Yunior Marte

P Richmond Flying Squirrels

Age 23 RHP 6'6" / 236 lbs AA Svc 0.0 · Ctrl thru 2032 peak 0.7 · 2029

Overview

AASP40-MANROOKIEPre-ArbFA 2033

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	20	MIX2 levels	9	8	25	8.76	4.11	18.2%	8.3%	—	K 12.3% · BB 12.0% · FIP 6.52
2025	21	ASF	24	22	102	2.91	2.58	23.8%	7.2%	—	K 17.6% · BB 8.5% · FIP 3.21
2026	22	MIX3 levels	27	23	132	3.95	3.90	23.0%	9.2%	2.4	K 18.9% · BB 10.1% · FIP 4.64
2027PROJ	23	MLBSF	10	10	54	4.92	5.19	18.1%	10.3%	0.1
2028PROJ76% MLB	24	MLBSF	13	13	73	4.78	4.83	19.2%	9.7%	0.4
2029PROJ82% MLB	25	MLBSF	12	12	72	4.72	4.72	19.8%	9.3%	0.4

Last 3 seasons WAR 2.4 · Next 3 projected WAR 0.9Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2032Service0.163First FA2033

2027Pre-Arb$0.8M2028Pre-Arb$0.8M2029Pre-Arb$0.8M2030Arb-1$2M2031Arb-2$3M2032Arb-3$3M

Skills · percentileStatcast 2026

FB Velo29

K%10

xwOBA vs10

Form4.44 ERA (proj 4.92) · K 14.6% (proj 18.1%) · BB 9.7% (proj 10.3%) ▼ last 60d · 24 IP through Oct 27

Career WAR0.0 WAR median (P10 -0.5 / P90 5.1, comp-based) · star 1% · didn't stick 80%

CompsRyan Atkinson (age 23) · Andrew Quezada (age 24) · Brandon White (age 23)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 132124vR 116

ERA4.92

FIP5.19

K%18.1%

BB%10.3%

K-BB%7.8%

Proj IP81

Value2027 · WAR

Runs saved vs league avg · 81 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$9M ctrl surplus

Statcast · Contract

Statcast Percentiles

FB Velo

p2993.0

Whiff%

p1320.1%

p1014.6%

xwOBA vs

p100.360

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status Pre-Arb

MLB Debut 2026

Service 0.163 yrs.days

Team Control Through 2032

First FA Year 2033

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Pre-Arb	$0.8M	+0.1	$0.5M	+$0.0M (cut)
2028	Pre-Arb	$0.8M	+0.4	$1M	+$0.8M
2029	Pre-Arb	$0.8M	+0.4	$1M	+$0.7M
2030	Arb-1	$2M	+0.5	$2M	+$0.3M
2031	Arb-2	$3M	+0.5	$1M	+$0.0M (cut)
2032	Arb-3	$3M	+0.4	$1M	+$0.0M (cut)
Totals		$3M		$8M	+$2M

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)
2022	18	ROK MLE	DSL KC Glass	11	8	20	92	10	3	1	73%	1.8	7.4%	4.1%	3.3%	1.7%	5.49	3.94	—
2022	18	ROK RAW	DSL KC Glass	11	8	20	92	10	3	1	73%	1.8	10.9%	3.3%	7.6%	1.1%	5.49	3.20	—
2023	19	ROK MLE	ACL Royals	12	6	37	162	39	11	3	50%	3.1	16.4%	8.5%	7.9%	2.6%	4.14	4.22	—
2023	19	ROK RAW	ACL Royals	12	6	37	162	39	11	3	50%	3.1	24.1%	6.8%	17.3%	1.9%	4.14	2.94	—
2024	20	MIX MLE	2 levels	9	8	25	121	22	10	3	89%	2.7	12.3%	12.0%	0.2%	5.3%	8.76	6.52	—
2024	20	MIX MLE	2 levels	9	8	25	121	22	10	3	89%	2.7	12.3%	12.0%	0.2%	5.3%	8.76	6.52	—
2024	20	MIX RAW	2 levels	9	8	25	121	22	10	3	89%	2.7	18.2%	8.3%	9.9%	2.5%	8.76	4.11	—
2025	21	A MLE	San Jose Giants	24	22	102	403	96	29	4	92%	4.2	17.6%	8.5%	9.1%	1.0%	2.91	3.21	—
2025	21	A MLE	San Jose Giants	24	22	102	403	96	29	4	92%	4.2	17.6%	8.5%	9.1%	1.0%	2.91	3.21	—
2025	21	A RAW	San Jose Giants	24	22	102	403	96	29	4	92%	4.2	23.8%	7.2%	16.6%	1.0%	2.91	2.58	—
2026	22	MIX MLE	3 levels	27	23	132	556	128	51	16	85%	4.9	18.9%	10.1%	8.8%	3.4%	3.95	4.64	+1.2
2026	22	MIX MLE	3 levels	27	23	132	556	128	51	16	85%	4.9	18.9%	10.1%	8.8%	3.4%	3.95	4.64	+1.2
2026	22	MIX RAW	3 levels	27	23	132	556	128	51	16	85%	4.9	23.0%	9.2%	13.8%	2.9%	3.95	3.90	+2.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			5	3	24	103	15	10	5	60%	4.9	14.6%	9.7%	4.9%	4.9%	4.44	5.77	-0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	23	MLB	SF	10	10	54	228	41	23	8	100%	5.4	18.1%	10.3%	7.8%	3.5%	4.92	5.19	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	24	MLB MLE	SF	17	17	96	405	78	39	14	100%	5.6	19.2%	9.7%	9.5%	3.4%	4.92	4.97	+0.5
2029	25	MLB MLE	SF	15	15	87	369	73	34	13	100%	5.8	19.8%	9.3%	10.5%	3.4%	4.86	4.86	+0.5
2030	26	MLB MLE	SF	14	14	85	359	72	33	12	100%	6.1	20.1%	9.2%	10.9%	3.4%	4.81	4.80	+0.6
2031	27	MLB MLE	SF	14	14	82	348	70	32	12	100%	5.9	20.2%	9.3%	10.9%	3.4%	4.82	4.83	+0.5
2032	28	MLB MLE	SF	13	13	78	331	66	31	12	100%	6.0	20.0%	9.4%	10.6%	3.5%	4.88	4.91	+0.4
2033	29	MLB MLE	SF	12	12	72	304	59	29	11	100%	6.0	19.4%	9.7%	9.8%	3.7%	5.00	5.07	+0.3
2034	30	MLB MLE	SF	11	11	65	274	51	27	11	100%	5.9	18.8%	10.0%	8.8%	3.9%	5.17	5.28	+0.1
2028	24	MLB CTX	SF	13	13	73	308	59	30	10	100%	5.6	19.2%	9.7%	9.5%	3.2%	4.78	4.83	+0.4
2029	25	MLB CTX	SF	12	12	72	304	60	28	10	100%	6.0	19.8%	9.3%	10.5%	3.1%	4.72	4.72	+0.4
2030	26	MLB CTX	SF	12	12	73	308	62	28	10	100%	6.1	20.1%	9.2%	10.9%	3.1%	4.67	4.66	+0.5
2031	27	MLB CTX	SF	12	12	73	308	62	29	10	100%	6.1	20.2%	9.3%	10.9%	3.2%	4.68	4.69	+0.5
2032	28	MLB CTX	SF	12	12	71	300	60	28	10	100%	5.9	20.0%	9.4%	10.6%	3.3%	4.74	4.77	+0.4
2033	29	MLB CTX	SF	11	11	66	279	54	27	9	100%	6.0	19.4%	9.7%	9.8%	3.4%	4.85	4.92	+0.2
2034	30	MLB CTX	SF	10	10	60	253	48	25	9	100%	6.0	18.8%	10.0%	8.8%	3.6%	5.01	5.12	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		87	85	512	2163	420	206	72	98%	5.9	19.4%	9.5%	9.9%	3.3%	4.75	4.49	+5.4
/ 200 IP	—	RAW		34	33	200	845	164	80	28	98%	5.9	19.4%	9.5%	9.9%	3.3%	4.75	4.49	+2.1
Career	—	MLE		83	67	315	1334	224	122	35	81%	3.8	16.8%	9.2%	7.6%	2.6%	4.11	4.28	+2.8
/ 200 IP	—	MLE		53	42	200	846	142	78	22	81%	3.8	16.8%	9.2%	7.6%	2.6%	4.11	4.28	+1.0

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.

2026 AARichmond Flying Squirrels · 64 IPFIP 3.50 → 4.35 (+0.85)K% 26.4% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.37%	—	×0.810	21.36%
BB% (unintentional) /BF	8.06%	—	×1.100	8.86%
HR / BF /BF	2.93%	÷1.000	×1.200	3.52%

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 3.50 → 4.35, 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 A+Eugene Emeralds · 43 IPFIP 3.43 → 4.30 (+0.87)K% 22.8% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.78%	—	×0.770	17.54%
BB% (unintentional) /BF	10.56%	—	×1.150	12.14%
HR / BF /BF	1.67%	÷1.000	×1.250	2.08%

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 3.43 → 4.30, 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 ASan Jose Giants · 102 IPFIP 2.54 → 3.21 (+0.66)K% 23.8% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.82%	—	×0.740	17.63%
BB% (unintentional) /BF	7.20%	—	×1.180	8.49%
HR / BF /BF	0.99%	÷1.358	×1.300	0.95%

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 172).

Result: FIP 2.54 → 3.21, 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).

2024 ROKACL Royals · 16 IPFIP 4.78 → 6.52 (+1.74)K% 18.1% → 12.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.07%	—	×0.680	12.29%
BB% (unintentional) /BF	9.64%	—	×1.250	12.05%
HR / BF /BF	3.61%	÷0.949	×1.400	5.33%

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 90).

Result: FIP 4.78 → 6.52, 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 AColumbia Fireflies · 8 IPFIP 2.21 → 2.74 (+0.52)K% 18.4% → 13.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.42%	—	×0.740	13.63%
BB% (unintentional) /BF	5.26%	—	×1.180	6.21%
HR / BF /BF	0.00%	÷1.020	×1.300	0.00%

Result: FIP 2.21 → 2.74, 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 Royals · 37 IPFIP 2.94 → 4.22 (+1.27)K% 24.1% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.07%	—	×0.680	16.37%
BB% (unintentional) /BF	6.79%	—	×1.250	8.49%
HR / BF /BF	1.85%	÷1.000	×1.400	2.59%

Result: FIP 2.94 → 4.22, 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).

2022 ROKDSL KC Glass · 20 IPFIP 3.19 → 3.94 (+0.75)K% 10.9% → 7.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	10.87%	—	×0.680	7.39%
BB% (unintentional) /BF	3.26%	—	×1.250	4.08%
HR / BF /BF	1.09%	÷0.879	×1.400	1.73%

Result: FIP 3.19 → 3.94, 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).

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
Yunior Marte (OGILVIE)	—	—	—	—	—	3.5%	—	4.88	19.7%	10.3%	268	-0.31	—	—	—
Ryan Atkinson R 2016 · 4.58 FIP	23	SP-	4.58	18.4%	11.3%	2.9%	.315	4.48	21.6%	9.0%	305	-0.10	4.14	338	90
Andrew Quezada R 2021 · 4.40 FIP	24	SP-	4.40	18.1%	8.1%	3.3%	.312	4.86	14.6%	6.1%	291	+0.46	4.40	412	87
Brandon White R 2023 · 4.93 FIP	23	SP	4.93	16.7%	10.3%	3.5%	.264	4.05	17.5%	10.6%	280	-0.88	3.90	299	85
Allen Webster R 2013 · 6.05 FIP	23	SP	6.05	15.9%	12.4%	5.0%	.309	4.66	14.0%	4.3%	167	-1.39	3.95	267	83
Noah Denoyer R 2021 · 4.51 FIP	23	SP-	4.51	21.5%	12.1%	3.1%	.275	4.10	25.7%	15.7%	121	-0.41	3.26	181	83
Jordan Geber R 2022 · 5.03 FIP	23	SP-	5.03	15.3%	10.7%	3.4%	.341	4.39	15.5%	7.8%	176	-0.64	4.26	241	82
Jason Grilli R 2001 · 5.93 FIP	24	SP	5.93	14.8%	9.6%	5.2%	.296	6.24	12.8%	2.9%	45	+0.31	2.00	678	82
Cha Seung Baek R 2004 · 4.77 FIP	24	SP-	4.77	14.4%	7.2%	3.6%	.288	3.95	15.7%	10.0%	108	-0.82	3.35	280	81
Tanner Hall R 2024 · 4.67 FIP	22	SP-	4.67	18.8%	11.2%	3.2%	.295	5.33	10.1%	-4.6%	72	+0.66	4.67	137	81
Cole Wiper R 2015 · 5.41 FIP	23	SP	5.41	14.6%	10.5%	4.0%	.343	4.52	15.6%	5.2%	136	-0.89	3.97	170	81
Nick Fraze R 2021 · 4.49 FIP	23	SP-	4.49	18.8%	7.3%	3.8%	.271	4.69	18.1%	10.4%	162	+0.20	3.86	278	81
Cody Laweryson R 2021 · 4.06 FIP	23	SP	4.06	21.7%	8.4%	3.1%	.329	3.48	21.4%	12.8%	178	-0.58	2.48	298	79
Sergio Mitre R 2004 · 4.16 FIP	23	SP-	4.16	15.2%	7.8%	2.5%	.357	4.16	13.2%	6.5%	250	+0.00	3.55	602	79
Carlos Torres R 2009 · 5.24 FIP	26	SP-	5.24	16.9%	11.5%	3.9%	.284	3.59	18.2%	7.3%	67	-1.65	2.89	604	79
Tim Redding R 2001 · 4.88 FIP	23	SP-	4.88	22.1%	9.6%	4.4%	.321	4.34	15.1%	6.6%	350	-0.54	3.97	822	79
Rafael Montero R 2014 · 5.04 FIP	23	SP-	5.04	21.6%	11.9%	4.1%	.298	4.32	19.3%	8.2%	296	-0.72	2.43	714	79
Robbie Peto R 2021 · 5.81 FIP	23	SP	5.81	16.6%	10.7%	5.0%	.303	5.57	15.5%	-1.0%	161	-0.24	5.39	232	79
Jon Rauch R 2002 · 5.99 FIP	23	SP-	5.99	14.6%	9.2%	5.4%	.228	3.36	17.6%	10.5%	62	-2.63	2.87	595	79
Grant Judkins R 2021 · 5.77 FIP	23	SP-	5.77	21.0%	11.2%	5.5%	.346	5.61	16.4%	5.4%	150	-0.16	5.13	322	78
Levi Thomas R 2021 · 5.22 FIP	23	SP-	5.22	18.1%	11.9%	3.9%	.328	5.16	20.8%	3.3%	31	-0.06	5.16	116	78

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	3.4	75	19.3%	9.6%	1.38	4.90
Brian Matusz ('16)	2.6	76	19.8%	8.7%	1.34	4.92
Vicente Palacios ('87-'00, 1 WAR*)	1.9	62	21.0%*	10.0%*	1.41*	4.86*
Daniel Norris ('23)	2.9	73	21.5%	8.9%	1.39	4.73
Rich Folkers ('70-'77, -0 WAR*)	2.1	85	19.1%*	8.8%*	1.35*	4.91*
Jorge López ('25)	2.8	70	19.8%	8.8%	1.36	5.31
Mike Willis ('77-'81, 0 WAR*)	1.5	59	18.4%*	9.6%*	1.45*	4.77*