Zach Willeman

P Chattanooga Lookouts

Age 31 RHP 6'2" / 219 lbs AA

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	26	MIX2 levels	50	0	60	5.85	5.02	23.4%	13.8%	—	K 20.0% · BB 14.6% · FIP 5.71
2023	27	AAMIA	14	0	18	7.13	6.55	18.8%	16.2%	—	K 15.2% · BB 17.9% · FIP 7.10
2025	29	AACIN	12	11	58	4.34	4.05	13.4%	9.3%	—	K 10.9% · BB 10.3% · FIP 4.53
2026	30	No MLB games played
2027PROJ	31	MLBCIN	1	0	1	5.70	5.70	10.2%	12.0%	-0.0
2028PROJ31% MLB	32	MLBCIN	13	0	14	5.70	5.79	11.1%	12.1%	-0.2
2029PROJ51% MLB	33	MLBCIN	17	0	18	5.79	5.93	11.5%	12.4%	-0.3

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

Stuff30Control50Command30

CompsRudy Gonzalez (age 34) · Marco Carrillo (age 30) · Luis Angel Daniel (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 141133vR 125

ERA5.70

FIP5.70

K%10.2%

BB%12.0%

K-BB%-1.8%

Proj IP65

Value2027 · WAR

Runs saved vs league avg · 65 IP

Grades · Contract

Scouting Grades

STUF3030

CTRL5050

CMD3030

K†3030

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	22	MIX MLE	2 levels	8	1	19	70	24	8	0	12%	2.4	34.3%	11.4%	22.9%	0.0%	1.42	1.65	—
2018	22	MIX RAW	2 levels	8	1	19	70	24	8	0	12%	2.4	34.3%	11.4%	22.9%	0.0%	1.42	1.84	—
2019	23	A MLE	Great Lakes Loons	21	6	80	378	55	48	8	29%	3.8	10.8%	15.0%	-4.2%	2.7%	5.38	5.57	—
2019	23	A RAW	Great Lakes Loons	21	6	80	378	55	48	8	29%	3.8	14.6%	12.7%	1.9%	2.1%	5.38	4.82	—
2021	25	AA MLE	Tulsa Drillers	33	0	48	209	59	23	4	0%	1.4	22.9%	12.1%	10.8%	2.5%	3.78	4.05	—
2021	25	AA RAW	Tulsa Drillers	33	0	48	209	59	23	4	0%	1.4	28.2%	11.0%	17.2%	1.9%	3.78	3.16	—
2022	26	MIX MLE	2 levels	50	0	60	269	63	37	10	0%	1.2	20.0%	14.6%	5.4%	4.5%	5.85	5.71	—
2022	26	MIX RAW	2 levels	50	0	60	269	63	37	10	0%	1.2	23.4%	13.8%	9.7%	3.7%	5.85	5.02	—
2023	27	AA MLE	Pensacola Blue Wahoos	14	0	18	80	15	13	4	0%	1.3	15.2%	17.9%	-2.7%	5.5%	7.13	7.10	—
2023	27	AA RAW	Pensacola Blue Wahoos	14	0	18	80	15	13	4	0%	1.3	18.8%	16.2%	2.5%	5.0%	7.13	6.55	—
2025	29	AA MLE	Chattanooga Lookouts	12	11	58	246	33	23	4	92%	4.8	10.9%	10.3%	0.6%	1.9%	4.34	4.53	—
2025	29	AA MLE	Chattanooga Lookouts	12	11	58	246	33	23	4	92%	4.8	10.9%	10.3%	0.6%	1.9%	4.34	4.53	—
2025	29	AA RAW	Chattanooga Lookouts	12	11	58	246	33	23	4	92%	4.8	13.4%	9.3%	4.1%	1.6%	4.34	4.05	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	CIN	1	0	1	4	0	1	0	0%	1.0	10.2%	12.0%	-1.8%	2.9%	5.70	5.70	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	CIN	42	0	44	185	21	22	6	0%	1.0	11.1%	12.1%	-1.0%	3.1%	5.70	5.79	-0.6
2029	33	MLB MLE	CIN	33	0	34	145	17	18	5	0%	1.0	11.5%	12.4%	-0.8%	3.4%	5.79	5.93	-0.5
2028	32	MLB CTX	CIN	13	0	14	59	7	7	2	0%	1.1	11.1%	12.1%	-1.0%	3.1%	5.70	5.79	-0.2
2029	33	MLB CTX	CIN	17	0	18	76	9	9	3	0%	1.1	11.5%	12.4%	-0.8%	3.4%	5.79	5.93	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		30	0	31	132	15	16	4	0%	1.0	11.3%	12.3%	-0.9%	3.3%	5.75	5.49	-0.3
/ 200 IP	—	RAW		190	0	200	844	96	102	26	0%	1.1	11.3%	12.3%	-0.9%	3.3%	5.75	5.49	-2.2
Career	—	MLE		138	18	283	1252	205	169	36	13%	2.0	16.4%	13.5%	2.9%	2.9%	4.84	5.02	-1.2
/ 200 IP	—	MLE		98	13	200	886	145	119	26	13%	2.0	16.4%	13.5%	2.9%	2.9%	4.84	5.02	-3.0

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 AAChattanooga Lookouts · 58 IPFIP 4.04 → 4.53 (+0.49)K% 13.4% → 10.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.41%	—	×0.810	10.87%
BB% (unintentional) /BF	9.35%	—	×1.100	10.28%
HR / BF /BF	1.63%	÷1.021	×1.200	1.91%

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 104).

Result: FIP 4.04 → 4.53, 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 AAPensacola Blue Wahoos · 18 IPFIP 6.32 → 7.10 (+0.78)K% 18.8% → 15.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.75%	—	×0.810	15.19%
BB% (unintentional) /BF	16.25%	—	×1.100	17.88%
HR / BF /BF	5.00%	÷1.091	×1.200	5.50%

Result: FIP 6.32 → 7.10, 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).

2022 AAAOmaha Storm Chasers · 37 IPFIP 5.25 → 5.80 (+0.55)K% 21.7% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.71%	—	×0.880	19.11%
BB% (unintentional) /BF	16.57%	—	×1.050	17.40%
HR / BF /BF	3.43%	÷0.984	×1.100	3.83%

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 97).

Result: FIP 5.25 → 5.80, 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 AANorthwest Arkansas Naturals · 23 IPFIP 4.27 → 5.56 (+1.29)K% 26.6% → 21.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.60%	—	×0.810	21.54%
BB% (unintentional) /BF	8.51%	—	×1.100	9.36%
HR / BF /BF	4.26%	÷0.905	×1.200	5.64%

Result: FIP 4.27 → 5.56, 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).

2021 AATulsa Drillers · 48 IPFIP 3.16 → 4.05 (+0.89)K% 28.2% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.23%	—	×0.810	22.87%
BB% (unintentional) /BF	11.00%	—	×1.100	12.11%
HR / BF /BF	1.91%	÷0.935	×1.200	2.46%

Result: FIP 3.16 → 4.05, 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 AGreat Lakes Loons · 80 IPFIP 4.64 → 5.57 (+0.93)K% 14.6% → 10.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.55%	—	×0.740	10.77%
BB% (unintentional) /BF	12.70%	—	×1.180	14.98%
HR / BF /BF	2.12%	÷1.018	×1.300	2.70%

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 104).

Result: FIP 4.64 → 5.57, 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 ROKAZL Dodgers · 11 IPFIP 2.32 → 3.90 (+1.58)K% 36.8% → 25.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.84%	—	×0.680	25.05%
BB% (unintentional) /BF	18.42%	—	×1.250	23.03%
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 2.32 → 3.90, 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 AGreat Lakes Loons · 8 IPFIP 0.86 → 1.61 (+0.76)K% 31.2% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.25%	—	×0.740	23.12%
BB% (unintentional) /BF	3.12%	—	×1.180	3.69%
HR / BF /BF	0.00%	÷1.100	×1.300	0.00%

Result: FIP 0.86 → 1.61, 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
Zach Willeman (OGILVIE)	—	—	5.70	10.2%	12.0%	2.9%	—	5.85	11.3%	-0.9%	78	+0.15	—	—	—
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	80
Marco Carrillo R 2017 · 5.33 FIP	30	SW	5.33	11.1%	7.4%	4.1%	.278	6.08	9.9%	0.8%	104	+0.75	5.33	194	77
Luis Angel Daniel R 2016 · 4.56 FIP	31	SU	4.56	13.4%	8.9%	2.7%	.286	4.16	9.8%	0.3%	53	-0.40	4.16	156	76
Marco Antonio Duarte R 2019 · 5.03 FIP	32	SW	5.03	12.2%	9.1%	3.3%	.420	—	—	—	—	—	4.07	203	74
Grant Black R 2023 · 5.49 FIP	29	SU	5.49	15.9%	11.3%	4.2%	.352	—	—	—	—	—	4.46	215	74
Jeff Gray R 2012 · 5.43 FIP	30	SU	5.43	11.0%	9.3%	3.8%	.274	—	—	—	—	—	3.46	127	74
Bradin Hagens R 2019 · 5.46 FIP	30	SW	5.46	13.2%	12.6%	3.4%	.303	—	—	—	—	—	3.79	254	73
Murphy Smith R 2018 · 4.57 FIP	30	SW	4.57	13.6%	9.3%	2.6%	.273	—	—	—	—	—	3.16	300	73
Ivan Zavala R 2017 · 5.02 FIP	30	SU	5.02	12.8%	8.0%	3.6%	.286	5.15	12.7%	5.3%	61	+0.13	4.27	209	72
Felipe Arredondo R 2017 · 4.76 FIP	30	SW	4.76	14.8%	7.3%	3.6%	.311	4.65	16.2%	9.1%	64	-0.11	3.92	337	72
Rodney Myers R 2001 · 4.70 FIP	32	SU	4.70	13.7%	9.5%	2.8%	.301	3.98	10.9%	1.0%	21	-0.72	3.98	218	71
Chris Jakubauskas R 2009 · 4.97 FIP	30	SW	4.97	12.1%	6.2%	3.9%	.250	4.42	15.7%	7.8%	72	-0.55	4.42	165	71
Tony Fiore R 2003 · 5.17 FIP	31	SU	5.17	14.3%	12.4%	3.1%	.239	—	—	—	—	—	4.60	142	68
Benjamin Sandoval R 2017 · 5.23 FIP	30	SU	5.23	3.4%	12.3%	1.6%	.281	5.65	11.8%	-2.2%	33	+0.42	4.66	146	68
Clay Hensley R 2011 · 4.78 FIP	31	SW	4.78	15.5%	9.8%	3.2%	.249	4.37	17.9%	5.9%	51	-0.41	2.58	517	67
Esmailin Caridad R 2015 · 5.85 FIP	31	SU	5.85	9.9%	9.4%	4.3%	.324	3.80	18.9%	10.7%	63	-2.05	1.67	101	67
Jaye Chapman R 2017 · 5.51 FIP	30	SU	5.51	13.0%	13.4%	3.3%	.311	—	—	—	—	—	3.10	162	67
Francisco Cordova R 2015 · 5.51 FIP	31	SW	5.51	6.4%	4.6%	4.3%	.261	4.59	7.1%	-0.6%	83	-0.92	4.59	115	66
Fredy Quintero R 2019 · 4.62 FIP	31	SU	4.62	17.2%	13.7%	2.2%	.310	—	—	—	—	—	4.29	241	66
Tim Corcoran R 2007 · 5.29 FIP	29	SU	5.29	7.6%	11.4%	2.5%	.242	—	—	—	—	—	4.10	130	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	48	10.8%	12.1%	1.18	5.72
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Luther Hackman ('03)	1.1	71	13.3%	10.9%	1.10	5.09
Rodney Myers ('04)	1.2	60	15.0%	10.3%	1.05	5.07
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Greg Booker ('83-'90, -1 WAR*)	1.3	53	13.3%*	10.2%*	1.07*	4.51*
Larry Bearnarth ('63-'71, -3 WAR*)	1.6	81	11.0%*	10.7%*	1.16*	5.02*