Bryan Woo

P Seattle Mariners

Age 27 RHP 6'2" / 205 lbs MLB Svc 3.0 · Ctrl thru 2029 peak 3.3 · 2027

Overview

MLBSP40-MANArb-1FA 2030

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	MIX3 levels	26	26	135	2.73	3.10	23.0%	2.9%	3.9	K 21.4% · BB 2.8% · FIP 3.31
2025	25	MLBSEA	30	30	187	2.94	3.37	27.1%	4.9%	4.7
2026	26	MLBSEA	30	30	173	4.01	3.09	24.6%	5.4%	5.0
2027PROJ	27	MLBSEA	25	25	150	3.51	3.61	25.5%	5.1%	3.3
2028PROJ	28	MLBSEA	22	22	133	3.58	3.66	25.4%	5.3%	2.7
2029PROJ	29	MLBSEA	20	20	119	3.72	3.82	24.8%	5.5%	2.2

Last 3 seasons WAR 13.6 · Next 3 projected WAR 8.2Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2029Service3.703First FA2030

2027Arb-1$7M2028Arb-2$10M2029Arb-3$12M

Skills · percentileStatcast 2026

FB Velo72

xwOBA vs66

K%63

Form2.35 ERA (proj 3.51) · K 25.6% (proj 25.5%) · BB 7.0% (proj 5.1%) · last 60d · 31 IP through Oct 27

CompsGeorge Kirby (age 26) · Chris Archer (age 27) · Logan Gilbert (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9991vR 83

ERA3.51

FIP3.61

K%25.5%

BB%5.1%

K-BB%20.3%

Proj IP150

Value2027 · WAR

Runs saved vs league avg · 150 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$37M ctrl surplus

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL7070

CMD6060

K†6060

Statcast Percentiles

FB Velo

p7296.1

Whiff%

p5025.2%

p6324.6%

xwOBA vs

p660.296

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

Status Arb-1

MLB Debut 2023

Service 3.703 yrs.days

Team Control Through 2029

First FA Year 2030

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-1	$7M	+3.3	$32M	+$25M
2028	Arb-2	$10M	+2.7	$21M	+$12M
2029	Arb-3	$12M	+2.2	$15M	+$5M
Totals		$29M		$68M	+$42M

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	22	MIX MLE	3 levels	16	16	57	250	84	22	4	100%	3.6	24.4%	10.9%	13.5%	2.2%	4.11	3.62	—
2022	22	MIX RAW	3 levels	16	16	57	250	84	22	4	100%	3.6	33.6%	8.8%	24.8%	1.6%	4.11	2.22	—
2023	23	MIX MLE	2 levels	27	27	132	543	152	42	15	100%	4.9	25.9%	8.0%	18.0%	3.0%	3.49	3.55	+3.0
2023	23	MIX RAW	2 levels	27	27	132	543	152	42	15	100%	4.9	28.0%	7.7%	20.3%	2.8%	3.49	3.23	+3.5
2024	24	MIX MLE	3 levels	26	26	135	521	120	15	15	100%	5.2	21.4%	2.8%	18.6%	3.0%	2.73	3.31	+3.5
2024	24	MIX MLE	3 levels	26	26	135	521	120	15	15	100%	5.2	21.4%	2.8%	18.6%	3.0%	2.73	3.31	+3.5
2024	24	MIX RAW	3 levels	26	26	135	521	120	15	15	100%	5.2	23.0%	2.9%	20.2%	2.9%	2.73	3.10	+3.9
2025	25	MLB MLE	Seattle Mariners	30	30	187	731	198	36	26	100%	6.2	27.1%	4.9%	22.2%	3.6%	2.94	3.44	+4.5
2025	25	MLB MLE	Seattle Mariners	30	30	187	731	198	36	26	100%	6.2	27.1%	4.9%	22.2%	3.6%	2.94	3.44	+4.5
2025	25	MLB RAW	Seattle Mariners	30	30	187	731	198	36	26	100%	6.2	27.1%	4.9%	22.2%	3.6%	2.94	3.37	+4.7
2026	26	MLB MLE	Seattle Mariners	30	30	173	710	175	38	18	100%	5.8	24.6%	5.4%	19.3%	2.6%	4.01	3.12	+4.9
2026	26	MLB MLE	Seattle Mariners	30	30	173	710	175	38	18	100%	5.8	24.6%	5.4%	19.3%	2.6%	4.01	3.12	+4.9
2026	26	MLB RAW	Seattle Mariners	30	30	173	710	175	38	18	100%	5.8	24.6%	5.4%	19.3%	2.5%	4.01	3.09	+5.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			100	100	569	2284	567	117	71	100%	5.7	24.8%	5.1%	19.7%	3.1%	3.45	3.35	+14.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	SEA	25	25	150	633	161	32	19	100%	6.0	25.5%	5.1%	20.3%	3.0%	3.51	3.61	+3.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	SEA	22	22	133	563	143	30	17	100%	6.1	25.4%	5.3%	20.1%	3.1%	3.62	3.70	+2.7
2029	29	MLB MLE	SEA	20	20	119	503	125	28	16	100%	6.0	24.8%	5.5%	19.3%	3.2%	3.76	3.86	+2.2
2030	30	MLB MLE	SEA	18	18	106	450	108	26	15	100%	5.9	24.1%	5.8%	18.3%	3.4%	3.94	4.06	+1.7
2031	31	MLB MLE	SEA	15	15	93	391	91	24	14	100%	6.2	23.3%	6.1%	17.2%	3.7%	4.15	4.30	+1.2
2032	32	MLB MLE	SEA	13	13	77	324	73	21	13	100%	5.9	22.5%	6.5%	16.0%	3.9%	4.39	4.55	+0.8
2033	33	MLB MLE	SEA	10	10	59	248	54	17	10	100%	5.9	21.7%	7.0%	14.7%	4.2%	4.65	4.83	+0.4
2034	34	MLB MLE	SEA	7	7	41	172	36	13	8	100%	5.8	20.8%	7.5%	13.3%	4.5%	4.94	5.14	+0.1
2028	28	MLB CTX	SEA	22	22	133	562	142	30	17	100%	6.0	25.4%	5.3%	20.1%	3.0%	3.58	3.66	+2.7
2029	29	MLB CTX	SEA	20	20	119	502	124	28	16	100%	6.0	24.8%	5.5%	19.3%	3.2%	3.72	3.82	+2.2
2030	30	MLB CTX	SEA	18	18	106	448	108	26	15	100%	5.9	24.1%	5.8%	18.3%	3.3%	3.89	4.01	+1.7
2031	31	MLB CTX	SEA	16	16	93	393	92	24	14	100%	5.8	23.3%	6.1%	17.2%	3.6%	4.10	4.25	+1.2
2032	32	MLB CTX	SEA	13	13	77	325	73	21	12	100%	5.9	22.5%	6.5%	16.0%	3.8%	4.34	4.50	+0.8
2033	33	MLB CTX	SEA	10	10	59	249	54	17	10	100%	5.9	21.7%	7.0%	14.7%	4.1%	4.59	4.77	+0.4
2034	34	MLB CTX	SEA	7	7	41	173	36	13	8	100%	5.9	20.8%	7.5%	13.3%	4.4%	4.88	5.08	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		205	205	1197	4936	1196	276	163	100%	5.8	24.2%	5.6%	18.6%	3.3%	3.74	3.57	+26.7
/ 200 IP	—	RAW		34	34	200	825	200	46	27	100%	5.8	24.2%	5.6%	18.6%	3.3%	3.74	3.57	+4.5
Career	—	MLE		129	129	684	2755	686	159	83	100%	5.3	24.9%	5.8%	19.1%	3.0%	3.37	3.37	+23.2
/ 200 IP	—	MLE		38	38	200	806	201	46	24	100%	5.3	24.9%	5.8%	19.1%	3.0%	3.37	3.37	+3.9

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.

2024 AAATacoma Rainiers · 11 IPFIP -0.58 → -0.07 (+0.52)K% 43.6% → 37.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	43.59%	—	×0.860	37.49%
BB% (unintentional) /BF	0.00%	—	×0.900	0.00%
HR / BF /BF	0.00%	÷1.142	×1.100	0.00%

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 128).

Result: FIP -0.58 → -0.07, 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 AAArkansas Travelers · 44 IPFIP 1.73 → 2.62 (+0.90)K% 34.3% → 27.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.30%	—	×0.810	27.78%
BB% (unintentional) /BF	6.98%	—	×1.100	7.67%
HR / BF /BF	1.16%	÷0.853	×1.200	1.64%

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 71).

Result: FIP 1.73 → 2.62, 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 A+Everett AquaSox · 32 IPFIP 2.59 → 3.40 (+0.82)K% 31.1% → 23.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.08%	—	×0.770	23.93%
BB% (unintentional) /BF	10.81%	—	×1.150	12.43%
HR / BF /BF	1.35%	÷1.237	×1.250	1.37%

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 147).

Result: FIP 2.59 → 3.40, 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 AModesto Nuts · 20 IPFIP 2.40 → 3.99 (+1.58)K% 34.1% → 25.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.12%	—	×0.740	25.25%
BB% (unintentional) /BF	7.06%	—	×1.180	8.33%
HR / BF /BF	2.35%	÷0.855	×1.300	3.58%

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 71).

Result: FIP 2.40 → 3.99, 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
Bryan Woo (OGILVIE)	—	—	3.61	25.5%	5.1%	3.0%	—	3.86	24.8%	19.3%	359	+0.25	—	—	—
George Kirby R 2024 · 3.12 FIP	26	SP	3.12	23.0%	3.0%	2.9%	.287	3.59	22.6%	16.6%	301	+0.47	2.18	905	72
Chris Archer R 2016 · 3.78 FIP	27	SP	3.78	27.4%	7.9%	3.6%	.294	3.82	27.5%	19.6%	469	+0.04	2.85	1,371	66
Logan Gilbert R 2024 · 3.18 FIP	27	SP	3.18	27.4%	4.5%	3.3%	.234	3.53	29.4%	23.3%	317	+0.35	3.04	1,156	66
Kevin Gausman R 2018 · 4.13 FIP	27	SP	4.13	19.1%	6.3%	3.4%	.295	3.14	28.6%	22.3%	354	-0.99	2.34	2,103	66
Jon Gray R 2019 · 3.60 FIP	27	SP	3.60	23.5%	8.2%	2.6%	.308	3.75	23.5%	15.5%	315	+0.15	2.93	1,345	64
Bud Norris R 2012 · 4.08 FIP	27	SP	4.08	22.5%	8.7%	3.2%	.295	3.91	19.4%	11.4%	425	-0.17	3.51	1,221	63
Max Scherzer R 2011 · 4.17 FIP	27	SP	4.17	20.9%	6.6%	3.6%	.310	2.90	28.6%	21.6%	622	-1.27	2.13	3,078	62
Brady Singer R 2024 · 3.83 FIP	27	SP	3.83	22.3%	7.1%	3.1%	.297	4.25	20.2%	11.7%	327	+0.42	3.57	1,174	62
Mike Foltynewicz R 2019 · 4.20 FIP	27	SP	4.20	20.4%	7.5%	3.4%	.278	5.53	16.6%	10.5%	139	+1.33	3.17	957	62
Stephen Strasburg R 2015 · 2.70 FIP	27	SP	2.70	29.6%	5.0%	2.7%	.308	2.81	29.5%	22.9%	453	+0.11	1.08	1,460	61
Gerrit Cole R 2018 · 2.54 FIP	27	SP	2.54	34.5%	8.0%	2.5%	.282	2.74	36.3%	30.5%	467	+0.20	2.48	2,096	61
Javier Vazquez R 2003 · 3.27 FIP	27	SP	3.27	25.7%	5.5%	3.0%	.276	4.05	20.0%	14.2%	616	+0.78	2.67	2,840	60
James McDonald R 2012 · 4.18 FIP	27	SP	4.18	21.2%	8.8%	3.2%	.264	3.74	18.1%	4.3%	30	-0.44	2.99	506	60
Matt Garza R 2011 · 2.94 FIP	27	SP	2.94	23.5%	6.9%	1.7%	.302	3.68	20.4%	13.6%	422	+0.74	2.94	1,711	59
Ricky Nolasco R 2010 · 3.93 FIP	27	SP	3.93	22.1%	4.8%	3.8%	.314	3.45	17.2%	12.5%	596	-0.48	3.19	1,897	59
Dave Bush R 2007 · 4.21 FIP	27	SP	4.21	16.5%	5.3%	3.3%	.314	4.70	14.9%	8.1%	474	+0.49	3.65	1,141	57
Ian Kennedy R 2012 · 3.75 FIP	27	SP	3.75	20.8%	5.7%	3.1%	.297	3.83	23.2%	15.3%	551	+0.08	2.88	1,929	57
Jason Hammel R 2010 · 3.45 FIP	27	SP	3.45	18.3%	6.0%	2.1%	.324	4.13	16.5%	8.2%	428	+0.68	3.10	1,810	57
Joe Ryan R 2023 · 3.87 FIP	27	SP	3.87	29.3%	5.1%	4.7%	.301	3.40	27.2%	22.1%	451	-0.47	2.41	976	57
Masahiro Tanaka R 2016 · 3.34 FIP	27	SP	3.34	20.5%	4.5%	2.6%	.270	3.91	23.4%	18.0%	516	+0.57	2.82	1,054	57

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	6.7	112	24.4%	5.6%	1.28	3.74
Doug Bird ('73-'83, 10 WAR*)	6.1	110	20.3%*	5.8%*	1.41*	4.43*
Drew Smyly ('24)	5.7	104	23.1%	7.7%	1.49	4.20
Scott Bankhead ('86-'95, 10 WAR*)	4.5	100	21.2%*	7.3%*	1.36*	4.16*
Michael Pineda ('22)	5.0	112	23.1%	5.3%	1.28	4.06
Julio Urías ('23)	3.6	102	24.3%	6.6%	1.05	3.11
Greg Swindell ('86-'02, 30 WAR*)	11.2	131	20.9%*	5.3%*	1.32*	3.99*