Luke Stofel

P West Michigan Whitecaps

Age 25 RHP 6'5" / 235 lbs A+

Overview

A+PROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	22	MIX2 levels	31	0	42	4.89	3.29	23.8%	10.3%	—	K 17.6% · BB 12.4% · FIP 4.26
2025	23	ADET	23	12	97	3.05	3.45	17.3%	10.1%	—	K 12.8% · BB 11.9% · FIP 4.32
2026	24	MIX2 levels	33	0	50	3.58	3.70	21.2%	10.8%	—	K 16.5% · BB 12.8% · FIP 4.61
2027PROJ	25	MLBDET	—	—	0	5.68	5.68	13.3%	14.4%	—
2028PROJ43% MLB	26	MLBDET	26	0	27	5.49	5.46	15.1%	13.7%	-0.3
2029PROJ63% MLB	27	MLBDET	31	0	33	5.40	5.41	15.6%	13.3%	-0.3

Next 3 projected WAR -0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff30Control40Command30

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

CompsJeff Soptic (age 25) · Clate Schmidt (age 25) · Kender Villegas (age 24)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 141133vR 125

ERA5.68

FIP5.68

K%13.3%

BB%14.4%

K-BB%-1.0%

Proj IP60

Value2027 · WAR

Runs saved vs league avg · 60 IP

Grades · Contract

Scouting Grades

STUF3030

CTRL4040

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	21	MIX MLE	2 levels	4	0	2	18	3	5	0	0%	0.6	16.7%	27.8%	-11.1%	0.0%	30.86	5.21	—
2023	21	MIX RAW	2 levels	4	0	2	18	3	5	0	0%	0.6	16.7%	27.8%	-11.1%	0.0%	30.86	6.96	—
2024	22	MIX MLE	2 levels	31	0	42	185	44	19	3	0%	1.4	17.6%	12.4%	5.2%	2.0%	4.89	4.26	—
2024	22	MIX MLE	2 levels	31	0	42	185	44	19	3	0%	1.4	17.6%	12.4%	5.2%	2.0%	4.89	4.26	—
2024	22	MIX RAW	2 levels	31	0	42	185	44	19	3	0%	1.4	23.8%	10.3%	13.5%	1.6%	4.89	3.29	—
2025	23	A MLE	Lakeland Flying Tigers	23	12	97	415	72	42	4	52%	4.2	12.8%	11.9%	0.9%	1.5%	3.05	4.32	—
2025	23	A MLE	Lakeland Flying Tigers	23	12	97	415	72	42	4	52%	4.2	12.8%	11.9%	0.9%	1.5%	3.05	4.32	—
2025	23	A RAW	Lakeland Flying Tigers	23	12	97	415	72	42	4	52%	4.2	17.3%	10.1%	7.2%	1.0%	3.05	3.45	—
2026	24	MIX MLE	2 levels	33	0	50	222	47	24	4	0%	1.5	16.5%	12.8%	3.6%	2.3%	3.58	4.61	—
2026	24	MIX MLE	2 levels	33	0	50	222	47	24	4	0%	1.5	16.5%	12.8%	3.6%	2.3%	3.58	4.61	—
2026	24	MIX RAW	2 levels	33	0	50	222	47	24	4	0%	1.5	21.2%	10.8%	10.4%	1.8%	3.58	3.70	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	DET	—	—	0	—	—	—	—	—	—	13.3%	14.4%	-1.0%	2.8%	5.68	5.68	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	DET	60	0	62	264	40	36	7	0%	1.0	15.1%	13.7%	1.4%	2.8%	5.49	5.46	-0.6
2029	27	MLB MLE	DET	50	0	53	223	35	30	6	0%	1.1	15.6%	13.3%	2.3%	2.8%	5.40	5.41	-0.5
2030	28	MLB MLE	DET	46	0	48	204	32	27	6	0%	1.0	15.8%	13.2%	2.6%	3.0%	5.40	5.43	-0.5
2031	29	MLB MLE	DET	44	0	46	196	35	24	6	0%	1.1	17.7%	12.4%	5.3%	3.1%	5.31	5.26	-0.4
2032	30	MLB MLE	DET	40	0	42	178	31	23	6	0%	1.1	17.4%	12.8%	4.6%	3.3%	5.39	5.44	-0.4
2028	26	MLB CTX	DET	26	0	27	114	17	16	3	0%	1.0	15.1%	13.7%	1.4%	2.8%	5.49	5.46	-0.3
2029	27	MLB CTX	DET	31	0	33	139	22	19	4	0%	1.1	15.6%	13.3%	2.3%	2.8%	5.40	5.41	-0.3
2030	28	MLB CTX	DET	34	0	36	152	24	20	4	0%	1.1	15.8%	13.2%	2.6%	3.0%	5.40	5.43	-0.4
2031	29	MLB CTX	DET	36	0	38	160	28	20	5	0%	1.1	17.7%	12.4%	5.3%	3.1%	5.31	5.26	-0.3
2032	30	MLB CTX	DET	34	0	36	152	26	19	5	0%	1.1	17.4%	12.8%	4.6%	3.3%	5.39	5.44	-0.4
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		162	0	170	719	118	94	22	0%	1.1	16.4%	13.0%	3.4%	3.0%	5.39	5.02	-0.9
/ 200 IP	—	RAW		190	0	200	844	139	110	26	0%	1.1	16.4%	13.0%	3.4%	3.0%	5.39	5.02	-1.1
Career	—	MLE		91	12	192	840	125	106	15	13%	2.1	14.9%	12.6%	2.3%	1.8%	3.93	4.41	-2.5
/ 200 IP	—	MLE		95	12	200	873	130	110	15	13%	2.1	14.9%	12.6%	2.3%	1.8%	3.93	4.41	-2.0

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.

2026 A+West Michigan Whitecaps · 49 IPFIP 3.73 → 4.61 (+0.88)K% 21.4% → 16.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.40%	—	×0.770	16.47%
BB% (unintentional) /BF	11.16%	—	×1.150	12.84%
HR / BF /BF	1.86%	÷1.000	×1.250	2.33%

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 3.73 → 4.61, 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).

2025 ALakeland Flying Tigers · 97 IPFIP 3.45 → 4.32 (+0.88)K% 17.3% → 12.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.35%	—	×0.740	12.84%
BB% (unintentional) /BF	10.12%	—	×1.180	11.94%
HR / BF /BF	0.96%	÷0.864	×1.300	1.45%

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 3.45 → 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).

2024 ALakeland Flying Tigers · 41 IPFIP 3.33 → 4.26 (+0.93)K% 23.8% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.76%	—	×0.740	17.58%
BB% (unintentional) /BF	10.50%	—	×1.180	12.39%
HR / BF /BF	1.66%	÷1.099	×1.300	1.96%

Result: FIP 3.33 → 4.26, 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).

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
Luke Stofel (OGILVIE)	—	—	5.68	13.3%	14.4%	2.8%	—	5.44	15.5%	2.1%	164	-0.24	—	—	—
Jeff Soptic R 2016 · 5.52 FIP	25	SU	5.52	13.6%	15.3%	3.0%	.326	—	—	—	—	—	5.30	124	86
Clate Schmidt R 2019 · 5.66 FIP	25	SU	5.66	13.5%	13.9%	3.5%	.290	—	—	—	—	—	3.51	160	85
Kender Villegas R 2017 · 4.70 FIP	24	SU	4.70	13.3%	13.3%	1.9%	.269	—	—	—	—	—	3.26	131	85
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	85
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	84
Julian Arballo R 2015 · 5.13 FIP	27	SU	5.13	15.1%	13.8%	2.8%	.335	4.46	12.6%	0.6%	116	-0.67	4.45	214	84
Ian Villers R 2024 · 4.55 FIP	23	SU	4.55	13.2%	11.9%	1.9%	.311	4.23	15.6%	5.2%	59	-0.32	4.23	107	84
Jarod Wright R 2022 · 5.73 FIP	25	SU	5.73	12.7%	13.2%	3.7%	.282	4.46	13.2%	3.8%	53	-1.27	4.46	170	84
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	84
Tyler Burch R 2023 · 4.92 FIP	25	SU	4.92	15.0%	12.6%	2.7%	.285	—	—	—	—	—	4.56	119	84
Stephen Johnson R 2016 · 5.15 FIP	25	SU	5.15	16.7%	12.7%	3.4%	.268	—	—	—	—	—	3.12	141	84
Mitchell Osnowitz R 2015 · 4.54 FIP	24	SU	4.54	13.2%	13.8%	1.5%	.330	5.30	16.5%	-2.2%	23	+0.76	4.54	132	83
Justin Camp R 2018 · 4.56 FIP	25	SU	4.56	13.2%	11.9%	1.9%	.296	—	—	—	—	—	2.59	140	83
Rob Huber R 2016 · 4.73 FIP	24	SU	4.73	15.7%	14.7%	2.0%	.333	—	—	—	—	—	3.90	117	83
Andrew McInvale R 2022 · 5.15 FIP	25	SU	5.15	17.6%	15.9%	2.8%	.324	6.44	24.5%	10.0%	23	+1.29	4.92	103	83
Zach Nuding R 2015 · 4.76 FIP	25	SU	4.76	12.5%	10.5%	2.5%	.236	5.03	12.6%	3.3%	106	+0.27	4.76	146	82
Philip Walby R 2017 · 4.49 FIP	25	SU	4.49	12.7%	12.0%	1.7%	.311	—	—	—	—	—	3.46	137	82
Reece Karalus R 2018 · 4.73 FIP	24	SU	4.73	15.4%	11.9%	2.6%	.299	—	—	—	—	—	4.73	149	82
José A. Váldez R 2015 · 4.55 FIP	25	SU	4.55	15.3%	15.3%	1.5%	.279	4.32	22.3%	9.9%	167	-0.23	4.02	328	81
Jake Gilbert R 2022 · 4.65 FIP	25	SU	4.65	18.2%	16.2%	1.9%	.331	—	—	—	—	—	4.14	103	81

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	1.6	52	15.7%	13.4%	1.13	5.46
Mike Mohler ('01)	2.1	60	15.0%	12.4%	0.97	4.99
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
C.J. Nitkowski ('05)	2.4	68	15.8%	11.9%	1.07	5.37
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*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*