J.B. Wendelken

P San Antonio Missions

Age 34 RHP 6'1" / 242 lbs AA peak 0.1 · 2027

Overview

AARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2021	28	MIX2 levels	50	0	49	4.25	3.92	20.6%	9.8%	0.4	K 20.1% · BB 9.8% · FIP 3.84
2022	29	MIX2 levels	49	0	53	4.08	3.29	25.0%	10.2%	0.8	K 23.2% · BB 10.4% · FIP 3.53
2025	32	MIX3 levels	16	2	23	7.33	3.19	23.8%	12.4%	—	K 20.2% · BB 15.9% · FIP 4.32
2026	33	No MLB games played
2027PROJ	34	MLBSD	1	0	1	4.50	4.50	23.0%	10.6%	0.0
2028PROJMLE	35	MLBSD	—	—	0	4.70	4.83	22.0%	11.2%	—
2029PROJMLE	36	MLBSD	—	—	0	5.00	5.20	21.0%	11.8%	—

Last 3 seasons WAR 1.2 · Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2022

FB Velo57

K%16

xwOBA vs10

CompsKeiichi Yabu (age 36) · Diego Moreno (age 34) · Zack Segovia (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 119111vR 102

ERA4.50

FIP4.50

K%23.0%

BB%10.6%

K-BB%12.3%

Proj IP53

Value2027 · WAR

Runs saved vs league avg · 53 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL4040

CMD4545

K†5555

Statcast Percentiles

FB Velo

p5795.0

Whiff%

p2822.2%

p1617.2%

xwOBA vs

p100.378

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	39	0	59	244	69	16	6	0%	1.5	23.3%	7.1%	16.2%	2.5%	3.20	3.39	—
2015	22	MIX RAW	2 levels	39	0	59	244	69	16	6	0%	1.5	28.3%	6.6%	21.7%	2.5%	3.20	2.90	—
2016	23	MIX MLE	2 levels	47	0	59	281	77	33	8	0%	1.2	24.6%	12.2%	12.5%	3.5%	5.37	4.46	+0.1
2016	23	MIX RAW	2 levels	47	0	59	281	77	33	8	0%	1.2	27.4%	11.7%	15.7%	2.8%	5.37	3.94	+0.4
2018	25	MIX MLE	3 levels	46	1	65	266	89	24	6	2%	1.4	29.5%	9.5%	19.9%	2.7%	2.34	3.31	+1.0
2018	25	MIX RAW	3 levels	46	1	65	266	89	24	6	2%	1.4	33.5%	9.0%	24.4%	2.3%	2.34	2.67	+1.5
2019	26	MIX MLE	2 levels	57	1	71	310	77	25	10	2%	1.3	23.2%	8.4%	14.8%	3.2%	4.67	3.98	+0.5
2019	26	MIX RAW	2 levels	57	1	71	310	77	25	10	2%	1.3	24.8%	8.1%	16.8%	3.2%	4.67	3.81	+0.6
2020	27	MLB MLE	Oakland Athletics	21	0	25	106	31	11	2	0%	1.2	29.2%	10.4%	18.9%	2.1%	1.80	3.08	+0.4
2020	27	MLB RAW	Oakland Athletics	21	0	25	106	31	11	2	0%	1.2	29.2%	10.4%	18.9%	1.9%	1.80	2.98	+0.5
2021	28	MIX MLE	2 levels	50	0	49	214	44	21	5	0%	1.0	20.1%	9.8%	10.3%	2.2%	4.25	3.84	+0.4
2021	28	MIX RAW	2 levels	50	0	49	214	44	21	5	0%	1.0	20.6%	9.8%	10.7%	2.3%	4.25	3.92	+0.4
2022	29	MIX MLE	2 levels	49	0	53	216	54	22	4	0%	1.1	23.2%	10.4%	12.8%	2.0%	4.08	3.53	+0.6
2022	29	MIX RAW	2 levels	49	0	53	216	54	22	4	0%	1.1	25.0%	10.2%	14.8%	1.9%	4.08	3.29	+0.8
2025	32	MIX MLE	3 levels	16	2	23	105	25	13	1	12%	1.5	20.2%	15.9%	4.3%	1.7%	7.33	4.32	—
2025	32	MIX MLE	3 levels	16	2	23	105	25	13	1	12%	1.5	20.2%	15.9%	4.3%	1.7%	7.33	4.32	—
2025	32	MIX RAW	3 levels	16	2	23	105	25	13	1	12%	1.5	23.8%	12.4%	11.4%	1.0%	7.33	3.19	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			144	0	160	679	151	65	16	0%	1.1	22.2%	9.6%	12.7%	2.4%	4.00	3.73	+1.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	SD	1	0	1	4	1	0	0	0%	1.0	23.0%	10.6%	12.3%	2.9%	4.50	4.50	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	SD	36	0	38	160	35	18	5	0%	1.0	22.0%	11.2%	10.8%	3.3%	4.70	4.83	-0.1
2029	36	MLB MLE	SD	27	0	28	119	25	14	4	0%	1.0	21.0%	11.8%	9.2%	3.6%	5.00	5.20	-0.2
2028	35	MLB CTX	SD	—	—	0	—	—	—	—	—	—	22.0%	11.2%	10.8%	3.3%	4.70	4.83	—
2029	36	MLB CTX	SD	—	—	0	—	—	—	—	—	—	21.0%	11.8%	9.2%	3.6%	5.00	5.20	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		144	0	160	679	151	65	16	0%	1.1	22.2%	9.6%	12.7%	2.4%	4.00	3.73	+1.6
/ 200 IP	—	RAW		180	0	200	851	189	81	20	0%	1.1	22.2%	9.6%	12.7%	2.4%	4.00	3.73	+2.0
Career	—	MLE		325	4	404	1742	422	174	46	1%	1.2	24.2%	10.0%	14.2%	2.6%	4.03	3.77	+1.2
/ 200 IP	—	MLE		161	2	200	862	209	86	23	1%	1.2	24.2%	10.0%	14.2%	2.6%	4.03	3.77	+1.1

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 AASan Antonio Missions · 17 IPFIP 3.54 → 4.32 (+0.77)K% 25.0% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.810	20.25%
BB% (unintentional) /BF	14.47%	—	×1.100	15.92%
HR / BF /BF	1.32%	÷0.950	×1.200	1.66%

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 90).

Result: FIP 3.54 → 4.32, 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 ROKACL Padres · 5 IPFIP 1.87 → 2.56 (+0.69)K% 20.8% → 14.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.83%	—	×0.680	14.17%
BB% (unintentional) /BF	4.17%	—	×1.250	5.21%
HR / BF /BF	0.00%	÷1.018	×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 104).

Result: FIP 1.87 → 2.56, 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 AAAReno Aces · 24 IPFIP 1.21 → 1.62 (+0.41)K% 35.1% → 30.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.11%	—	×0.880	30.89%
BB% (unintentional) /BF	8.51%	—	×1.050	8.94%
HR / BF /BF	0.00%	÷0.965	×1.100	0.00%

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 93).

Result: FIP 1.21 → 1.62, 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 AAALas Vegas Aviators · 5 IPFIP 5.00 → 5.78 (+0.78)K% 25.0% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.880	22.00%
BB% (unintentional) /BF	10.00%	—	×1.050	10.50%
HR / BF /BF	5.00%	÷0.941	×1.100	5.84%

Result: FIP 5.00 → 5.78, 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 AAALas Vegas Aviators · 39 IPFIP 4.80 → 5.06 (+0.26)K% 24.0% → 21.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.02%	—	×0.880	21.14%
BB% (unintentional) /BF	10.06%	—	×1.050	10.56%
HR / BF /BF	4.47%	÷1.119	×1.100	4.39%

Result: FIP 4.80 → 5.06, 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 AAANashville Sounds · 35 IPFIP 1.68 → 2.18 (+0.50)K% 36.4% → 32.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.36%	—	×0.880	32.00%
BB% (unintentional) /BF	6.99%	—	×1.050	7.34%
HR / BF /BF	1.40%	÷0.988	×1.100	1.56%

Result: FIP 1.68 → 2.18, 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 AAMidland RockHounds · 13 IPFIP 4.48 → 6.09 (+1.61)K% 37.7% → 30.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.70%	—	×0.810	30.54%
BB% (unintentional) /BF	14.75%	—	×1.100	16.23%
HR / BF /BF	4.92%	÷0.922	×1.200	6.40%

Result: FIP 4.48 → 6.09, 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).

2016 AAANashville Sounds · 46 IPFIP 3.24 → 3.97 (+0.73)K% 30.0% → 26.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.95%	—	×0.880	26.36%
BB% (unintentional) /BF	11.06%	—	×1.050	11.61%
HR / BF /BF	2.30%	÷0.856	×1.100	2.96%

Result: FIP 3.24 → 3.97, 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
J.B. Wendelken (OGILVIE)	—	—	4.50	23.0%	10.6%	2.9%	—	4.99	21.6%	10.1%	66	+0.49	—	—	—
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	78
Diego Moreno R 2021 · 4.75 FIP	34	SU	4.75	18.6%	9.4%	3.7%	.232	—	—	—	—	—	2.29	187	77
Zack Segovia R 2016 · 3.33 FIP	33	SU	3.33	20.2%	5.9%	2.2%	.312	4.55	17.6%	4.0%	57	+1.22	3.33	144	76
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	76
Leo Rosales R 2015 · 3.99 FIP	34	SU	3.99	18.1%	10.8%	1.9%	.261	4.24	7.8%	-0.4%	22	+0.25	3.85	130	73
Josh Lueke R 2019 · 4.11 FIP	34	SU	4.11	20.4%	6.4%	3.5%	.311	—	—	—	—	—	2.29	191	72
Juan Sandoval R 2015 · 3.82 FIP	34	SU	3.82	15.4%	6.0%	2.3%	.294	3.33	17.4%	8.8%	116	-0.49	3.24	225	72
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	71
Jean Machi R 2016 · 4.36 FIP	34	SU	4.36	18.3%	6.6%	3.6%	.282	4.12	18.6%	12.0%	67	-0.24	2.16	306	71
Hector Navarro R 2015 · 4.35 FIP	35	SU	4.35	15.0%	5.4%	3.3%	.281	3.00	15.2%	9.0%	81	-1.35	2.30	126	70
Carlos Fisher R 2017 · 3.91 FIP	34	SU	3.91	18.1%	12.9%	1.3%	.333	—	—	—	—	—	2.48	245	69
Dustin Molleken R 2017 · 3.38 FIP	32	SU	3.38	24.3%	12.4%	1.4%	.311	—	—	—	—	—	3.38	129	69
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	69
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	69
Fernando Rodriguez Jr. R 2018 · 4.07 FIP	34	SW	4.07	23.7%	9.9%	3.1%	.253	5.11	25.0%	13.8%	32	+1.04	3.34	335	67
Scott McGough R 2024 · 4.56 FIP	34	SU	4.56	18.6%	12.2%	2.7%	.289	3.82	20.3%	13.1%	57	-0.74	3.55	429	67
Greg Burke R 2015 · 3.61 FIP	32	SU	3.61	22.1%	7.3%	2.7%	.241	—	—	—	—	—	3.61	139	66
Brendan Donnelly R 2005 · 4.02 FIP	34	SU	4.02	19.6%	5.9%	3.3%	.264	4.02	17.6%	8.5%	98	-0.00	2.23	385	66
Jim Miller R 2016 · 5.43 FIP	34	SU	5.43	20.4%	14.1%	4.1%	.347	—	—	—	—	—	3.95	140	66
Rafael Martín R 2017 · 3.40 FIP	33	SU	3.40	20.4%	5.1%	2.5%	.305	4.71	22.5%	16.5%	47	+1.31	2.94	227	65

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	1.4	40	22.2%	10.6%	1.05	4.29
José Cisnero ('24)	1.4	46	24.0%	11.3%	1.01	4.16
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Al Reyes ('08)	2.1	54	23.2%	10.7%	1.11	3.84
Ray Searage ('81-'90, 4 WAR*)	1.4	41	21.0%*	10.8%*	0.84*	3.70*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Dave Geisel ('78-'85, 2 WAR*)	1.0	42	23.5%*	10.6%*	0.84*	4.12*