Leonardo Rossel

P FCL Tigers

Age 22 RHP 6'0" / 170 lbs ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	19	ROKDSL Tigers 1	18	2	28	4.82	3.71	17.5%	12.7%	—	K 11.9% · BB 15.9% · FIP 4.66
2025	20	ROKDSL Tigers 1	11	0	14	7.90	5.51	19.1%	16.2%	—	K 13.0% · BB 20.2% · FIP 5.27
2026	21	MIX2 levels	21	0	27	5.60	4.09	20.3%	13.8%	—	K 14.9% · BB 14.4% · FIP 5.43
2027PROJ	22	MLBDET	11	0	12	5.24	5.24	20.0%	14.3%	-0.1
2028PROJ49% MLB	23	MLBDET	12	0	13	4.99	4.89	21.2%	12.5%	-0.1

Next 2 projected WAR -0.1Projected 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 99%

CompsKasey Ford (age 23) · Ismael Cabrera (age 22) · Easton Sikorski (age 23)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 133125vR 116

ERA5.24

FIP5.24

K%20.0%

BB%14.3%

K-BB%5.7%

Proj IP12

Value2027 · WAR

Runs saved vs league avg · 12 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)
2023	18	ROK MLE	DSL Tigers 1	12	1	14	65	18	7	2	8%	1.2	18.8%	13.5%	5.4%	5.0%	4.40	5.96	—
2023	18	ROK RAW	DSL Tigers 1	12	1	14	65	18	7	2	8%	1.2	27.7%	10.8%	16.9%	3.1%	4.40	3.87	—
2024	19	ROK MLE	DSL Tigers 1	18	2	28	126	22	16	1	11%	1.6	11.9%	15.9%	-4.0%	1.0%	4.82	4.66	—
2024	19	ROK MLE	DSL Tigers 1	18	2	28	126	22	16	1	11%	1.6	11.9%	15.9%	-4.0%	1.0%	4.82	4.66	—
2024	19	ROK RAW	DSL Tigers 1	18	2	28	126	22	16	1	11%	1.6	17.5%	12.7%	4.8%	0.8%	4.82	3.71	—
2025	20	ROK MLE	DSL Tigers 1	11	0	14	68	13	11	2	0%	1.2	13.0%	20.2%	-7.2%	1.3%	7.90	5.27	—
2025	20	ROK MLE	DSL Tigers 1	11	0	14	68	13	11	2	0%	1.2	13.0%	20.2%	-7.2%	1.3%	7.90	5.27	—
2025	20	ROK RAW	DSL Tigers 1	11	0	14	68	13	11	2	0%	1.2	19.1%	16.2%	2.9%	2.9%	7.90	5.51	—
2026	21	MIX MLE	2 levels	21	0	27	123	25	17	2	0%	1.3	14.9%	14.4%	0.5%	3.2%	5.60	5.43	—
2026	21	MIX MLE	2 levels	21	0	27	123	25	17	2	0%	1.3	14.9%	14.4%	0.5%	3.2%	5.60	5.43	—
2026	21	MIX RAW	2 levels	21	0	27	123	25	17	2	0%	1.3	20.3%	13.8%	6.5%	1.6%	5.60	4.09	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	22	MLB	DET	11	0	12	51	10	7	2	0%	1.1	20.0%	14.3%	5.7%	3.0%	5.24	5.24	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	23	MLB MLE	DET	24	0	26	108	23	13	3	0%	1.1	21.2%	12.5%	8.6%	2.9%	4.99	4.89	-0.1
2028	23	MLB CTX	DET	12	0	13	55	12	7	2	0%	1.1	21.2%	12.5%	8.6%	2.9%	4.99	4.89	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		12	0	13	53	11	7	2	0%	1.0	21.2%	12.5%	8.6%	2.9%	4.99	4.51	+0.0
/ 200 IP	—	RAW		190	0	200	844	175	112	32	0%	1.1	21.2%	12.5%	8.6%	2.9%	4.99	4.51	+0.1
Career	—	MLE		62	3	83	382	54	60	9	5%	1.3	14.2%	15.8%	-1.5%	2.4%	5.51	5.24	-0.1
/ 200 IP	—	MLE		149	7	200	917	130	144	22	5%	1.3	14.2%	15.8%	-1.5%	2.4%	5.51	5.24	-0.8

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
Leonardo Rossel (OGILVIE)	—	—	5.24	20.0%	14.3%	3.0%	—	4.89	21.2%	8.6%	26	-0.35	—	—	—
Kasey Ford R 2021 · 4.89 FIP	23	SU	4.89	20.3%	14.5%	3.0%	.310	4.26	21.9%	5.8%	98	-0.63	2.53	114	94
Ismael Cabrera R 2016 · 4.77 FIP	22	SU	4.77	19.5%	12.4%	3.2%	.276	5.29	16.9%	6.5%	95	+0.52	3.56	133	90
Easton Sikorski R 2023 · 4.85 FIP	23	SU	4.85	20.9%	14.1%	3.1%	.254	4.62	17.5%	6.3%	154	-0.23	4.23	183	89
Tyler Smith R 2018 · 5.30 FIP	22	SU	5.30	17.8%	14.3%	3.4%	.329	4.35	19.8%	7.8%	94	-0.95	3.44	121	89
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	89
Brandon Dufault R 2021 · 5.32 FIP	22	SU	5.32	22.1%	15.9%	3.8%	.278	4.83	21.0%	4.2%	66	-0.49	4.38	152	89
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	89
Zack Hess R 2019 · 5.00 FIP	22	SU	5.00	18.1%	13.1%	3.2%	.232	5.47	22.9%	6.3%	50	+0.47	5.00	101	88
Samuel Carpio R 2024 · 4.20 FIP	21	SU	4.20	21.2%	15.3%	1.7%	.300	5.36	21.6%	-3.4%	112	+1.16	4.20	134	88
Carson Hobbs R 2024 · 5.63 FIP	22	SU	5.63	18.9%	13.6%	4.4%	.303	3.97	22.0%	10.4%	118	-1.66	3.54	143	88
Junior Rincon R 2015 · 4.93 FIP	23	SU	4.93	17.8%	13.8%	2.9%	.318	3.75	17.6%	5.1%	82	-1.18	3.52	113	87
Jordan Mikel R 2021 · 4.49 FIP	22	SU	4.49	20.5%	12.5%	2.8%	.330	4.16	19.2%	9.0%	109	-0.33	3.04	195	87
Jason Ruffcorn R 2021 · 4.74 FIP	23	SU	4.74	16.6%	14.2%	2.3%	.297	4.69	17.6%	4.2%	136	-0.05	4.01	283	87
Hobie Harris R 2015 · 4.28 FIP	22	SU	4.28	18.1%	13.3%	1.9%	.239	3.36	21.2%	12.0%	144	-0.92	3.31	476	87
Morgan McSweeney R 2021 · 5.36 FIP	23	SU	5.36	21.9%	16.3%	3.7%	.295	5.15	18.5%	5.3%	93	-0.21	3.20	213	86
Adam Ravenelle R 2015 · 4.32 FIP	22	SU	4.32	19.6%	14.8%	1.8%	.322	5.06	17.1%	4.3%	130	+0.74	4.32	165	86
Jake Bird R 2018 · 4.59 FIP	22	SU	4.59	17.7%	13.0%	2.4%	.254	3.65	16.1%	4.9%	156	-0.94	3.06	525	86
Brandyn Sittinger R 2017 · 4.37 FIP	23	SU	4.37	22.2%	13.8%	2.5%	.324	3.97	21.2%	7.2%	72	-0.40	3.58	152	86
Sean Isaac R 2016 · 4.27 FIP	23	SU	4.27	19.5%	12.3%	2.3%	.342	3.76	25.0%	10.7%	128	-0.51	3.27	155	86
Randy Messenger R 2005 · 4.90 FIP	23	SU	4.90	16.3%	12.9%	2.8%	.281	3.93	13.8%	7.1%	137	-0.97	3.56	174	86