Zack Lee

P West Michigan Whitecaps

Age 26 RHP 6'4" / 200 lbs A+ peak 0.2 · 2029

Overview

A+PROSPECT

ETA2029MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	ADET	21	17	83	3.16	2.64	26.0%	5.9%	—	K 19.2% · BB 7.0% · FIP 3.51
2025	24	ADET	22	12	93	3.79	4.15	15.6%	7.6%	—	K 11.6% · BB 8.9% · FIP 5.40
2026	25	MIX3 levels	36	6	65	3.60	2.55	25.4%	7.7%	—	K 20.2% · BB 7.9% · FIP 3.22
2027PROJ	26	MLBDET	—	—	0	5.05	5.05	14.7%	10.0%	—
2028PROJ37% MLB	27	MLBDET	21	0	22	4.99	5.01	15.4%	9.8%	-0.1
2029PROJ59% MLB	28	MLBDET	30	0	32	4.83	4.76	17.8%	9.0%	-0.1

Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff25Control50Command30

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 100%

CompsTyler Yates (age 26) · Dennis O'Grady (age 26) · Josh Roeder (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 129121vR 113

ERA5.05

FIP5.05

K%14.7%

BB%10.0%

K-BB%4.7%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF2525

CTRL5050

CMD3030

K†3040

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	22	ROK MLE	FCL Tigers	3	0	4	16	4	1	0	0%	1.3	25.0%	6.2%	18.8%	0.0%	9.00	1.78	—
2023	22	ROK RAW	FCL Tigers	3	0	4	16	4	1	0	0%	1.3	25.0%	6.2%	18.8%	0.0%	9.00	1.85	—
2024	23	A MLE	Lakeland Flying Tigers	21	17	83	339	88	20	6	81%	3.9	19.2%	7.0%	12.2%	2.1%	3.16	3.51	—
2024	23	A MLE	Lakeland Flying Tigers	21	17	83	339	88	20	6	81%	3.9	19.2%	7.0%	12.2%	2.1%	3.16	3.51	—
2024	23	A RAW	Lakeland Flying Tigers	21	17	83	339	88	20	6	81%	3.9	26.0%	5.9%	20.1%	1.8%	3.16	2.64	—
2025	24	A MLE	Lakeland Flying Tigers	22	12	93	384	60	29	10	55%	4.2	11.6%	8.9%	2.7%	3.9%	3.79	5.40	—
2025	24	A MLE	Lakeland Flying Tigers	22	12	93	384	60	29	10	55%	4.2	11.6%	8.9%	2.7%	3.9%	3.79	5.40	—
2025	24	A RAW	Lakeland Flying Tigers	22	12	93	384	60	29	10	55%	4.2	15.6%	7.6%	8.1%	2.6%	3.79	4.15	—
2026	25	MIX MLE	3 levels	36	6	65	272	69	21	3	17%	1.8	20.2%	7.9%	12.3%	1.5%	3.60	3.22	—
2026	25	MIX MLE	3 levels	36	6	65	272	69	21	3	17%	1.8	20.2%	7.9%	12.3%	1.5%	3.60	3.22	—
2026	25	MIX RAW	3 levels	36	6	65	272	69	21	3	17%	1.8	25.4%	7.7%	17.6%	1.1%	3.60	2.55	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	DET	—	—	0	—	—	—	—	—	—	14.7%	10.0%	4.7%	2.8%	5.05	5.05	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	DET	58	0	61	258	40	25	7	0%	1.1	15.4%	9.8%	5.6%	2.9%	4.99	5.01	-0.3
2029	28	MLB MLE	DET	52	0	55	232	41	21	7	0%	1.1	17.8%	9.0%	8.8%	3.0%	4.83	4.76	-0.1
2030	29	MLB MLE	DET	47	0	49	208	37	19	7	0%	1.0	17.8%	9.2%	8.6%	3.1%	4.85	4.87	-0.2
2031	30	MLB MLE	DET	42	0	44	186	33	18	6	0%	1.0	17.6%	9.5%	8.1%	3.3%	4.96	5.04	-0.2
2028	27	MLB CTX	DET	21	0	22	93	14	9	3	0%	1.0	15.4%	9.8%	5.6%	2.9%	4.99	5.01	-0.1
2029	28	MLB CTX	DET	30	0	32	135	24	12	4	0%	1.1	17.8%	9.0%	8.8%	3.0%	4.83	4.76	-0.1
2030	29	MLB CTX	DET	33	0	35	148	26	14	5	0%	1.1	17.8%	9.2%	8.6%	3.1%	4.85	4.87	-0.1
2031	30	MLB CTX	DET	32	0	34	144	25	14	5	0%	1.1	17.6%	9.5%	8.1%	3.3%	4.96	5.04	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		118	0	124	523	90	49	16	0%	1.0	17.3%	9.4%	7.9%	3.1%	4.90	4.53	+0.0
/ 200 IP	—	RAW		190	0	200	844	145	79	26	0%	1.1	17.3%	9.4%	7.9%	3.1%	4.90	4.53	+0.0
Career	—	MLE		82	35	244	1011	168	80	26	43%	3.0	16.7%	7.9%	8.7%	2.6%	3.61	4.12	-0.9
/ 200 IP	—	MLE		67	29	200	828	138	66	21	43%	3.0	16.7%	7.9%	8.7%	2.6%	3.61	4.12	-0.9

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 A+West Michigan Whitecaps · 61 IPFIP 2.42 → 3.22 (+0.81)K% 26.2% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.21%	—	×0.770	20.18%
BB% (unintentional) /BF	6.85%	—	×1.150	7.88%
HR / BF /BF	1.21%	÷1.000	×1.250	1.51%

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 2.42 → 3.22, 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).

2025 ALakeland Flying Tigers · 93 IPFIP 4.17 → 5.40 (+1.24)K% 15.6% → 11.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.62%	—	×0.740	11.56%
BB% (unintentional) /BF	7.55%	—	×1.180	8.91%
HR / BF /BF	2.60%	÷0.864	×1.300	3.92%

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 73).

Result: FIP 4.17 → 5.40, 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 ALakeland Flying Tigers · 83 IPFIP 2.63 → 3.51 (+0.88)K% 26.0% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.96%	—	×0.740	19.21%
BB% (unintentional) /BF	5.90%	—	×1.180	6.96%
HR / BF /BF	1.77%	÷1.099	×1.300	2.09%

Result: FIP 2.63 → 3.51, 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
Zack Lee (OGILVIE)	—	—	5.05	14.7%	10.0%	2.8%	—	4.89	16.9%	7.5%	165	-0.16	—	—	—
Tyler Yates R 2004 · 4.47 FIP	26	SW	4.47	15.4%	9.6%	2.6%	.333	3.64	22.5%	13.5%	116	-0.83	3.23	248	89
Dennis O'Grady R 2015 · 4.95 FIP	26	SW	4.95	13.5%	11.0%	2.9%	.339	—	—	—	—	—	3.62	157	89
Josh Roeder R 2019 · 4.71 FIP	26	SW	4.71	15.1%	8.7%	3.3%	.264	—	—	—	—	—	4.71	175	88
Jorge Reyes R 2015 · 4.58 FIP	27	SW	4.58	15.9%	8.5%	3.2%	.307	3.49	14.2%	6.2%	129	-1.09	3.39	227	86
Dakota Hawkins R 2024 · 4.31 FIP	24	SW	4.31	16.3%	8.9%	2.7%	.277	4.32	19.4%	10.4%	102	+0.01	3.50	186	86
Cameron Foster R 2024 · 4.83 FIP	25	SW	4.83	17.4%	11.5%	3.2%	.321	3.09	25.5%	17.5%	60	-1.74	2.50	213	85
Ranfi Casimiro R 2018 · 4.62 FIP	26	SW	4.62	16.4%	10.7%	2.8%	.285	4.93	8.4%	-0.2%	16	+0.31	3.81	420	84
Roberto Gómez R 2017 · 3.95 FIP	27	SW	3.95	18.4%	8.9%	2.3%	.315	5.25	13.8%	4.9%	18	+1.30	3.95	115	83
Donovan Hand R 2013 · 4.72 FIP	27	SW	4.72	12.9%	7.0%	3.3%	.279	4.30	11.1%	6.8%	97	-0.42	4.30	305	83
Brad Allen R 2015 · 4.25 FIP	26	SW	4.25	14.0%	12.6%	1.3%	.315	5.82	14.7%	1.5%	87	+1.57	4.25	149	83
Aaron Northcraft R 2016 · 4.19 FIP	26	SW	4.19	16.1%	8.3%	2.5%	.309	3.32	24.1%	13.4%	34	-0.87	3.32	252	83
Paulshawn Pasqualotto R 2024 · 4.84 FIP	23	SW	4.84	15.6%	9.5%	3.4%	.354	3.77	20.2%	10.8%	111	-1.07	3.73	186	82
Cooper Adams R 2024 · 5.42 FIP	24	SW	5.42	13.0%	12.2%	3.4%	.275	4.32	21.7%	10.4%	141	-1.10	3.05	221	81
Alfonso Sanchez R 2015 · 4.96 FIP	27	SP-	4.96	12.5%	9.1%	3.2%	.346	4.85	14.0%	5.3%	138	-0.11	4.51	224	81
Danny Kirwin R 2024 · 4.19 FIP	24	SW	4.19	17.9%	9.9%	2.4%	.262	5.33	16.8%	4.6%	91	+1.14	4.16	161	81
Colby Morris R 2022 · 5.76 FIP	25	SW	5.76	16.2%	11.8%	4.6%	.268	—	—	—	—	—	4.11	105	80
Nick Hull R 2024 · 4.62 FIP	24	SW	4.62	19.0%	12.2%	2.9%	.296	5.00	16.8%	6.2%	111	+0.38	4.26	292	80
Felipe Gonzalez R 2017 · 4.60 FIP	25	SW	4.60	18.3%	9.2%	3.4%	.337	3.27	22.7%	12.7%	50	-1.33	3.27	339	80
Kurt Heyer R 2016 · 3.99 FIP	25	SW	3.99	14.1%	6.7%	2.2%	.337	—	—	—	—	—	3.75	178	80
Mike Connolly R 2018 · 5.13 FIP	26	SW	5.13	13.2%	9.4%	3.5%	.321	—	—	—	—	—	3.94	328	80

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	56	16.5%	9.6%	1.16	4.94
Vic Darensbourg ('05)	1.5	50	17.0%	9.3%	1.01	4.96
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Tom Martin ('07)	1.6	53	15.8%	10.1%	1.02	4.92
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Dave Leiper ('84-'96, 0 WAR*)	1.4	46	15.6%*	9.1%*	0.94*	4.28*