Blake Snell

P Los Angeles Dodgers

Age 34 LHP 6'4" / 225 lbs MLB Svc 10.0 · Ctrl thru 2029 peak 2.3 · 2028

Overview

MLBSP40-MANExtFA 2028

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	31	MIX3 levels	25	25	123	3.01	2.18	36.4%	10.3%	5.1	K 35.1% · BB 10.4% · FIP 2.33
2025	32	MIX4 levels	15	15	75	2.16	2.26	31.3%	9.8%	3.0	K 28.3% · BB 9.8% · FIP 2.57
2026	33	MIX3 levels	16	16	62	2.31	2.14	33.2%	9.1%	2.6	K 31.8% · BB 9.2% · FIP 1.59
2027PROJ	34	MLBLAD	11	11	64	2.94	2.91	31.6%	9.6%	2.0
2028PROJ	35	MLBLAD	14	14	84	3.17	3.29	30.6%	10.1%	2.2
2029PROJ	36	MLBLAD	13	13	76	3.30	3.39	31.6%	9.9%	1.9

Last 3 seasons WAR 10.7 · Next 3 projected WAR 6.2Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2029Service10.419First FA2028Options2

2027Ext$36M2028Ext$36M2029Ext$36M

Skills · percentileStatcast 2026

K%90

xwOBA vs90

FB Velo71

Form1.25 ERA (proj 2.94) · K 33.7% (proj 31.6%) · BB 8.1% (proj 9.6%) ▲ last 60d · 22 IP through Oct 27

CompsOrlando Lara (age 34) · Francisley Bueno (age 34) · Oscar Rivera (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 5866vR 75

ERA2.94

FIP2.91

K%31.6%

BB%9.6%

K-BB%22.0%

Proj IP64

Value2027 · WAR

Runs saved vs league avg · 64 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit option yr-$111M ctrl surplus

Statcast · Contract

Statcast Percentiles

FB Velo

p7196.0

Whiff%

p9034.8%

p9031.8%

xwOBA vs

p900.228

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

Status FA

MLB Debut 2016

Service 10.419 yrs.days

Team Control Through 2029

First FA Year 2028

OPTDEF 20%

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$36M	+2.0	$16M	-$20M
2028	Ext	$36M	+2.2	$16M	-$16M
2029	Ext	$36M	+1.9	$13M	-$16M
Totals		$109M		$45M	-$53M

Options · projected decision
2030	PLAYER OPT	$30.0M / $0.0M buyout	EXERCISE
2031	PLAYER OPT	$36.4M / $0.0M buyout	EXERCISE

Underwater contract
Projected production over the remaining contract is worth -$53M 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 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	22	MIX MLE	3 levels	25	23	134	521	163	53	7	92%	5.4	25.9%	11.2%	14.7%	1.6%	1.41	3.19	—
2015	22	MIX RAW	3 levels	25	23	134	521	163	53	7	92%	5.4	31.3%	10.2%	21.1%	1.3%	1.41	2.53	—
2016	23	MIX MLE	2 levels	31	31	152	671	188	79	9	100%	4.9	26.4%	12.0%	14.4%	1.3%	3.43	3.12	+4.3
2016	23	MIX RAW	2 levels	31	31	152	671	188	79	9	100%	4.9	28.0%	11.8%	16.2%	1.3%	3.43	2.96	+4.6
2017	24	MIX MLE	2 levels	31	31	173	734	180	73	20	100%	5.6	23.5%	10.0%	13.5%	2.8%	3.69	3.93	+3.0
2017	24	MIX RAW	2 levels	31	31	173	734	180	73	20	100%	5.6	24.5%	9.9%	14.6%	2.7%	3.69	3.79	+3.4
2018	25	MLB MLE	Tampa Bay Rays	31	31	181	700	221	62	16	100%	5.8	31.6%	8.9%	22.7%	2.4%	1.89	2.85	+5.9
2018	25	MLB RAW	Tampa Bay Rays	31	31	181	700	221	62	16	100%	5.8	31.6%	8.9%	22.7%	2.3%	1.89	2.83	+5.9
2019	26	MLB MLE	Tampa Bay Rays	23	23	107	441	147	39	14	100%	4.7	33.3%	8.8%	24.5%	3.3%	4.29	3.20	+2.9
2019	26	MLB RAW	Tampa Bay Rays	23	23	107	441	147	39	14	100%	4.7	33.3%	8.8%	24.5%	3.2%	4.29	3.15	+3.0
2020	27	MLB MLE	Tampa Bay Rays	11	11	50	203	63	18	10	100%	4.5	31.0%	8.9%	22.2%	5.1%	3.24	4.38	+0.6
2020	27	MLB RAW	Tampa Bay Rays	11	11	50	203	63	18	10	100%	4.5	31.0%	8.9%	22.2%	4.9%	3.24	4.26	+0.7
2021	28	MLB MLE	San Diego Padres	27	27	129	550	170	68	16	100%	4.8	30.9%	12.4%	18.5%	2.8%	4.20	3.61	+2.8
2021	28	MLB RAW	San Diego Padres	27	27	129	550	170	68	16	100%	4.8	30.9%	12.4%	18.5%	2.9%	4.20	3.66	+2.7
2022	29	MIX MLE	4 levels	27	27	141	587	190	53	12	100%	5.2	32.0%	9.5%	22.4%	2.0%	3.32	2.71	+4.8
2022	29	MIX RAW	4 levels	27	27	141	587	190	53	12	100%	5.2	32.4%	9.0%	23.3%	2.0%	3.32	2.64	+4.9
2023	30	MLB MLE	San Diego Padres	32	32	180	742	234	99	15	100%	5.6	31.5%	13.3%	18.2%	2.0%	2.25	3.21	+4.9
2023	30	MLB RAW	San Diego Padres	32	32	180	742	234	99	15	100%	5.6	31.5%	13.3%	18.2%	2.0%	2.25	3.23	+4.8
2024	31	MIX MLE	3 levels	25	25	123	486	177	50	7	100%	4.9	35.1%	10.4%	24.7%	1.6%	3.01	2.33	+4.8
2024	31	MIX MLE	3 levels	25	25	123	486	177	50	7	100%	4.9	35.1%	10.4%	24.7%	1.6%	3.01	2.33	+4.8
2024	31	MIX RAW	3 levels	25	25	123	486	177	50	7	100%	4.9	36.4%	10.3%	26.1%	1.4%	3.01	2.18	+5.1
2025	32	MIX MLE	4 levels	15	15	75	307	96	30	3	100%	5.0	28.3%	9.8%	18.5%	1.1%	2.16	2.57	+2.7
2025	32	MIX MLE	4 levels	15	15	75	307	96	30	3	100%	5.0	28.3%	9.8%	18.5%	1.1%	2.16	2.57	+2.7
2025	32	MIX RAW	4 levels	15	15	75	307	96	30	3	100%	5.0	31.3%	9.8%	21.5%	1.0%	2.16	2.26	+3.0
2026	33	MIX MLE	3 levels	16	16	62	253	84	23	3	100%	3.9	31.8%	9.2%	22.5%	0.0%	2.31	1.59	+3.1
2026	33	MIX MLE	3 levels	16	16	62	253	84	23	3	100%	3.9	31.8%	9.2%	22.5%	0.0%	2.31	1.59	+3.1
2026	33	MIX RAW	3 levels	16	16	62	253	84	23	3	100%	3.9	33.2%	9.1%	24.1%	1.2%	2.31	2.14	+2.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			231	231	1201	4964	1495	531	111	100%	5.2	30.1%	10.7%	19.4%	2.2%	3.10	3.14	+33.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	LAD	11	11	64	270	85	26	4	100%	5.8	31.6%	9.6%	22.0%	1.6%	2.94	2.91	+2.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	LAD	14	14	84	353	108	36	7	100%	6.0	30.6%	10.1%	20.5%	1.9%	3.12	3.24	+2.2
2029	36	MLB MLE	LAD	13	13	76	320	101	32	7	100%	5.8	31.6%	9.9%	21.7%	2.3%	3.25	3.34	+1.9
2030	37	MLB MLE	LAD	11	11	66	280	85	30	8	100%	6.0	30.5%	10.6%	20.0%	2.7%	3.54	3.74	+1.3
2031	38	MLB MLE	LAD	8	8	51	214	63	24	7	100%	6.3	29.4%	11.3%	18.1%	3.2%	3.92	4.17	+0.7
2028	35	MLB CTX	LAD	14	14	84	355	109	36	7	100%	6.0	30.6%	10.1%	20.5%	2.0%	3.17	3.29	+2.2
2029	36	MLB CTX	LAD	13	13	76	321	101	32	8	100%	5.8	31.6%	9.9%	21.7%	2.4%	3.30	3.39	+1.9
2030	37	MLB CTX	LAD	11	11	66	279	85	29	8	100%	6.0	30.5%	10.6%	20.0%	2.9%	3.60	3.80	+1.3
2031	38	MLB CTX	LAD	8	8	51	215	63	24	7	100%	6.4	29.4%	11.3%	18.1%	3.3%	3.99	4.24	+0.7
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		277	277	1477	6131	1853	652	141	100%	5.3	30.2%	10.6%	19.6%	2.3%	3.17	3.16	+41.1
/ 200 IP	—	RAW		38	38	200	830	251	88	19	100%	5.3	30.2%	10.6%	19.6%	2.3%	3.17	3.16	+5.6
Career	—	MLE		294	292	1507	6195	1846	659	132	99%	5.1	29.8%	10.6%	19.2%	2.1%	2.92	3.10	+39.8
/ 200 IP	—	MLE		39	39	200	822	245	87	18	99%	5.1	29.8%	10.6%	19.2%	2.1%	2.92	3.10	+5.4

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 5.60 → 6.12 (+0.52)K% 28.6% → 24.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.57%	—	×0.860	24.57%
BB% (unintentional) /BF	12.24%	—	×0.900	11.02%
HR / BF /BF	6.12%	÷1.000	×1.100	6.73%

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 5.60 → 6.12, 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).

2026 AOntario Tower Buzzers · 8 IPFIP -0.58 → 0.56 (+1.14)K% 48.4% → 35.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	48.39%	—	×0.740	35.81%
BB% (unintentional) /BF	3.23%	—	×1.180	3.81%
HR / BF /BF	0.00%	÷1.000	×1.300	0.00%

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 100).

Result: FIP -0.58 → 0.56, 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 1.69 → 1.97 (+0.27)K% 39.4% → 33.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.39%	—	×0.860	33.88%
BB% (unintentional) /BF	15.15%	—	×0.900	13.64%
HR / BF /BF	0.00%	÷0.956	×1.100	0.00%

Result: FIP 1.69 → 1.97, 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).

2024 AAASacramento River Cats · 15 IPFIP 1.67 → 2.15 (+0.48)K% 44.6% → 38.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	44.64%	—	×0.860	38.39%
BB% (unintentional) /BF	10.71%	—	×0.900	9.64%
HR / BF /BF	1.79%	÷1.010	×1.100	1.94%

Result: FIP 1.67 → 2.15, 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 AAADurham Bulls · 44 IPFIP 2.83 → 3.28 (+0.45)K% 32.6% → 28.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.62%	—	×0.880	28.71%
BB% (unintentional) /BF	8.02%	—	×1.050	8.42%
HR / BF /BF	2.67%	÷1.049	×1.100	2.80%

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 110).

Result: FIP 2.83 → 3.28, 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 AAADurham Bulls · 63 IPFIP 2.41 → 2.77 (+0.36)K% 33.3% → 29.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.880	29.33%
BB% (unintentional) /BF	10.37%	—	×1.050	10.89%
HR / BF /BF	1.48%	÷1.167	×1.100	1.40%

Result: FIP 2.41 → 2.77, 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 AAMontgomery Biscuits · 69 IPFIP 3.01 → 3.84 (+0.84)K% 29.5% → 23.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.48%	—	×0.810	23.88%
BB% (unintentional) /BF	10.82%	—	×1.100	11.90%
HR / BF /BF	1.87%	÷0.983	×1.200	2.28%

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 97).

Result: FIP 3.01 → 3.84, 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 AAADurham Bulls · 44 IPFIP 1.89 → 2.31 (+0.42)K% 33.3% → 29.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.880	29.33%
BB% (unintentional) /BF	7.60%	—	×1.050	7.98%
HR / BF /BF	1.17%	÷1.039	×1.100	1.24%

Result: FIP 1.89 → 2.31, 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
Blake Snell (OGILVIE)	—	—	—	—	—	1.6%	—	3.42	30.9%	20.8%	226	+0.51	—	—	—
Orlando Lara L 2019 · 4.09 FIP	34	SP	4.09	22.0%	7.8%	3.4%	.329	—	—	—	—	—	3.85	426	55
Francisley Bueno L 2015 · 3.77 FIP	34	SP	3.77	14.8%	7.1%	1.9%	.315	3.99	13.3%	6.6%	110	+0.22	2.43	188	41
Oscar Rivera L 2015 · 3.68 FIP	34	SP	3.68	14.2%	6.9%	1.7%	.298	4.66	10.4%	3.0%	129	+0.98	3.68	237	34
Tsuyoshi Wada L 2015 · 3.66 FIP	34	SP	3.66	16.8%	7.1%	2.0%	.307	—	—	—	—	—	3.60	188	34
Jose Oyervides R 2016 · 3.09 FIP	34	SP	3.09	24.9%	8.2%	1.9%	.318	5.55	17.0%	7.8%	195	+2.46	3.01	407	32
Mauricio Lara L 2015 · 3.62 FIP	36	SP	3.62	13.9%	6.9%	1.5%	.310	3.69	12.1%	5.1%	220	+0.07	3.62	444	32
Orlando Hernandez R 2004 · 3.77 FIP	34	SP	3.77	23.4%	10.0%	2.5%	.278	4.34	20.5%	11.7%	438	+0.57	3.35	1,315	31
Josh Lowey R 2019 · 3.45 FIP	34	SP	3.45	22.4%	6.8%	2.5%	.303	—	—	—	—	—	2.22	426	28
Hiroki Kuroda R 2009 · 3.54 FIP	34	SP	3.54	17.9%	4.7%	2.5%	.270	3.43	19.1%	14.2%	618	-0.11	2.96	1,319	20
Jonathan Castellanos R 2016 · 3.40 FIP	34	SP	3.40	15.2%	7.4%	1.2%	.314	5.04	9.4%	0.3%	174	+1.64	3.40	394	16
Merrill Kelly R 2023 · 3.73 FIP	34	SP	3.73	25.9%	9.6%	2.9%	.276	4.36	19.7%	12.0%	420	+0.63	3.60	1,170	15
Jorge Martinez R 2019 · 3.71 FIP	34	SP	3.71	16.3%	5.7%	2.3%	.348	—	—	—	—	—	3.53	214	14
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	14
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	13
Josh Lindblom R 2021 · 3.79 FIP	34	SP-	3.79	22.7%	6.9%	3.2%	.319	5.07	20.8%	12.0%	133	+1.28	1.83	480	13
Logan Duran R 2016 · 3.77 FIP	34	SP	3.77	15.3%	8.9%	1.5%	.299	3.66	15.5%	6.6%	29	-0.11	3.42	187	12
Jonathan Albaladejo R 2017 · 3.21 FIP	34	SP	3.21	14.2%	3.3%	1.6%	.341	—	—	—	—	—	2.30	173	11
Chris Smith R 2015 · 3.79 FIP	34	SP	3.79	20.0%	8.1%	2.5%	.306	4.41	18.4%	10.2%	285	+0.62	3.79	477	10
Albert Suárez R 2024 · 4.00 FIP	34	SP-	4.00	19.5%	6.8%	3.1%	.293	4.14	17.8%	10.6%	80	+0.14	3.58	616	10
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	9

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	7.7	96	30.3%	10.7%	0.87	3.15
John Hiller ('65-'80, 25 WAR*)	6.2	96	28.7%*	10.1%*	1.16*	3.19*
Kerry Wood ('12)	6.9	115	27.0%	11.4%	0.97	3.67
Rich Gossage ('72-'94, 35 WAR*)	9.0	82	29.1%*	9.6%*	0.88*	3.36*
Dave Righetti ('79-'95, 21 WAR*)	7.0	94	26.2%*	9.8%*	0.76*	3.76*
Francisco Rodríguez ('17)	4.9	65	28.5%	9.7%	0.90	2.86
David Robertson ('25)	4.5	64	31.9%	9.9%	0.82	2.93