Bernard Jose

P San Antonio Missions

Age 24 RHP 5'11" / 160 lbs AA

Overview

AAPROSPECT

ETA2028MLB%2%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	21	MIX2 levels	30	47	4.82	4.71	20.8%	15.4%	—	K 14.4% · BB 19.0% · FIP 6.14
2025	22	ASD	40	66	3.95	3.27	25.7%	11.0%	—	K 19.0% · BB 12.9% · FIP 4.44
2026	23	MIX3 levels	42	68	5.72	4.40	24.0%	10.1%	—	K 18.0% · BB 11.4% · FIP 5.44
2027PROJ	24	MLBSD	1	1	5.71	5.71	16.1%	13.8%	-0.0
2028PROJ44% MLB	25	MLBSD	20	21	5.48	5.42	17.4%	12.6%	-0.2
2029PROJ67% MLB	26	MLBSD	28	29	5.34	5.31	18.1%	12.3%	-0.2

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

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control35Command40

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsBrett Lockwood (age 24) · David Trexler (age 24) · Josh Harlow (age 23)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 142133vR 125

ERA5.71

FIP5.71

K%16.1%

BB%13.8%

K-BB%2.3%

Proj IP67

Value2027 · WAR

Runs saved vs league avg · 67 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL3535

CMD4040

K†4045

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)
2023	20	ROK MLE	DSL Padres Gold	16	2	42	181	41	26	1	12%	2.6	15.4%	18.0%	-2.6%	0.7%	4.93	4.47	—
2023	20	ROK RAW	DSL Padres Gold	16	2	42	181	41	26	1	12%	2.6	22.7%	14.4%	8.3%	0.6%	4.93	3.31	—
2024	21	MIX MLE	2 levels	30	0	47	221	46	34	5	0%	1.6	14.4%	19.0%	-4.6%	3.4%	4.82	6.14	—
2024	21	MIX MLE	2 levels	30	0	47	221	46	34	5	0%	1.6	14.4%	19.0%	-4.6%	3.4%	4.82	6.14	—
2024	21	MIX RAW	2 levels	30	0	47	221	46	34	5	0%	1.6	20.8%	15.4%	5.4%	2.3%	4.82	4.71	—
2025	22	A MLE	Lake Elsinore Storm	40	0	66	292	75	32	5	0%	1.6	19.0%	12.9%	6.1%	2.4%	3.95	4.44	—
2025	22	A MLE	Lake Elsinore Storm	40	0	66	292	75	32	5	0%	1.6	19.0%	12.9%	6.1%	2.4%	3.95	4.44	—
2025	22	A RAW	Lake Elsinore Storm	40	0	66	292	75	32	5	0%	1.6	25.7%	11.0%	14.7%	1.7%	3.95	3.27	—
2026	23	MIX MLE	3 levels	42	0	68	308	74	31	11	0%	1.6	18.0%	11.4%	6.6%	4.4%	5.72	5.44	—
2026	23	MIX MLE	3 levels	42	0	68	308	74	31	11	0%	1.6	18.0%	11.4%	6.6%	4.4%	5.72	5.44	—
2026	23	MIX RAW	3 levels	42	0	68	308	74	31	11	0%	1.6	24.0%	10.1%	14.0%	3.6%	5.72	4.40	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	24	MLB	SD	1	0	1	4	1	1	0	0%	1.0	16.1%	13.8%	2.3%	3.3%	5.71	5.71	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	25	MLB MLE	SD	47	0	49	206	36	26	7	0%	1.0	17.4%	12.6%	4.8%	3.3%	5.48	5.42	-0.5
2029	26	MLB MLE	SD	41	0	43	181	33	22	6	0%	1.0	18.1%	12.3%	5.8%	3.3%	5.34	5.31	-0.4
2030	27	MLB MLE	SD	38	0	40	169	31	21	6	0%	1.1	18.3%	12.2%	6.1%	3.3%	5.29	5.30	-0.3
2031	28	MLB MLE	SD	36	0	38	159	29	20	5	0%	1.0	18.3%	12.3%	6.0%	3.4%	5.32	5.36	-0.3
2028	25	MLB CTX	SD	20	0	21	89	15	11	3	0%	1.1	17.4%	12.6%	4.8%	3.3%	5.48	5.42	-0.2
2029	26	MLB CTX	SD	28	0	29	122	22	15	4	0%	1.0	18.1%	12.3%	5.8%	3.3%	5.34	5.31	-0.2
2030	27	MLB CTX	SD	30	0	31	131	24	16	4	0%	1.0	18.3%	12.2%	6.1%	3.3%	5.29	5.30	-0.3
2031	28	MLB CTX	SD	30	0	32	135	25	17	5	0%	1.1	18.3%	12.3%	6.0%	3.4%	5.32	5.36	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		108	0	113	477	86	59	16	0%	1.0	18.1%	12.3%	5.7%	3.3%	5.35	4.96	-0.5
/ 200 IP	—	RAW		190	0	200	844	152	105	28	0%	1.1	18.1%	12.3%	5.7%	3.3%	5.35	4.96	-1.0
Career	—	MLE		128	2	222	1002	171	147	29	2%	1.7	17.1%	14.7%	2.3%	2.9%	4.86	5.12	-1.6
/ 200 IP	—	MLE		115	2	200	901	154	133	26	2%	1.7	17.1%	14.7%	2.3%	2.9%	4.86	5.12	-1.9

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 AASan Antonio Missions · 29 IPFIP 4.44 → 5.23 (+0.78)K% 19.7% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.70%	—	×0.810	15.95%
BB% (unintentional) /BF	10.61%	—	×1.100	11.67%
HR / BF /BF	3.03%	÷1.000	×1.200	3.64%

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 100).

Result: FIP 4.44 → 5.23, 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).

2026 A+Fort Wayne TinCaps · 22 IPFIP 6.74 → 8.26 (+1.52)K% 19.3% → 14.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.27%	—	×0.770	14.83%
BB% (unintentional) /BF	13.76%	—	×1.150	15.83%
HR / BF /BF	6.42%	÷1.000	×1.250	8.03%

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 100).

Result: FIP 6.74 → 8.26, 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).

2026 ROKACL Padres · 16 IPFIP 0.08 → 1.26 (+1.18)K% 40.3% → 27.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.30%	—	×0.680	27.40%
BB% (unintentional) /BF	2.99%	—	×1.250	3.73%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 0.08 → 1.26, 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 ALake Elsinore Storm · 66 IPFIP 3.26 → 4.44 (+1.18)K% 25.7% → 19.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.68%	—	×0.740	19.01%
BB% (unintentional) /BF	10.96%	—	×1.180	12.93%
HR / BF /BF	1.71%	÷0.936	×1.300	2.38%

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 87).

Result: FIP 3.26 → 4.44, 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 ROKACL Padres · 31 IPFIP 4.51 → 6.43 (+1.92)K% 25.0% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.680	17.00%
BB% (unintentional) /BF	18.75%	—	×1.250	23.44%
HR / BF /BF	2.08%	÷0.892	×1.400	3.27%

Result: FIP 4.51 → 6.43, 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 ALake Elsinore Storm · 16 IPFIP 4.58 → 5.59 (+1.01)K% 13.0% → 9.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.99%	—	×0.740	9.61%
BB% (unintentional) /BF	9.09%	—	×1.180	10.73%
HR / BF /BF	2.60%	÷0.953	×1.300	3.54%

Result: FIP 4.58 → 5.59, 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 ROKDSL Padres Gold · 42 IPFIP 3.31 → 4.47 (+1.16)K% 22.7% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.65%	—	×0.680	15.40%
BB% (unintentional) /BF	14.36%	—	×1.250	17.96%
HR / BF /BF	0.55%	÷1.083	×1.400	0.71%

Result: FIP 3.31 → 4.47, 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
Bernard Jose (OGILVIE)	—	—	5.71	16.1%	13.8%	3.3%	—	5.35	17.9%	5.5%	132	-0.36	—	—	—
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	92
David Trexler R 2015 · 4.62 FIP	24	SU	4.62	17.7%	13.4%	2.4%	.313	4.44	18.3%	4.8%	31	-0.18	4.44	100	90
Josh Harlow R 2024 · 5.17 FIP	23	SU	5.17	18.5%	13.5%	3.5%	.266	5.73	17.1%	-4.2%	51	+0.56	5.17	107	89
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	89
Juan Paniagua R 2015 · 4.69 FIP	25	SU	4.69	15.7%	11.9%	2.6%	.262	4.63	16.2%	1.8%	93	-0.06	4.57	151	89
Jake Johansen R 2015 · 5.34 FIP	24	SU	5.34	15.8%	12.8%	3.6%	.351	4.14	13.6%	3.0%	114	-1.20	3.65	162	88
Cole Hillier R 2024 · 4.64 FIP	23	SU	4.64	16.9%	14.7%	2.0%	.297	4.45	18.1%	4.5%	111	-0.19	3.80	169	88
Taylor Grover R 2015 · 5.03 FIP	24	SU	5.03	15.1%	12.9%	2.9%	.229	4.30	18.7%	9.1%	150	-0.73	3.68	239	88
Hayden Snelsire R 2024 · 5.10 FIP	23	SU	5.10	18.9%	13.8%	3.4%	.272	4.28	20.0%	13.7%	135	-0.82	3.83	178	87
Will Geerdes R 2024 · 5.57 FIP	24	SU	5.57	16.3%	12.2%	4.2%	.284	—	—	—	—	—	3.51	121	86
Jack Carey R 2024 · 5.32 FIP	24	SU	5.32	15.6%	11.3%	3.8%	.305	4.27	19.6%	5.3%	88	-1.05	3.79	250	86
Jonathan Teaney R 2019 · 5.65 FIP	23	SU	5.65	16.4%	15.7%	3.5%	.301	—	—	—	—	—	4.77	108	86
Tanner Duncan R 2019 · 5.37 FIP	24	SU	5.37	17.5%	14.8%	3.4%	.301	—	—	—	—	—	3.28	123	86
Conner O'Neil R 2019 · 5.78 FIP	24	SU	5.78	12.8%	13.6%	3.7%	.340	6.92	16.4%	4.1%	26	+1.14	2.89	115	86
Michael Mertz R 2018 · 5.18 FIP	24	SU	5.18	16.1%	13.9%	3.0%	.282	—	—	—	—	—	3.48	133	85
Reece Karalus R 2018 · 4.73 FIP	24	SU	4.73	15.4%	11.9%	2.6%	.299	—	—	—	—	—	4.73	149	85
Marc Brakeman R 2018 · 4.67 FIP	24	SU	4.67	18.3%	13.7%	2.5%	.294	—	—	—	—	—	3.85	156	85
Morgan McSweeney R 2022 · 5.16 FIP	24	SU	5.16	18.0%	13.9%	3.3%	.278	4.31	16.6%	6.6%	107	-0.85	3.20	213	85
Ryan Ledbetter R 2016 · 4.76 FIP	24	SU	4.76	18.5%	12.3%	3.0%	.338	—	—	—	—	—	4.76	124	85
Everhett Hazelwood R 2023 · 5.70 FIP	24	SU	5.70	19.0%	15.4%	4.1%	.343	9.36	17.5%	0.6%	14	+3.66	5.23	117	85

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	1.2	47	17.4%	12.8%	1.29	5.46
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Mike Mohler ('01)	2.1	60	15.0%	12.4%	0.97	4.99