Esmerlin Vinicio

P Eugene Emeralds

Age 24 LHP 6'1" / 146 lbs A+

Overview

A+PROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	21	MIX2 levels	25	11	82	4.72	3.88	21.7%	14.4%	—	K 16.2% · BB 16.8% · FIP 4.81
2025	22	A+SF	29	5	48	6.14	4.24	23.1%	17.6%	—	K 17.8% · BB 20.3% · FIP 5.05
2026	23	MIX2 levels	30	2	65	3.34	2.88	26.6%	11.5%	—	K 20.7% · BB 13.1% · FIP 3.73
2027PROJ	24	MLBSF	—	—	0	5.60	5.60	18.6%	18.1%	—
2028PROJ43% MLB	25	MLBSF	20	0	21	5.36	5.28	19.5%	16.1%	-0.2
2029PROJ66% MLB	26	MLBSF	27	0	28	5.23	5.19	20.0%	15.5%	-0.2

Next 3 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control20Command30

Career WAR0.0 WAR median (P10 -0.1 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsBraeden Fausnaught (age 24) · Matt Mikulski (age 24) · Colby Langford (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 123131vR 140

ERA5.60

FIP5.60

K%18.6%

BB%18.1%

K-BB%0.5%

Proj IP67

Value2027 · WAR

Runs saved vs league avg · 67 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL2020

CMD3030

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 Black	14	11	58	239	70	29	2	79%	4.1	19.9%	15.2%	4.7%	1.0%	2.64	3.87	—
2021	18	ROK RAW	ACL Giants Black	14	11	58	239	70	29	2	79%	4.1	29.3%	12.1%	17.2%	0.8%	2.64	2.63	—
2022	19	MIX MLE	2 levels	28	5	53	243	59	32	4	18%	1.9	17.6%	15.7%	1.9%	2.0%	5.26	4.71	—
2022	19	MIX RAW	2 levels	28	5	53	243	59	32	4	18%	1.9	24.3%	13.2%	11.1%	1.6%	5.26	3.67	—
2023	20	MIX MLE	2 levels	32	5	82	367	90	45	6	16%	2.6	17.9%	14.4%	3.4%	2.5%	4.72	4.82	—
2023	20	MIX RAW	2 levels	32	5	82	367	90	45	6	16%	2.6	24.5%	12.3%	12.3%	1.6%	4.72	3.50	—
2024	21	MIX MLE	2 levels	25	11	82	355	77	51	5	44%	3.3	16.2%	16.8%	-0.6%	1.7%	4.72	4.81	—
2024	21	MIX MLE	2 levels	25	11	82	355	77	51	5	44%	3.3	16.2%	16.8%	-0.6%	1.7%	4.72	4.81	—
2024	21	MIX RAW	2 levels	25	11	82	355	77	51	5	44%	3.3	21.7%	14.4%	7.3%	1.4%	4.72	3.88	—
2025	22	A+ MLE	Eugene Emeralds	29	5	48	238	55	42	3	17%	1.7	17.8%	20.3%	-2.5%	1.6%	6.14	5.05	—
2025	22	A+ MLE	Eugene Emeralds	29	5	48	238	55	42	3	17%	1.7	17.8%	20.3%	-2.5%	1.6%	6.14	5.05	—
2025	22	A+ RAW	Eugene Emeralds	29	5	48	238	55	42	3	17%	1.7	23.1%	17.6%	5.5%	1.3%	6.14	4.24	—
2026	23	MIX MLE	2 levels	30	2	65	286	76	33	3	7%	2.2	20.7%	13.1%	7.6%	1.3%	3.34	3.73	—
2026	23	MIX MLE	2 levels	30	2	65	286	76	33	3	7%	2.2	20.7%	13.1%	7.6%	1.3%	3.34	3.73	—
2026	23	MIX RAW	2 levels	30	2	65	286	76	33	3	7%	2.2	26.6%	11.5%	15.0%	1.0%	3.34	2.88	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	24	MLB	SF	—	—	0	—	—	—	—	—	—	18.6%	18.1%	0.5%	2.5%	5.60	5.60	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	25	MLB MLE	SF	46	0	48	203	40	33	5	0%	1.0	19.5%	16.1%	3.4%	2.6%	5.36	5.28	-0.4
2029	26	MLB MLE	SF	40	0	42	177	35	27	5	0%	1.0	20.0%	15.5%	4.4%	2.6%	5.23	5.19	-0.3
2030	27	MLB MLE	SF	37	0	39	166	33	25	4	0%	1.1	20.1%	15.3%	4.8%	2.7%	5.18	5.18	-0.3
2031	28	MLB MLE	SF	35	0	37	156	31	24	4	0%	1.1	20.1%	15.3%	4.8%	2.8%	5.21	5.24	-0.3
2028	25	MLB CTX	SF	20	0	21	89	17	14	2	0%	1.1	19.5%	16.1%	3.4%	2.6%	5.36	5.28	-0.2
2029	26	MLB CTX	SF	27	0	28	118	24	18	3	0%	1.0	20.0%	15.5%	4.4%	2.6%	5.23	5.19	-0.2
2030	27	MLB CTX	SF	29	0	30	127	25	19	3	0%	1.0	20.1%	15.3%	4.8%	2.7%	5.18	5.18	-0.2
2031	28	MLB CTX	SF	30	0	31	131	26	20	4	0%	1.0	20.1%	15.3%	4.8%	2.8%	5.21	5.24	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		105	0	110	464	93	72	12	0%	1.0	19.9%	15.5%	4.5%	2.7%	5.24	4.84	-0.4
/ 200 IP	—	RAW		190	0	200	844	169	131	22	0%	1.1	19.9%	15.5%	4.5%	2.7%	5.24	4.84	-0.7
Career	—	MLE		158	39	388	1728	315	273	30	25%	2.5	18.2%	15.8%	2.4%	1.8%	4.43	4.52	-1.3
/ 200 IP	—	MLE		81	20	200	891	162	141	16	25%	2.5	18.2%	15.8%	2.4%	1.8%	4.43	4.52	-1.6

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+Eugene Emeralds · 52 IPFIP 2.88 → 3.76 (+0.89)K% 26.4% → 20.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.43%	—	×0.770	20.35%
BB% (unintentional) /BF	10.13%	—	×1.150	11.65%
HR / BF /BF	1.32%	÷1.000	×1.250	1.65%

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 2.88 → 3.76, 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 AARichmond Flying Squirrels · 13 IPFIP 2.96 → 3.61 (+0.65)K% 27.1% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.12%	—	×0.810	21.97%
BB% (unintentional) /BF	16.95%	—	×1.100	18.64%
HR / BF /BF	0.00%	÷1.000	×1.200	0.00%

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 2.96 → 3.61, 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+Eugene Emeralds · 48 IPFIP 4.08 → 5.05 (+0.97)K% 23.1% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.11%	—	×0.770	17.79%
BB% (unintentional) /BF	17.65%	—	×1.150	20.29%
HR / BF /BF	1.26%	÷0.980	×1.250	1.61%

Result: FIP 4.08 → 5.05, 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 ASan Jose Giants · 58 IPFIP 2.85 → 3.66 (+0.81)K% 22.9% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.92%	—	×0.740	16.96%
BB% (unintentional) /BF	13.33%	—	×1.180	15.73%
HR / BF /BF	0.00%	÷0.959	×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 92).

Result: FIP 2.85 → 3.66, 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+Eugene Emeralds · 24 IPFIP 5.96 → 7.22 (+1.25)K% 19.1% → 14.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.13%	—	×0.770	14.73%
BB% (unintentional) /BF	16.52%	—	×1.150	19.00%
HR / BF /BF	4.35%	÷1.010	×1.250	5.38%

Result: FIP 5.96 → 7.22, 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 ASan Jose Giants · 77 IPFIP 3.57 → 4.82 (+1.25)K% 24.1% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.13%	—	×0.740	17.85%
BB% (unintentional) /BF	12.21%	—	×1.180	14.41%
HR / BF /BF	1.74%	÷0.890	×1.300	2.55%

Result: FIP 3.57 → 4.82, 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 Orange · 5 IPFIP 2.18 → 3.42 (+1.24)K% 30.4% → 20.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.43%	—	×0.680	20.70%
BB% (unintentional) /BF	13.04%	—	×1.250	16.30%
HR / BF /BF	0.00%	÷1.377	×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 175).

Result: FIP 2.18 → 3.42, 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 · 39 IPFIP 4.11 → 5.21 (+1.10)K% 23.4% → 17.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.37%	—	×0.740	17.29%
BB% (unintentional) /BF	14.13%	—	×1.180	16.67%
HR / BF /BF	2.17%	÷1.063	×1.300	2.66%

Result: FIP 4.11 → 5.21, 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
Esmerlin Vinicio (OGILVIE)	—	—	5.60	18.6%	18.1%	2.5%	—	5.22	19.8%	4.2%	129	-0.38	—	—	—
Braeden Fausnaught L 2023 · 4.77 FIP	24	SW	4.77	16.9%	16.4%	1.8%	.287	4.60	17.9%	9.7%	179	-0.17	4.43	242	90
Matt Mikulski L 2023 · 6.17 FIP	24	SW	6.17	16.4%	18.6%	3.8%	.303	5.90	16.3%	-3.3%	78	-0.27	4.92	223	84
Colby Langford L 2024 · 5.34 FIP	22	SW	5.34	21.6%	22.5%	2.2%	.273	6.01	22.2%	-1.1%	110	+0.67	4.92	168	83
Larson Kindreich L 2023 · 5.29 FIP	24	SW	5.29	21.5%	18.8%	3.0%	.269	4.68	23.0%	9.0%	79	-0.61	4.16	214	82
Ty Madrigal L 2021 · 4.56 FIP	24	SU	4.56	19.3%	15.7%	2.0%	.329	5.75	17.6%	2.4%	49	+1.19	4.56	107	79
Matt Walker L 2022 · 4.54 FIP	24	SW	4.54	17.7%	12.8%	2.4%	.338	4.73	12.7%	2.7%	41	+0.19	4.21	156	78
Mark Manfredi Sr. L 2024 · 4.60 FIP	24	SW	4.60	22.0%	14.9%	2.7%	.289	3.22	25.4%	11.6%	128	-1.38	2.91	204	78
Bryan King L 2021 · 5.20 FIP	24	SU	5.20	17.4%	17.8%	2.4%	.317	2.82	24.4%	14.9%	77	-2.38	2.41	244	77
Estevan Gonzalez L 2016 · 4.58 FIP	24	SU	4.58	16.9%	15.7%	1.7%	.240	5.21	12.1%	-1.2%	58	+0.63	4.58	195	76
John Kilichowski L 2018 · 4.99 FIP	24	SU	4.99	17.6%	16.2%	2.4%	.336	—	—	—	—	—	4.10	115	76
Angel Hernandez L 2024 · 4.55 FIP	24	SU	4.55	19.2%	18.0%	1.4%	.262	—	—	—	—	—	3.33	182	76
Kelly Secrest L 2016 · 4.42 FIP	24	SU	4.42	18.6%	13.7%	2.1%	.267	3.47	20.8%	10.4%	38	-0.95	3.11	151	75
Max Roberts L 2021 · 4.85 FIP	24	SW	4.85	19.3%	15.2%	2.6%	.330	4.62	24.5%	8.4%	115	-0.23	4.27	173	75
Mason Green L 2023 · 5.28 FIP	24	SW	5.28	17.9%	16.7%	2.9%	.278	4.24	18.4%	6.3%	265	-1.04	3.68	450	75
Nicolo Pinazzi L 2023 · 6.79 FIP	23	SU	6.79	19.3%	26.9%	3.5%	.307	2.58	30.1%	16.3%	62	-4.21	2.58	155	75
Caleb Frare L 2017 · 5.45 FIP	24	SU	5.45	22.6%	21.3%	2.9%	.307	3.14	28.0%	15.6%	80	-2.31	2.27	237	74
Chris Reed L 2015 · 4.92 FIP	25	SU	4.92	15.4%	14.5%	2.3%	.284	4.67	16.4%	6.6%	81	-0.25	4.67	137	74
Juan Pichardo L 2021 · 4.83 FIP	23	SU	4.83	17.7%	17.1%	1.9%	.301	—	—	—	—	—	2.13	103	74
Brendan Cellucci L 2022 · 4.95 FIP	24	SW	4.95	22.4%	17.9%	2.7%	.320	4.48	23.3%	7.7%	137	-0.47	3.98	288	74
Fabian Williamson L 2015 · 5.31 FIP	26	SU	5.31	17.4%	17.9%	2.6%	.289	4.16	20.0%	8.2%	77	-1.15	3.39	154	74

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	1.2	47	19.5%	16.3%	1.01	5.35
Brian Bruney ('12)	1.3	43	21.2%	15.8%	0.94	4.68
John Parrish ('10)	1.4	46	17.6%	14.8%	0.88	4.51
Doug Bochtler ('00)	1.3	65	18.6%	14.4%	1.25	4.57
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*