Tyler Glasnow — OGILVIE

Tyler Glasnow P Los Angeles Dodgers

Age 32 RHP 6'8" / 225 lbs MLB Svc 8.0 · Ctrl thru 2028 peak 2.2 · 2026

2026 ROS PROJECTION75 act + 9 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 8879vR 71

ERA3.01

FIP3.08

K%31.6%

BB%8.9%

K-BB%22.6%

ROS IP9

Value2026 · WAR

Runs saved vs league avg · 84 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control-$34M ctrl surplus

Grades · Statcast · Arsenal · Contract

Scouting Grades

OFP—65

STUF6570

CTRL5055

CMD5555

K†7070

Statcast Percentiles

FB Velo

p6295.4

Whiff%

p8330.4%

p9032.0%

xwOBA vs

p900.274

FB+4.3 (55%)

SL+1.2 (18%)

SI (22%)

CU (6%)

Contract CONFIRMED · hand-curated extension

Status FA

MLB Debut 2016

Service 8.919 yrs.days

Team Control Through 2028

First FA Year 2029

Year	Status	Salary	Proj WAR	Value	Surplus
2026ROS	Ext	$2M	+0.2	$0.7M	-$1M
2027	Ext	$25M	+1.3	$10M	-$13M
2028	Ext	$25M	+0.8	$3M	-$18M
Totals		$52M		$13M	-$32M

Underwater contract
Projected production over the remaining contract is worth -$32M less than the salary owed. Most often this reflects an aging-curve fade that was visible at signing — the team paid a premium for the early years.

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)
2015	21	MIX MLE	2 levels	20	20	104	422	130	41	3	100%	5.2	25.7%	10.4%	15.3%	0.9%	2.34	2.76	—
2015	21	MIX RAW	2 levels	20	20	104	422	130	41	3	100%	5.2	30.8%	9.7%	21.1%	0.7%	2.34	2.16	—
2016	22	MIX MLE	3 levels	29	26	140	570	168	81	7	90%	4.8	26.0%	14.4%	11.6%	1.3%	2.31	3.42	+2.5
2016	22	MIX RAW	3 levels	29	26	140	570	168	81	7	90%	4.8	29.5%	14.2%	15.3%	1.2%	2.31	3.09	+3.1
2017	23	MIX MLE	2 levels	30	28	155	669	196	74	19	93%	5.2	26.8%	11.3%	15.5%	3.3%	4.23	4.06	+1.5
2017	23	MIX RAW	2 levels	30	28	155	669	196	74	19	93%	5.2	29.3%	11.1%	18.2%	2.8%	4.23	3.60	+2.5
2018	24	MLB MLE	Tampa Bay Rays	45	11	112	468	136	50	15	24%	2.5	29.1%	10.7%	18.4%	3.3%	4.27	3.81	+1.0
2018	24	MLB RAW	Tampa Bay Rays	45	11	112	468	136	50	15	24%	2.5	29.1%	10.7%	18.4%	3.2%	4.27	3.75	+1.1
2019	25	MIX MLE	2 levels	14	14	63	241	79	17	4	100%	4.5	33.0%	6.1%	27.0%	1.8%	1.71	2.06	+2.3
2019	25	MIX RAW	2 levels	14	14	63	241	79	17	4	100%	4.5	32.8%	7.1%	25.7%	1.7%	1.71	2.23	+2.2
2020	26	MLB MLE	Tampa Bay Rays	11	11	57	238	91	22	11	100%	5.2	38.2%	9.2%	29.0%	4.8%	4.08	3.65	+0.9
2020	26	MLB RAW	Tampa Bay Rays	11	11	57	238	91	22	11	100%	5.2	38.2%	9.2%	29.0%	4.6%	4.08	3.57	+0.9
2021	27	MLB MLE	Tampa Bay Rays	14	14	88	340	123	27	10	100%	6.3	36.2%	7.9%	28.2%	3.0%	2.66	2.71	+2.5
2021	27	MLB RAW	Tampa Bay Rays	14	14	88	340	123	27	10	100%	6.3	36.2%	7.9%	28.2%	2.9%	2.66	2.70	+2.5
2022	28	MIX MLE	2 levels	6	6	14	52	24	6	1	100%	2.3	46.2%	11.5%	34.6%	1.9%	1.32	1.72	+0.5
2022	28	MIX RAW	2 levels	6	6	14	52	24	6	1	100%	2.3	46.2%	11.5%	34.6%	1.9%	1.32	1.86	+0.5
2023	29	MIX MLE	2 levels	25	25	133	537	182	42	14	100%	5.3	33.3%	7.7%	25.5%	2.7%	3.24	2.74	+3.7
2023	29	MIX MLE	2 levels	25	25	133	537	182	42	14	100%	5.3	33.3%	7.7%	25.5%	2.7%	3.24	2.74	+3.7
2023	29	MIX RAW	2 levels	25	25	133	537	182	42	14	100%	5.3	33.9%	7.8%	26.1%	2.6%	3.24	2.68	+3.8
2024	30	MLB MLE	Los Angeles Dodgers	22	22	134	522	168	35	15	100%	6.1	32.2%	6.7%	25.5%	2.8%	3.49	2.74	+3.7
2024	30	MLB MLE	Los Angeles Dodgers	22	22	134	522	168	35	15	100%	6.1	32.2%	6.7%	25.5%	2.8%	3.49	2.74	+3.7
2024	30	MLB RAW	Los Angeles Dodgers	22	22	134	522	168	35	15	100%	6.1	32.2%	6.7%	25.5%	2.9%	3.49	2.83	+3.5
2025	31	MIX MLE	2 levels	21	21	99	409	118	48	11	100%	4.7	29.0%	11.7%	17.2%	2.6%	3.64	3.58	+1.6
2025	31	MIX MLE	2 levels	21	21	99	409	118	48	11	100%	4.7	29.0%	11.7%	17.2%	2.6%	3.64	3.58	+1.6
2025	31	MIX RAW	2 levels	21	21	99	409	118	48	11	100%	4.7	28.9%	11.7%	17.1%	2.7%	3.64	3.62	+1.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			178	139	816	3326	1029	305	100	78%	4.6	30.9%	9.2%	21.8%	3.0%	3.72	3.29	+16.1
▸ 2026 season
YTD	32	MLB MLE	Los Angeles Dodgers	15	15	75	289	97	24	6	100%	5.0	32.0%	8.3%	23.7%	2.4%	3.11	2.76	+2.0
YTD	32	MLB MLE	Los Angeles Dodgers	15	15	75	289	97	24	6	100%	5.0	32.0%	8.3%	23.7%	2.4%	3.11	2.76	+2.0
▸ 2026 season — so far · projected rest · full
2026	32	A RAW	LAD	1	1	2	7	1	0	0	100%	2.0	14.3%	0.0%	14.3%	0.0%	0.00	1.89	—
2026	32	AAA RAW	LAD	3	3	12	41	19	4	0	100%	3.9	46.3%	9.8%	36.6%	0.0%	1.54	0.42	—
2026	32	MLB RAW	LAD	11	11	62	241	77	20	6	100%	5.6	32.0%	8.3%	23.7%	2.5%	3.50	2.82	+1.6
SO FAR	32	MLB RAW	LAD	11	11	62	241	77	20	6	100%	5.6	32.0%	8.3%	23.7%	2.5%	3.50	2.82	+1.6
ROS	32	MLB MLE	LAD	1	1	9	37	12	3	1	100%	8.8	31.6%	8.9%	22.6%	2.8%	3.01	3.08	+0.2
ROS	32	MLB CTX	LAD	2	2	9	38	12	3	1	100%	4.5	31.6%	8.9%	22.6%	2.9%	3.07	3.14	+0.2
2026 TOT	32	MLB MLE	LAD	—	—	84	326	109	27	7	—	—	33.3%	8.4%	25.0%	2.2%	3.10	2.80	+2.1
FULL	32	MLB A+C	LAD	—	—	71	298	109	27	7	—	—	36.5%	9.2%	27.4%	2.4%	3.70	2.48	+1.7
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	33	MLB MLE	LAD	15	15	89	377	116	35	11	100%	6.0	30.6%	9.4%	21.2%	3.0%	3.58	3.72	+1.3
2028	34	MLB MLE	LAD	14	14	81	344	102	34	11	100%	5.8	29.7%	9.9%	19.8%	3.3%	3.85	4.02	+0.9
2029	35	MLB MLE	LAD	12	12	73	309	95	30	11	100%	6.1	30.8%	9.7%	21.1%	3.6%	3.99	4.09	+0.7
2030	36	MLB MLE	LAD	11	11	65	273	81	28	11	100%	5.9	29.7%	10.2%	19.5%	4.0%	4.27	4.46	+0.3
2027	33	MLB CTX	LAD	15	15	89	376	115	35	12	100%	5.9	30.6%	9.4%	21.2%	3.1%	3.65	3.79	+1.3
2028	34	MLB CTX	LAD	14	14	81	342	102	34	12	100%	5.8	29.7%	9.9%	19.8%	3.4%	3.93	4.10	+0.8
2029	35	MLB CTX	LAD	12	12	73	308	95	30	12	100%	6.1	30.8%	9.7%	21.1%	3.8%	4.07	4.17	+0.7
2030	36	MLB CTX	LAD	11	11	65	274	82	28	11	100%	5.9	29.7%	10.2%	19.5%	4.2%	4.36	4.55	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		231	192	1133	4666	1435	436	148	83%	4.9	30.7%	9.3%	21.4%	3.2%	3.78	3.42	+20.5
/ 200 IP	—	RAW		41	34	200	824	253	77	26	83%	4.9	30.7%	9.3%	21.4%	3.2%	3.78	3.42	+3.6
Career	—	MLE		252	213	1175	4757	1447	470	122	85%	4.7	30.4%	9.9%	20.5%	2.6%	3.23	3.19	+19.3
/ 200 IP	—	MLE		43	36	200	810	246	80	21	85%	4.7	30.4%	9.9%	20.5%	2.6%	3.23	3.19	+3.4

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
Tyler Glasnow (OGILVIE)	—	—	3.58	31.1%	9.4%	2.8%	—	3.93	30.4%	20.7%	244	+0.35	—	—	—
Zack Wheeler R 2022 · 2.62 FIP	32	SP	2.62	26.9%	5.4%	2.0%	.281	2.75	29.3%	23.5%	542	+0.13	2.28	1,586	54
Matt Shoemaker R 2019 · 3.80 FIP	32	SP	3.80	22.2%	8.3%	2.8%	.181	5.06	18.8%	11.1%	159	+1.26	3.17	592	53
Charlie Morton R 2016 · 2.99 FIP	32	SP	2.99	26.8%	11.3%	1.3%	.326	2.96	28.8%	20.7%	508	-0.03	2.52	1,534	52
Tim Adleman R 2019 · 4.30 FIP	31	SP	4.30	22.8%	7.8%	3.9%	.266	4.71	18.5%	11.1%	90	+0.41	3.63	605	50
Kenta Maeda R 2020 · 2.87 FIP	32	SP	2.87	32.3%	4.0%	3.6%	.208	3.75	26.1%	19.3%	224	+0.88	2.87	1,092	49
Brad Peacock R 2019 · 4.22 FIP	31	SP-	4.22	25.1%	8.1%	4.0%	.261	4.15	22.8%	12.5%	96	-0.07	2.97	533	49
Chris Archer R 2021 · 4.44 FIP	32	SP	4.44	25.4%	8.1%	4.5%	.250	4.37	19.2%	8.2%	103	-0.07	2.85	1,018	48
Garrett Richards R 2020 · 4.05 FIP	32	SP-	4.05	21.6%	8.0%	3.2%	.280	4.16	18.8%	9.8%	179	+0.11	2.31	577	47
Tom Koehler R 2017 · 4.66 FIP	31	SP-	4.66	22.4%	9.0%	4.2%	.298	—	—	—	—	—	4.38	474	46
Tanner Roark R 2019 · 4.47 FIP	32	SP	4.47	21.9%	6.9%	4.3%	.313	4.76	19.6%	9.9%	94	+0.29	3.13	942	46
Kodai Senga R 2023 · 3.40 FIP	30	SP	3.40	29.1%	11.1%	2.5%	.274	4.52	23.1%	10.6%	183	+1.12	3.40	349	45
Yu Darvish R 2019 · 3.98 FIP	32	SP	3.98	31.3%	7.5%	4.7%	.258	3.10	28.0%	22.7%	437	-0.88	1.97	1,253	44
Aaron Wilkerson R 2021 · 3.33 FIP	32	SP	3.33	24.6%	5.6%	2.9%	.300	5.51	20.6%	14.7%	47	+2.18	2.75	902	42
Miles Mikolas R 2021 · 4.27 FIP	32	SP	4.27	16.4%	5.5%	3.4%	.269	4.09	17.3%	13.0%	575	-0.18	3.13	1,296	41
Odrisamer Despaigne R 2019 · 3.77 FIP	32	SP	3.77	19.4%	8.9%	2.2%	.330	—	—	—	—	—	3.13	593	40
Jason Hammel R 2015 · 3.54 FIP	32	SP	3.54	24.2%	5.1%	3.4%	.282	4.31	18.4%	11.9%	474	+0.77	3.54	645	40
Josh Lindblom R 2020 · 3.50 FIP	33	SP	3.50	27.2%	8.4%	3.0%	.308	4.46	21.7%	13.8%	255	+0.96	3.50	348	40
Carlos Carrasco R 2019 · 4.18 FIP	32	SP-	4.18	28.2%	4.4%	5.3%	.349	3.69	24.5%	17.3%	274	-0.49	2.67	1,455	39
Ubaldo Jiménez R 2016 · 4.10 FIP	32	SP	4.10	19.6%	11.1%	2.3%	.315	4.95	21.5%	12.5%	143	+0.85	3.63	469	39
Michael Pineda R 2021 · 4.06 FIP	32	SP	4.06	19.2%	4.4%	3.7%	.291	5.24	14.5%	10.2%	72	+1.18	2.00	786	39

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	2.0	81	30.4%	9.7%	1.27	3.80
Brad Peacock ('19)	1.6	80	28.7%	9.2%	1.18	3.48
Dinelson Lamet ('23)	1.8	61	30.0%	10.7%	1.29	4.66
Robert Stephenson ('23)	1.7	57	26.2%	9.9%	1.39	4.33
Colin Poche ('24)	1.0	52	27.0%	9.2%	1.34	3.63
Joe Jiménez ('24)	1.9	53	29.8%	8.6%	1.11	4.06
Diego Castillo ('22)	1.3	52	28.1%	8.9%	1.07	3.12