Ebduar Loina

P DSL Giants Black

Age 20 RHP 5'11" / 168 lbs ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	18	ROKDSL Giants Or…	3	2	11.57	7.39	7.1%	28.6%	—	K 7.1% · BB 28.6% · FIP 6.12
2026	19	ROKDSL Giants Bl…	15	13	15.92	9.95	11.0%	35.2%	—	K 7.5% · BB 44.0% · FIP 8.88
2027PROJ	20	MLBSF	8	8	6.02	6.02	19.1%	20.0%	-0.1
2028PROJ49% MLB	21	MLBSF	10	10	5.64	5.50	20.2%	16.8%	-0.1

Next 2 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0 WAR median (P10 0 / P90 0, comp-based) · star 0% · didn't stick 100%

CompsJackson Rose (age 22) · Michael Perez (age 21) · Daniel Lloyd (age 20)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 147139vR 131

ERA6.02

FIP6.02

K%19.1%

BB%20.0%

K-BB%-0.9%

Proj IP8

Value2027 · WAR

Runs saved vs league avg · 8 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 industry-standard fWAR.

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)
2025	18	ROK MLE	DSL Giants Orange	3	0	2	14	1	4	0	0%	0.8	7.1%	28.6%	-21.4%	0.0%	11.57	6.12	—
2025	18	ROK MLE	DSL Giants Orange	3	0	2	14	1	4	0	0%	0.8	7.1%	28.6%	-21.4%	0.0%	11.57	6.12	—
2025	18	ROK RAW	DSL Giants Orange	3	0	2	14	1	4	0	0%	0.8	7.1%	28.6%	-21.4%	0.0%	11.57	7.39	—
2026	19	ROK MLE	DSL Giants Black	15	0	13	91	10	32	1	0%	0.9	7.5%	44.0%	-36.5%	1.5%	15.92	8.88	—
2026	19	ROK MLE	DSL Giants Black	15	0	13	91	10	32	1	0%	0.9	7.5%	44.0%	-36.5%	1.5%	15.92	8.88	—
2026	19	ROK RAW	DSL Giants Black	15	0	13	91	10	32	1	0%	0.9	11.0%	35.2%	-24.2%	1.1%	15.92	9.95	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	20	MLB	SF	8	0	8	34	6	7	1	0%	1.0	19.1%	20.0%	-0.9%	3.0%	6.02	6.02	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	21	MLB MLE	SF	19	0	20	84	17	14	2	0%	1.1	20.2%	16.8%	3.4%	2.9%	5.64	5.50	-0.2
2028	21	MLB CTX	SF	10	0	10	42	9	7	1	0%	1.0	20.2%	16.8%	3.4%	2.9%	5.64	5.50	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	0	10	42	8	7	1	0%	1.1	20.2%	16.8%	3.4%	2.9%	5.64	5.12	-0.1
/ 200 IP	—	RAW		190	0	200	844	163	142	20	0%	1.1	20.2%	16.8%	3.4%	2.9%	5.64	5.12	-1.3
Career	—	MLE		18	0	15	105	8	44	1	0%	0.9	7.4%	41.9%	-34.5%	1.3%	15.26	8.51	-0.2
/ 200 IP	—	MLE		235	0	200	1370	102	574	18	0%	0.9	7.4%	41.9%	-34.5%	1.3%	15.26	8.51	-2.2

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
Ebduar Loina (OGILVIE)	—	—	6.02	19.1%	20.0%	3.0%	—	5.50	20.2%	3.4%	20	-0.52	—	—	—
Jackson Rose R 2018 · 5.32 FIP	22	SU	5.32	17.3%	17.2%	2.8%	.267	4.77	23.5%	16.5%	56	-0.55	3.33	147	88
Michael Perez R 2024 · 5.44 FIP	21	SU	5.44	18.3%	16.1%	3.4%	.296	4.65	23.4%	7.7%	132	-0.79	4.38	153	88
Daniel Lloyd R 2021 · 5.40 FIP	20	SU	5.40	20.4%	22.4%	2.2%	.367	4.15	18.0%	8.5%	226	-1.25	3.59	319	87
Elison Joseph R 2021 · 5.31 FIP	20	SU	5.31	17.4%	19.2%	2.3%	.254	4.55	23.5%	6.8%	133	-0.76	3.32	217	86
Andrew Schultz R 2019 · 5.25 FIP	22	SU	5.25	20.9%	17.8%	3.0%	.345	4.59	23.0%	4.7%	45	-0.66	3.56	176	86
Greg Weissert R 2016 · 5.22 FIP	21	SU	5.22	19.4%	19.3%	2.4%	.382	3.80	23.0%	10.3%	126	-1.42	2.57	487	86
Hudson Leach R 2024 · 5.37 FIP	22	SU	5.37	20.5%	20.0%	2.7%	.261	4.54	20.9%	3.1%	71	-0.83	2.77	101	86
Samuel Fabian R 2023 · 6.61 FIP	20	SU	6.61	16.8%	27.4%	2.7%	.352	4.33	17.2%	4.8%	64	-2.28	4.21	120	85
Marcus Crescentini R 2015 · 5.80 FIP	22	SU	5.80	21.8%	21.9%	3.2%	.365	3.95	23.3%	11.6%	123	-1.85	2.74	150	84
Erian Rodriguez R 2022 · 5.51 FIP	20	SU	5.51	16.2%	19.8%	2.3%	.378	4.16	16.2%	3.6%	241	-1.35	3.81	287	84
Jairo Beras R 2017 · 6.07 FIP	22	SU	6.07	16.4%	16.9%	4.0%	.237	4.35	20.7%	4.5%	96	-1.72	3.48	110	83
Nick Kuzia R 2017 · 5.18 FIP	21	SU	5.18	16.5%	15.2%	2.8%	.361	5.35	17.6%	6.6%	60	+0.17	4.54	231	83
Junior Flores R 2021 · 5.28 FIP	19	SU	5.28	20.5%	24.1%	1.6%	.220	4.93	14.5%	-3.9%	92	-0.35	4.87	110	83
Angel Reyes R 2018 · 4.91 FIP	20	SU	4.91	16.5%	19.4%	1.4%	.328	4.51	17.1%	5.7%	119	-0.40	3.99	308	83
Adrian Rodriguez R 2021 · 6.92 FIP	20	SU	6.92	23.1%	34.0%	2.7%	.368	5.46	23.1%	-1.6%	93	-1.46	2.43	148	83
Paul Gervase R 2022 · 4.91 FIP	22	SU	4.91	20.3%	16.2%	2.7%	.345	3.76	29.3%	16.0%	152	-1.15	3.38	211	83
Tommy McCollum R 2021 · 6.21 FIP	22	SU	6.21	17.1%	27.2%	2.0%	.235	3.80	26.4%	10.9%	112	-2.41	2.90	219	83
Christian Ruebeck R 2024 · 6.03 FIP	23	SU	6.03	20.6%	24.4%	2.9%	.265	4.57	21.6%	1.9%	70	-1.46	4.35	104	82
Andrew Marrero R 2021 · 5.09 FIP	21	SU	5.09	21.7%	22.0%	1.9%	.395	4.61	24.3%	9.1%	148	-0.48	3.45	221	82
Brendan Hardy R 2021 · 6.99 FIP	21	SU	6.99	15.9%	33.1%	1.9%	.324	3.67	22.9%	7.9%	83	-3.32	2.54	137	82