Gerardo Reyes

P Las Vegas Aviators

Age 34 RHP 5'11" / 195 lbs AAA peak 0.1 · 2027

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	29	MIX2 levels	48	0	48	3.78	4.44	26.5%	15.5%	0.1	K 24.7% · BB 15.7% · FIP 4.50
2023	30	MIX2 levels	44	0	50	5.94	4.60	28.0%	12.7%	-0.0	K 25.8% · BB 11.6% · FIP 4.64
2024	31	MIX2 levels	46	0	48	4.84	5.15	30.1%	15.0%	-0.3	K 27.4% · BB 13.4% · FIP 5.69
2025	32	No MLB games played
2026	33	No MLB games played
2027PROJ	34	MLBOAK	5	0	5	3.92	3.96	29.7%	9.8%	0.0
2028PROJ6% MLB	35	MLBOAK	2	0	2	4.18	4.33	28.1%	10.3%	0.0
2029PROJMLE	36	MLBOAK	—	—	0	4.49	4.70	26.8%	10.8%	—

Last 3 seasons WAR -0.3 · Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff71Control45Command68FB velo62

CompsJay Jackson (age 34) · Jumbo Diaz (age 34) · Zack Segovia (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 108100vR 92

ERA3.92

FIP3.96

K%29.7%

BB%9.8%

K-BB%19.9%

Proj IP53

Value2027 · WAR

Runs saved vs league avg · 53 IP

Grades · Contract

Scouting Grades

STUF7070

CTRL4545

CMD7070

K†6565

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)
2016	23	MIX MLE	2 levels	40	0	53	227	47	21	3	0%	1.3	15.7%	10.7%	5.0%	1.8%	3.59	4.14	—
2016	23	MIX RAW	2 levels	40	0	53	227	47	21	3	0%	1.3	20.7%	9.3%	11.5%	1.3%	3.59	3.25	—
2017	24	A+ MLE	Lake Elsinore Storm	47	0	62	262	65	31	3	0%	1.3	19.1%	13.6%	5.5%	1.6%	2.63	4.06	—
2017	24	A+ RAW	Lake Elsinore Storm	47	0	62	262	65	31	3	0%	1.3	24.8%	11.8%	13.0%	1.1%	2.63	3.13	—
2018	25	MIX MLE	2 levels	45	0	55	240	69	28	1	0%	1.2	23.0%	13.1%	9.9%	0.6%	2.77	3.15	—
2018	25	MIX RAW	2 levels	45	0	55	240	69	28	1	0%	1.2	28.7%	11.7%	17.1%	0.4%	2.77	2.36	—
2019	26	MIX MLE	2 levels	61	0	71	308	99	30	11	0%	1.2	29.8%	10.1%	19.7%	4.0%	5.05	4.03	+0.4
2019	26	MIX RAW	2 levels	61	0	71	308	99	30	11	0%	1.2	32.1%	9.7%	22.4%	3.6%	5.05	3.59	+0.8
2022	29	MIX MLE	2 levels	48	0	48	219	58	34	6	0%	1.0	24.7%	15.7%	8.9%	2.7%	3.78	4.50	+0.0
2022	29	MIX RAW	2 levels	48	0	48	219	58	34	6	0%	1.0	26.5%	15.5%	11.0%	2.7%	3.78	4.44	+0.1
2023	30	MIX MLE	2 levels	44	0	50	236	66	30	9	0%	1.1	25.8%	11.6%	14.2%	4.1%	5.94	4.64	-0.1
2023	30	MIX RAW	2 levels	44	0	50	236	66	30	9	0%	1.1	28.0%	12.7%	15.3%	3.8%	5.94	4.60	-0.0
2024	31	MIX MLE	2 levels	46	0	48	206	62	31	10	0%	1.1	27.4%	13.4%	14.0%	5.8%	4.84	5.69	-0.6
2024	31	MIX MLE	2 levels	46	0	48	206	62	31	10	0%	1.1	27.4%	13.4%	14.0%	5.8%	4.84	5.69	-0.6
2024	31	MIX RAW	2 levels	46	0	48	206	62	31	10	0%	1.1	30.1%	15.0%	15.0%	4.9%	4.84	5.15	-0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			40	0	42	196	50	22	6	0%	1.0	25.5%	11.2%	14.3%	3.1%	7.13	4.16	+0.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	OAK	5	0	5	21	6	2	1	0%	1.0	29.7%	9.8%	19.9%	3.2%	3.92	3.96	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	OAK	41	0	44	184	52	19	6	0%	1.1	28.1%	10.3%	17.8%	3.5%	4.18	4.33	+0.1
2029	36	MLB MLE	OAK	33	0	34	144	39	16	6	0%	1.0	26.8%	10.8%	16.0%	3.8%	4.49	4.70	-0.1
2028	35	MLB CTX	OAK	2	0	2	8	2	1	0	0%	1.0	28.1%	10.3%	17.8%	3.5%	4.18	4.33	+0.0
2029	36	MLB CTX	OAK	—	—	0	—	—	—	—	—	—	26.8%	10.8%	16.0%	3.8%	4.49	4.70	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		42	0	44	206	53	23	6	0%	1.0	25.6%	11.2%	14.5%	3.1%	6.97	4.04	+0.3
/ 200 IP	—	RAW		192	0	200	936	241	104	27	0%	1.0	25.6%	11.2%	14.5%	3.1%	6.97	4.04	+1.2
Career	—	MLE		331	0	387	1698	404	212	50	0%	1.2	23.8%	12.5%	11.3%	2.9%	4.07	4.27	+0.2
/ 200 IP	—	MLE		171	0	200	878	209	109	26	0%	1.2	23.8%	12.5%	11.3%	2.9%	4.07	4.27	+0.4

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.

2024 AAALas Vegas Aviators · 44 IPFIP 5.21 → 5.69 (+0.48)K% 31.9% → 27.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.91%	—	×0.860	27.45%
BB% (unintentional) /BF	14.89%	—	×0.900	13.40%
HR / BF /BF	5.32%	÷1.001	×1.100	5.84%

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 5.21 → 5.69, 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 AAASalt Lake Bees · 40 IPFIP 4.25 → 4.64 (+0.39)K% 29.9% → 25.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.95%	—	×0.860	25.75%
BB% (unintentional) /BF	12.83%	—	×0.900	11.55%
HR / BF /BF	3.74%	÷1.003	×1.100	4.10%

Result: FIP 4.25 → 4.64, 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).

2022 AAASalt Lake Bees · 46 IPFIP 3.96 → 4.50 (+0.54)K% 28.0% → 24.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.02%	—	×0.880	24.66%
BB% (unintentional) /BF	14.98%	—	×1.050	15.72%
HR / BF /BF	2.42%	÷0.978	×1.100	2.72%

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 96).

Result: FIP 3.96 → 4.50, 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 AAAEl Paso Chihuahuas · 45 IPFIP 4.03 → 4.78 (+0.75)K% 31.9% → 28.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.94%	—	×0.880	28.10%
BB% (unintentional) /BF	10.47%	—	×1.050	10.99%
HR / BF /BF	4.19%	÷0.950	×1.100	4.85%

Result: FIP 4.03 → 4.78, 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 AASan Antonio Missions · 39 IPFIP 2.25 → 2.99 (+0.74)K% 29.0% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.99%	—	×0.810	23.49%
BB% (unintentional) /BF	10.06%	—	×1.100	11.07%
HR / BF /BF	0.59%	÷0.824	×1.200	0.86%

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 65).

Result: FIP 2.25 → 2.99, 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 A+Lake Elsinore Storm · 16 IPFIP 2.68 → 3.53 (+0.84)K% 28.2% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.17%	—	×0.770	21.69%
BB% (unintentional) /BF	15.49%	—	×1.150	17.82%
HR / BF /BF	0.00%	÷0.839	×1.250	0.00%

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 68).

Result: FIP 2.68 → 3.53, 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).

2017 A+Lake Elsinore Storm · 62 IPFIP 3.13 → 4.06 (+0.93)K% 24.8% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.81%	—	×0.770	19.10%
BB% (unintentional) /BF	11.83%	—	×1.150	13.61%
HR / BF /BF	1.15%	÷0.921	×1.250	1.55%

Result: FIP 3.13 → 4.06, 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).

2016 A+Lake Elsinore Storm · 27 IPFIP 3.35 → 4.38 (+1.02)K% 24.8% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.79%	—	×0.770	19.09%
BB% (unintentional) /BF	11.11%	—	×1.150	12.78%
HR / BF /BF	1.71%	÷0.925	×1.250	2.31%

Result: FIP 3.35 → 4.38, 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 Reyes (OGILVIE)	—	—	3.96	29.7%	9.8%	3.2%	—	4.49	27.5%	17.0%	78	+0.53	—	—	—
Jay Jackson R 2022 · 2.98 FIP	34	SU	2.98	27.5%	5.3%	2.8%	.327	4.83	26.2%	20.2%	85	+1.85	2.36	261	67
Jumbo Diaz R 2018 · 2.80 FIP	34	SU	2.80	23.2%	10.4%	0.6%	.296	2.98	25.0%	17.3%	56	+0.18	2.80	319	62
Zack Segovia R 2016 · 3.33 FIP	33	SU	3.33	20.2%	5.9%	2.2%	.312	4.55	17.6%	4.0%	57	+1.22	3.33	144	60
Nate Jones R 2020 · 4.53 FIP	34	SU	4.53	26.7%	5.8%	5.4%	.377	7.14	16.1%	6.9%	19	+2.61	2.57	307	60
Huascar Brazobán R 2024 · 3.08 FIP	34	SU	3.08	23.5%	11.5%	0.9%	.259	3.71	21.3%	11.7%	144	+0.63	3.08	370	59
Neil Wagner R 2017 · 3.11 FIP	33	SU	3.11	20.7%	8.6%	1.2%	.257	—	—	—	—	—	3.11	135	59
Josh Lueke R 2019 · 4.11 FIP	34	SU	4.11	20.4%	6.4%	3.5%	.311	—	—	—	—	—	2.29	191	58
Ryan Brasier R 2022 · 3.55 FIP	34	SU	3.55	24.3%	4.6%	3.5%	.331	2.95	22.3%	16.1%	114	-0.60	2.31	426	57
Dustin Molleken R 2017 · 3.38 FIP	32	SU	3.38	24.3%	12.4%	1.4%	.311	—	—	—	—	—	3.38	129	57
Fernando Rodriguez Jr. R 2018 · 4.07 FIP	34	SW	4.07	23.7%	9.9%	3.1%	.253	5.11	25.0%	13.8%	32	+1.04	3.34	335	57
Greg Burke R 2015 · 3.61 FIP	32	SU	3.61	22.1%	7.3%	2.7%	.241	—	—	—	—	—	3.61	139	56
Diego Moreno R 2021 · 4.75 FIP	34	SU	4.75	18.6%	9.4%	3.7%	.232	—	—	—	—	—	2.29	187	56
Chin-hui Tsao R 2015 · 3.29 FIP	34	SU	3.29	23.8%	6.8%	2.5%	.280	2.38	17.4%	11.5%	16	-0.91	2.38	134	54
Fernando Cruz R 2024 · 2.94 FIP	34	SU	2.94	37.8%	11.5%	2.9%	.328	3.39	32.1%	19.6%	103	+0.45	2.50	371	54
Chris Nichting R 2001 · 4.11 FIP	35	SU	4.11	21.2%	3.7%	4.2%	.351	4.67	16.6%	13.3%	36	+0.56	4.11	103	53
Rodolfo Aguirre R 2019 · 4.50 FIP	34	SU	4.50	21.3%	5.1%	4.7%	.244	—	—	—	—	—	3.39	212	53
Brendan Donnelly R 2005 · 4.02 FIP	34	SU	4.02	19.6%	5.9%	3.3%	.264	4.02	17.6%	8.5%	98	-0.00	2.23	385	53
Jean Machi R 2016 · 4.36 FIP	34	SU	4.36	18.3%	6.6%	3.6%	.282	4.12	18.6%	12.0%	67	-0.24	2.16	306	53
Blake Parker R 2019 · 4.65 FIP	34	SU	4.65	25.5%	8.6%	4.8%	.258	4.26	24.9%	15.4%	87	-0.39	2.52	406	53
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	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	0.9	43	27.7%	10.6%	1.30	4.88
Michael Feliz ('22)	1.2	50	29.9%	9.9%	1.55	5.29
Colin Poche ('25)	1.1	54	26.7%	10.2%	1.32	4.01
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Tom Dukes ('67-'72, -2 WAR*)	1.1	43	22.7%*	8.7%*	1.16*	5.37*
Buddy Schultz ('75-'79, 2 WAR*)	1.2	60	27.4%*	8.5%*	1.21*	4.14*