Erick Leal

P Scranton/Wilkes-Barre RailRiders

Age 32 RHP 6'3" / 180 lbs AAA peak 0.4 · 2027

Overview

AAAPROSPECT

MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2018	23	A+CHC	21	8	64	1.41	2.39	25.0%	7.0%	—	K 19.2% · BB 8.0% · FIP 3.09
2019	24	MIX2 levels	17	16	85	5.21	3.55	23.1%	9.5%	—	K 18.3% · BB 10.7% · FIP 4.24
2025	30	AAAScranton/Wilk…	28	26	127	5.61	5.25	23.9%	10.4%	—	K 20.5% · BB 9.4% · FIP 5.39
2027PROJ	32	MLBNYY	25	25	149	5.02	5.02	20.7%	9.6%	-0.2
2028PROJ37% MLB	33	MLBNYY	8	8	50	5.09	5.19	20.3%	9.9%	-0.2
2029PROJ32% MLB	34	MLBNYY	7	7	40	5.25	5.40	19.9%	10.2%	-0.2

Next 3 projected WAR -0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff50Control45Command50

CompsKenshin Kawakami (age 34) · Nate Long (age 29) · Juan Delgadillo (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 129120vR 112

ERA5.02

FIP5.02

K%20.7%

BB%9.6%

K-BB%11.1%

Proj IP149

Value2027 · WAR

Runs saved vs league avg · 149 IP

Grades · Contract

Scouting Grades

STUF5050

CTRL4545

CMD5050

K†5050

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)
2015	20	A MLE	South Bend Cubs	23	23	129	551	86	32	11	100%	5.6	11.5%	6.9%	4.7%	2.4%	3.85	4.33	—
2015	20	A RAW	South Bend Cubs	23	23	129	551	86	32	11	100%	5.6	15.6%	5.8%	9.8%	2.0%	3.85	3.62	—
2016	21	MIX MLE	2 levels	21	19	98	404	71	23	5	90%	4.7	12.9%	6.4%	6.5%	1.2%	3.13	3.49	—
2016	21	MIX RAW	2 levels	21	19	98	404	71	23	5	90%	4.7	17.6%	5.7%	11.9%	1.2%	3.13	3.02	—
2018	23	A+ MLE	Myrtle Beach Pelicans	21	8	64	244	61	17	2	38%	3.0	19.2%	8.0%	11.2%	1.1%	1.41	3.09	—
2018	23	A+ RAW	Myrtle Beach Pelicans	21	8	64	244	61	17	2	38%	3.0	25.0%	7.0%	18.0%	0.8%	1.41	2.39	—
2019	24	MIX MLE	2 levels	17	16	85	377	87	36	8	94%	5.0	18.3%	10.7%	7.7%	2.4%	5.21	4.24	—
2019	24	MIX RAW	2 levels	17	16	85	377	87	36	8	94%	5.0	23.1%	9.5%	13.5%	2.1%	5.21	3.55	—
2025	30	AAA MLE	Scranton/Wilkes-Barre RailRiders	28	26	127	557	133	58	28	93%	4.5	20.5%	9.4%	11.2%	5.2%	5.61	5.39	—
2025	30	AAA MLE	Scranton/Wilkes-Barre RailRiders	28	26	127	557	133	58	28	93%	4.5	20.5%	9.4%	11.2%	5.2%	5.61	5.39	—
2025	30	AAA RAW	Scranton/Wilkes-Barre RailRiders	28	26	127	557	133	58	28	93%	4.5	23.9%	10.4%	13.5%	5.0%	5.61	5.25	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	NYY	25	25	149	629	130	60	24	100%	6.0	20.7%	9.6%	11.1%	3.8%	5.02	5.02	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	NYY	23	23	136	576	117	57	23	100%	5.9	20.3%	9.9%	10.5%	4.0%	5.09	5.19	-0.4
2029	34	MLB MLE	NYY	21	21	124	524	104	53	22	100%	5.9	19.9%	10.2%	9.7%	4.2%	5.25	5.40	-0.7
2028	33	MLB CTX	NYY	8	8	50	211	43	21	8	100%	6.2	20.3%	9.9%	10.5%	4.0%	5.09	5.19	-0.2
2029	34	MLB CTX	NYY	7	7	40	169	34	17	7	100%	5.7	19.9%	10.2%	9.7%	4.2%	5.25	5.40	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		15	15	90	381	77	38	16	100%	6.0	20.1%	10.0%	10.1%	4.1%	5.16	4.90	-0.0
/ 200 IP	—	RAW		33	33	200	844	171	84	35	100%	6.0	20.1%	10.0%	10.1%	4.1%	5.16	4.90	-0.0
Career	—	MLE		110	92	501	2133	346	176	59	84%	4.6	16.2%	8.2%	8.0%	2.8%	4.08	4.29	-1.1
/ 200 IP	—	MLE		44	37	200	851	138	70	24	84%	4.6	16.2%	8.2%	8.0%	2.8%	4.08	4.29	-0.9

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
Erick Leal (OGILVIE)	—	—	5.02	20.7%	9.6%	3.8%	—	5.29	20.1%	10.1%	260	+0.27	—	—	—
Kenshin Kawakami R 2009 · 3.97 FIP	34	SP-	3.97	15.7%	7.6%	2.2%	.277	4.06	15.1%	9.5%	87	+0.09	3.97	244	80
Nate Long R 2015 · 4.67 FIP	29	SP	4.67	14.8%	10.6%	2.7%	.285	—	—	—	—	—	4.67	151	74
Juan Delgadillo R 2015 · 4.54 FIP	32	SP	4.54	15.5%	7.2%	3.3%	.316	4.47	10.9%	4.7%	39	-0.07	4.47	143	73
Patrick Johnson R 2019 · 4.14 FIP	30	SP	4.14	15.7%	9.3%	2.2%	.344	—	—	—	—	—	3.82	248	70
Cory Riordan R 2016 · 4.24 FIP	30	SP	4.24	14.3%	5.0%	3.1%	.341	—	—	—	—	—	4.24	154	70
Shawn Haviland R 2017 · 5.00 FIP	31	SP-	5.00	16.3%	8.1%	4.1%	.261	—	—	—	—	—	3.69	283	69
Jose Contreras R 2004 · 5.06 FIP	32	SP	5.06	19.8%	10.9%	4.1%	.273	4.06	15.8%	8.6%	590	-1.00	2.43	1,279	68
Matt Buschmann R 2016 · 4.84 FIP	32	SP	4.84	12.8%	8.4%	3.2%	.325	—	—	—	—	—	4.03	277	68
Nestor Molina R 2019 · 4.27 FIP	30	SP	4.27	16.1%	7.4%	2.9%	.325	—	—	—	—	—	3.01	401	67
Logan Verrett R 2022 · 3.84 FIP	32	SP	3.84	17.5%	5.5%	2.8%	.261	—	—	—	—	—	3.81	550	66
Cody Mincey R 2022 · 5.56 FIP	30	SP	5.56	13.9%	8.4%	4.7%	.297	—	—	—	—	—	2.49	147	66
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	63
Tim Adleman R 2019 · 4.30 FIP	31	SP	4.30	22.8%	7.8%	3.9%	.266	4.71	18.5%	11.1%	90	+0.41	3.63	605	63
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	62
Hector Noesí R 2019 · 5.11 FIP	32	SP-	5.11	22.3%	7.2%	5.4%	.271	—	—	—	—	—	3.73	613	62
Michael Nix R 2015 · 3.82 FIP	32	SP	3.82	12.4%	8.9%	1.2%	.310	4.60	11.9%	0.3%	115	+0.78	3.82	234	62
Mario Gonzalez R 2017 · 4.53 FIP	30	SP	4.53	14.1%	5.0%	3.6%	.345	—	—	—	—	—	3.94	368	61
Cesar Carrillo R 2016 · 4.28 FIP	32	SP	4.28	12.8%	9.3%	2.0%	.301	5.76	11.4%	1.2%	103	+1.48	4.14	336	61
Hector Galvan R 2019 · 4.84 FIP	31	SP-	4.84	14.3%	12.2%	2.6%	.357	—	—	—	—	—	3.59	406	61
Zack Segovia R 2015 · 4.78 FIP	32	SP	4.78	15.0%	8.3%	3.4%	.314	3.33	20.2%	14.3%	39	-1.45	3.33	144	61

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,853 starter careers (497 from 1990-2025 + 1,356 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	2.0	136	20.3%	9.9%	1.54	5.11
Matt Beech ('98)	1.5	98	20.2%	10.0%	1.59	5.37
Bill Grahame ('08-'10, 0 WAR*)	1.7	116	17.7%*	9.3%*	1.52*	5.11*
Kevin Foster ('01)	2.5	127	18.9%	10.0%	1.55	4.86
Wayland Dean ('24-'27, -1 WAR*)	2.4	162	18.6%*	10.1%*	1.45*	5.13*
Jack Armstrong ('88-'94, 2 WAR*)	3.9	131	19.2%*	9.2%*	1.59*	4.89*
Brandon Claussen ('06)	1.6	105	16.0%	8.5%	1.37	5.04