 IP	—	RAW		191	0	200	886	159	79	23	0%	1.0	17.9%	9.2%	8.6%	2.8%	4.93	4.28	+0.6
Career	—	MLE		217	10	297	1304	244	160	27	5%	1.4	18.7%	12.2%	6.5%	2.0%	3.70	4.19	-0.0
/ 200 IP	—	MLE		146	7	200	878	164	108	18	5%	1.4	18.7%	12.2%	6.5%	2.0%	3.70	4.19	-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 AAAReno Aces · 49 IPFIP 4.66 → 4.91 (+0.25)K% 19.1% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.11%	—	×0.860	16.44%
BB% (unintentional) /BF	11.56%	—	×0.900	10.40%
HR / BF /BF	3.11%	÷1.000	×1.100	3.42%

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 4.66 → 4.91, 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).

2025 AAArkansas Travelers · 28 IPFIP 2.13 → 2.92 (+0.79)K% 27.6% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.62%	—	×0.810	22.37%
BB% (unintentional) /BF	6.67%	—	×1.100	7.33%
HR / BF /BF	0.95%	÷0.800	×1.200	1.43%

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 60).

Result: FIP 2.13 → 2.92, 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 AAAReno Aces · 7 IPFIP 3.66 → 3.64 (−0.01)K% 13.2% → 11.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.16%	—	×0.860	11.32%
BB% (unintentional) /BF	13.16%	—	×0.900	11.84%
HR / BF /BF	0.00%	÷0.904	×1.100	0.00%

Result: FIP 3.66 → 3.64, 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+Everett AquaSox · 61 IPFIP 3.00 → 3.77 (+0.76)K% 27.1% → 20.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.13%	—	×0.770	20.89%
BB% (unintentional) /BF	8.91%	—	×1.150	10.25%
HR / BF /BF	1.94%	÷1.175	×1.250	2.06%

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 135).

Result: FIP 3.00 → 3.77, 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 AModesto Nuts · 32 IPFIP 2.70 → 3.72 (+1.03)K% 26.7% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.71%	—	×0.740	19.77%
BB% (unintentional) /BF	11.64%	—	×1.180	13.74%
HR / BF /BF	0.68%	÷0.883	×1.300	1.01%

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 2.70 → 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).

2022 AModesto Nuts · 25 IPFIP 3.80 → 5.05 (+1.24)K% 25.8% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.83%	—	×0.740	19.12%
BB% (unintentional) /BF	19.17%	—	×1.180	22.62%
HR / BF /BF	0.83%	÷0.855	×1.300	1.27%

Result: FIP 3.80 → 5.05, 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 Mariners · 18 IPFIP 2.60 → 3.63 (+1.04)K% 22.4% → 15.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.39%	—	×0.680	15.22%
BB% (unintentional) /BF	4.48%	—	×1.250	5.60%
HR / BF /BF	1.49%	÷1.033	×1.400	2.02%

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 107).

Result: FIP 2.60 → 3.63, 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 ROKACL Mariners · 15 IPFIP 2.73 → 3.90 (+1.16)K% 26.1% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.09%	—	×0.680	17.74%
BB% (unintentional) /BF	14.49%	—	×1.250	18.12%
HR / BF /BF	0.00%	÷0.904	×1.400	0.00%

Result: FIP 2.73 → 3.90, 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
Juan Burgos (OGILVIE)	—	—	4.85	18.4%	9.9%	3.0%	—	4.89	18.7%	8.8%	22	+0.04	—	—	—
Joe Colón J R 2017 · 4.25 FIP	27	SU	4.25	20.4%	12.1%	2.4%	.315	—	—	—	—	—	3.27	113	84
Scott Proctor R 2004 · 5.43 FIP	27	SU	5.43	17.8%	11.9%	4.2%	.308	4.36	18.8%	11.0%	233	-1.07	3.68	337	83
Chris Hatcher R 2012 · 5.60 FIP	27	SU	5.60	15.2%	9.1%	4.8%	.298	2.68	26.4%	20.9%	95	-2.92	2.51	246	83
C.C. Lee R 2014 · 3.77 FIP	27	SU	3.77	20.5%	8.7%	2.4%	.310	2.80	25.7%	17.6%	96	-0.97	2.59	149	83
Jeff Fulchino R 2008 · 4.62 FIP	28	SU	4.62	16.7%	11.1%	2.8%	.380	3.86	21.0%	12.4%	164	-0.76	3.36	178	83
Francisco Del Rosario R 2007 · 3.93 FIP	26	SU	3.93	19.7%	9.4%	2.4%	.356	—	—	—	—	—	3.93	194	82
Francisco Rodriguez R 2010 · 4.33 FIP	27	SU	4.33	17.2%	11.0%	2.4%	.283	5.00	11.9%	3.4%	14	+0.67	3.16	334	82
Justin Lehr R 2005 · 4.58 FIP	27	SU	4.58	14.9%	10.4%	2.6%	.252	4.23	16.0%	8.0%	16	-0.35	4.23	148	81
Ross Wolf R 2010 · 3.95 FIP	27	SU	3.95	16.1%	8.9%	2.0%	.268	4.37	10.1%	3.3%	48	+0.42	3.43	179	81
Michael Dimock R 2017 · 4.12 FIP	27	SU	4.12	18.9%	7.8%	2.9%	.339	3.37	23.5%	12.8%	29	-0.75	3.08	166	81
Rob Scahill R 2014 · 5.07 FIP	27	SU	5.07	15.3%	9.7%	3.7%	.275	3.59	15.6%	8.6%	141	-1.48	3.06	250	81
David Holman R 2017 · 5.53 FIP	27	SU	5.53	15.6%	12.7%	3.9%	.324	5.45	9.6%	0.5%	107	-0.08	5.28	129	81
Greg Burke R 2009 · 3.93 FIP	26	SU	3.93	16.2%	8.8%	2.0%	.295	—	—	—	—	—	3.61	139	80
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	80
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	80
Thad Weber R 2013 · 5.18 FIP	28	SU	5.18	16.4%	13.1%	3.3%	.244	4.52	12.2%	6.0%	308	-0.66	4.40	378	80
Arcenio Leon R 2015 · 4.73 FIP	28	SU	4.73	17.9%	12.5%	2.9%	.450	3.37	18.0%	9.1%	85	-1.36	3.00	115	79
Adrian Garza R 2015 · 5.47 FIP	27	SU	5.47	14.9%	10.5%	4.2%	.360	4.17	13.1%	6.5%	84	-1.30	3.94	229	79
Luis Mateo R 2017 · 4.60 FIP	27	SU	4.60	17.6%	11.2%	2.9%	.309	5.55	8.6%	-4.8%	43	+0.95	3.48	160	79
Zach Bryant R 2024 · 4.85 FIP	26	SU	4.85	18.0%	9.6%	3.7%	.313	4.87	16.1%	5.0%	106	+0.02	4.51	215	79

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	0.3	34	18.1%	9.9%	1.13	4.80
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Randy Flores ('10)	1.2	42	17.7%	9.3%	1.04	4.61
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Vic Darensbourg ('05)	1.5	50	17.0%	9.3%	1.01	4.96
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*