Logan VanWey

P Sugar Land Space Cowboys

Age 28 RHP 6'2" / 205 lbs AAA peak 0.4 · 2027

Overview

AAARP40-MANROOKIE

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	AAAHOU	60	73	3.22	3.27	31.5%	12.5%	—	K 27.1% · BB 11.3% · FIP 3.75
2025	26	MIX2 levels	32	34	4.81	5.45	21.1%	16.9%	-0.4	K 20.6% · BB 19.2% · FIP 5.41
2026	27	MIX2 levels	62	64	4.38	2.63	29.1%	6.0%	1.5	K 26.7% · BB 6.1% · FIP 2.97
2027PROJ	28	MLBHOU	21	22	4.08	4.08	25.2%	9.2%	0.1
2028PROJ79% MLB	29	MLBHOU	21	22	4.18	4.23	24.8%	9.4%	0.1

Last 3 seasons WAR 1.1 · Next 2 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.3 / P90 0.8, comp-based) · star 0% · didn't stick 91%

CompsScott Atchison (age 28) · Matt Ramsey (age 28) · Josh Lueke (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 111103vR 94

ERA4.08

FIP4.08

K%25.2%

BB%9.2%

K-BB%16.0%

Proj IP31

Value2027 · WAR

Runs saved vs league avg · 31 IP

Grades · Contract

Scouting Grades

K†6060

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)
2022	23	ROK MLE	FCL Astros Orange	4	2	8	28	16	3	0	50%	2.0	57.1%	10.7%	46.4%	0.0%	0.00	-0.37	—
2022	23	ROK RAW	FCL Astros Orange	4	2	8	28	16	3	0	50%	2.0	57.1%	10.7%	46.4%	0.0%	0.00	0.23	—
2023	24	MIX MLE	3 levels	40	0	48	216	63	29	6	0%	1.2	23.9%	14.0%	9.8%	2.7%	3.72	4.34	—
2023	24	MIX RAW	3 levels	40	0	48	216	63	29	6	0%	1.2	29.2%	13.4%	15.7%	2.8%	3.72	3.91	—
2024	25	AAA MLE	Sugar Land Space Cowboys	60	0	73	311	98	39	7	0%	1.2	27.1%	11.3%	15.8%	2.7%	3.22	3.75	—
2024	25	AAA MLE	Sugar Land Space Cowboys	60	0	73	311	98	39	7	0%	1.2	27.1%	11.3%	15.8%	2.7%	3.22	3.75	—
2024	25	AAA RAW	Sugar Land Space Cowboys	60	0	73	311	98	39	7	0%	1.2	31.5%	12.5%	19.0%	2.3%	3.22	3.27	—
2025	26	MIX MLE	2 levels	32	0	34	166	35	28	5	0%	1.1	20.6%	19.2%	1.4%	2.9%	4.81	5.41	-0.3
2025	26	MIX MLE	2 levels	32	0	34	166	35	28	5	0%	1.1	20.6%	19.2%	1.4%	2.9%	4.81	5.41	-0.3
2025	26	MIX RAW	2 levels	32	0	34	166	35	28	5	0%	1.1	21.1%	16.9%	4.2%	3.0%	4.81	5.45	-0.4
2026	27	MIX MLE	2 levels	62	0	64	268	78	16	6	0%	1.0	26.7%	6.1%	20.6%	2.5%	4.38	2.97	+1.2
2026	27	MIX MLE	2 levels	62	0	64	268	78	16	6	0%	1.0	26.7%	6.1%	20.6%	2.5%	4.38	2.97	+1.2
2026	27	MIX RAW	2 levels	62	0	64	268	78	16	6	0%	1.0	29.1%	6.0%	23.1%	2.2%	4.38	2.63	+1.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			19	0	23	95	16	4	3	0%	1.2	16.8%	4.2%	12.6%	3.2%	3.09	3.91	+0.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	HOU	21	0	22	93	23	9	3	0%	1.0	25.2%	9.2%	16.0%	2.8%	4.08	4.08	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	HOU	26	0	27	116	29	11	3	0%	1.1	24.8%	9.4%	15.3%	3.0%	4.18	4.23	+0.1
2028	29	MLB CTX	HOU	21	0	22	93	23	9	3	0%	1.0	24.8%	9.4%	15.3%	3.0%	4.18	4.23	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		40	0	45	186	39	13	6	0%	1.1	20.7%	6.8%	14.0%	3.1%	3.61	3.90	+0.3
/ 200 IP	—	RAW		176	0	200	829	174	58	27	0%	1.1	20.7%	6.8%	14.0%	3.1%	3.61	3.90	+1.5
Career	—	MLE		198	2	226	989	258	117	26	1%	1.1	26.1%	11.8%	14.3%	2.6%	3.78	3.83	+0.3
/ 200 IP	—	MLE		175	2	200	874	228	103	23	1%	1.1	26.1%	11.8%	14.3%	2.6%	3.78	3.83	+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.

2026 AAASugar Land Space Cowboys · 51 IPFIP 2.57 → 2.97 (+0.41)K% 31.1% → 26.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.08%	—	×0.860	26.73%
BB% (unintentional) /BF	6.76%	—	×0.900	6.08%
HR / BF /BF	2.25%	÷1.000	×1.100	2.48%

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 2.57 → 2.97, 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).

2025 AAASugar Land Space Cowboys · 23 IPFIP 5.19 → 5.41 (+0.22)K% 23.9% → 20.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.93%	—	×0.860	20.58%
BB% (unintentional) /BF	21.37%	—	×0.900	19.23%
HR / BF /BF	2.56%	÷0.961	×1.100	2.93%

Result: FIP 5.19 → 5.41, 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 AAASugar Land Space Cowboys · 73 IPFIP 3.26 → 3.75 (+0.48)K% 31.5% → 27.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.51%	—	×0.860	27.10%
BB% (unintentional) /BF	12.54%	—	×0.900	11.29%
HR / BF /BF	2.25%	÷0.903	×1.100	2.74%

Result: FIP 3.26 → 3.75, 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 AACorpus Christi Hooks · 30 IPFIP 4.15 → 4.64 (+0.49)K% 32.6% → 26.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.56%	—	×0.810	26.37%
BB% (unintentional) /BF	13.18%	—	×1.100	14.50%
HR / BF /BF	3.88%	÷1.322	×1.200	3.52%

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 164).

Result: FIP 4.15 → 4.64, 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 A+Asheville Tourists · 17 IPFIP 3.10 → 3.84 (+0.74)K% 25.6% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.64%	—	×0.770	19.74%
BB% (unintentional) /BF	11.54%	—	×1.150	13.27%
HR / BF /BF	1.28%	÷1.218	×1.250	1.32%

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 144).

Result: FIP 3.10 → 3.84, 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 ROKFCL Astros Orange · 8 IPFIP -0.37 → 1.52 (+1.88)K% 57.1% → 38.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	57.14%	—	×0.680	38.86%
BB% (unintentional) /BF	10.71%	—	×1.250	13.39%
HR / BF /BF	0.00%	÷1.056	×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 111).

Result: FIP -0.37 → 1.52, 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
Logan VanWey (OGILVIE)	—	—	4.08	25.2%	9.2%	2.8%	—	4.23	24.8%	15.3%	27	+0.15	—	—	—
Scott Atchison R 2004 · 3.61 FIP	28	SU	3.61	27.1%	9.0%	3.0%	.309	4.55	19.1%	11.5%	31	+0.94	2.52	340	86
Matt Ramsey R 2018 · 3.78 FIP	28	SU	3.78	24.9%	8.8%	3.0%	.276	2.42	21.7%	12.6%	34	-1.36	2.42	125	86
Josh Lueke R 2013 · 4.09 FIP	28	SU	4.09	25.3%	11.1%	3.1%	.333	3.28	24.6%	20.9%	90	-0.81	2.29	191	84
Marcos Mateo R 2011 · 3.40 FIP	27	SU	3.40	25.5%	10.2%	2.1%	.361	—	—	—	—	—	3.12	104	83
Jason Bulger R 2008 · 4.60 FIP	29	SU	4.60	27.4%	12.3%	4.1%	.293	3.94	25.1%	13.3%	90	-0.66	3.78	106	83
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	82
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	82
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	82
Rafael Betancourt R 2003 · 3.81 FIP	28	SU	3.81	23.4%	7.1%	3.2%	.216	2.84	25.0%	20.8%	191	-0.97	1.79	686	81
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	81
Ryan Brasier R 2016 · 3.68 FIP	28	SU	3.68	25.0%	7.7%	3.1%	.289	3.09	24.2%	17.9%	130	-0.59	2.31	426	81
Jason Motte R 2010 · 3.24 FIP	28	SU	3.24	26.0%	7.2%	2.6%	.269	2.69	27.3%	21.8%	140	-0.55	2.22	387	80
Zach Franklin R 2024 · 3.24 FIP	25	SU	3.24	26.4%	10.9%	1.8%	.301	4.15	27.5%	18.3%	117	+0.91	3.24	158	80
Michael Flynn R 2024 · 3.99 FIP	27	SU	3.99	27.6%	8.3%	3.9%	.277	4.68	16.2%	3.7%	50	+0.69	3.89	168	79
Michael Dimock R 2018 · 3.37 FIP	28	SU	3.37	23.5%	10.7%	1.6%	.346	—	—	—	—	—	3.08	166	79
Dayan Díaz R 2017 · 3.45 FIP	28	SU	3.45	25.1%	8.7%	2.5%	.358	3.96	29.4%	19.3%	16	+0.51	3.08	205	78
Kiko Calero R 2003 · 3.54 FIP	28	SU	3.54	31.5%	11.1%	3.1%	.273	3.11	26.1%	18.9%	159	-0.43	2.27	298	78
Ryan Tepera R 2016 · 3.11 FIP	28	SU	3.11	22.6%	8.9%	1.4%	.266	3.81	24.3%	15.9%	164	+0.70	2.35	445	78
Fernando Rodney R 2005 · 3.62 FIP	28	SU	3.62	22.7%	7.6%	2.7%	.274	3.54	23.4%	12.9%	163	-0.08	1.85	933	78
Matt Pushard R 2024 · 3.87 FIP	26	SU	3.87	24.1%	8.9%	3.0%	.242	3.29	22.2%	14.0%	115	-0.58	2.84	220	78

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	0.4	41	22.8%	7.9%	1.15	3.83
Shawn Tolleson ('16)	1.1	54	23.1%	8.3%	1.28	3.92
David Carpenter ('19)	1.1	43	23.5%	8.4%	0.92	3.69
Charlie Furbush ('15)	1.3	52	24.5%	8.1%	1.04	3.97
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*
Gary Wayne ('89-'94, 2 WAR*)	1.2	62	19.9%*	9.4%*	1.05*	3.88*
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*