José De León

P Worcester Red Sox

Age 34 RHP 6'0" / 220 lbs AAA

Overview

AAASP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	29	MIX3 levels	11	6	13	4.05	3.85	33.9%	13.6%	—	K 33.9% · BB 13.6% · FIP 3.82
2023	30	MIX2 levels	21	5	45	4.03	3.48	23.0%	9.1%	0.6	K 21.0% · BB 8.4% · FIP 3.62
2025	32	MIX2 levels	23	14	82	6.70	5.44	24.9%	14.1%	-0.0	K 21.1% · BB 12.9% · FIP 5.66
2026	33	No MLB games played
2027PROJ	34	MLBBOS	2	2	13	5.37	5.38	21.1%	13.3%	0.0
2028PROJ6% MLB	35	MLBBOS	1	1	5	5.46	5.60	20.2%	13.2%	-0.0
2029PROJMLE	36	MLBBOS	—	—	0	5.66	5.86	19.3%	13.4%	—

Last 3 seasons WAR 0.5 · Next 3 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff50Control35Command45FB velo47

CompsJarrett Grube (age 34) · Tim Adleman (age 34) · Paolo Espino (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 135127vR 119

ERA5.37

FIP5.38

K%21.1%

BB%13.3%

K-BB%7.8%

Proj IP134

Value2027 · WAR

Runs saved vs league avg · 134 IP

Grades · Contract

Scouting Grades

STUF5050

CTRL3535

CMD4545

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)
2015	22	MIX MLE	2 levels	23	23	114	465	163	36	12	100%	5.0	27.9%	8.6%	19.3%	3.0%	2.99	3.50	—
2015	22	MIX RAW	2 levels	23	23	114	465	163	36	12	100%	5.0	35.1%	7.7%	27.3%	2.6%	2.99	2.56	—
2016	23	MIX MLE	2 levels	20	20	103	422	126	26	14	100%	5.2	26.7%	6.4%	20.3%	3.6%	3.22	3.64	+2.2
2016	23	MIX RAW	2 levels	20	20	103	422	126	26	14	100%	5.2	29.9%	6.2%	23.7%	3.3%	3.22	3.18	+2.8
2017	24	MIX MLE	4 levels	11	8	41	170	46	19	3	73%	3.7	23.0%	14.6%	8.4%	0.9%	3.51	3.52	+0.9
2017	24	MIX RAW	4 levels	11	8	41	170	46	19	3	73%	3.7	27.1%	11.2%	15.9%	1.8%	3.51	3.20	+1.1
2019	26	MIX MLE	3 levels	22	15	60	262	81	32	5	68%	2.7	28.9%	12.8%	16.2%	1.8%	3.45	3.24	+1.6
2019	26	MIX RAW	3 levels	22	15	60	262	81	32	5	68%	2.7	30.9%	12.2%	18.7%	1.9%	3.45	3.08	+1.7
2020	27	MLB MLE	Cincinnati Reds	5	0	6	35	10	9	1	0%	1.2	28.6%	25.7%	2.9%	2.9%	18.00	5.51	-0.1
2020	27	MLB RAW	Cincinnati Reds	5	0	6	35	10	9	1	0%	1.2	28.6%	25.7%	2.9%	2.9%	18.00	6.43	-0.1
2021	28	MIX MLE	3 levels	23	2	32	151	56	18	6	9%	1.4	35.0%	12.9%	22.1%	3.3%	7.03	3.60	+0.4
2021	28	MIX RAW	3 levels	23	2	32	151	56	18	6	9%	1.4	37.1%	11.9%	25.2%	4.0%	7.03	3.73	+0.3
2022	29	MIX MLE	3 levels	11	6	13	59	20	8	2	55%	1.2	33.9%	13.6%	20.3%	3.4%	4.05	3.82	—
2022	29	MIX RAW	3 levels	11	6	13	59	20	8	2	55%	1.2	33.9%	13.6%	20.3%	3.4%	4.05	3.85	—
2023	30	MIX MLE	2 levels	21	5	45	187	43	17	4	24%	2.1	21.0%	8.4%	12.6%	2.2%	4.03	3.62	+0.5
2023	30	MIX RAW	2 levels	21	5	45	187	43	17	4	24%	2.1	23.0%	9.1%	13.9%	2.1%	4.03	3.48	+0.6
2025	32	MIX MLE	2 levels	23	14	82	390	97	55	17	61%	3.6	21.1%	12.9%	8.2%	4.9%	6.70	5.66	-0.2
2025	32	MIX MLE	2 levels	23	14	82	390	97	55	17	61%	3.6	21.1%	12.9%	8.2%	4.9%	6.70	5.66	-0.2
2025	32	MIX RAW	2 levels	23	14	82	390	97	55	17	61%	3.6	24.9%	14.1%	10.8%	4.4%	6.70	5.44	-0.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			35	8	72	340	92	39	14	23%	2.1	27.1%	11.5%	15.6%	4.1%	7.12	4.70	-0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	BOS	2	2	13	55	12	7	2	100%	6.5	21.1%	13.3%	7.8%	3.6%	5.37	5.38	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	BOS	15	15	90	381	77	51	15	100%	6.0	20.2%	13.2%	7.0%	3.9%	5.46	5.60	-0.2
2029	36	MLB MLE	BOS	11	11	67	283	55	38	12	100%	6.1	19.3%	13.4%	5.9%	4.2%	5.66	5.86	-0.3
2028	35	MLB CTX	BOS	1	1	5	21	4	3	1	100%	5.0	20.2%	13.2%	7.0%	3.9%	5.46	5.60	-0.0
2029	36	MLB CTX	BOS	—	—	0	—	—	—	—	—	—	19.3%	13.4%	5.9%	4.2%	5.66	5.86	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		36	9	77	361	96	42	15	25%	2.1	26.7%	11.6%	15.1%	4.1%	7.02	4.57	-0.0
/ 200 IP	—	RAW		93	23	200	938	249	109	39	25%	2.1	26.7%	11.6%	15.1%	4.1%	7.02	4.57	-0.0
Career	—	MLE		159	93	497	2141	562	228	67	58%	3.1	26.2%	10.7%	15.6%	3.1%	4.31	3.95	+0.0
/ 200 IP	—	MLE		64	37	200	862	226	92	27	58%	3.1	26.2%	10.7%	15.6%	3.1%	4.31	3.95	+0.0

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.

2025 AAAWorcester Red Sox · 75 IPFIP 5.27 → 5.66 (+0.39)K% 24.6% → 21.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.59%	—	×0.860	21.14%
BB% (unintentional) /BF	14.36%	—	×0.900	12.93%
HR / BF /BF	4.42%	÷0.984	×1.100	4.94%

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 97).

Result: FIP 5.27 → 5.66, 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 AAASt. Paul Saints · 27 IPFIP 3.46 → 3.68 (+0.22)K% 22.2% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.22%	—	×0.860	19.11%
BB% (unintentional) /BF	10.26%	—	×0.900	9.23%
HR / BF /BF	1.71%	÷1.009	×1.100	1.86%

Result: FIP 3.46 → 3.68, 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 AAABuffalo Bisons · 10 IPFIP 4.60 → 5.36 (+0.77)K% 31.2% → 27.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.25%	—	×0.880	27.50%
BB% (unintentional) /BF	14.58%	—	×1.050	15.31%
HR / BF /BF	4.17%	÷0.951	×1.100	4.82%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, 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 90).

Result: FIP 4.60 → 5.36, 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).

2021 AAALouisville Bats · 12 IPFIP 2.77 → 3.25 (+0.48)K% 37.3% → 32.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.25%	—	×0.880	32.78%
BB% (unintentional) /BF	13.73%	—	×1.050	14.41%
HR / BF /BF	1.96%	÷1.088	×1.100	1.98%

Result: FIP 2.77 → 3.25, 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).

2019 AAADurham Bulls · 51 IPFIP 2.85 → 3.24 (+0.39)K% 32.9% → 28.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.88%	—	×0.880	28.94%
BB% (unintentional) /BF	12.16%	—	×1.050	12.77%
HR / BF /BF	1.80%	÷1.128	×1.100	1.76%

Result: FIP 2.85 → 3.24, 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).

2017 A+Charlotte Stone Crabs · 14 IPFIP 2.47 → 3.33 (+0.87)K% 30.0% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.00%	—	×0.770	23.10%
BB% (unintentional) /BF	15.00%	—	×1.150	17.25%
HR / BF /BF	0.00%	÷0.917	×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 83).

Result: FIP 2.47 → 3.33, 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).

2017 AAADurham Bulls · 12 IPFIP 3.33 → 3.72 (+0.38)K% 25.9% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.93%	—	×0.880	22.81%
BB% (unintentional) /BF	11.11%	—	×1.050	11.67%
HR / BF /BF	1.85%	÷1.049	×1.100	1.94%

Result: FIP 3.33 → 3.72, 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).

2017 ROKGCL Rays · 12 IPFIP 2.28 → 3.68 (+1.40)K% 29.3% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.27%	—	×0.680	19.90%
BB% (unintentional) /BF	2.44%	—	×1.250	3.05%
HR / BF /BF	2.44%	÷1.000	×1.400	3.41%

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 2.28 → 3.68, 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
José De León (OGILVIE)	—	—	5.38	21.1%	13.3%	3.6%	—	5.71	19.8%	6.5%	157	+0.33	—	—	—
Jarrett Grube R 2016 · 4.74 FIP	34	SP-	4.74	18.9%	7.2%	4.2%	.280	4.41	15.8%	7.7%	134	-0.33	3.75	393	62
Tim Adleman R 2022 · 5.69 FIP	34	SP-	5.69	17.5%	8.6%	5.4%	.275	—	—	—	—	—	3.63	605	57
Paolo Espino R 2021 · 4.32 FIP	34	SP-	4.32	20.2%	5.1%	4.2%	.277	4.81	16.6%	10.9%	260	+0.49	3.42	933	55
Guillermo Moscoso R 2018 · 5.07 FIP	34	SP-	5.07	18.2%	8.4%	4.5%	.318	4.35	12.6%	5.9%	104	-0.72	3.56	486	54
Zach Neal R 2023 · 5.98 FIP	34	SW	5.98	15.6%	6.0%	6.3%	.291	—	—	—	—	—	4.24	732	53
Juan Omar Espinoza R 2016 · 4.84 FIP	32	SP-	4.84	8.4%	9.2%	2.4%	.348	—	—	—	—	—	4.81	104	52
Chris Jakubauskas R 2011 · 4.42 FIP	32	SW	4.42	15.7%	7.9%	3.0%	.339	—	—	—	—	—	4.42	165	51
Ivan Maldonado R 2015 · 4.60 FIP	35	SW	4.60	12.8%	8.7%	2.7%	.269	5.41	6.4%	-3.3%	104	+0.81	4.60	172	51
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	49
Marco Antonio Duarte R 2019 · 5.03 FIP	32	SW	5.03	12.2%	9.1%	3.3%	.420	—	—	—	—	—	4.07	203	49
David Buchanan R 2024 · 4.26 FIP	35	SP-	4.26	14.7%	6.5%	2.9%	.337	5.56	12.2%	4.1%	29	+1.30	3.88	560	48
Sergio Valenzuela R 2017 · 5.66 FIP	32	SP	5.66	10.6%	6.5%	4.8%	.355	—	—	—	—	—	3.66	244	48
Daniel Guerrero R 2019 · 5.59 FIP	34	SW	5.59	14.7%	11.1%	4.2%	.353	—	—	—	—	—	4.61	269	47
Rudy Gonzalez R 2015 · 4.52 FIP	34	SW	4.52	13.5%	9.6%	2.4%	.347	3.84	14.0%	6.5%	79	-0.68	3.31	119	45
Leo Medrano R 2016 · 4.34 FIP	33	SP	4.34	11.0%	7.3%	2.3%	.312	—	—	—	—	—	3.76	222	45
Pete Walker R 2003 · 5.73 FIP	34	SW	5.73	12.0%	9.1%	4.5%	.267	4.70	14.0%	5.1%	114	-1.03	4.45	327	45
Manuel Flores R 2019 · 4.32 FIP	33	SP	4.32	17.1%	7.4%	3.1%	.291	—	—	—	—	—	3.46	515	45
Rolando Valdez R 2019 · 5.36 FIP	33	SP-	5.36	11.7%	7.6%	4.2%	.360	—	—	—	—	—	3.06	258	44
Matt Buschmann R 2016 · 4.84 FIP	32	SP	4.84	12.8%	8.4%	3.2%	.325	—	—	—	—	—	4.03	277	41
Michael Nix R 2016 · 4.60 FIP	33	SP	4.60	11.9%	11.6%	1.9%	.322	—	—	—	—	—	3.82	234	40

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	1.8	121	21.8%	13.2%	1.51	5.79
Lowell Palmer ('69-'74, -4 WAR*)	1.6	79	21.9%*	13.3%*	1.59*	6.09*
Jim Duckworth ('63-'66, -4 WAR*)	1.3	67	23.1%*	12.4%*	1.43*	6.15*
Darrel Akerfelds ('86-'91, -3 WAR*)	1.2	78	15.8%*	11.9%*	1.61*	5.40*
Wayne Franklin ('06)	1.6	81	14.8%	11.5%	1.59	5.54
Sean Douglass ('05)	1.0	52	16.6%	12.1%	1.47	6.11
Seth McClung ('09)	2.2	86	16.2%	13.1%	1.28	5.46