Brant Hurter

P Detroit Tigers

Age 28 LHP 6'6" / 250 lbs MLB peak 0.3 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	29	19	117	4.55	3.33	21.7%	5.8%	2.2	K 19.7% · BB 5.4% · FIP 3.80
2025	26	MIX2 levels	46	4	67	2.83	2.86	23.8%	8.2%	1.4	K 24.5% · BB 8.7% · FIP 2.95
2026	27	MIX3 levels	38	2	43	4.81	3.33	17.6%	11.2%	0.6	K 16.8% · BB 9.8% · FIP 3.32
2027PROJ	28	MLBDET	51	0	54	3.72	4.05	19.1%	8.1%	0.3
2028PROJ95% MLB	29	MLBDET	47	0	49	4.02	4.21	18.5%	8.3%	0.2
2029PROJ95% MLB	30	MLBDET	44	0	46	4.26	4.42	17.8%	8.6%	0.1

Last 3 seasons WAR 4.2 · Next 3 projected WAR 0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs66

Whiff%18

K%13

FB Velo11

CompsTommy Phelps (age 29) · Hector Hernandez (age 28) · Mark Hendrickson (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 94102vR 110

ERA3.72

FIP4.05

K%19.1%

BB%8.1%

K-BB%11.1%

Proj IP54

Value2027 · WAR

Runs saved vs league avg · 54 IP

Grades · Statcast · Arsenal · Contract

Scouting Grades

STUF4545

CTRL5555

CMD5555

K†4545

Statcast Percentiles

FB Velo

p1191.7

Whiff%

p1820.8%

p1316.8%

xwOBA vs

p660.296

FB+2.2 (59%)

CH (11%)

SI (55%)

SL-0.7 (30%)

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 industry-standard fWAR.

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	MIX MLE	3 levels	25	18	107	437	136	21	7	72%	4.3	23.7%	5.5%	18.2%	1.9%	3.71	2.84	—
2022	23	MIX RAW	3 levels	25	18	107	437	136	21	7	72%	4.3	31.1%	4.8%	26.3%	1.6%	3.71	1.99	—
2023	24	AA MLE	Erie SeaWolves	26	26	118	498	133	33	7	100%	4.5	21.6%	7.3%	14.3%	1.6%	3.28	3.07	—
2023	24	AA RAW	Erie SeaWolves	26	26	118	498	133	33	7	100%	4.5	26.7%	6.6%	20.1%	1.4%	3.28	2.46	—
2024	25	MIX MLE	2 levels	29	19	117	498	108	29	12	66%	4.0	19.7%	5.4%	14.4%	3.1%	4.55	3.80	+1.5
2024	25	MIX MLE	2 levels	29	19	117	498	108	29	12	66%	4.0	19.7%	5.4%	14.4%	3.1%	4.55	3.80	+1.5
2024	25	MIX RAW	2 levels	29	19	117	498	108	29	12	66%	4.0	21.7%	5.8%	15.9%	2.4%	4.55	3.33	+2.2
2025	26	MIX MLE	2 levels	46	4	67	294	70	24	4	9%	1.4	24.5%	8.7%	15.9%	1.5%	2.83	2.95	+1.3
2025	26	MIX MLE	2 levels	46	4	67	294	70	24	4	9%	1.4	24.5%	8.7%	15.9%	1.5%	2.83	2.95	+1.3
2025	26	MIX RAW	2 levels	46	4	67	294	70	24	4	9%	1.4	23.8%	8.2%	15.6%	1.4%	2.83	2.86	+1.4
2026	27	MIX MLE	3 levels	38	2	43	188	33	21	1	5%	1.1	16.8%	9.8%	7.0%	0.7%	4.81	3.32	+0.6
2026	27	MIX MLE	3 levels	38	2	43	188	33	21	1	5%	1.1	16.8%	9.8%	7.0%	0.7%	4.81	3.32	+0.6
2026	27	MIX RAW	3 levels	38	2	43	188	33	21	1	5%	1.1	17.6%	11.2%	6.4%	0.5%	4.81	3.33	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			82	5	144	595	130	44	9	6%	1.8	21.8%	7.4%	14.5%	1.5%	2.63	3.02	+2.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	DET	51	0	54	228	44	18	5	0%	1.1	19.1%	8.1%	11.1%	2.1%	3.72	4.05	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	DET	49	0	52	217	40	18	5	0%	1.1	18.5%	8.3%	10.3%	2.3%	4.02	4.21	+0.2
2029	30	MLB MLE	DET	46	0	48	204	36	18	5	0%	1.1	17.8%	8.6%	9.3%	2.5%	4.26	4.42	+0.1
2028	29	MLB CTX	DET	47	0	49	207	38	17	5	0%	1.0	18.5%	8.3%	10.3%	2.3%	4.02	4.21	+0.2
2029	30	MLB CTX	DET	44	0	46	194	35	17	5	0%	1.0	17.8%	8.6%	9.3%	2.5%	4.26	4.42	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		172	5	239	996	203	78	19	3%	1.4	20.4%	7.8%	12.6%	1.9%	3.23	3.39	+3.3
/ 200 IP	—	RAW		145	4	200	835	170	65	16	3%	1.4	20.4%	7.8%	12.6%	1.9%	3.23	3.39	+2.8
Career	—	MLE		164	69	451	1915	413	131	37	42%	2.8	21.6%	6.8%	14.7%	2.0%	3.79	3.21	+2.9
/ 200 IP	—	MLE		73	31	200	849	183	58	17	42%	2.7	21.6%	6.8%	14.7%	2.0%	3.79	3.21	+2.4

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
Brant Hurter (OGILVIE)	—	—	4.05	19.1%	8.1%	2.1%	—	4.31	18.2%	9.8%	100	+0.26	—	—	—
Tommy Phelps L 2003 · 3.39 FIP	29	SW	3.39	15.6%	8.0%	1.1%	.322	4.47	16.9%	8.9%	57	+1.08	3.39	120	75
Hector Hernandez L 2019 · 3.39 FIP	28	SW	3.39	20.2%	9.0%	1.5%	.290	—	—	—	—	—	2.17	121	73
Mark Hendrickson L 2002 · 3.04 FIP	28	SW	3.04	14.8%	6.3%	0.7%	.216	4.51	10.9%	5.5%	520	+1.47	3.04	1,169	72
John Rheinecker L 2007 · 5.13 FIP	28	SW	5.13	16.7%	10.9%	3.8%	.317	—	—	—	—	—	4.14	121	72
Matt Whitehouse L 2019 · 4.07 FIP	28	SW	4.07	20.1%	10.9%	2.3%	.339	—	—	—	—	—	3.37	353	70
Chad Bell L 2017 · 4.57 FIP	28	SW	4.57	19.4%	8.9%	3.6%	.341	4.38	18.8%	11.4%	57	-0.19	3.39	393	70
Kyle Hunter L 2017 · 4.50 FIP	28	SU	4.50	14.0%	6.1%	3.3%	.335	—	—	—	—	—	4.32	188	68
Ryan Verdugo L 2015 · 3.61 FIP	28	SU	3.61	19.8%	10.8%	1.5%	.281	3.36	22.7%	17.3%	82	-0.25	3.36	153	68
Edgar Olmos L 2017 · 3.64 FIP	27	SW	3.64	18.9%	9.7%	1.7%	.252	—	—	—	—	—	3.19	203	67
Yohan Flande L 2014 · 3.65 FIP	28	SP-	3.65	14.1%	5.8%	1.8%	.266	3.90	14.1%	7.9%	312	+0.25	3.18	394	67
Randy Keisler L 2005 · 5.07 FIP	29	SW	5.07	16.4%	9.9%	3.8%	.295	5.51	6.5%	0.0%	17	+0.44	5.07	135	66
Jimmy Reyes L 2017 · 4.92 FIP	28	SU	4.92	13.8%	8.0%	3.6%	.294	—	—	—	—	—	3.02	200	65
David Huff L 2013 · 4.42 FIP	28	SU	4.42	20.5%	5.3%	4.3%	.248	3.76	17.1%	11.5%	169	-0.66	3.40	540	65
Brian Johnson L 2019 · 4.49 FIP	28	SW	4.49	18.8%	11.2%	2.8%	.349	4.94	15.5%	6.4%	61	+0.45	3.39	506	64
Austin Warner L 2022 · 4.78 FIP	28	SW	4.78	16.9%	9.0%	3.6%	.319	—	—	—	—	—	3.81	491	64
Kelvin Marte L 2016 · 3.44 FIP	28	SU	3.44	16.6%	7.0%	1.6%	.276	4.97	14.3%	3.1%	157	+1.53	3.44	360	63
Brendan Nail L 2023 · 4.36 FIP	27	SU	4.36	19.3%	10.5%	2.8%	.262	—	—	—	—	—	3.45	165	63
Chad Zerbe L 2001 · 3.75 FIP	29	SU	3.75	13.6%	6.2%	1.8%	.299	3.88	9.4%	2.6%	106	+0.13	3.75	145	63
Cesár Ramos L 2012 · 3.06 FIP	28	SU	3.06	24.2%	8.3%	1.7%	.215	3.47	18.6%	11.4%	202	+0.41	2.56	463	63
Carson Teel L 2022 · 4.26 FIP	26	SU	4.26	17.7%	7.1%	3.2%	.355	—	—	—	—	—	3.43	248	63

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,474 reliever careers (754 from 1990-2025 + 720 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	1.5	50	20.1%	8.2%	0.74	3.33
Jared Burton ('14)	1.8	60	19.9%	8.9%	0.77	3.44
Alex Colomé ('23)	2.7	60	21.0%	8.3%	0.83	3.36
Sam Dyson ('19)	1.9	64	19.1%	8.0%	0.72	3.40
Bill Landrum ('86-'93, 4 WAR*)	1.8	60	18.2%*	8.1%*	0.64*	3.86*
Steve Olin ('89-'92, 4 WAR*)	1.4	68	20.3%*	7.5%*	0.64*	3.30*
Fred Gladding ('61-'73, 6 WAR*)	3.0	67	19.6%*	8.6%*	0.76*	3.76*