Logan Webb — OGILVIE

Logan Webb P San Francisco Giants

Age 29 RHP 6'2" / 221 lbs MLB Svc 6.0 · Ctrl thru 2028 peak 5.6 · 2026

2026 ROS PROJECTION159 act + 15 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 9890vR 81

ERA3.31

FIP3.19

K%20.6%

BB%5.9%

K-BB%14.7%

ROS IP15

Value2026 · WAR

Runs saved vs league avg · 174 IP

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

Grades · Statcast · Arsenal · Contract

Scouting Grades

OFP—50

STUF7070

CTRL6565

CMD6565

K†5555

Statcast Percentiles

FB Velo

p1992.3

Whiff%

p2321.5%

p3319.7%

xwOBA vs

p510.311

FB+2.6 (43%)

CH (24%)

SI (29%)

SL (20%)

CT-2.1 (13%)

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

Status FA

MLB Debut 2019

Service 6.256 yrs.days

Team Control Through 2028

First FA Year 2027

Year	Status	Salary	Proj WAR	Value	Surplus
2026ROS	Ext	$1M	+0.3	$1M	-$0.4M
2027	Ext	$18M	+2.8	$22M	+$6M
2028	Ext	$18M	+2.0	$14M	-$0.8M
Totals		$37M		$37M	+$5M

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)
2016	19	A MLE	Augusta GreenJackets	9	9	42	194	30	12	7	100%	4.7	11.4%	7.3%	4.1%	5.6%	6.21	6.14	—
2016	19	A RAW	Augusta GreenJackets	9	9	42	194	30	12	7	100%	4.7	15.5%	6.2%	9.3%	3.6%	6.21	4.70	—
2018	21	MIX MLE	2 levels	27	26	105	434	100	46	6	96%	3.9	18.0%	12.1%	5.9%	1.9%	2.41	4.15	—
2018	21	MIX RAW	2 levels	27	26	105	434	100	46	6	96%	3.9	23.0%	10.6%	12.4%	1.4%	2.41	3.25	—
2019	22	MIX MLE	5 levels	20	18	103	435	106	29	7	90%	5.2	21.3%	7.7%	13.6%	2.3%	3.15	3.54	+1.7
2019	22	MIX RAW	5 levels	20	18	103	435	106	29	7	90%	5.2	24.4%	6.7%	17.7%	1.6%	3.15	2.77	+2.8
2020	23	MLB MLE	San Francisco Giants	13	11	54	246	46	23	4	85%	4.2	18.7%	9.3%	9.3%	1.8%	5.47	3.67	+0.8
2020	23	MLB RAW	San Francisco Giants	13	11	54	246	46	23	4	85%	4.2	18.7%	9.3%	9.3%	1.6%	5.47	3.63	+0.8
2021	24	MIX MLE	2 levels	28	27	150	603	159	37	9	96%	5.4	26.5%	6.0%	20.5%	1.6%	3.05	2.52	+4.6
2021	24	MIX RAW	2 levels	28	27	150	603	159	37	9	96%	5.4	26.4%	6.1%	20.2%	1.5%	3.05	2.50	+4.6
2022	25	MLB MLE	San Francisco Giants	32	32	192	787	163	49	11	100%	6.0	20.7%	6.2%	14.5%	1.5%	2.90	2.97	+4.7
2022	25	MLB RAW	San Francisco Giants	32	32	192	787	163	49	11	100%	6.0	20.7%	6.2%	14.5%	1.4%	2.90	2.91	+4.8
2023	26	MLB MLE	San Francisco Giants	33	33	216	850	194	31	20	100%	6.5	22.8%	3.6%	19.2%	2.5%	3.25	3.03	+5.1
2023	26	MLB MLE	San Francisco Giants	33	33	216	850	194	31	20	100%	6.5	22.8%	3.6%	19.2%	2.5%	3.25	3.03	+5.1
2023	26	MLB RAW	San Francisco Giants	33	33	216	850	194	31	20	100%	6.5	22.8%	3.6%	19.2%	2.4%	3.25	2.94	+5.4
2024	27	MLB MLE	San Francisco Giants	33	33	205	841	172	47	11	100%	6.2	20.5%	5.6%	14.9%	1.4%	3.47	2.86	+5.3
2024	27	MLB MLE	San Francisco Giants	33	33	205	841	172	47	11	100%	6.2	20.5%	5.6%	14.9%	1.4%	3.47	2.86	+5.3
2024	27	MLB RAW	San Francisco Giants	33	33	205	841	172	47	11	100%	6.2	20.5%	5.6%	14.9%	1.3%	3.47	2.81	+5.5
2025	28	MLB MLE	San Francisco Giants	34	34	207	856	224	46	14	100%	6.1	26.2%	5.4%	20.8%	1.8%	3.22	2.54	+6.3
2025	28	MLB MLE	San Francisco Giants	34	34	207	856	224	46	14	100%	6.1	26.2%	5.4%	20.8%	1.8%	3.22	2.54	+6.3
2025	28	MLB RAW	San Francisco Giants	34	34	207	856	224	46	14	100%	6.1	26.2%	5.4%	20.8%	1.6%	3.22	2.48	+6.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			206	203	1218	4994	1121	286	86	99%	5.9	22.4%	5.7%	16.7%	1.7%	3.47	2.88	+31.1
▸ 2026 season
YTD	29	MLB MLE	San Francisco Giants	27	27	159	659	129	43	12	100%	5.9	19.7%	6.2%	13.5%	2.0%	4.02	3.33	+3.1
YTD	29	MLB MLE	San Francisco Giants	27	27	159	659	129	43	12	100%	5.9	19.7%	6.2%	13.5%	2.0%	4.02	3.33	+3.1
▸ 2026 season — so far · projected rest · full
2026	29	AAA RAW	SF	1	1	3	15	2	3	0	100%	3.3	13.3%	20.0%	-6.7%	0.0%	0.00	4.51	—
2026	29	MLB RAW	SF	26	26	156	644	127	40	12	100%	6.0	19.7%	6.2%	13.5%	1.9%	4.10	3.24	+3.2
SO FAR	29	MLB RAW	SF	26	26	156	644	127	40	12	100%	6.0	19.7%	6.2%	13.5%	1.9%	4.10	3.24	+3.2
ROS	29	MLB MLE	SF	3	3	15	65	13	4	1	100%	5.2	20.6%	5.9%	14.7%	2.0%	3.31	3.19	+0.3
ROS	29	MLB CTX	SF	2	2	15	63	13	4	1	100%	7.5	20.6%	5.9%	14.7%	1.8%	3.23	3.11	+0.3
2026 TOT	29	MLB MLE	SF	—	—	174	724	142	47	13	—	—	19.7%	6.5%	13.2%	1.8%	3.96	3.31	+3.4
FULL	29	MLB A+C	SF	—	—	171	723	142	47	13	—	—	19.7%	6.5%	13.2%	1.8%	4.03	3.26	+3.4
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	30	MLB MLE	SF	32	32	191	806	163	50	17	100%	6.0	20.2%	6.2%	14.0%	2.1%	3.68	3.71	+2.7
2028	31	MLB MLE	SF	30	30	178	752	146	49	18	100%	5.9	19.5%	6.6%	12.9%	2.3%	3.84	3.94	+2.0
2029	32	MLB MLE	SF	27	27	165	695	130	48	18	100%	6.1	18.7%	7.0%	11.7%	2.6%	4.06	4.20	+1.4
2030	33	MLB MLE	SF	25	25	151	638	114	47	18	100%	6.0	17.8%	7.4%	10.4%	2.9%	4.31	4.48	+0.7
2031	34	MLB MLE	SF	23	23	138	581	98	46	18	100%	6.0	16.9%	7.9%	9.0%	3.2%	4.59	4.78	+0.2
2027	30	MLB CTX	SF	32	32	191	806	163	50	16	100%	6.0	20.2%	6.2%	14.0%	1.9%	3.59	3.62	+2.8
2028	31	MLB CTX	SF	30	30	178	752	146	49	16	100%	5.9	19.5%	6.6%	12.9%	2.2%	3.74	3.84	+2.0
2029	32	MLB CTX	SF	28	28	165	697	130	48	17	100%	5.9	18.7%	7.0%	11.7%	2.4%	3.95	4.09	+1.4
2030	33	MLB CTX	SF	25	25	151	638	114	47	17	100%	6.0	17.8%	7.4%	10.4%	2.6%	4.19	4.36	+0.7
2031	34	MLB CTX	SF	23	23	138	583	99	46	17	100%	6.0	16.9%	7.9%	9.0%	2.9%	4.46	4.65	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		346	343	2056	8531	1785	530	169	99%	5.9	20.9%	6.2%	14.7%	2.0%	3.66	3.21	+43.2
/ 200 IP	—	RAW		34	33	200	830	174	52	16	99%	5.9	20.9%	6.2%	14.7%	2.0%	3.66	3.21	+4.2
Career	—	MLE		256	250	1433	5905	1282	373	117	98%	5.6	21.7%	6.3%	15.4%	2.0%	3.40	3.16	+37.8
/ 200 IP	—	MLE		36	35	200	824	179	52	16	98%	5.6	21.7%	6.3%	15.4%	2.0%	3.40	3.16	+3.7

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
Logan Webb (OGILVIE)	—	—	3.24	23.5%	5.3%	2.0%	—	3.94	19.5%	12.9%	534	+0.70	—	—	—
Rick Porcello R 2018 · 3.75 FIP	29	SP	3.75	23.5%	5.9%	3.4%	.276	4.16	19.1%	13.5%	233	+0.41	3.13	1,023	76
Jake Odorizzi R 2019 · 3.16 FIP	29	SP	3.16	27.1%	8.1%	2.4%	.299	4.33	19.8%	12.5%	225	+1.17	3.16	1,048	68
Mike Leake R 2017 · 3.69 FIP	29	SP	3.69	16.6%	4.3%	2.6%	.303	4.53	15.2%	11.7%	383	+0.84	3.69	937	66
Masahiro Tanaka R 2018 · 3.71 FIP	29	SP	3.71	25.0%	5.5%	3.7%	.279	4.02	20.2%	15.1%	230	+0.31	3.34	918	64
Chris Archer R 2018 · 3.64 FIP	29	SP	3.64	25.4%	7.2%	3.2%	.331	4.80	26.8%	17.1%	153	+1.16	2.85	1,018	63
Jimmy Nelson R 2017 · 2.76 FIP	28	SP	2.76	27.3%	6.5%	2.1%	.333	4.28	26.9%	12.3%	62	+1.52	1.32	650	62
Kyle Hendricks R 2019 · 3.39 FIP	29	SP	3.39	20.5%	4.2%	2.7%	.281	4.38	18.0%	13.1%	347	+0.99	3.02	1,685	62
Kyle Gibson R 2017 · 4.42 FIP	29	SP	4.42	18.6%	8.6%	3.3%	.323	4.09	21.7%	12.9%	424	-0.33	3.56	1,689	59
Chase Anderson R 2017 · 3.30 FIP	29	SP	3.30	23.4%	7.0%	2.3%	.259	4.81	20.8%	12.5%	331	+1.51	3.30	1,146	58
Matt Harvey R 2018 · 4.17 FIP	29	SP	4.17	19.8%	5.3%	3.8%	.294	4.74	16.9%	9.2%	222	+0.57	2.90	806	57
Sonny Gray R 2019 · 3.07 FIP	29	SP	3.07	29.0%	9.5%	2.2%	.251	3.31	26.5%	17.9%	311	+0.24	2.55	1,792	55
Zack Wheeler R 2019 · 3.28 FIP	29	SP	3.28	23.6%	5.6%	2.7%	.308	2.47	26.6%	21.3%	437	-0.81	2.28	1,586	54
Collin McHugh R 2016 · 3.84 FIP	29	SP	3.84	22.2%	6.7%	3.2%	.335	3.44	26.5%	18.5%	225	-0.40	1.77	806	50
Anthony DeSclafani R 2019 · 3.99 FIP	29	SP	3.99	24.0%	6.3%	3.9%	.268	3.98	21.1%	14.5%	220	-0.01	3.38	981	48
Jacob deGrom R 2017 · 3.35 FIP	29	SP	3.35	28.9%	6.5%	3.4%	.300	2.04	32.9%	27.5%	489	-1.31	0.74	1,538	47
Stephen Strasburg R 2017 · 2.42 FIP	29	SP	2.42	29.1%	6.0%	1.8%	.267	3.08	29.4%	23.0%	339	+0.66	2.42	811	47
Jhoulys Chacín R 2017 · 3.85 FIP	29	SP	3.85	20.0%	8.8%	2.4%	.262	4.33	20.3%	11.4%	296	+0.48	3.71	887	46
Jeremy Hellickson R 2016 · 3.74 FIP	29	SP	3.74	19.9%	5.8%	2.9%	.271	4.80	15.6%	9.2%	311	+1.06	3.74	646	44
Jameson Taillon R 2021 · 4.09 FIP	29	SP	4.09	23.2%	7.1%	3.7%	.268	4.02	20.2%	15.0%	497	-0.07	3.12	1,401	43
Carlos Carrasco R 2016 · 3.59 FIP	29	SP	3.59	25.0%	5.3%	3.5%	.285	3.02	28.8%	23.7%	472	-0.57	2.67	1,455	43

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	5.1	171	19.7%	6.6%	0.94	3.92
Jordan Montgomery ('24)	4.3	124	21.4%	6.9%	1.07	4.01
Noah Syndergaard ('23)	4.7	134	23.8%	5.5%	0.95	3.70
Alex Cobb ('23)	4.0	114	19.5%	6.6%	1.03	4.14
Julio Teheran ('23)	5.2	147	20.4%	8.8%	1.34	4.12
Mike Foltynewicz ('21)	4.0	134	21.4%	7.7%	1.46	4.45
Trevor Bauer ('21)	5.6	159	26.8%	8.7%	1.13	3.68