Marcelo Perez

P Arkansas Travelers

Age 27 RHP 5'10" / 195 lbs AA peak 0.2 · 2027

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	A+SEA	25	25	104	6.81	4.43	18.8%	6.0%	—	K 14.5% · BB 6.9% · FIP 4.93
2025	25	MIX2 levels	19	19	92	3.44	3.92	16.8%	6.2%	—	K 13.2% · BB 6.9% · FIP 4.95
2026	26	MIX2 levels	36	0	47	4.98	3.91	25.1%	8.2%	—	K 18.3% · BB 9.5% · FIP 5.23
2027PROJ	27	MLBSEA	1	0	1	5.04	5.04	15.2%	7.7%	-0.0
2028PROJ27% MLB	28	MLBSEA	13	0	14	5.02	5.05	15.9%	8.0%	-0.1
2029PROJ42% MLB	29	MLBSEA	18	0	19	5.06	5.13	16.3%	8.3%	-0.1

Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 98%

CompsAlfonso Sanchez (age 27) · Ramon Delgado (age 29) · Josh Roeder (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 129121vR 113

ERA5.04

FIP5.04

K%15.2%

BB%7.7%

K-BB%7.6%

Proj IP60

Value2027 · WAR

Runs saved vs league avg · 60 IP

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)
2023	23	MIX MLE	2 levels	18	18	75	303	76	24	4	100%	4.1	18.0%	8.6%	9.4%	2.1%	3.38	3.84	—
2023	23	MIX RAW	2 levels	18	18	75	303	76	24	4	100%	4.1	25.1%	7.9%	17.2%	1.3%	3.38	2.73	—
2024	24	A+ MLE	Everett AquaSox	25	25	104	483	91	29	18	100%	4.2	14.5%	6.9%	7.6%	4.0%	6.81	4.93	—
2024	24	A+ MLE	Everett AquaSox	25	25	104	483	91	29	18	100%	4.2	14.5%	6.9%	7.6%	4.0%	6.81	4.93	—
2024	24	A+ RAW	Everett AquaSox	25	25	104	483	91	29	18	100%	4.2	18.8%	6.0%	12.8%	3.7%	6.81	4.43	—
2025	25	MIX MLE	2 levels	19	19	92	370	62	23	10	100%	4.8	13.2%	6.9%	6.3%	3.8%	3.44	4.95	—
2025	25	MIX MLE	2 levels	19	19	92	370	62	23	10	100%	4.8	13.2%	6.9%	6.3%	3.8%	3.44	4.95	—
2025	25	MIX RAW	2 levels	19	19	92	370	62	23	10	100%	4.8	16.8%	6.2%	10.5%	2.7%	3.44	3.92	—
2026	26	MIX MLE	2 levels	36	0	47	207	52	17	7	0%	1.3	18.3%	9.5%	8.8%	4.5%	4.98	5.23	—
2026	26	MIX MLE	2 levels	36	0	47	207	52	17	7	0%	1.3	18.3%	9.5%	8.8%	4.5%	4.98	5.23	—
2026	26	MIX RAW	2 levels	36	0	47	207	52	17	7	0%	1.3	25.1%	8.2%	16.9%	3.4%	4.98	3.91	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	SEA	1	0	1	4	1	0	0	0%	1.0	15.2%	7.7%	7.6%	3.4%	5.04	5.04	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	SEA	48	0	50	213	34	17	7	0%	1.1	15.9%	8.0%	8.0%	3.5%	5.02	5.05	-0.3
2029	29	MLB MLE	SEA	42	0	45	188	31	16	7	0%	1.1	16.3%	8.3%	8.0%	3.6%	5.06	5.13	-0.3
2028	28	MLB CTX	SEA	13	0	14	59	9	5	2	0%	1.1	15.9%	8.0%	8.0%	3.5%	5.02	5.05	-0.1
2029	29	MLB CTX	SEA	18	0	19	80	13	7	3	0%	1.1	16.3%	8.3%	8.0%	3.6%	5.06	5.13	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		31	0	33	138	22	11	5	0%	1.1	16.1%	8.2%	8.0%	3.5%	5.04	4.71	-0.1
/ 200 IP	—	RAW		190	0	200	844	134	67	31	0%	1.1	16.1%	8.2%	8.0%	3.5%	5.04	4.71	-0.4
Career	—	MLE		98	62	318	1363	211	104	49	63%	3.2	15.5%	7.7%	7.8%	3.6%	4.76	4.74	+0.3
/ 200 IP	—	MLE		62	39	200	858	133	66	31	63%	3.2	15.5%	7.7%	7.8%	3.6%	4.76	4.74	+0.7

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 AAArkansas Travelers · 42 IPFIP 4.35 → 5.23 (+0.88)K% 22.6% → 18.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.58%	—	×0.810	18.29%
BB% (unintentional) /BF	8.60%	—	×1.100	9.46%
HR / BF /BF	3.76%	÷1.000	×1.200	4.52%

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 4.35 → 5.23, 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 AInland Empire 66ers · 5 IPFIP -0.32 → 0.84 (+1.15)K% 47.6% → 35.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	47.62%	—	×0.740	35.24%
BB% (unintentional) /BF	4.76%	—	×1.180	5.62%
HR / BF /BF	0.00%	÷1.000	×1.300	0.00%

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 100).

Result: FIP -0.32 → 0.84, 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 · 56 IPFIP 4.69 → 5.79 (+1.10)K% 11.9% → 9.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	11.86%	—	×0.810	9.61%
BB% (unintentional) /BF	7.63%	—	×1.100	8.39%
HR / BF /BF	2.97%	÷0.800	×1.200	4.45%

Result: FIP 4.69 → 5.79, 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+Everett AquaSox · 35 IPFIP 2.66 → 3.48 (+0.82)K% 25.4% → 19.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.37%	—	×0.770	19.54%
BB% (unintentional) /BF	3.73%	—	×1.150	4.29%
HR / BF /BF	2.24%	÷1.036	×1.250	2.70%

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 107).

Result: FIP 2.66 → 3.48, 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 · 104 IPFIP 4.32 → 4.93 (+0.61)K% 18.8% → 14.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.84%	—	×0.770	14.51%
BB% (unintentional) /BF	6.00%	—	×1.150	6.90%
HR / BF /BF	3.73%	÷1.175	×1.250	3.96%

Result: FIP 4.32 → 4.93, 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).

2023 AModesto Nuts · 68 IPFIP 2.76 → 3.84 (+1.08)K% 24.4% → 18.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.36%	—	×0.740	18.03%
BB% (unintentional) /BF	7.27%	—	×1.180	8.58%
HR / BF /BF	1.45%	÷0.883	×1.300	2.14%

Result: FIP 2.76 → 3.84, 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+Everett AquaSox · 7 IPFIP 2.20 → 3.09 (+0.90)K% 32.1% → 24.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.14%	—	×0.770	24.75%
BB% (unintentional) /BF	14.29%	—	×1.150	16.43%
HR / BF /BF	0.00%	÷1.012	×1.250	0.00%

Result: FIP 2.20 → 3.09, 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).

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
Marcelo Perez (OGILVIE)	—	—	—	—	—	3.4%	—	5.09	16.1%	8.0%	95	+0.05	—	—	—
Alfonso Sanchez R 2015 · 4.96 FIP	27	SP-	4.96	12.5%	9.1%	3.2%	.346	4.85	14.0%	5.3%	138	-0.11	4.51	224	85
Ramon Delgado R 2016 · 4.60 FIP	29	SW	4.60	13.8%	5.9%	3.5%	.332	4.31	11.2%	7.2%	74	-0.29	4.31	135	84
Josh Roeder R 2019 · 4.71 FIP	26	SW	4.71	15.1%	8.7%	3.3%	.264	—	—	—	—	—	4.71	175	83
Aaron Northcraft R 2016 · 4.19 FIP	26	SW	4.19	16.1%	8.3%	2.5%	.309	3.32	24.1%	13.4%	34	-0.87	3.32	252	83
Tyler Yates R 2004 · 4.47 FIP	26	SW	4.47	15.4%	9.6%	2.6%	.333	3.64	22.5%	13.5%	116	-0.83	3.23	248	82
Roberto Gómez R 2017 · 3.95 FIP	27	SW	3.95	18.4%	8.9%	2.3%	.315	5.25	13.8%	4.9%	18	+1.30	3.95	115	80
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	79
Aldo Montes R 2017 · 4.96 FIP	27	SP-	4.96	12.4%	8.5%	3.3%	.322	4.69	18.2%	7.6%	75	-0.27	4.69	210	79
Zach Stewart R 2015 · 4.43 FIP	28	SP-	4.43	14.4%	8.3%	2.7%	.322	5.17	11.7%	2.1%	51	+0.74	4.27	194	79
Dennis O'Grady R 2015 · 4.95 FIP	26	SW	4.95	13.5%	11.0%	2.9%	.339	—	—	—	—	—	3.62	157	79
Jorge Reyes R 2015 · 4.58 FIP	27	SW	4.58	15.9%	8.5%	3.2%	.307	3.49	14.2%	6.2%	129	-1.09	3.39	227	79
Donovan Hand R 2013 · 4.72 FIP	27	SW	4.72	12.9%	7.0%	3.3%	.279	4.30	11.1%	6.8%	97	-0.42	4.30	305	78
Bryce Morrow R 2015 · 4.31 FIP	27	SP-	4.31	12.8%	7.9%	2.4%	.316	5.44	10.1%	-0.2%	50	+1.13	4.31	125	78
Mike Connolly R 2018 · 5.13 FIP	26	SW	5.13	13.2%	9.4%	3.5%	.321	—	—	—	—	—	3.94	328	78
Colby Morris R 2022 · 5.76 FIP	25	SW	5.76	16.2%	11.8%	4.6%	.268	—	—	—	—	—	4.11	105	77
Andres Santiago R 2017 · 4.16 FIP	27	SW	4.16	16.3%	9.1%	2.3%	.384	5.26	13.1%	3.2%	159	+1.10	3.76	291	77
Kurt Heyer R 2016 · 3.99 FIP	25	SW	3.99	14.1%	6.7%	2.2%	.337	—	—	—	—	—	3.75	178	76
Cory Lidle R 2000 · 4.32 FIP	28	SW	4.32	14.6%	6.1%	3.1%	.313	4.06	14.2%	8.7%	573	-0.26	3.48	1,318	76
Cameron Foster R 2024 · 4.83 FIP	25	SW	4.83	17.4%	11.5%	3.2%	.321	3.09	25.5%	17.5%	60	-1.74	2.50	213	76
Jon Leicester R 2007 · 4.44 FIP	28	SP-	4.44	11.0%	9.0%	2.1%	.292	—	—	—	—	—	3.76	113	76

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	0.8	52	15.8%	7.9%	1.35	5.04
Carlos Almánzar ('05)	1.2	60	16.3%	7.9%	1.32	4.82
Jose Cabrera ('02)	1.4	68	16.2%	7.9%	1.39	4.95
Ricky Stone ('07)	1.3	64	15.2%	8.0%	1.55	4.68
Larry Casian ('90-'98, 0 WAR*)	1.2	40	14.7%*	6.8%*	1.25*	4.37*
Chuck Hartenstein ('66-'77, -1 WAR*)	1.5	59	13.7%*	7.2%*	1.50*	5.28*
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*