Rubén Menes

P Peoria Chiefs

Age 25 RHP 6'3" / 185 lbs A+

Overview

A+PROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	22	ROKSTL	5	4	19	3.72	4.03	23.2%	12.2%	—	K 15.8% · BB 15.2% · FIP 5.62
2025	23	MIX2 levels	13	9	37	6.08	3.42	20.5%	8.5%	—	K 15.8% · BB 8.7% · FIP 3.39
2026	24	MIX2 levels	36	0	64	4.36	4.04	21.5%	12.2%	—	K 15.5% · BB 15.7% · FIP 5.55
2027PROJ	25	MLBSTL	—	—	0	5.38	5.38	17.4%	13.6%	—
2028PROJ43% MLB	26	MLBSTL	17	0	18	5.23	5.21	18.8%	13.1%	-0.1
2029PROJ63% MLB	27	MLBSTL	22	0	23	5.17	5.18	19.1%	12.9%	-0.2

Next 3 projected WAR -0.3Projected 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 100%

CompsHayden Snelsire (age 23) · Andrew McInvale (age 25) · Grant Black (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 135127vR 119

ERA5.38

FIP5.38

K%17.4%

BB%13.6%

K-BB%3.8%

Proj IP29

Value2027 · WAR

Runs saved vs league avg · 29 IP

Grades · Contract

Scouting Grades

K†4045

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	21	ROK MLE	FCL Cardinals	5	3	12	57	11	10	1	60%	2.4	13.1%	21.9%	-8.8%	2.5%	4.50	6.12	—
2023	21	ROK RAW	FCL Cardinals	5	3	12	57	11	10	1	60%	2.4	19.3%	17.5%	1.8%	1.8%	4.50	4.85	—
2024	22	ROK MLE	FCL Cardinals	5	4	19	82	19	10	2	80%	3.9	15.8%	15.2%	0.5%	3.5%	3.72	5.62	—
2024	22	ROK MLE	FCL Cardinals	5	4	19	82	19	10	2	80%	3.9	15.8%	15.2%	0.5%	3.5%	3.72	5.62	—
2024	22	ROK RAW	FCL Cardinals	5	4	19	82	19	10	2	80%	3.9	23.2%	12.2%	11.0%	2.4%	3.72	4.03	—
2025	23	MIX MLE	2 levels	13	9	37	176	36	15	3	69%	2.8	15.8%	8.7%	7.1%	0.9%	6.08	3.39	—
2025	23	MIX MLE	2 levels	13	9	37	176	36	15	3	69%	2.8	15.8%	8.7%	7.1%	0.9%	6.08	3.39	—
2025	23	MIX RAW	2 levels	13	9	37	176	36	15	3	69%	2.8	20.5%	8.5%	11.9%	1.7%	6.08	3.42	—
2026	24	MIX MLE	2 levels	36	0	64	279	60	34	6	0%	1.8	15.5%	15.7%	-0.3%	3.2%	4.36	5.55	—
2026	24	MIX MLE	2 levels	36	0	64	279	60	34	6	0%	1.8	15.5%	15.7%	-0.3%	3.2%	4.36	5.55	—
2026	24	MIX RAW	2 levels	36	0	64	279	60	34	6	0%	1.8	21.5%	12.2%	9.3%	2.2%	4.36	4.04	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	STL	—	—	0	—	—	—	—	—	—	17.4%	13.6%	3.8%	3.0%	5.38	5.38	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	STL	40	0	42	179	34	24	5	0%	1.1	18.8%	13.1%	5.6%	3.0%	5.23	5.21	-0.3
2029	27	MLB MLE	STL	35	0	36	154	29	20	5	0%	1.0	19.1%	12.9%	6.2%	3.1%	5.17	5.18	-0.3
2028	26	MLB CTX	STL	17	0	18	76	14	10	2	0%	1.1	18.8%	13.1%	5.6%	3.0%	5.23	5.21	-0.1
2029	27	MLB CTX	STL	22	0	23	97	19	13	3	0%	1.0	19.1%	12.9%	6.2%	3.1%	5.17	5.18	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		39	0	41	174	33	23	5	0%	1.1	18.9%	13.0%	6.0%	3.0%	5.20	4.81	-0.1
/ 200 IP	—	RAW		190	0	200	844	160	112	24	0%	1.0	18.9%	13.0%	6.0%	3.0%	5.20	4.81	-0.6
Career	—	MLE		59	16	132	594	91	84	15	27%	2.2	15.4%	14.2%	1.2%	2.5%	4.76	4.97	-0.6
/ 200 IP	—	MLE		89	24	200	898	138	127	22	27%	2.2	15.4%	14.2%	1.2%	2.5%	4.76	4.97	-1.5

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 A+Peoria Chiefs · 52 IPFIP 4.54 → 5.55 (+1.00)K% 20.1% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.09%	—	×0.770	15.47%
BB% (unintentional) /BF	13.68%	—	×1.150	15.73%
HR / BF /BF	2.56%	÷1.000	×1.250	3.21%

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 100).

Result: FIP 4.54 → 5.55, 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 APalm Beach Cardinals · 12 IPFIP 1.22 → 1.96 (+0.74)K% 28.9% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.89%	—	×0.740	21.38%
BB% (unintentional) /BF	4.44%	—	×1.180	5.24%
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 1.22 → 1.96, 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 ROKFCL Cardinals · 29 IPFIP 2.45 → 3.39 (+0.94)K% 23.3% → 15.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.26%	—	×0.680	15.81%
BB% (unintentional) /BF	6.98%	—	×1.250	8.72%
HR / BF /BF	0.78%	÷1.149	×1.400	0.94%

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 130).

Result: FIP 2.45 → 3.39, 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 APalm Beach Cardinals · 8 IPFIP 5.97 → 7.33 (+1.35)K% 12.8% → 9.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.77%	—	×0.740	9.45%
BB% (unintentional) /BF	12.77%	—	×1.180	15.06%
HR / BF /BF	4.26%	÷0.973	×1.300	5.68%

Result: FIP 5.97 → 7.33, 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 ROKFCL Cardinals · 19 IPFIP 4.03 → 5.62 (+1.59)K% 23.2% → 15.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.17%	—	×0.680	15.76%
BB% (unintentional) /BF	12.20%	—	×1.250	15.24%
HR / BF /BF	2.44%	÷0.975	×1.400	3.50%

Result: FIP 4.03 → 5.62, 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 ROKFCL Cardinals · 12 IPFIP 4.66 → 6.12 (+1.46)K% 19.3% → 13.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.30%	—	×0.680	13.12%
BB% (unintentional) /BF	17.54%	—	×1.250	21.93%
HR / BF /BF	1.75%	÷1.000	×1.400	2.46%

Result: FIP 4.66 → 6.12, 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
Rubén Menes (OGILVIE)	—	—	5.38	17.4%	13.6%	3.0%	—	5.20	18.9%	5.9%	79	-0.18	—	—	—
Hayden Snelsire R 2024 · 5.10 FIP	23	SU	5.10	18.9%	13.8%	3.4%	.272	4.28	20.0%	13.7%	135	-0.82	3.83	178	85
Andrew McInvale R 2022 · 5.15 FIP	25	SU	5.15	17.6%	15.9%	2.8%	.324	6.44	24.5%	10.0%	23	+1.29	4.92	103	85
Grant Black R 2021 · 4.46 FIP	27	SW	4.46	19.0%	13.9%	2.2%	.327	5.35	15.0%	3.8%	156	+0.89	4.46	215	84
Francisco Del Rosario R 2006 · 5.13 FIP	25	SU	5.13	19.4%	13.0%	3.7%	.290	3.93	19.7%	10.3%	26	-1.20	3.93	194	84
Brad Deppermann R 2021 · 4.51 FIP	25	SW	4.51	17.1%	9.6%	3.0%	.289	3.52	20.0%	7.8%	45	-0.99	1.94	143	83
Ryan Vogelsong R 2001 · 5.34 FIP	24	SU	5.34	14.6%	11.6%	3.7%	.287	4.78	14.9%	5.7%	155	-0.56	3.14	1,184	83
Stephen Johnson R 2016 · 5.15 FIP	25	SU	5.15	16.7%	12.7%	3.4%	.268	—	—	—	—	—	3.12	141	82
Juan Paniagua R 2015 · 4.69 FIP	25	SU	4.69	15.7%	11.9%	2.6%	.262	4.63	16.2%	1.8%	93	-0.06	4.57	151	82
Ryan Conroy R 2022 · 4.75 FIP	25	SU	4.75	19.3%	12.6%	3.1%	.361	—	—	—	—	—	4.01	106	82
Jeremy Guthrie R 2006 · 4.92 FIP	27	SU	4.92	15.1%	15.1%	2.1%	.349	4.57	14.8%	8.1%	566	-0.35	4.08	1,834	82
Haden Erbe R 2024 · 5.28 FIP	25	SU	5.28	18.4%	16.5%	3.0%	.320	5.19	17.8%	0.5%	40	-0.09	5.19	116	81
Tyler Burch R 2023 · 4.92 FIP	25	SU	4.92	15.0%	12.6%	2.7%	.285	—	—	—	—	—	4.56	119	81
Kevin Kopps R 2022 · 4.56 FIP	25	SU	4.56	20.2%	15.1%	2.3%	.278	4.40	16.3%	4.0%	182	-0.16	3.45	237	81
Reece Karalus R 2018 · 4.73 FIP	24	SU	4.73	15.4%	11.9%	2.6%	.299	—	—	—	—	—	4.73	149	81
Fernando Cruz R 2015 · 5.29 FIP	25	SU	5.29	15.6%	12.2%	3.6%	.284	—	—	—	—	—	2.50	371	81
Marc Brakeman R 2018 · 4.67 FIP	24	SU	4.67	18.3%	13.7%	2.5%	.294	—	—	—	—	—	3.85	156	81
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	80
Cole Hillier R 2024 · 4.64 FIP	23	SU	4.64	16.9%	14.7%	2.0%	.297	4.45	18.1%	4.5%	111	-0.19	3.80	169	80
Zach Nuding R 2015 · 4.76 FIP	25	SU	4.76	12.5%	10.5%	2.5%	.236	5.03	12.6%	3.3%	106	+0.27	4.76	146	80
Josh Harlow R 2024 · 5.17 FIP	23	SU	5.17	18.5%	13.5%	3.5%	.266	5.73	17.1%	-4.2%	51	+0.56	5.17	107	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	0.5	36	18.5%	13.2%	1.17	5.25
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
Tyler Yates ('09)	1.2	62	19.7%	12.0%	0.94	5.12
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57