Eric Silva

P Erie SeaWolves

Age 24 RHP 6'1" / 185 lbs AA

Overview

AAPROSPECT

ETA2028MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	21	AADET	41	0	59	4.73	3.64	27.8%	8.9%	—	K 22.5% · BB 9.8% · FIP 4.69
2025	22	MIX4 levels	11	5	45	3.80	3.92	16.5%	8.2%	—	K 8.6% · BB 11.7% · FIP 5.91
2026	23	MIX2 levels	37	2	60	6.41	4.92	24.5%	10.8%	—	K 19.5% · BB 11.1% · FIP 5.37
2027PROJ	24	MLBDET	1	0	1	5.06	5.06	19.6%	10.8%	-0.0
2028PROJ44% MLB	25	MLBDET	18	0	19	4.92	4.87	20.5%	10.2%	-0.1
2029PROJ67% MLB	26	MLBDET	25	0	26	4.83	4.80	21.0%	10.0%	-0.1

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

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.3 / P90 0.6, comp-based) · star 0% · didn't stick 96%

CompsBrad Deppermann (age 25) · Jimmy Kingsbury (age 24) · Jonathan Papelbon (age 24)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 129121vR 113

ERA5.06

FIP5.06

K%19.6%

BB%10.8%

K-BB%8.8%

Proj IP32

Value2027 · WAR

Runs saved vs league avg · 32 IP

Grades · Contract

Scouting Grades

K†4550

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)
2021	18	ROK MLE	ACL Giants Orange	2	0	1	10	2	3	0	0%	0.5	20.0%	30.0%	-10.0%	0.0%	36.00	5.21	—
2021	18	ROK RAW	ACL Giants Orange	2	0	1	10	2	3	0	0%	0.5	20.0%	30.0%	-10.0%	0.0%	36.00	8.10	—
2022	19	A MLE	San Jose Giants	22	22	86	365	99	39	11	100%	3.9	20.1%	12.6%	7.5%	3.7%	5.88	5.03	—
2022	19	A RAW	San Jose Giants	22	22	86	365	99	39	11	100%	3.9	27.1%	10.7%	16.4%	3.0%	5.88	3.82	—
2023	20	MIX MLE	2 levels	30	20	81	367	86	39	7	67%	2.7	16.4%	13.1%	3.3%	2.4%	5.86	4.68	—
2023	20	MIX RAW	2 levels	30	20	81	367	86	39	7	67%	2.7	23.4%	10.6%	12.8%	1.9%	5.86	3.54	—
2024	21	AA MLE	Erie SeaWolves	41	0	59	248	69	22	8	0%	1.4	22.5%	9.8%	12.8%	4.1%	4.73	4.69	—
2024	21	AA MLE	Erie SeaWolves	41	0	59	248	69	22	8	0%	1.4	22.5%	9.8%	12.8%	4.1%	4.73	4.69	—
2024	21	AA RAW	Erie SeaWolves	41	0	59	248	69	22	8	0%	1.4	27.8%	8.9%	19.0%	3.2%	4.73	3.64	—
2025	22	MIX MLE	4 levels	11	5	45	182	30	15	4	45%	4.1	8.6%	11.7%	-3.1%	3.7%	3.80	5.91	—
2025	22	MIX MLE	4 levels	11	5	45	182	30	15	4	45%	4.1	8.6%	11.7%	-3.1%	3.7%	3.80	5.91	—
2025	22	MIX RAW	4 levels	11	5	45	182	30	15	4	45%	4.1	16.5%	8.2%	8.2%	2.2%	3.80	3.92	—
2026	23	MIX MLE	2 levels	37	2	60	278	68	30	12	5%	1.6	19.5%	11.1%	8.3%	4.6%	6.41	5.37	—
2026	23	MIX MLE	2 levels	37	2	60	278	68	30	12	5%	1.6	19.5%	11.1%	8.3%	4.6%	6.41	5.37	—
2026	23	MIX RAW	2 levels	37	2	60	278	68	30	12	5%	1.6	24.5%	10.8%	13.7%	4.3%	6.41	4.92	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	24	MLB	DET	1	0	1	4	1	0	0	0%	1.0	19.6%	10.8%	8.8%	3.4%	5.06	5.06	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	25	MLB MLE	DET	40	0	42	179	37	18	6	0%	1.1	20.5%	10.2%	10.4%	3.3%	4.92	4.87	-0.2
2029	26	MLB MLE	DET	36	0	38	161	34	16	5	0%	1.1	21.0%	10.0%	11.0%	3.3%	4.83	4.80	-0.1
2028	25	MLB CTX	DET	18	0	19	80	16	8	3	0%	1.1	20.5%	10.2%	10.4%	3.3%	4.92	4.87	-0.1
2029	26	MLB CTX	DET	25	0	26	110	23	11	4	0%	1.0	21.0%	10.0%	11.0%	3.3%	4.83	4.80	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		42	0	44	186	39	19	6	0%	1.0	20.8%	10.1%	10.7%	3.3%	4.87	4.45	+0.1
/ 200 IP	—	RAW		190	0	200	844	177	86	27	0%	1.1	20.8%	10.1%	10.7%	3.3%	4.87	4.45	+0.2
Career	—	MLE		143	49	332	1450	261	174	52	34%	2.3	18.0%	12.0%	6.0%	3.6%	5.58	5.06	-0.3
/ 200 IP	—	MLE		86	29	200	873	157	104	31	34%	2.3	18.0%	12.0%	6.0%	3.6%	5.58	5.06	-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 AAErie SeaWolves · 52 IPFIP 4.44 → 5.37 (+0.93)K% 24.1% → 19.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.05%	—	×0.810	19.48%
BB% (unintentional) /BF	10.13%	—	×1.100	11.14%
HR / BF /BF	3.80%	÷1.000	×1.200	4.56%

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 4.44 → 5.37, 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 AAAToledo Mud Hens · 8 IPFIP 6.70 → 7.24 (+0.53)K% 26.8% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.83%	—	×0.860	23.07%
BB% (unintentional) /BF	14.63%	—	×0.900	13.17%
HR / BF /BF	7.32%	÷1.000	×1.100	8.05%

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 6.70 → 7.24, 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 ALakeland Flying Tigers · 28 IPFIP 4.74 → 5.91 (+1.17)K% 11.6% → 8.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	11.57%	—	×0.740	8.56%
BB% (unintentional) /BF	9.92%	—	×1.180	11.70%
HR / BF /BF	2.48%	÷0.864	×1.300	3.73%

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 73).

Result: FIP 4.74 → 5.91, 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 AAErie SeaWolves · 8 IPFIP 1.35 → 1.94 (+0.59)K% 31.0% → 25.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.03%	—	×0.810	25.14%
BB% (unintentional) /BF	6.90%	—	×1.100	7.59%
HR / BF /BF	0.00%	÷1.056	×1.200	0.00%

Result: FIP 1.35 → 1.94, 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 AAErie SeaWolves · 59 IPFIP 3.64 → 4.69 (+1.05)K% 27.8% → 22.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.82%	—	×0.810	22.54%
BB% (unintentional) /BF	8.87%	—	×1.100	9.76%
HR / BF /BF	3.23%	÷0.941	×1.200	4.11%

Result: FIP 3.64 → 4.69, 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 A+Eugene Emeralds · 76 IPFIP 3.87 → 4.68 (+0.81)K% 21.3% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.35%	—	×0.770	16.44%
BB% (unintentional) /BF	11.40%	—	×1.150	13.11%
HR / BF /BF	2.05%	÷1.076	×1.250	2.38%

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 115).

Result: FIP 3.87 → 4.68, 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 ROKACL Giants Black · 5 IPFIP -1.29 → 0.11 (+1.41)K% 52.0% → 35.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	52.00%	—	×0.680	35.36%
BB% (unintentional) /BF	0.00%	—	×1.250	0.00%
HR / BF /BF	0.00%	÷1.031	×1.400	0.00%

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 106).

Result: FIP -1.29 → 0.11, 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 ASan Jose Giants · 86 IPFIP 3.82 → 5.03 (+1.21)K% 27.1% → 20.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.12%	—	×0.740	20.07%
BB% (unintentional) /BF	10.68%	—	×1.180	12.61%
HR / BF /BF	3.01%	÷1.063	×1.300	3.69%

Result: FIP 3.82 → 5.03, 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
Eric Silva (OGILVIE)	—	—	5.06	19.6%	10.8%	3.4%	—	4.84	20.8%	10.7%	80	-0.22	—	—	—
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	90
Jimmy Kingsbury R 2023 · 5.11 FIP	24	SW	5.11	18.2%	9.9%	4.2%	.304	3.67	18.0%	9.9%	189	-1.44	3.51	330	83
Jonathan Papelbon R 2005 · 3.93 FIP	24	SW	3.93	23.0%	10.1%	2.7%	.305	1.90	31.3%	26.8%	196	-2.03	1.33	726	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
Trent Fennell R 2019 · 4.08 FIP	23	SW	4.08	20.6%	12.2%	2.1%	.328	5.52	19.4%	3.5%	107	+1.44	4.08	163	82
Ross Ohlendorf R 2008 · 4.73 FIP	25	SW	4.73	16.3%	9.3%	3.3%	.357	4.63	15.4%	7.7%	324	-0.10	3.30	617	81
Shohei Tomioka R 2021 · 4.00 FIP	25	SW	4.00	18.9%	9.0%	2.5%	.311	4.39	17.2%	4.0%	141	+0.39	3.65	301	80
Carlo Reyes R 2022 · 4.06 FIP	24	SW	4.06	20.4%	8.6%	2.9%	.318	3.92	24.1%	12.9%	61	-0.14	2.60	229	80
Jeff Niemann R 2008 · 5.04 FIP	25	SW	5.04	18.4%	10.5%	4.0%	.294	4.16	17.4%	10.3%	490	-0.88	2.96	544	80
Emmanuel Chapman R 2024 · 4.08 FIP	25	SW	4.08	19.7%	10.6%	2.4%	.256	4.52	17.8%	1.3%	117	+0.44	3.81	198	80
Ryan Conroy R 2021 · 4.01 FIP	24	SU	4.01	22.2%	9.8%	2.8%	.353	4.75	19.3%	6.7%	54	+0.74	4.01	106	80
Colby Morris R 2021 · 4.11 FIP	24	SU	4.11	20.4%	10.7%	2.5%	.291	5.76	16.2%	4.4%	54	+1.65	4.11	105	80
Nick Lockhart R 2023 · 4.63 FIP	22	SW	4.63	16.1%	10.6%	2.8%	.274	—	—	—	—	—	4.44	140	79
Jarret Whorff R 2023 · 4.24 FIP	24	SW	4.24	19.5%	14.2%	1.8%	.287	4.34	19.4%	10.8%	193	+0.10	3.88	257	79
Scott Burke R 2018 · 4.55 FIP	24	SW	4.55	14.2%	7.7%	3.0%	.316	5.27	14.9%	6.7%	61	+0.72	4.55	119	79
Nick Hull R 2024 · 4.62 FIP	24	SW	4.62	19.0%	12.2%	2.9%	.296	5.00	16.8%	6.2%	111	+0.38	4.26	292	78
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	78
Ryan Zeferjahn R 2022 · 4.45 FIP	24	SW	4.45	21.0%	12.4%	2.8%	.325	4.36	27.3%	13.8%	163	-0.09	3.05	349	78
Heath Slatton R 2017 · 5.56 FIP	23	SW	5.56	17.9%	12.9%	4.3%	.382	—	—	—	—	—	2.46	120	78
Andrew Bellatti R 2015 · 4.34 FIP	23	SU	4.34	19.3%	8.8%	3.2%	.288	—	—	—	—	—	2.67	278	78

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	0.6	37	20.4%	10.3%	1.30	4.93
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*