Leomar Rosario

P Fayetteville Woodpeckers

Age 24 RHP 6'6" / 217 lbs A

Overview

APROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	20	ROKHOU	6	1	16	6.32	4.95	21.3%	21.3%	—	K 14.5% · BB 26.7% · FIP 6.00
2025	22	MIX2 levels	21	5	49	4.41	3.69	29.0%	17.9%	—	K 21.5% · BB 20.2% · FIP 4.95
2026	23	AHOU	40	0	48	4.50	5.10	28.0%	26.7%	—	K 20.7% · BB 31.5% · FIP 6.25
2027PROJ	24	MLBHOU	—	—	0	5.75	5.75	21.3%	20.0%	—
2028PROJ43% MLB	25	MLBHOU	17	0	18	5.46	5.37	21.9%	17.3%	-0.2
2029PROJ66% MLB	26	MLBHOU	23	0	24	5.31	5.27	22.2%	16.7%	-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

Stuff50Control20Command35

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 100%

CompsRyan Sublette (age 24) · Taylor Floyd (age 24) · Kris Hall (age 24)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 142134vR 126

ERA5.75

FIP5.75

K%21.3%

BB%20.0%

K-BB%1.3%

Proj IP57

Value2027 · WAR

Runs saved vs league avg · 57 IP

Grades · Contract

Scouting Grades

STUF5050

CTRL2020

CMD3535

K†5055

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)
2022	19	ROK MLE	DSL HOU Blue	11	5	28	128	29	27	1	45%	2.5	15.4%	26.4%	-11.0%	1.1%	6.43	5.75	—
2022	19	ROK RAW	DSL HOU Blue	11	5	28	128	29	27	1	45%	2.5	22.7%	21.1%	1.6%	0.8%	6.43	4.39	—
2023	20	ROK MLE	FCL Astros	6	1	16	75	16	16	1	17%	2.6	14.5%	26.7%	-12.2%	1.4%	6.32	6.00	—
2023	20	ROK RAW	FCL Astros	6	1	16	75	16	16	1	17%	2.6	21.3%	21.3%	0.0%	1.3%	6.32	4.95	—
2025	22	MIX MLE	2 levels	21	5	49	224	65	40	3	24%	2.3	21.5%	20.2%	1.3%	2.0%	4.41	4.95	—
2025	22	MIX MLE	2 levels	21	5	49	224	65	40	3	24%	2.3	21.5%	20.2%	1.3%	2.0%	4.41	4.95	—
2025	22	MIX RAW	2 levels	21	5	49	224	65	40	3	24%	2.3	29.0%	17.9%	11.2%	1.3%	4.41	3.69	—
2026	23	A MLE	Fayetteville Woodpeckers	40	0	48	236	66	63	3	0%	1.2	20.7%	31.5%	-10.8%	1.7%	4.50	6.25	—
2026	23	A MLE	Fayetteville Woodpeckers	40	0	48	236	66	63	3	0%	1.2	20.7%	31.5%	-10.8%	1.7%	4.50	6.25	—
2026	23	A RAW	Fayetteville Woodpeckers	40	0	48	236	66	63	3	0%	1.2	28.0%	26.7%	1.3%	1.3%	4.50	5.10	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	24	MLB	HOU	—	—	0	—	—	—	—	—	—	21.3%	20.0%	1.3%	2.8%	5.75	5.75	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	25	MLB MLE	HOU	39	0	41	175	38	30	5	0%	1.1	21.9%	17.3%	4.6%	2.8%	5.46	5.37	-0.4
2029	26	MLB MLE	HOU	34	0	36	153	34	25	4	0%	1.1	22.2%	16.7%	5.5%	2.8%	5.31	5.27	-0.3
2028	25	MLB CTX	HOU	17	0	18	76	17	13	2	0%	1.1	21.9%	17.3%	4.6%	2.8%	5.46	5.37	-0.2
2029	26	MLB CTX	HOU	23	0	24	101	22	17	3	0%	1.0	22.2%	16.7%	5.5%	2.8%	5.31	5.27	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		40	0	42	176	39	30	5	0%	1.0	22.1%	16.9%	5.1%	2.8%	5.37	4.93	-0.2
/ 200 IP	—	RAW		190	0	200	844	187	144	24	0%	1.0	22.1%	16.9%	5.1%	2.8%	5.37	4.93	-0.9
Career	—	MLE		78	11	141	663	128	173	11	14%	1.8	19.2%	26.1%	-6.9%	1.6%	5.05	5.68	-0.7
/ 200 IP	—	MLE		111	16	200	943	181	246	15	14%	1.8	19.2%	26.1%	-6.9%	1.6%	5.05	5.68	-1.8

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 AFayetteville Woodpeckers · 48 IPFIP 4.82 → 6.25 (+1.43)K% 28.0% → 20.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.97%	—	×0.740	20.69%
BB% (unintentional) /BF	26.69%	—	×1.180	31.50%
HR / BF /BF	1.27%	÷1.000	×1.300	1.65%

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 100).

Result: FIP 4.82 → 6.25, 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 AFayetteville Woodpeckers · 42 IPFIP 3.67 → 4.95 (+1.28)K% 29.0% → 21.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.02%	—	×0.740	21.47%
BB% (unintentional) /BF	17.10%	—	×1.180	20.18%
HR / BF /BF	1.55%	÷1.005	×1.300	2.01%

Result: FIP 3.67 → 4.95, 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 ROKFCL Astros · 7 IPFIP 3.51 → 5.01 (+1.50)K% 29.0% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.03%	—	×0.680	19.74%
BB% (unintentional) /BF	22.58%	—	×1.250	28.23%
HR / BF /BF	0.00%	÷1.023	×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 105).

Result: FIP 3.51 → 5.01, 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 ROKFCL Astros · 16 IPFIP 4.73 → 6.00 (+1.26)K% 21.3% → 14.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.33%	—	×0.680	14.51%
BB% (unintentional) /BF	21.33%	—	×1.250	26.67%
HR / BF /BF	1.33%	÷1.379	×1.400	1.35%

Result: FIP 4.73 → 6.00, 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 HOU Blue · 28 IPFIP 4.29 → 5.75 (+1.46)K% 22.7% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.66%	—	×0.680	15.41%
BB% (unintentional) /BF	21.09%	—	×1.250	26.37%
HR / BF /BF	0.78%	÷0.989	×1.400	1.11%

Result: FIP 4.29 → 5.75, 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
Leomar Rosario (OGILVIE)	—	—	5.75	21.3%	20.0%	2.8%	—	5.32	22.0%	5.0%	78	-0.43	—	—	—
Ryan Sublette R 2023 · 5.72 FIP	24	SU	5.72	21.4%	22.3%	2.9%	.278	5.06	19.2%	3.8%	102	-0.66	3.74	203	87
Taylor Floyd R 2022 · 4.84 FIP	24	SU	4.84	19.6%	18.4%	1.9%	.305	4.30	19.8%	10.2%	184	-0.54	3.48	359	87
Kris Hall R 2015 · 4.63 FIP	24	SU	4.63	18.3%	17.8%	1.5%	.281	7.01	12.7%	-7.8%	34	+2.38	4.63	106	86
Kevin Kopps R 2022 · 4.56 FIP	25	SU	4.56	20.2%	15.1%	2.3%	.278	4.40	16.3%	4.0%	182	-0.16	3.45	237	85
Will Varmette R 2024 · 5.06 FIP	21	SU	5.06	22.8%	19.3%	2.6%	.302	5.13	16.1%	2.3%	135	+0.07	4.69	182	85
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	85
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	85
Noah Murdock R 2023 · 4.56 FIP	24	SU	4.56	19.8%	17.1%	1.8%	.314	3.13	23.1%	9.6%	148	-1.43	2.57	310	84
Jacob Morris R 2015 · 5.43 FIP	24	SU	5.43	18.0%	19.6%	2.5%	.218	4.77	18.7%	-2.4%	46	-0.66	4.77	102	84
Zane Russell R 2024 · 4.95 FIP	24	SU	4.95	22.7%	18.3%	2.6%	.314	5.36	18.2%	6.7%	71	+0.41	4.63	108	84
Caleb Simpson R 2017 · 5.37 FIP	25	SU	5.37	23.7%	17.2%	3.8%	.263	3.93	23.5%	5.1%	71	-1.44	3.57	197	83
Tommy DeJuneas R 2019 · 5.15 FIP	23	SU	5.15	20.8%	18.8%	2.6%	.324	5.65	13.7%	-3.9%	51	+0.50	3.93	178	83
Yoel Espinal R 2017 · 5.37 FIP	24	SU	5.37	21.4%	23.1%	2.1%	.255	4.24	22.9%	10.0%	99	-1.13	3.86	231	83
Brett Lockwood R 2021 · 5.46 FIP	24	SU	5.46	16.2%	15.5%	3.2%	.312	4.58	11.0%	-6.3%	79	-0.88	4.24	132	83
Hunter Parsons R 2021 · 5.38 FIP	24	SU	5.38	21.4%	15.3%	3.9%	.247	4.78	21.8%	10.2%	115	-0.60	4.73	183	83
Cody Scroggins R 2021 · 5.35 FIP	24	SU	5.35	17.4%	15.1%	3.3%	.263	4.28	18.6%	4.4%	59	-1.07	3.78	108	83
Grayson Thurman R 2023 · 4.63 FIP	24	SU	4.63	19.5%	14.1%	2.5%	.319	4.85	19.9%	10.5%	87	+0.22	4.58	132	83
Yunior Montero R 2017 · 5.21 FIP	24	SU	5.21	21.3%	17.6%	3.1%	.294	—	—	—	—	—	3.65	127	83
Sal Biasi R 2019 · 5.22 FIP	23	SU	5.22	20.1%	15.8%	3.3%	.295	7.66	15.3%	-0.2%	23	+2.44	4.68	188	83
Antonio Knowles R 2024 · 4.58 FIP	24	SU	4.58	20.9%	15.1%	2.4%	.250	3.28	20.9%	11.7%	66	-1.30	3.24	223	82

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	0.7	45	21.7%	18.3%	1.09	5.54
Brian Bruney ('12)	1.3	43	21.2%	15.8%	0.94	4.68
Doug Creek ('05)	1.4	58	22.2%	15.1%	1.52	5.32
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*
Armando Almanza ('05)	1.1	54	24.4%	14.3%	1.43	4.82
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*