Jack Weisenburger

P Syracuse Mets

Age 29 RHP 6'3" / 220 lbs AAA

Overview

AAARP40-MANROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	25	MIX2 levels	16	3	21	3.48	3.29	24.7%	12.9%	—	K 21.4% · BB 17.8% · FIP 4.56
2024	26	AAOAK	8	0	7	1.35	4.15	29.4%	26.5%	—	K 29.4% · BB 26.5% · FIP 3.97
2026	28	MIX2 levels	25	13	75	5.91	4.18	20.7%	11.4%	1.1	K 18.4% · BB 10.4% · FIP 4.36
2027PROJ	29	MLBNYM	33	0	35	4.41	4.67	19.4%	10.1%	-0.0
2028PROJ77% MLB	30	MLBNYM	29	0	30	4.65	4.84	19.1%	10.3%	-0.1
2029PROJ83% MLB	31	MLBNYM	25	0	26	4.86	5.03	18.7%	10.6%	-0.1

Last 3 seasons WAR 1.1 · Next 3 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs90

K%81

FB Velo57

Career WAR0.0 WAR median (P10 -0.1 / P90 0.1, comp-based) · star 0% · didn't stick 99%

CompsDiego Moreno (age 29) · Wirfin Obispo (age 30) · Dustin Molleken (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 122114vR 106

ERA4.41

FIP4.67

K%19.4%

BB%10.1%

K-BB%9.3%

Proj IP51

Value2027 · WAR

Runs saved vs league avg · 51 IP

Grades · Statcast · Contract

Scouting Grades

K†4545

Statcast Percentiles

FB Velo

p5795.0

Whiff%

p5526.0%

p8128.0%

xwOBA vs

p900.246

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)
2019	21	ROK MLE	AZL Athletics Gold	11	1	15	61	28	10	0	9%	1.4	31.2%	20.5%	10.7%	0.0%	3.00	3.06	—
2019	21	ROK RAW	AZL Athletics Gold	11	1	15	61	28	10	0	9%	1.4	45.9%	16.4%	29.5%	0.0%	3.00	1.37	—
2021	23	MIX MLE	2 levels	41	0	53	237	74	35	5	0%	1.3	24.9%	16.3%	8.5%	3.0%	3.76	4.73	—
2021	23	MIX RAW	2 levels	41	0	53	237	74	35	5	0%	1.3	31.2%	14.8%	16.5%	2.1%	3.76	3.52	—
2022	24	AA MLE	Midland RockHounds	8	0	9	37	11	3	2	0%	1.2	29.7%	8.1%	21.6%	5.4%	4.82	4.58	—
2022	24	AA RAW	Midland RockHounds	8	0	9	37	11	3	2	0%	1.2	29.7%	8.1%	21.6%	5.4%	4.82	4.49	—
2023	25	MIX MLE	2 levels	16	3	21	85	21	11	1	19%	1.3	21.4%	17.8%	3.6%	1.8%	3.48	4.56	—
2023	25	MIX RAW	2 levels	16	3	21	85	21	11	1	19%	1.3	24.7%	12.9%	11.8%	1.2%	3.48	3.29	—
2024	26	AA MLE	Midland RockHounds	8	0	7	34	10	9	0	0%	0.8	29.4%	26.5%	2.9%	0.0%	1.35	3.97	—
2024	26	AA MLE	Midland RockHounds	8	0	7	34	10	9	0	0%	0.8	29.4%	26.5%	2.9%	0.0%	1.35	3.97	—
2024	26	AA RAW	Midland RockHounds	8	0	7	34	10	9	0	0%	0.8	29.4%	26.5%	2.9%	0.0%	1.35	4.15	—
2026	28	MIX MLE	2 levels	25	13	75	324	67	37	8	52%	3.0	18.4%	10.4%	8.0%	2.7%	5.91	4.36	+0.9
2026	28	MIX MLE	2 levels	25	13	75	324	67	37	8	52%	3.0	18.4%	10.4%	8.0%	2.7%	5.91	4.36	+0.9
2026	28	MIX RAW	2 levels	25	13	75	324	67	37	8	52%	3.0	20.7%	11.4%	9.3%	2.5%	5.91	4.18	+1.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			7	0	13	50	14	4	0	0%	1.8	28.0%	8.0%	20.0%	0.0%	2.13	1.84	+0.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	NYM	33	0	35	148	29	15	4	0%	1.1	19.4%	10.1%	9.3%	2.8%	4.41	4.67	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	NYM	36	0	38	162	31	17	5	0%	1.1	19.1%	10.3%	8.8%	3.0%	4.65	4.84	-0.1
2029	31	MLB MLE	NYM	30	0	31	131	25	14	4	0%	1.0	18.7%	10.6%	8.1%	3.3%	4.86	5.03	-0.2
2028	30	MLB CTX	NYM	29	0	30	127	24	13	4	0%	1.0	19.1%	10.3%	8.8%	3.0%	4.65	4.84	-0.1
2029	31	MLB CTX	NYM	25	0	26	110	20	12	4	0%	1.0	18.7%	10.6%	8.1%	3.3%	4.86	5.03	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		60	0	68	283	58	28	7	0%	1.1	20.5%	10.0%	10.5%	2.6%	4.26	4.06	+0.4
/ 200 IP	—	RAW		176	0	200	834	171	82	21	0%	1.1	20.5%	10.0%	10.5%	2.6%	4.26	4.06	+1.2
Career	—	MLE		109	17	179	778	177	112	20	16%	1.6	22.7%	14.4%	8.3%	2.5%	4.53	4.38	+0.1
/ 200 IP	—	MLE		122	19	200	869	197	125	22	16%	1.6	22.7%	14.4%	8.3%	2.5%	4.53	4.38	+0.2

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 AAASyracuse Mets · 62 IPFIP 4.59 → 4.83 (+0.24)K% 19.3% → 16.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.34%	—	×0.860	16.64%
BB% (unintentional) /BF	12.04%	—	×0.900	10.84%
HR / BF /BF	2.92%	÷1.000	×1.100	3.21%

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 100).

Result: FIP 4.59 → 4.83, 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 AAMidland RockHounds · 7 IPFIP 3.97 → 4.78 (+0.81)K% 29.4% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.41%	—	×0.810	23.82%
BB% (unintentional) /BF	26.47%	—	×1.100	29.12%
HR / BF /BF	0.00%	÷0.940	×1.200	0.00%

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 88).

Result: FIP 3.97 → 4.78, 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).

2023 AAMidland RockHounds · 17 IPFIP 3.72 → 4.56 (+0.83)K% 26.5% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.47%	—	×0.810	21.44%
BB% (unintentional) /BF	16.18%	—	×1.100	17.79%
HR / BF /BF	1.47%	÷0.957	×1.200	1.84%

Result: FIP 3.72 → 4.56, 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 AAMidland RockHounds · 9 IPFIP 4.58 → 6.69 (+2.10)K% 29.7% → 24.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.73%	—	×0.810	24.08%
BB% (unintentional) /BF	8.11%	—	×1.100	8.92%
HR / BF /BF	5.41%	÷0.793	×1.200	8.18%

Result: FIP 4.58 → 6.69, 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 AAMidland RockHounds · 37 IPFIP 4.57 → 5.89 (+1.32)K% 27.0% → 21.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.97%	—	×0.810	21.84%
BB% (unintentional) /BF	17.42%	—	×1.100	19.16%
HR / BF /BF	2.81%	÷0.838	×1.200	4.02%

Result: FIP 4.57 → 5.89, 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 A+Lansing Lugnuts · 15 IPFIP 0.24 → 1.22 (+0.98)K% 44.1% → 33.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	44.07%	—	×0.770	33.93%
BB% (unintentional) /BF	6.78%	—	×1.150	7.80%
HR / BF /BF	0.00%	÷0.959	×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 92).

Result: FIP 0.24 → 1.22, 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 ROKAZL Athletics Gold · 15 IPFIP 1.30 → 3.06 (+1.76)K% 45.9% → 31.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	45.90%	—	×0.680	31.21%
BB% (unintentional) /BF	16.39%	—	×1.250	20.49%
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 1.30 → 3.06, 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).

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
Jack Weisenburger (OGILVIE)	—	—	4.67	19.4%	10.1%	2.8%	—	4.93	18.9%	8.5%	69	+0.26	—	—	—
Diego Moreno R 2016 · 3.75 FIP	29	SU	3.75	21.0%	8.2%	2.5%	.347	3.13	17.8%	11.9%	54	-0.62	2.29	187	80
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	79
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	79
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	78
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	76
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	76
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	76
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	76
Carlos Fisher R 2011 · 4.33 FIP	28	SU	4.33	15.5%	9.1%	2.5%	.275	—	—	—	—	—	2.48	245	76
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	75
Jason Urquidez R 2015 · 3.59 FIP	32	SU	3.59	15.6%	9.3%	1.1%	.386	1.81	25.5%	20.7%	90	-1.78	1.25	123	75
Brian Sanches R 2008 · 4.74 FIP	29	SU	4.74	18.5%	9.3%	3.7%	.378	4.01	20.5%	10.8%	182	-0.73	3.39	229	74
Yoanner Negrin R 2015 · 3.79 FIP	31	SW	3.79	15.1%	7.5%	1.9%	.256	3.29	15.0%	8.5%	270	-0.50	3.15	485	74
Joe Colón J R 2017 · 4.25 FIP	27	SU	4.25	20.4%	12.1%	2.4%	.315	—	—	—	—	—	3.27	113	74
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	74
Tyler Sturdevant R 2015 · 4.37 FIP	29	SU	4.37	21.3%	8.5%	3.6%	.241	3.97	18.5%	11.9%	118	-0.40	3.44	149	74
Gerardo Sanchez R 2017 · 3.47 FIP	28	SU	3.47	21.6%	8.4%	2.1%	.355	3.58	20.5%	15.1%	56	+0.11	2.65	137	73
Ronald Peña R 2021 · 4.49 FIP	29	SU	4.49	16.5%	10.4%	2.7%	.288	—	—	—	—	—	3.72	187	72
Francisco Mendoza R 2016 · 3.81 FIP	28	SU	3.81	17.9%	7.7%	2.3%	.344	—	—	—	—	—	3.13	120	72
Bo Schultz R 2015 · 4.30 FIP	29	SU	4.30	18.3%	7.9%	3.2%	.218	3.49	15.1%	8.9%	77	-0.81	2.73	141	72

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	44	19.9%	10.1%	1.06	4.37
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Manny Acosta ('12)	1.2	41	20.5%	10.9%	1.09	3.99
Kevin Quackenbush ('21)	1.0	52	21.0%	9.2%	1.04	4.41
Ed Vosberg ('86-'02, 1 WAR*)	1.2	47	21.0%*	9.6%*	0.86*	4.06*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*