Will Vest

P Detroit Tigers

Age 32 RHP 6'0" / 180 lbs MLB peak 0.3 · 2027 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MLBDET	69	70	2.82	2.55	21.8%	5.5%	1.7
2025	30	MLBDET	64	69	3.01	2.59	26.4%	7.4%	1.6
2026	31	MIX2 levels	28	28	5.86	3.10	23.5%	8.4%	0.5	K 23.3% · BB 8.6% · FIP 3.21
2027PROJ	32	MLBDET	27	28	3.57	3.52	25.1%	7.5%	0.4
2028PROJ95% MLB	33	MLBDET	31	33	3.71	3.80	24.3%	8.0%	0.3

Last 3 seasons WAR 3.8 · Next 2 projected WAR 0.7Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo68

K%56

xwOBA vs55

CompsJumbo Diaz (age 32) · Jose Veras (age 32) · Josh Fields (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10092vR 84

ERA3.57

FIP3.52

K%25.1%

BB%7.5%

K-BB%17.6%

Proj IP28

Value2027 · WAR

Runs saved vs league avg · 28 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL5555

CMD5555

K†6060

Statcast Percentiles

FB Velo

p6895.8

Whiff%

p6427.5%

p5623.3%

xwOBA vs

p550.307

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	23	MIX MLE	2 levels	30	0	49	221	56	13	1	0%	1.6	18.9%	6.9%	12.0%	0.4%	5.18	2.62	—
2018	23	MIX RAW	2 levels	30	0	49	221	56	13	1	0%	1.6	25.3%	5.9%	19.5%	0.5%	5.18	1.87	—
2019	24	MIX MLE	3 levels	37	0	55	226	58	17	6	0%	1.5	21.8%	8.5%	13.3%	2.5%	3.27	3.71	—
2019	24	MIX RAW	3 levels	37	0	55	226	58	17	6	0%	1.5	25.7%	7.5%	18.1%	2.7%	3.27	3.34	—
2021	26	MIX MLE	2 levels	55	0	61	265	52	26	5	0%	1.1	18.5%	10.0%	8.5%	2.0%	5.64	3.88	+0.5
2021	26	MIX RAW	2 levels	55	0	61	265	52	26	5	0%	1.1	19.6%	9.8%	9.8%	1.9%	5.64	3.74	+0.6
2022	27	MIX MLE	2 levels	60	2	64	276	64	22	6	3%	1.1	23.2%	8.1%	15.1%	2.3%	3.94	3.43	+0.9
2022	27	MIX RAW	2 levels	60	2	64	276	64	22	6	3%	1.1	23.2%	8.0%	15.2%	2.2%	3.94	3.35	+0.9
2023	28	MIX MLE	2 levels	59	5	61	258	76	21	8	8%	1.0	28.4%	7.8%	20.6%	3.6%	4.11	3.66	+0.7
2023	28	MIX RAW	2 levels	59	5	61	258	76	21	8	8%	1.0	29.5%	8.1%	21.3%	3.1%	4.11	3.34	+0.9
2024	29	MLB MLE	Detroit Tigers	69	0	70	289	63	16	3	0%	1.0	21.8%	5.5%	16.3%	1.1%	2.82	2.56	+1.7
2024	29	MLB MLE	Detroit Tigers	69	0	70	289	63	16	3	0%	1.0	21.8%	5.5%	16.3%	1.1%	2.82	2.56	+1.7
2024	29	MLB RAW	Detroit Tigers	69	0	70	289	63	16	3	0%	1.0	21.8%	5.5%	16.3%	1.0%	2.82	2.55	+1.7
2025	30	MLB MLE	Detroit Tigers	64	0	69	284	75	21	4	0%	1.1	26.4%	7.4%	19.0%	1.5%	3.01	2.61	+1.6
2025	30	MLB MLE	Detroit Tigers	64	0	69	284	75	21	4	0%	1.1	26.4%	7.4%	19.0%	1.5%	3.01	2.61	+1.6
2025	30	MLB RAW	Detroit Tigers	64	0	69	284	75	21	4	0%	1.1	26.4%	7.4%	19.0%	1.4%	3.01	2.59	+1.6
2026	31	MIX MLE	2 levels	28	0	28	119	28	10	2	0%	1.0	23.3%	8.6%	14.7%	1.8%	5.86	3.21	+0.4
2026	31	MIX MLE	2 levels	28	0	28	119	28	10	2	0%	1.0	23.3%	8.6%	14.7%	1.8%	5.86	3.21	+0.4
2026	31	MIX RAW	2 levels	28	0	28	119	28	10	2	0%	1.0	23.5%	8.4%	15.1%	1.7%	5.86	3.10	+0.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			299	6	312	1316	311	99	20	2%	1.0	23.6%	7.5%	16.1%	1.5%	3.78	2.89	+6.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	DET	27	0	28	118	30	9	3	0%	1.0	25.1%	7.5%	17.6%	2.2%	3.57	3.52	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	DET	34	0	35	149	36	12	4	0%	1.0	24.3%	8.0%	16.3%	2.5%	3.71	3.80	+0.3
2028	33	MLB CTX	DET	31	0	33	139	34	11	3	0%	1.1	24.3%	8.0%	16.3%	2.5%	3.71	3.80	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		331	6	345	1457	345	110	23	2%	1.0	23.7%	7.6%	16.1%	1.6%	3.77	2.94	+6.6
/ 200 IP	—	RAW		192	3	200	844	200	64	13	2%	1.0	23.7%	7.6%	16.1%	1.6%	3.77	2.94	+3.8
Career	—	MLE		402	7	456	1938	443	150	37	2%	1.1	22.9%	7.8%	15.1%	1.9%	4.04	3.20	+6.5
/ 200 IP	—	MLE		176	3	200	849	194	66	16	2%	1.1	22.9%	7.8%	15.1%	1.9%	4.04	3.20	+3.7

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.

2023 AAAToledo Mud Hens · 13 IPFIP 6.82 → 8.06 (+1.23)K% 33.9% → 29.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.90%	—	×0.860	29.15%
BB% (unintentional) /BF	15.25%	—	×0.900	13.73%
HR / BF /BF	8.47%	÷0.901	×1.100	10.34%

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 80).

Result: FIP 6.82 → 8.06, 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).

2021 AAAToledo Mud Hens · 26 IPFIP 3.60 → 3.95 (+0.35)K% 22.9% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.94%	—	×0.880	20.18%
BB% (unintentional) /BF	7.34%	—	×1.050	7.71%
HR / BF /BF	2.75%	÷1.052	×1.100	2.88%

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 110).

Result: FIP 3.60 → 3.95, 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 AAErie SeaWolves · 27 IPFIP 4.03 → 4.32 (+0.29)K% 21.2% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.19%	—	×0.810	17.16%
BB% (unintentional) /BF	6.78%	—	×1.100	7.46%
HR / BF /BF	3.39%	÷1.294	×1.200	3.14%

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 159).

Result: FIP 4.03 → 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).

2019 A+Lakeland Flying Tigers · 21 IPFIP 1.74 → 2.83 (+1.09)K% 37.0% → 28.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.04%	—	×0.770	28.52%
BB% (unintentional) /BF	8.64%	—	×1.150	9.94%
HR / BF /BF	1.23%	÷0.963	×1.250	1.60%

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 93).

Result: FIP 1.74 → 2.83, 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).

2019 AAAToledo Mud Hens · 7 IPFIP 5.13 → 5.78 (+0.64)K% 11.1% → 9.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	11.11%	—	×0.880	9.78%
BB% (unintentional) /BF	7.41%	—	×1.050	7.78%
HR / BF /BF	3.70%	÷0.888	×1.100	4.59%

Result: FIP 5.13 → 5.78, 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).

2018 AWest Michigan Whitecaps · 35 IPFIP 1.66 → 2.41 (+0.76)K% 27.3% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.33%	—	×0.740	20.22%
BB% (unintentional) /BF	6.83%	—	×1.180	8.06%
HR / BF /BF	0.00%	÷0.942	×1.300	0.00%

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 88).

Result: FIP 1.66 → 2.41, 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).

2018 A+Lakeland Flying Tigers · 13 IPFIP 2.75 → 3.18 (+0.43)K% 20.0% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.770	15.40%
BB% (unintentional) /BF	3.33%	—	×1.150	3.83%
HR / BF /BF	1.67%	÷1.277	×1.250	1.63%

Result: FIP 2.75 → 3.18, 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
Will Vest (OGILVIE)	—	—	3.52	25.1%	7.5%	2.2%	—	3.80	24.3%	16.3%	35	+0.28	—	—	—
Jumbo Diaz R 2016 · 3.85 FIP	32	SU	3.85	22.3%	9.2%	2.7%	.247	3.28	23.0%	13.8%	141	-0.57	2.80	319	77
Jose Veras R 2013 · 3.51 FIP	32	SU	3.51	23.6%	8.3%	2.5%	.234	4.28	21.9%	10.2%	65	+0.77	3.37	422	76
Josh Fields R 2018 · 3.48 FIP	32	SU	3.48	21.4%	6.5%	2.5%	.224	7.56	18.9%	9.5%	25	+4.08	1.80	330	75
Matt Lindstrom R 2012 · 2.71 FIP	32	SU	2.71	20.0%	6.0%	1.0%	.295	3.34	15.4%	7.9%	117	+0.63	2.40	443	75
Shawn Camp R 2008 · 2.79 FIP	32	SU	2.79	18.7%	4.8%	1.2%	.304	3.63	14.8%	9.2%	218	+0.84	2.79	589	74
Arcenio Leon R 2019 · 3.61 FIP	32	SU	3.61	21.4%	8.1%	2.4%	.314	—	—	—	—	—	3.00	115	74
Sergio Santos R 2015 · 4.17 FIP	32	SU	4.17	24.7%	8.2%	3.9%	.283	—	—	—	—	—	1.36	178	73
Dale Thayer R 2013 · 3.62 FIP	32	SU	3.62	23.7%	7.4%	2.9%	.287	3.85	20.6%	15.0%	103	+0.23	2.75	239	73
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	73
Mark Serrano R 2017 · 3.56 FIP	31	SU	3.56	21.9%	6.4%	2.7%	.240	5.25	20.2%	12.3%	42	+1.69	3.16	120	72
Grant Balfour R 2010 · 2.59 FIP	32	SU	2.59	25.2%	6.8%	1.4%	.270	3.50	25.6%	16.7%	199	+0.91	2.04	533	72
Ryan Brasier R 2020 · 2.97 FIP	32	SU	2.97	27.3%	9.1%	1.9%	.324	3.30	23.4%	17.1%	134	+0.33	2.31	426	72
Chris Hatcher R 2017 · 4.31 FIP	32	SU	4.31	24.5%	7.4%	4.3%	.291	5.32	18.0%	8.4%	36	+1.01	2.51	246	72
Jared Burton R 2013 · 3.20 FIP	32	SU	3.20	21.7%	6.0%	2.1%	.279	3.92	18.4%	10.0%	78	+0.72	3.09	367	72
Santiago Casilla R 2012 · 3.98 FIP	32	SU	3.98	20.2%	6.6%	3.2%	.246	3.23	21.6%	13.7%	166	-0.75	2.76	647	72
James Hoyt R 2019 · 3.45 FIP	32	SU	3.45	22.2%	9.9%	1.8%	.355	5.63	22.1%	10.4%	50	+2.18	1.61	312	71
Mike Broadway R 2018 · 4.65 FIP	31	SU	4.65	23.0%	10.6%	3.9%	.282	—	—	—	—	—	1.74	195	71
Hirokazu Sawamura R 2021 · 4.48 FIP	33	SU	4.48	26.2%	11.2%	4.0%	.263	4.02	18.1%	6.8%	51	-0.46	4.02	104	71
Steve Delabar R 2015 · 3.74 FIP	32	SU	3.74	25.0%	9.9%	2.7%	.246	4.62	20.4%	4.8%	24	+0.88	2.43	229	71
Jean Machi R 2014 · 3.33 FIP	32	SU	3.33	20.5%	6.0%	2.2%	.225	4.34	17.8%	10.6%	186	+1.01	2.16	306	70

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	1.9	47	23.8%	7.8%	0.64	3.76
Aaron Loup ('23)	2.6	52	21.8%	7.4%	0.68	3.43
Bobby Jenks ('11)	1.8	60	23.4%	8.2%	0.65	3.53
Heath Bell ('14)	3.1	63	24.2%	8.1%	0.69	3.49
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*
Carlos Diaz ('82-'86, 2 WAR*)	1.3	52	25.1%*	8.7%*	0.91*	3.84*
Fred Gladding ('61-'73, 6 WAR*)	3.0	67	19.6%*	8.6%*	0.76*	3.76*