Tyler Glasnow

P Los Angeles Dodgers

Age 33 RHP 6'8" / 225 lbs MLB Svc 9.0 · Ctrl thru 2028 peak 2.0 · 2027

Overview

MLBSP40-MANExtFA 2029

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	30	MLBLAD	22	22	134	3.49	2.83	32.2%	6.7%	4.4
2025	31	MIX2 levels	21	21	99	3.64	3.62	28.9%	11.7%	2.1	K 29.0% · BB 11.7% · FIP 3.58
2026	32	MIX3 levels	17	17	88	3.18	2.40	35.1%	8.3%	3.4	K 34.0% · BB 8.3% · FIP 2.56
2027PROJ	33	MLBLAD	13	13	76	3.36	3.39	32.2%	9.2%	1.9
2028PROJ	34	MLBLAD	12	12	70	3.63	3.77	31.3%	9.7%	1.4
2029PROJ	35	MLBLAD	10	10	62	3.92	4.11	30.3%	10.2%	1.0

Last 3 seasons WAR 9.9 · Next 3 projected WAR 4.3Projected rows: MLB playing time only, park and league context applied.

ContractCONFIRMED

Control thru2028Service9.919First FA2029

2027Ext$25M2028Ext$25M

Skills · percentileStatcast 2026

K%90

xwOBA vs90

FB Velo64

Form4.30 ERA (proj 3.36) · K 35.3% (proj 32.2%) · BB 10.1% (proj 9.2%) · last 60d · 29 IP through Oct 27

CompsKenta Maeda (age 33) · Junior Guerra (age 33) · Josh Lowey (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 8981vR 73

ERA3.36

FIP3.39

K%32.2%

BB%9.2%

K-BB%23.0%

Proj IP76

Value2027 · WAR

Runs saved vs league avg · 76 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control-$24M ctrl surplus

Statcast · Contract

Statcast Percentiles

FB Velo

p6495.5

Whiff%

p9032.1%

p9034.0%

xwOBA vs

p900.263

Contract CONFIRMED · hand-curated extension

Status FA

MLB Debut 2016

Service 9.919 yrs.days

Team Control Through 2028

First FA Year 2029

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$25M	+1.9	$15M	-$10M
2028	Ext	$25M	+1.4	$10M	-$12M
Totals		$50M		$26M	-$22M

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)
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	+3.4
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	+4.0
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	+2.5
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	+3.4
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	+2.7
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	+2.6
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	+1.2
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	+1.3
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	+3.0
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	+3.1
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	+0.6
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	+0.6
2023	29	MIX MLE	2 levels	25	25	133	537	182	42	14	100%	5.3	33.4%	7.7%	25.6%	2.7%	3.24	2.73	+4.5
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	+4.6
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	+4.6
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	+4.6
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	+4.4
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	+2.2
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	+2.2
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	+2.1
2026	32	MIX MLE	3 levels	17	17	88	336	118	28	7	100%	5.2	34.0%	8.3%	25.7%	2.3%	3.18	2.56	+3.2
2026	32	MIX MLE	3 levels	17	17	88	336	118	28	7	100%	5.2	34.0%	8.3%	25.7%	2.3%	3.18	2.56	+3.2
2026	32	MIX RAW	3 levels	17	17	88	336	118	28	7	100%	5.2	35.1%	8.3%	26.8%	2.1%	3.18	2.40	+3.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			180	141	828	3373	1050	309	101	78%	4.6	31.1%	9.2%	22.0%	3.0%	3.72	3.27	+21.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	LAD	13	13	76	321	103	29	9	100%	5.8	32.2%	9.2%	23.0%	2.7%	3.36	3.39	+1.9
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	LAD	12	12	70	293	92	28	9	100%	5.8	31.3%	9.7%	21.6%	3.0%	3.56	3.70	+1.4
2029	35	MLB MLE	LAD	10	10	62	263	80	27	9	100%	6.2	30.3%	10.2%	20.1%	3.3%	3.84	4.03	+1.0
2028	34	MLB CTX	LAD	12	12	70	296	93	29	9	100%	5.8	31.3%	9.7%	21.6%	3.1%	3.63	3.77	+1.4
2029	35	MLB CTX	LAD	10	10	62	262	79	27	9	100%	6.2	30.3%	10.2%	20.1%	3.5%	3.92	4.11	+1.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		202	163	960	3930	1222	364	119	81%	4.8	31.1%	9.3%	21.8%	3.0%	3.72	3.31	+24.5
/ 200 IP	—	RAW		42	34	200	819	255	76	25	81%	4.8	31.1%	9.3%	21.8%	3.0%	3.72	3.31	+5.1
Career	—	MLE		254	215	1187	4804	1470	474	123	85%	4.7	30.6%	9.9%	20.7%	2.6%	3.23	3.17	+24.1
/ 200 IP	—	MLE		43	36	200	809	248	80	21	85%	4.7	30.6%	9.9%	20.7%	2.6%	3.23	3.17	+5.0

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.

2026 AAAOklahoma City Comets · 12 IPFIP 0.42 → 0.85 (+0.42)K% 46.3% → 39.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	46.34%	—	×0.860	39.85%
BB% (unintentional) /BF	9.76%	—	×0.900	8.78%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 0.42 → 0.85, 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).

2025 AAAOklahoma City Comets · 9 IPFIP 3.49 → 3.87 (+0.37)K% 27.9% → 24.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.91%	—	×0.860	24.00%
BB% (unintentional) /BF	11.63%	—	×0.900	10.47%
HR / BF /BF	2.33%	÷0.956	×1.100	2.68%

Result: FIP 3.49 → 3.87, 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 AAADurham Bulls · 13 IPFIP 2.13 → 2.42 (+0.30)K% 38.5% → 33.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.46%	—	×0.860	33.08%
BB% (unintentional) /BF	9.62%	—	×0.900	8.65%
HR / BF /BF	1.92%	÷1.137	×1.100	1.86%

Result: FIP 2.13 → 2.42, 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 AAADurham Bulls · 7 IPFIP 0.50 → 1.14 (+0.64)K% 53.8% → 47.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	53.85%	—	×0.880	47.38%
BB% (unintentional) /BF	15.38%	—	×1.050	16.15%
HR / BF /BF	0.00%	÷1.034	×1.100	0.00%

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 107).

Result: FIP 0.50 → 1.14, 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).

2017 AAAIndianapolis Indians · 93 IPFIP 1.87 → 2.58 (+0.71)K% 38.5% → 33.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.46%	—	×0.880	33.85%
BB% (unintentional) /BF	8.79%	—	×1.050	9.23%
HR / BF /BF	1.65%	÷0.850	×1.100	2.13%

Result: FIP 1.87 → 2.58, 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).

2016 AAAIndianapolis Indians · 111 IPFIP 2.83 → 3.32 (+0.49)K% 30.4% → 26.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.37%	—	×0.880	26.72%
BB% (unintentional) /BF	14.16%	—	×1.050	14.86%
HR / BF /BF	0.91%	÷0.933	×1.100	1.08%

Result: FIP 2.83 → 3.32, 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).

2016 AAAltoona Curve · 6 IPFIP 4.51 → 5.81 (+1.30)K% 40.7% → 33.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.74%	—	×0.810	33.00%
BB% (unintentional) /BF	22.22%	—	×1.100	24.44%
HR / BF /BF	3.70%	÷1.016	×1.200	4.37%

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 103).

Result: FIP 4.51 → 5.81, 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).

2015 AAAltoona Curve · 63 IPFIP 1.72 → 2.49 (+0.77)K% 33.1% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.06%	—	×0.810	26.78%
BB% (unintentional) /BF	7.66%	—	×1.100	8.43%
HR / BF /BF	0.81%	÷0.912	×1.200	1.06%

Result: FIP 1.72 → 2.49, 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
Tyler Glasnow (OGILVIE)	—	—	—	—	—	2.7%	—	3.86	30.8%	20.9%	132	+0.47	—	—	—
Kenta Maeda R 2021 · 3.79 FIP	33	SP	3.79	24.9%	6.8%	3.5%	.307	4.26	23.6%	17.1%	230	+0.47	2.87	1,092	56
Junior Guerra R 2018 · 3.99 FIP	33	SP	3.99	22.3%	9.0%	3.0%	.309	4.12	21.2%	9.1%	173	+0.13	3.18	646	53
Josh Lowey R 2017 · 2.36 FIP	32	SP	2.36	24.7%	6.9%	0.9%	.330	3.45	22.4%	15.6%	53	+1.09	2.22	426	41
Jose Oyervides R 2015 · 3.01 FIP	33	SP	3.01	19.1%	6.2%	1.4%	.333	4.09	21.9%	14.5%	184	+1.08	3.01	407	39
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	1.83	480	38
Chuck Smith R 2001 · 3.99 FIP	31	SP	3.99	18.4%	8.1%	2.6%	.289	—	—	—	—	—	3.08	211	38
Jarrett Grube R 2015 · 3.75 FIP	33	SP	3.75	18.7%	4.2%	3.1%	.285	4.57	17.3%	9.6%	253	+0.82	3.75	393	37
Manuel Flores R 2019 · 4.32 FIP	33	SP	4.32	17.1%	7.4%	3.1%	.291	—	—	—	—	—	3.46	515	33
Juan Delgadillo R 2015 · 4.54 FIP	32	SP	4.54	15.5%	7.2%	3.3%	.316	4.47	10.9%	4.7%	39	-0.07	4.47	143	30
Mitch Lively R 2017 · 3.47 FIP	31	SP-	3.47	17.0%	6.4%	1.8%	.304	—	—	—	—	—	2.39	158	30
Hector Ambriz R 2016 · 3.63 FIP	32	SP	3.63	16.0%	6.4%	2.0%	.273	6.40	10.4%	2.9%	91	+2.77	2.24	259	28
Logan Duran R 2015 · 3.42 FIP	33	SP	3.42	15.8%	10.0%	0.7%	.287	3.77	15.3%	6.4%	95	+0.35	3.42	187	28
Kenshin Kawakami R 2009 · 3.97 FIP	34	SP-	3.97	15.7%	7.6%	2.2%	.277	4.06	15.1%	9.5%	87	+0.09	3.97	244	27
Merrill Kelly R 2022 · 3.69 FIP	33	SP	3.69	22.0%	7.3%	2.8%	.267	3.76	23.5%	15.9%	435	+0.07	3.60	1,170	27
Yusei Kikuchi L 2024 · 3.41 FIP	33	SP	3.41	28.0%	6.0%	3.5%	.308	3.93	22.4%	13.1%	246	+0.52	3.23	1,056	27
Hisashi Iwakuma R 2014 · 3.19 FIP	33	SP	3.19	21.7%	2.7%	2.9%	.285	4.19	18.6%	13.5%	360	+1.00	3.19	884	26
Koji Uehara R 2009 · 3.52 FIP	34	SP	3.52	17.2%	3.9%	2.5%	.300	2.55	33.5%	30.6%	145	-0.97	1.28	481	26
Jorge Martinez R 2017 · 3.70 FIP	32	SP	3.70	17.1%	2.6%	3.1%	.355	3.71	16.3%	10.6%	117	+0.01	3.53	214	26
Yoanner Negrin R 2017 · 3.15 FIP	33	SP	3.15	15.6%	6.0%	1.1%	.277	3.87	17.5%	9.4%	148	+0.72	3.15	485	26
Miguel González R 2017 · 4.54 FIP	33	SP	4.54	14.6%	7.7%	3.1%	.285	6.88	7.6%	-1.5%	12	+2.34	3.72	905	24

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	5.2	80	31.2%	9.4%	1.16	3.69
John Hiller ('65-'80, 25 WAR*)	6.2	96	28.7%*	10.1%*	1.16*	3.19*
Tom Hall ('68-'77, 7 WAR*)	4.3	95	30.7%*	10.2%*	1.35*	3.95*
Dick Radatz ('62-'69, 14 WAR*)	3.5	99	32.8%*	10.1%*	1.06*	3.49*
Octavio Dotel ('13)	4.8	79	28.4%	10.2%	1.11	3.78
Héctor Neris ('25)	3.1	57	29.4%	9.2%	1.19	3.47
Ugueth Urbina ('05)	3.5	70	27.9%	10.5%	1.11	3.45