Matt Brash

P Seattle Mariners

Age 29 RHP 6'1" / 173 lbs MLB peak 0.5 · 2027 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	25	MLBSEA	78	71	3.06	1.85	34.7%	9.4%	2.3
2025	27	MIX2 levels	59	53	3.08	2.97	27.8%	7.9%	1.0	K 29.1% · BB 8.0% · FIP 2.79
2026	28	MIX2 levels	22	18	0.49	2.17	26.8%	9.9%	0.5	K 23.4% · BB 7.8% · FIP 2.11
2027PROJ	29	MLBSEA	34	36	3.40	3.34	28.9%	7.7%	0.5
2028PROJ95% MLB	30	MLBSEA	46	48	3.49	3.55	28.2%	8.0%	0.6
2029PROJ95% MLB	31	MLBSEA	39	41	3.67	3.78	27.5%	8.4%	0.4

Last 3 seasons WAR 3.8 · Next 3 projected WAR 1.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo78

K%57

xwOBA vs46

CompsJumbo Diaz (age 30) · Daniel Robert (age 29) · Kaleb Ort (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9789vR 80

ERA3.40

FIP3.34

K%28.9%

BB%7.7%

K-BB%21.2%

Proj IP36

Value2027 · WAR

Runs saved vs league avg · 36 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL4545

CMD6060

K†6565

Statcast Percentiles

FB Velo

p7896.5

Whiff%

p9032.1%

p5723.4%

xwOBA vs

p460.316

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)
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 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
2026	28	MIX MLE	2 levels	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	28	MIX MLE	2 levels	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	28	MIX RAW	2 levels	22	0	18	71	19	7	0	0%	0.8	26.8%	9.9%	16.9%	0.0%	0.49	2.17	+0.5
▸ 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
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	SEA	34	0	36	152	44	12	4	0%	1.1	28.9%	7.7%	21.2%	2.4%	3.40	3.34	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	SEA	49	0	51	215	61	17	6	0%	1.0	28.2%	8.0%	20.2%	2.6%	3.49	3.55	+0.6
2029	31	MLB MLE	SEA	41	0	43	182	50	15	5	0%	1.0	27.5%	8.4%	19.1%	2.9%	3.67	3.78	+0.4
2028	30	MLB CTX	SEA	46	0	48	203	57	16	5	0%	1.0	28.2%	8.0%	20.2%	2.6%	3.49	3.55	+0.6
2029	31	MLB CTX	SEA	39	0	41	173	48	14	5	0%	1.1	27.5%	8.4%	19.1%	2.9%	3.67	3.78	+0.4
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		275	5	275	1170	347	113	20	2%	1.0	29.7%	9.6%	20.0%	1.7%	3.23	2.77	+5.9
/ 200 IP	—	RAW		200	4	200	852	253	82	15	2%	1.0	29.7%	9.6%	20.0%	1.7%	3.23	2.77	+4.3
Career	—	MLE		245	25	321	1360	408	154	22	10%	1.3	30.0%	11.3%	18.7%	1.6%	2.92	2.89	+5.5
/ 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	+4.0

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.

2025 AAATacoma Rainiers · 5 IPFIP 4.46 → 4.41 (−0.05)K% 17.9% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.86%	—	×0.860	15.36%
BB% (unintentional) /BF	7.14%	—	×0.900	6.43%
HR / BF /BF	3.57%	÷1.204	×1.100	3.26%

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 141).

Result: FIP 4.46 → 4.41, 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).

2022 AAATacoma Rainiers · 26 IPFIP 3.57 → 3.97 (+0.39)K% 38.3% → 33.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.32%	—	×0.880	33.72%
BB% (unintentional) /BF	13.08%	—	×1.050	13.74%
HR / BF /BF	3.74%	÷1.144	×1.100	3.60%

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 129).

Result: FIP 3.57 → 3.97, 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).

2021 AAArkansas Travelers · 55 IPFIP 2.11 → 3.08 (+0.97)K% 36.0% → 29.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.04%	—	×0.810	29.19%
BB% (unintentional) /BF	10.36%	—	×1.100	11.40%
HR / BF /BF	1.35%	÷0.892	×1.200	1.82%

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 78).

Result: FIP 2.11 → 3.08, 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 A+Everett AquaSox · 42 IPFIP 2.87 → 3.93 (+1.06)K% 33.9% → 26.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.88%	—	×0.770	26.09%
BB% (unintentional) /BF	13.66%	—	×1.150	15.71%
HR / BF /BF	1.64%	÷1.078	×1.250	1.90%

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 116).

Result: FIP 2.87 → 3.93, 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
Matt Brash (OGILVIE)	—	—	3.34	28.9%	7.7%	2.4%	—	3.66	27.9%	19.7%	94	+0.32	—	—	—
Jumbo Diaz R 2014 · 2.87 FIP	30	SU	2.87	26.1%	7.0%	2.0%	.283	3.64	23.0%	15.0%	186	+0.77	2.80	319	78
Daniel Robert R 2024 · 2.90 FIP	29	SU	2.90	26.6%	7.0%	2.1%	.190	3.14	24.1%	14.6%	43	+0.24	2.32	186	76
Kaleb Ort R 2021 · 2.91 FIP	29	SU	2.91	27.3%	9.4%	1.7%	.310	3.98	24.8%	15.3%	157	+1.07	1.75	423	75
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	72
Robert Coello R 2013 · 2.56 FIP	28	SU	2.56	31.5%	11.0%	1.3%	.317	4.31	13.4%	2.8%	95	+1.75	2.56	112	72
Jon Edwards R 2018 · 2.40 FIP	30	SU	2.40	30.3%	7.7%	1.6%	.304	4.43	25.1%	13.5%	49	+2.03	2.40	132	71
Brendan Donnelly R 2002 · 2.38 FIP	31	SU	2.38	27.1%	8.0%	1.0%	.236	3.06	25.1%	17.9%	181	+0.68	2.23	385	71
David Carpenter R 2014 · 2.84 FIP	29	SU	2.84	25.9%	6.2%	2.1%	.327	4.98	15.8%	5.8%	50	+2.14	2.66	275	71
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	70
John Brebbia R 2019 · 2.89 FIP	29	SU	2.89	28.6%	8.2%	2.1%	.285	3.34	22.8%	17.4%	102	+0.45	2.89	576	70
Cody Hall R 2017 · 4.03 FIP	29	SU	4.03	26.8%	10.0%	3.5%	.299	3.92	25.9%	8.4%	19	-0.11	3.51	134	70
Kiko Calero R 2004 · 3.05 FIP	29	SU	3.05	28.0%	5.4%	3.0%	.206	3.33	23.1%	14.6%	154	+0.28	2.27	298	70
Matt Magill R 2019 · 3.40 FIP	29	SU	3.40	27.9%	7.4%	3.1%	.312	—	—	—	—	—	3.40	287	69
Marcos Mateo R 2011 · 3.40 FIP	27	SU	3.40	25.5%	10.2%	2.1%	.361	—	—	—	—	—	3.12	104	69
Manny Acosta R 2010 · 3.61 FIP	29	SU	3.61	26.8%	10.8%	2.5%	.277	4.12	21.9%	12.6%	94	+0.51	3.08	350	69
Jay Jackson R 2015 · 2.36 FIP	27	SU	2.36	24.1%	6.2%	0.9%	.320	—	—	—	—	—	2.36	261	69
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	68
Jason Adam R 2021 · 2.55 FIP	29	SU	2.55	38.0%	12.0%	2.1%	.375	2.72	30.3%	23.1%	191	+0.17	2.42	396	68
Jason Stoffel R 2016 · 3.49 FIP	27	SU	3.49	27.2%	8.0%	3.0%	.293	—	—	—	—	—	3.49	103	68
Jake Cousins R 2023 · 4.38 FIP	29	SU	4.38	27.3%	11.4%	3.9%	.379	3.42	34.2%	21.9%	38	-0.96	1.11	160	68

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	53	29.5%	9.7%	0.71	3.25
Jordan Walden ('15)	1.1	56	28.6%	10.3%	0.53	3.00
Kiko Calero ('09)	1.5	50	26.0%	10.1%	0.71	3.24
Hung-Chih Kuo ('11)	1.5	49	28.1%	10.4%	0.55	3.73
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*
Rob Murphy ('85-'95, 6 WAR*)	3.1	69	25.2%*	9.2%*	1.07*	3.94*