Bryan Woo — OGILVIE

Bryan Woo P Seattle Mariners

Age 27 RHP 6'2" / 205 lbs MLB Svc 2.0 · Ctrl thru 2030 peak 3.8 · 2027

2027 FULL-SEASON PROJECTION0 act + 173 ip · rates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9991vR 83

ERA3.51

FIP3.61

K%25.5%

BB%5.1%

K-BB%20.3%

ROS IP173

Value2026 · WAR

Runs saved vs league avg · 173 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$32M ctrl surplus

Grades · Statcast · Arsenal · Contract

Scouting Grades

STUF5050

CTRL7070

CMD6060

K†6060

Statcast Percentiles

FB Velo

p7296.1

Whiff%

p5025.2%

p6324.6%

xwOBA vs

p660.296

FB+6.0 (66%)

SL+1.7 (25%)

CH+1.3 (6%)

SI (19%)

CU (3%)

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

Status Pre-Arb SUPER-2

MLB Debut 2023

Service 2.703 yrs.days

Team Control Through 2030

First FA Year 2031

Year	Status	Salary	Proj WAR	Value	Surplus
2027ROS	Arb-1	$6M	+2.6	$21M	+$16M
2028	Arb-2	$8M	+2.5	$19M	+$12M
2029	Arb-3	$11M	+2.1	$14M	+$5M
2030	Arb-4	$14M	+1.5	$10M	+$0.0M (cut)
Totals		$24M		$64M	+$33M

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	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	+2.2
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	+2.7
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	+2.6
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	+2.6
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	+3.0
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	+3.4
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	+3.4
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	+3.5
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	+3.8
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	+3.8
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	+3.9
▸ 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	+10.9
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	SEA	29	29	173	730	186	37	22	100%	6.0	25.5%	5.1%	20.3%	3.0%	3.51	3.61	+2.7
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	SEA	29	29	173	730	185	38	22	100%	6.0	25.4%	5.3%	20.1%	3.1%	3.62	3.70	+2.5
2029	29	MLB MLE	SEA	28	28	165	697	172	38	23	100%	5.9	24.8%	5.5%	19.3%	3.2%	3.76	3.86	+2.1
2030	30	MLB MLE	SEA	26	26	155	655	158	38	22	100%	6.0	24.1%	5.8%	18.3%	3.4%	3.94	4.06	+1.5
2031	31	MLB MLE	SEA	24	24	145	611	142	37	22	100%	6.0	23.3%	6.1%	17.2%	3.7%	4.15	4.30	+1.0
2032	32	MLB MLE	SEA	22	22	134	565	127	37	22	100%	6.1	22.5%	6.5%	16.0%	3.9%	4.39	4.55	+0.5
2033	33	MLB MLE	SEA	20	20	123	518	112	36	22	100%	6.1	21.7%	7.0%	14.7%	4.2%	4.65	4.83	+0.1
2034	34	MLB MLE	SEA	19	19	112	472	98	35	21	100%	5.9	20.8%	7.5%	13.3%	4.5%	4.94	5.14	-0.3
2028	28	MLB CTX	SEA	29	29	173	730	185	38	22	100%	6.0	25.4%	5.3%	20.1%	3.0%	3.58	3.66	+2.5
2029	29	MLB CTX	SEA	28	28	165	697	172	38	22	100%	5.9	24.8%	5.5%	19.3%	3.2%	3.72	3.82	+2.1
2030	30	MLB CTX	SEA	26	26	155	654	157	38	22	100%	6.0	24.1%	5.8%	18.3%	3.3%	3.89	4.01	+1.5
2031	31	MLB CTX	SEA	24	24	145	612	143	38	22	100%	6.0	23.3%	6.1%	17.2%	3.6%	4.10	4.25	+1.0
2032	32	MLB CTX	SEA	22	22	134	566	127	37	22	100%	6.1	22.5%	6.5%	16.0%	3.8%	4.34	4.50	+0.5
2033	33	MLB CTX	SEA	20	20	123	519	112	36	21	100%	6.2	21.7%	7.0%	14.7%	4.1%	4.59	4.77	+0.1
2034	34	MLB CTX	SEA	19	19	112	473	98	35	21	100%	5.9	20.8%	7.5%	13.3%	4.4%	4.88	5.08	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		268	268	1574	6531	1562	378	222	100%	5.9	23.9%	5.8%	18.1%	3.4%	3.86	3.68	+23.3
/ 200 IP	—	RAW		34	34	200	830	198	48	28	100%	5.9	23.9%	5.8%	18.1%	3.4%	3.86	3.68	+3.0
Career	—	MLE		129	129	684	2755	686	159	83	100%	5.3	24.9%	5.8%	19.1%	3.0%	3.37	3.37	+18.0
/ 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	+2.3

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%	—	3.87	24.7%	19.2%	493	+0.26	—	—	—
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: 497 starter careers (1990-2025).

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	8.7	146	24.1%	5.7%	1.32	3.86
Michael Pineda ('22)	5.0	112	23.1%	5.3%	1.28	4.06
Masahiro Tanaka ('20)	5.3	151	23.1%	4.8%	1.36	3.74
Pablo López ('25)	4.8	121	24.9%	6.3%	1.07	3.81
Mike Fiers ('21)	5.8	128	20.5%	7.0%	1.44	4.07
Kyle Hendricks ('25)	8.7	145	19.0%	5.6%	1.08	3.79
Anthony DeSclafani ('25)	4.9	109	20.9%	6.4%	1.34	4.24