Matt Brash — OGILVIE

Matt Brash P Seattle Mariners

Age 28 RHP 6'1" / 173 lbs MLB Svc 3.0 · Ctrl thru 2028 peak 0.8 · 2026 ILInjured 60-Day (D60)

2026 ROS PROJECTION18 act + 2 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 8981vR 73

ERA3.05

FIP2.94

K%29.4%

BB%8.0%

K-BB%21.4%

ROS IP2

Value2026 · WAR

Runs saved vs league avg · 20 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit+$3M ctrl surplus

Grades · Statcast · Arsenal · Contract

Scouting Grades

STUF6060

CTRL4545

CMD6060

K†7070

Statcast Percentiles

FB Velo

p7896.5

Whiff%

p9032.1%

p5723.4%

xwOBA vs

p460.316

SL+1.9 (60%)

CH+1.0 (13%)

FB+0.8 (27%)

SI (21%)

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status Arb-1

MLB Debut 2022

Service 3.703 yrs.days

Team Control Through 2028

First FA Year 2029

Year	Status	Salary	Proj WAR	Value	Surplus
2026ROS	Ext	$0.1M	+0.0	$0.2M	+$0.1M
2027	Arb-2	$4M	+0.8	$3M	+$0.0M (cut)
2028	Arb-3	$4M	+0.6	$2M	+$0.0M (cut)
Totals		$0.1M		$5M	+$0.1M

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 + 2026 so far)
2019	21	MIX MLE	2 levels	5	1	5	20	8	0	0	20%	1.1	40.0%	0.0%	40.0%	0.0%	1.69	-0.28	—
2019	21	MIX RAW	2 levels	5	1	5	20	8	0	0	20%	1.1	40.0%	0.0%	40.0%	0.0%	1.69	0.10	—
2021	23	MIX MLE	2 levels	20	19	97	405	142	48	6	95%	4.9	27.8%	13.3%	14.4%	1.9%	2.31	3.46	—
2021	23	MIX RAW	2 levels	20	19	97	405	142	48	6	95%	4.9	35.1%	11.9%	23.2%	1.5%	2.31	2.46	—
2022	24	MIX MLE	2 levels	61	5	77	329	103	46	7	8%	1.3	29.8%	14.2%	15.6%	2.1%	4.11	3.54	+0.9
2022	24	MIX RAW	2 levels	61	5	77	329	103	46	7	8%	1.3	31.3%	14.0%	17.3%	2.1%	4.11	3.40	+1.1
2023	25	MLB MLE	Seattle Mariners	78	0	71	308	107	29	3	0%	0.9	34.7%	9.4%	25.3%	1.0%	3.06	1.91	+2.2
2023	25	MLB MLE	Seattle Mariners	78	0	71	308	107	29	3	0%	0.9	34.7%	9.4%	25.3%	1.0%	3.06	1.91	+2.2
2023	25	MLB RAW	Seattle Mariners	78	0	71	308	107	29	3	0%	0.9	34.7%	9.4%	25.3%	1.0%	3.06	1.85	+2.3
2025	27	MIX MLE	2 levels	59	0	53	227	63	18	5	0%	0.9	29.1%	8.0%	21.1%	2.1%	3.08	2.79	+1.1
2025	27	MIX MLE	2 levels	59	0	53	227	63	18	5	0%	0.9	29.1%	8.0%	21.1%	2.1%	3.08	2.79	+1.1
2025	27	MIX RAW	2 levels	59	0	53	227	63	18	5	0%	0.9	27.8%	7.9%	19.8%	2.2%	3.08	2.97	+1.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			190	5	185	793	242	82	10	3%	1.0	30.5%	10.3%	20.2%	1.3%	3.06	2.52	+4.5
▸ 2026 season
YTD	28	MLB MLE	Seattle Mariners	22	0	18	71	19	7	0	0%	0.8	23.4%	7.8%	15.6%	0.0%	0.49	2.11	+0.5
YTD	28	MLB MLE	Seattle Mariners	22	0	18	71	19	7	0	0%	0.8	23.4%	7.8%	15.6%	0.0%	0.49	2.11	+0.5
▸ 2026 season — so far · projected rest · full
2026	28	AAA RAW	SEA	2	0	2	7	4	2	0	0%	0.8	57.1%	28.6%	28.6%	0.0%	0.00	1.89	—
2026	28	MLB RAW	SEA	20	0	17	64	15	5	0	0%	0.8	23.4%	7.8%	15.6%	0.0%	0.54	2.11	+0.5
SO FAR	28	MLB RAW	SEA	20	0	17	64	15	5	0	0%	0.8	23.4%	7.8%	15.6%	0.0%	0.54	2.11	+0.5
ROS	28	MLB MLE	SEA	2	0	2	7	2	1	0	0%	0.8	29.4%	8.0%	21.4%	2.4%	3.05	2.94	+0.0
ROS	28	MLB CTX	SEA	2	0	2	8	2	1	0	0%	1.0	29.4%	8.0%	21.4%	2.3%	3.02	2.91	+0.0
2026 TOT	28	MLB MLE	SEA	—	—	20	78	21	8	0	—	—	27.0%	9.7%	17.3%	0.2%	0.70	2.18	+0.6
FULL	28	MLB A+C	SEA	—	—	18	77	21	8	0	—	—	27.2%	9.8%	17.4%	0.2%	0.76	2.15	+0.6
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	29	MLB MLE	SEA	54	0	57	239	70	20	6	0%	1.0	29.4%	8.2%	21.2%	2.3%	3.30	3.32	+0.9
2028	30	MLB MLE	SEA	51	0	53	225	65	19	6	0%	1.0	28.7%	8.5%	20.2%	2.5%	3.43	3.52	+0.7
2027	29	MLB CTX	SEA	51	0	54	228	67	19	5	0%	1.1	29.4%	8.2%	21.2%	2.3%	3.27	3.29	+0.8
2028	30	MLB CTX	SEA	49	0	51	215	62	18	5	0%	1.0	28.7%	8.5%	20.2%	2.5%	3.40	3.49	+0.6
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		291	5	291	1240	372	119	21	2%	1.0	30.0%	9.6%	20.4%	1.7%	3.16	2.70	+6.5
/ 200 IP	—	RAW		200	3	200	852	255	82	14	2%	1.0	30.0%	9.6%	20.4%	1.7%	3.16	2.70	+4.4
Career	—	MLE		245	25	321	1360	408	154	22	10%	1.3	30.0%	11.3%	18.7%	1.6%	2.92	2.89	+6.0
/ 200 IP	—	MLE		153	16	200	847	254	96	14	10%	1.3	30.0%	11.3%	18.7%	1.6%	2.92	2.89	+4.1

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
Matt Brash (OGILVIE)	—	—	3.20	31.4%	8.0%	2.5%	—	3.42	29.1%	20.7%	110	+0.22	—	—	—
Daniel Hudson R 2015 · 3.35 FIP	28	SU	3.35	24.5%	7.9%	2.4%	.302	3.78	22.8%	13.6%	168	+0.43	1.68	468	78
Jake Cousins R 2022 · 3.15 FIP	28	SU	3.15	30.9%	11.9%	2.1%	.265	3.86	30.9%	19.0%	65	+0.71	1.11	160	76
Bryan Shaw R 2016 · 3.73 FIP	28	SU	3.73	25.1%	9.1%	2.9%	.277	3.83	21.1%	12.7%	203	+0.10	2.78	596	76
Trevor May R 2018 · 3.74 FIP	28	SU	3.74	26.1%	9.8%	2.9%	.291	3.47	31.9%	23.6%	150	-0.27	3.05	432	75
Liam Hendriks R 2017 · 3.30 FIP	28	SU	3.30	28.6%	8.4%	2.8%	.303	1.71	35.2%	30.1%	160	-1.59	0.63	495	74
Chris Hatcher R 2015 · 2.92 FIP	30	SU	2.92	27.1%	6.6%	2.3%	.292	4.67	22.6%	14.0%	137	+1.75	2.92	176	74
Pedro Báez R 2016 · 3.63 FIP	28	SU	3.63	28.1%	7.5%	3.6%	.229	3.39	24.6%	15.8%	190	-0.24	2.29	332	74
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	73
Arodys Vizcaíno R 2018 · 3.47 FIP	27	SU	3.47	25.3%	8.9%	2.5%	.260	—	—	—	—	—	2.28	183	73
John Brebbia R 2018 · 3.20 FIP	28	SU	3.20	30.0%	6.4%	3.3%	.317	3.09	29.3%	22.2%	106	-0.11	2.89	575	73
AJ Ramos R 2015 · 2.89 FIP	28	SU	2.89	31.4%	9.4%	2.3%	.247	3.43	26.8%	14.0%	142	+0.54	2.55	266	73
Mychal Givens R 2018 · 2.66 FIP	28	SU	2.66	24.9%	8.2%	1.1%	.274	4.13	29.1%	18.9%	136	+1.47	1.77	526	73
Matt Bush R 2016 · 2.87 FIP	30	SU	2.87	24.7%	6.0%	2.0%	.232	3.94	22.2%	12.7%	75	+1.07	2.87	249	72
Cody Allen R 2017 · 3.04 FIP	28	SU	3.04	32.6%	7.4%	3.2%	.300	5.02	27.0%	14.6%	90	+1.98	1.58	295	72
Jumbo Diaz R 2015 · 3.16 FIP	31	SU	3.16	25.2%	6.0%	2.6%	.286	3.65	21.9%	12.2%	152	+0.49	2.80	284	72
Spencer Patton R 2016 · 2.79 FIP	28	SU	2.79	30.3%	12.2%	1.3%	.290	—	—	—	—	—	2.79	239	72
Jay Jackson R 2015 · 2.36 FIP	27	SU	2.36	24.1%	6.2%	0.9%	.320	—	—	—	—	—	2.36	261	71
Jason Stoffel R 2016 · 3.49 FIP	27	SU	3.49	27.2%	8.0%	3.0%	.293	—	—	—	—	—	3.49	103	70
Hansel Robles R 2019 · 2.67 FIP	28	SU	2.67	26.5%	5.3%	2.1%	.278	4.57	23.3%	10.8%	128	+1.90	2.67	469	70
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	70

Career Comps

Retired MLB careers whose totals most resemble what we're projecting for this player. Pool: 133 completed pitcher careers (2015-2024).

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	0.8	55	29.9%	8.3%	0.95	3.35
Keone Kela ('19)	1.1	43	30.1%	9.4%	0.92	3.23
Diego Castillo ('22)	1.3	52	28.1%	8.9%	1.07	3.12
Sean Doolittle ('21)	1.2	49	28.7%	6.2%	1.18	3.31
Colin Poche ('24)	1.0	52	27.0%	9.2%	1.34	3.63
Seunghwan Oh ('18)	1.0	69	27.7%	5.9%	1.00	2.78
Giovanny Gallegos ('24)	1.5	52	29.4%	6.6%	1.19	3.46