Eury Ramos

P Reading Fightin Phils

Age 29 RHP 6'3" / 152 lbs AA

Overview

AAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2021	23	MIX2 levels	32	0	41	3.92	3.44	26.1%	10.2%	—	K 23.6% · BB 11.8% · FIP 4.34
2022	24	MIX2 levels	25	0	30	5.04	5.28	19.3%	19.3%	—	K 16.0% · BB 20.5% · FIP 5.64
2024	26	MIX2 levels	20	0	27	4.94	5.04	20.8%	14.2%	—	K 19.8% · BB 9.4% · FIP 3.33
2025	27	No MLB games played
2026	28	No MLB games played
2027PROJ	29	MLBPHI	—	—	0	4.37	4.37	22.7%	9.2%	—
2028PROJ31% MLB	30	MLBPHI	6	0	6	4.47	4.54	22.4%	9.5%	0.0

Next 2 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsDiego Moreno (age 29) · Neil Wagner (age 29) · Tyler Sturdevant (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 116108vR 100

ERA4.37

FIP4.37

K%22.7%

BB%9.2%

K-BB%13.4%

Proj IP12

Value2027 · WAR

Runs saved vs league avg · 12 IP

Grades · Contract

Scouting Grades

K†5555

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)
2015	17	ROK MLE	DSL Cubs	14	4	33	142	24	13	2	29%	2.3	11.5%	11.4%	0.0%	2.0%	4.41	4.66	—
2015	17	ROK RAW	DSL Cubs	14	4	33	142	24	13	2	29%	2.3	16.9%	9.2%	7.7%	1.4%	4.41	3.62	—
2016	18	ROK MLE	DSL Cubs 1	3	3	10	42	4	5	0	100%	3.3	9.5%	11.9%	-2.4%	0.0%	3.60	3.80	—
2016	18	ROK RAW	DSL Cubs 1	3	3	10	42	4	5	0	100%	3.3	9.5%	11.9%	-2.4%	0.0%	3.60	3.80	—
2017	19	ROK MLE	AZL Cubs	13	3	32	152	29	18	3	23%	2.5	13.0%	14.8%	-1.8%	2.8%	4.78	5.40	—
2017	19	ROK RAW	AZL Cubs	13	3	32	152	29	18	3	23%	2.5	19.1%	11.8%	7.2%	2.0%	4.78	4.19	—
2019	21	MIX MLE	2 levels	8	8	32	144	30	16	6	100%	4.0	14.1%	13.5%	0.6%	6.5%	7.31	7.19	—
2019	21	MIX RAW	2 levels	8	8	32	144	30	16	6	100%	4.0	20.8%	11.1%	9.7%	4.2%	7.31	5.16	—
2021	23	MIX MLE	2 levels	32	0	41	176	46	18	4	0%	1.3	23.6%	11.8%	11.9%	3.2%	3.92	4.34	—
2021	23	MIX RAW	2 levels	32	0	41	176	46	18	4	0%	1.3	26.1%	10.2%	15.9%	2.3%	3.92	3.44	—
2022	24	MIX MLE	2 levels	25	0	30	140	27	27	3	0%	1.2	16.0%	20.5%	-4.5%	2.4%	5.04	5.64	—
2022	24	MIX RAW	2 levels	25	0	30	140	27	27	3	0%	1.2	19.3%	19.3%	0.0%	2.1%	5.04	5.28	—
2024	26	MIX MLE	2 levels	20	0	27	120	25	17	4	0%	1.4	19.8%	9.4%	10.4%	1.3%	4.94	3.33	—
2024	26	MIX MLE	2 levels	20	0	27	120	25	17	4	0%	1.4	19.8%	9.4%	10.4%	1.3%	4.94	3.33	—
2024	26	MIX RAW	2 levels	20	0	27	120	25	17	4	0%	1.4	20.8%	14.2%	6.7%	3.3%	4.94	5.04	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	PHI	—	—	0	—	—	—	—	—	—	22.7%	9.2%	13.4%	3.0%	4.37	4.37	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	PHI	17	0	18	77	17	7	2	0%	1.1	22.4%	9.5%	12.9%	3.2%	4.47	4.54	+0.0
2028	30	MLB CTX	PHI	6	0	6	25	6	2	1	0%	1.0	22.4%	9.5%	12.9%	3.2%	4.47	4.54	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		5	0	6	24	5	2	1	0%	1.1	22.4%	9.5%	12.9%	3.2%	4.47	4.16	+0.0
/ 200 IP	—	RAW		190	0	200	844	175	70	35	0%	1.1	22.4%	9.5%	12.9%	3.2%	4.47	4.16	+0.9
Career	—	MLE		115	18	206	916	148	124	27	16%	1.8	16.2%	13.5%	2.6%	2.9%	4.94	5.06	+0.0
/ 200 IP	—	MLE		112	18	200	891	144	120	26	16%	1.8	16.2%	13.5%	2.6%	2.9%	4.94	5.06	+0.0

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 AAReading Fightin Phils · 21 IPFIP 2.79 → 3.33 (+0.54)K% 24.4% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.39%	—	×0.810	19.76%
BB% (unintentional) /BF	8.54%	—	×1.100	9.39%
HR / BF /BF	1.22%	÷1.137	×1.200	1.29%

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 127).

Result: FIP 2.79 → 3.33, 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 AAALehigh Valley IronPigs · 7 IPFIP 9.66 → 9.96 (+0.31)K% 13.2% → 11.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.16%	—	×0.860	11.32%
BB% (unintentional) /BF	26.32%	—	×0.900	23.68%
HR / BF /BF	7.89%	÷0.989	×1.100	8.78%

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 98).

Result: FIP 9.66 → 9.96, 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).

2022 AAAIowa Cubs · 14 IPFIP 7.43 → 7.89 (+0.47)K% 9.9% → 8.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	9.88%	—	×0.880	8.69%
BB% (unintentional) /BF	24.69%	—	×1.050	25.93%
HR / BF /BF	3.70%	÷0.996	×1.100	4.09%

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 99).

Result: FIP 7.43 → 7.89, 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 AATennessee Smokies · 16 IPFIP 1.88 → 2.55 (+0.67)K% 32.2% → 26.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.20%	—	×0.810	26.08%
BB% (unintentional) /BF	11.86%	—	×1.100	13.05%
HR / BF /BF	0.00%	÷1.010	×1.200	0.00%

Result: FIP 1.88 → 2.55, 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).

2021 A+South Bend Cubs · 31 IPFIP 3.10 → 4.34 (+1.24)K% 30.7% → 23.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.71%	—	×0.770	23.65%
BB% (unintentional) /BF	10.24%	—	×1.150	11.77%
HR / BF /BF	2.36%	÷0.928	×1.250	3.18%

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 86).

Result: FIP 3.10 → 4.34, 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 AATennessee Smokies · 10 IPFIP 4.31 → 4.83 (+0.52)K% 14.3% → 11.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.29%	—	×0.810	11.57%
BB% (unintentional) /BF	10.20%	—	×1.100	11.22%
HR / BF /BF	2.04%	÷1.050	×1.200	2.33%

Result: FIP 4.31 → 4.83, 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 ASouth Bend Cubs · 29 IPFIP 5.45 → 7.19 (+1.74)K% 19.1% → 14.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.08%	—	×0.740	14.12%
BB% (unintentional) /BF	11.45%	—	×1.180	13.51%
HR / BF /BF	4.58%	÷0.914	×1.300	6.51%

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 83).

Result: FIP 5.45 → 7.19, 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 ROKAZL Cubs · 32 IPFIP 4.07 → 5.40 (+1.32)K% 19.1% → 13.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.08%	—	×0.680	12.97%
BB% (unintentional) /BF	11.84%	—	×1.250	14.80%
HR / BF /BF	1.97%	÷1.000	×1.400	2.76%

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 4.07 → 5.40, 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
Eury Ramos (OGILVIE)	—	—	4.37	22.7%	9.2%	3.0%	—	4.54	22.4%	12.9%	18	+0.17	—	—	—
Diego Moreno R 2016 · 3.75 FIP	29	SU	3.75	21.0%	8.2%	2.5%	.347	3.13	17.8%	11.9%	54	-0.62	2.29	187	82
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	81
Tyler Sturdevant R 2015 · 4.37 FIP	29	SU	4.37	21.3%	8.5%	3.6%	.241	3.97	18.5%	11.9%	118	-0.40	3.44	149	80
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	79
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	78
Coleman Huntley III R 2022 · 4.05 FIP	29	SU	4.05	24.4%	10.9%	3.0%	.311	2.38	20.9%	12.6%	25	-1.67	2.38	160	77
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	77
Cody Hall R 2017 · 4.03 FIP	29	SU	4.03	26.8%	10.0%	3.5%	.299	3.92	25.9%	8.4%	19	-0.11	3.51	134	77
Gerardo Sanchez R 2017 · 3.47 FIP	28	SU	3.47	21.6%	8.4%	2.1%	.355	3.58	20.5%	15.1%	56	+0.11	2.65	137	77
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	77
Ryan Brasier R 2016 · 3.68 FIP	28	SU	3.68	25.0%	7.7%	3.1%	.289	3.09	24.2%	17.9%	130	-0.59	2.31	426	76
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	76
Scott Atchison R 2004 · 3.61 FIP	28	SU	3.61	27.1%	9.0%	3.0%	.309	4.55	19.1%	11.5%	31	+0.94	2.52	340	75
Marc Magliaro R 2018 · 3.94 FIP	28	SU	3.94	19.6%	7.3%	2.9%	.307	—	—	—	—	—	3.94	125	75
Marcos Mateo R 2011 · 3.40 FIP	27	SU	3.40	25.5%	10.2%	2.1%	.361	—	—	—	—	—	3.12	104	75
Alex Powers R 2021 · 4.24 FIP	29	SU	4.24	25.0%	10.3%	3.5%	.312	—	—	—	—	—	2.82	264	74
Brian Sanches R 2008 · 4.74 FIP	29	SU	4.74	18.5%	9.3%	3.7%	.378	4.01	20.5%	10.8%	182	-0.73	3.39	229	74
Michael Dimock R 2018 · 3.37 FIP	28	SU	3.37	23.5%	10.7%	1.6%	.346	—	—	—	—	—	3.08	166	74
Andrew Robinson R 2017 · 4.32 FIP	29	SU	4.32	23.4%	8.8%	3.8%	.245	—	—	—	—	—	3.19	160	74
Joel Peralta R 2005 · 4.67 FIP	29	SU	4.67	20.7%	8.3%	4.1%	.227	4.27	18.0%	13.3%	214	-0.40	2.70	648	74