Leonardo Pestana

P Scranton/Wilkes-Barre RailRiders

Age 29 RHP 6'4" / 198 lbs AAA

Overview

AAAPROSPECT

ETA2029MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	25	MIX2 levels	19	18	54	5.63	4.41	28.8%	11.1%	—	K 21.5% · BB 13.1% · FIP 5.67
2024	26	MIX2 levels	27	0	32	2.78	2.54	33.9%	11.0%	—	K 24.4% · BB 10.6% · FIP 3.77
2025	27	AAAScranton/Wilk…	33	1	43	6.49	6.22	24.6%	17.1%	—	K 21.2% · BB 15.4% · FIP 6.10
2026	28	No MLB games played
2027PROJ	29	MLBNYY	6	0	6	5.45	5.45	21.7%	15.6%	-0.1
2028PROJ37% MLB	30	MLBNYY	14	0	15	5.45	5.52	21.5%	15.2%	-0.2
2029PROJ55% MLB	31	MLBNYY	18	0	19	5.52	5.63	21.3%	15.1%	-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

Stuff50Control25Command40

CompsGregory Infante (age 29) · Jim Miller (age 30) · Wirfin Obispo (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 137129vR 120

ERA5.45

FIP5.45

K%21.7%

BB%15.6%

K-BB%6.2%

Proj IP58

Value2027 · WAR

Runs saved vs league avg · 58 IP

Grades · Contract

Scouting Grades

STUF5050

CTRL2525

CMD4040

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 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)
2018	20	ROK MLE	GCL Yankees West	11	8	35	176	53	20	1	73%	3.2	20.5%	14.2%	6.3%	0.8%	7.20	3.61	—
2018	20	ROK RAW	GCL Yankees West	11	8	35	176	53	20	1	73%	3.2	30.1%	11.4%	18.8%	0.6%	7.20	2.16	—
2021	23	ROK MLE	FCL Yankees	2	0	5	17	8	1	1	0%	2.3	47.1%	5.9%	41.2%	5.9%	5.79	3.10	—
2021	23	ROK RAW	FCL Yankees	2	0	5	17	8	1	1	0%	2.3	47.1%	5.9%	41.2%	5.9%	5.79	3.10	—
2022	24	ROK MLE	FCL Yankees	1	1	0	2	0	1	0	100%	—	0.0%	50.0%	-50.0%	0.0%	—	9.43	—
2022	24	ROK RAW	FCL Yankees	1	1	0	2	0	1	0	100%	—	0.0%	50.0%	-50.0%	0.0%	—	—	—
2023	25	MIX MLE	2 levels	19	18	54	243	70	27	10	95%	2.9	21.5%	13.1%	8.5%	5.0%	5.63	5.67	—
2023	25	MIX RAW	2 levels	19	18	54	243	70	27	10	95%	2.9	28.8%	11.1%	17.7%	4.1%	5.63	4.41	—
2024	26	MIX MLE	2 levels	27	0	32	127	43	14	2	0%	1.2	24.4%	10.6%	13.7%	2.5%	2.78	3.77	—
2024	26	MIX MLE	2 levels	27	0	32	127	43	14	2	0%	1.2	24.4%	10.6%	13.7%	2.5%	2.78	3.77	—
2024	26	MIX RAW	2 levels	27	0	32	127	43	14	2	0%	1.2	33.9%	11.0%	22.8%	1.6%	2.78	2.54	—
2025	27	AAA MLE	Scranton/Wilkes-Barre RailRiders	33	1	43	199	49	34	10	3%	1.3	21.2%	15.4%	5.8%	5.2%	6.49	6.10	—
2025	27	AAA MLE	Scranton/Wilkes-Barre RailRiders	33	1	43	199	49	34	10	3%	1.3	21.2%	15.4%	5.8%	5.2%	6.49	6.10	—
2025	27	AAA RAW	Scranton/Wilkes-Barre RailRiders	33	1	43	199	49	34	10	3%	1.3	24.6%	17.1%	7.5%	5.0%	6.49	6.22	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	NYY	6	0	6	25	6	4	1	0%	1.0	21.7%	15.6%	6.2%	3.3%	5.45	5.45	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	NYY	40	0	42	177	38	27	6	0%	1.0	21.5%	15.2%	6.3%	3.5%	5.45	5.52	-0.4
2029	31	MLB MLE	NYY	32	0	34	143	30	22	5	0%	1.1	21.3%	15.1%	6.2%	3.7%	5.52	5.63	-0.4
2028	30	MLB CTX	NYY	14	0	15	63	14	10	2	0%	1.1	21.5%	15.2%	6.3%	3.5%	5.45	5.52	-0.2
2029	31	MLB CTX	NYY	18	0	19	80	17	12	3	0%	1.1	21.3%	15.1%	6.2%	3.7%	5.52	5.63	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		32	0	34	144	31	22	5	0%	1.1	21.4%	15.2%	6.2%	3.6%	5.49	5.20	-0.3
/ 200 IP	—	RAW		190	0	200	844	182	129	29	0%	1.1	21.4%	15.2%	6.2%	3.6%	5.49	5.20	-1.5
Career	—	MLE		92	27	169	762	169	102	28	29%	1.8	22.2%	13.4%	8.9%	3.7%	5.63	4.93	-0.9
/ 200 IP	—	MLE		109	32	200	900	200	120	33	29%	1.8	22.2%	13.4%	8.9%	3.7%	5.63	4.93	-2.4

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.

2025 AAAScranton/Wilkes-Barre RailRiders · 43 IPFIP 5.94 → 6.10 (+0.15)K% 24.6% → 21.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.62%	—	×0.860	21.18%
BB% (unintentional) /BF	17.09%	—	×0.900	15.38%
HR / BF /BF	5.03%	÷1.070	×1.100	5.17%

Factors used: pitcher AAA level factors (Triple-A 2023+ robo-zone set: walks improve on promotion) — K ×0.86, BB ×0.90, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 114).

Result: FIP 5.94 → 6.10, 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 AASomerset Patriots · 23 IPFIP 2.96 → 3.77 (+0.80)K% 30.1% → 24.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.11%	—	×0.810	24.39%
BB% (unintentional) /BF	9.68%	—	×1.100	10.65%
HR / BF /BF	2.15%	÷1.027	×1.200	2.51%

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 105).

Result: FIP 2.96 → 3.77, 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 A+Hudson Valley Renegades · 10 IPFIP 1.24 → 2.37 (+1.14)K% 44.1% → 34.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	44.12%	—	×0.770	33.97%
BB% (unintentional) /BF	14.71%	—	×1.150	16.91%
HR / BF /BF	0.00%	÷1.032	×1.250	0.00%

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 106).

Result: FIP 1.24 → 2.37, 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 ATampa Tarpons · 41 IPFIP 4.24 → 5.53 (+1.29)K% 28.1% → 20.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.12%	—	×0.740	20.81%
BB% (unintentional) /BF	11.98%	—	×1.180	14.14%
HR / BF /BF	3.65%	÷1.086	×1.300	4.37%

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 117).

Result: FIP 4.24 → 5.53, 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 A+Hudson Valley Renegades · 13 IPFIP 4.67 → 6.21 (+1.54)K% 31.4% → 24.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.37%	—	×0.770	24.16%
BB% (unintentional) /BF	7.84%	—	×1.150	9.02%
HR / BF /BF	5.88%	÷1.006	×1.250	7.31%

Result: FIP 4.67 → 6.21, 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).

2018 ROKGCL Yankees West · 35 IPFIP 2.31 → 3.61 (+1.30)K% 30.1% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.11%	—	×0.680	20.48%
BB% (unintentional) /BF	11.36%	—	×1.250	14.20%
HR / BF /BF	0.57%	÷1.000	×1.400	0.80%

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 100).

Result: FIP 2.31 → 3.61, 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
Leonardo Pestana (OGILVIE)	—	—	5.45	21.7%	15.6%	3.3%	—	5.57	21.4%	6.2%	76	+0.12	—	—	—
Gregory Infante R 2016 · 4.47 FIP	29	SU	4.47	19.0%	12.3%	2.6%	.333	3.43	22.5%	15.8%	120	-1.04	2.97	230	74
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	73
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	72
André Rienzo R 2017 · 4.40 FIP	29	SW	4.40	18.9%	15.6%	1.7%	.301	5.33	17.9%	6.1%	29	+0.93	3.53	321	72
Mike Adams R 2022 · 5.36 FIP	27	SU	5.36	17.1%	11.2%	4.2%	.326	—	—	—	—	—	3.65	109	71
Grant Black R 2023 · 5.49 FIP	29	SU	5.49	15.9%	11.3%	4.2%	.352	—	—	—	—	—	4.46	215	70
Brandon Cunniff R 2017 · 4.79 FIP	28	SU	4.79	20.1%	11.6%	3.5%	.275	6.80	13.9%	-1.9%	30	+2.01	3.89	180	70
Jared Mortensen R 2016 · 4.99 FIP	28	SU	4.99	20.9%	18.8%	2.3%	.250	—	—	—	—	—	4.42	200	69
Dan Winkler R 2019 · 4.99 FIP	29	SU	4.99	20.6%	15.2%	3.1%	.237	4.44	23.0%	8.4%	104	-0.55	2.40	231	69
Beck Wheeler R 2017 · 5.40 FIP	28	SU	5.40	15.3%	12.2%	3.7%	.347	—	—	—	—	—	3.46	173	69
Wil Browning R 2017 · 4.44 FIP	28	SU	4.44	17.9%	13.1%	2.2%	.359	—	—	—	—	—	2.14	162	69
Dustin Antolin R 2017 · 4.35 FIP	27	SW	4.35	16.2%	14.4%	1.4%	.368	—	—	—	—	—	2.95	159	69
Thad Weber R 2013 · 5.18 FIP	28	SU	5.18	16.4%	13.1%	3.3%	.244	4.52	12.2%	6.0%	308	-0.66	4.40	378	69
Fernery Ozuna R 2023 · 5.65 FIP	27	SU	5.65	19.0%	11.6%	4.9%	.275	—	—	—	—	—	3.84	157	69
Cole McDonald R 2024 · 5.01 FIP	27	SU	5.01	20.9%	12.7%	3.8%	.281	—	—	—	—	—	2.81	153	69
Chris Jefferson R 2024 · 5.65 FIP	27	SU	5.65	16.4%	13.6%	4.0%	.308	—	—	—	—	—	3.53	140	68
Nelson Gonzalez R 2019 · 6.52 FIP	29	SW	6.52	15.7%	13.1%	5.6%	.294	5.62	19.2%	8.7%	25	-0.90	3.42	258	67
Jose Pina R 2015 · 4.90 FIP	29	SW	4.90	16.9%	9.2%	3.8%	.231	3.66	13.6%	6.9%	246	-1.24	3.63	424	66
Deck McGuire R 2018 · 5.28 FIP	29	SW	5.28	18.4%	13.2%	3.8%	.262	—	—	—	—	—	3.41	622	66
Kevin Lenik R 2019 · 4.91 FIP	27	SU	4.91	21.7%	14.9%	3.2%	.205	—	—	—	—	—	3.00	107	66

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	21.6%	15.3%	1.35	5.47
Doug Creek ('05)	1.4	58	22.2%	15.1%	1.52	5.32
Armando Almanza ('05)	1.1	54	24.4%	14.3%	1.43	4.82
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*