Griffin Canning

P San Diego Padres

Age 31 RHP 6'2" / 180 lbs MLB peak 0.5 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	28	MLBLAA	32	31	172	5.19	5.07	17.6%	8.8%	0.6
2025	29	MLBNYM	16	16	76	3.77	4.00	21.3%	10.7%	1.3
2026	30	MIX2 levels	35	16	104	5.38	4.61	22.8%	11.5%	-0.1	K 22.3% · BB 11.3% · FIP 4.54
2027PROJ	31	MLBSD	12	12	70	4.82	4.81	21.3%	10.5%	0.5
2028PROJ	32	MLBSD	11	11	66	4.97	5.07	20.5%	10.9%	0.2
2029PROJ	33	MLBSD	8	8	50	5.20	5.35	19.6%	11.4%	0.0

Last 3 seasons WAR 1.8 · Next 3 projected WAR 0.7Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo51

K%51

xwOBA vs34

Form3.04 ERA (proj 4.82) · K 19.6% (proj 21.3%) · BB 8.8% (proj 10.5%) · last 90d · 24 IP through Oct 27

CompsChase Anderson (age 31) · Daisuke Matsuzaka (age 31) · Tim Adleman (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 122114vR 106

ERA4.82

FIP4.81

K%21.3%

BB%10.5%

K-BB%10.7%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p5194.6

Whiff%

p5125.5%

p5122.3%

xwOBA vs

p340.331

Contract

No contract data on file. Pre-MLB players and minor-league free agents do not yet have salary projections — entries are added at first 40-man roster placement.

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)
2018	22	MIX MLE	3 levels	25	25	113	475	125	44	8	100%	4.5	21.8%	10.0%	11.8%	2.1%	3.65	3.69	—
2018	22	MIX RAW	3 levels	25	25	113	475	125	44	8	100%	4.5	26.3%	9.3%	17.1%	1.7%	3.65	2.98	—
2019	23	MIX MLE	2 levels	21	20	106	444	113	32	14	95%	5.1	25.0%	7.2%	17.8%	3.1%	3.98	3.60	+2.3
2019	23	MIX RAW	2 levels	21	20	106	444	113	32	14	95%	5.1	25.5%	7.2%	18.2%	3.2%	3.98	3.59	+2.3
2020	24	MLB MLE	Los Angeles Angels	11	11	56	238	56	23	8	100%	5.1	23.5%	9.7%	13.9%	3.3%	3.99	4.15	+0.8
2020	24	MLB RAW	Los Angeles Angels	11	11	56	238	56	23	8	100%	5.1	23.5%	9.7%	13.9%	3.4%	3.99	4.18	+0.8
2021	25	MIX MLE	2 levels	15	14	65	292	66	33	15	93%	4.3	22.4%	10.1%	12.3%	5.0%	6.26	5.21	+0.1
2021	25	MIX RAW	2 levels	15	14	65	292	66	33	15	93%	4.3	22.6%	11.3%	11.3%	5.1%	6.26	5.61	-0.1
2023	27	MIX MLE	2 levels	25	23	132	558	149	37	22	92%	5.3	25.9%	6.5%	19.4%	4.0%	4.23	3.95	+2.3
2023	27	MIX RAW	2 levels	25	23	132	558	149	37	22	92%	5.3	26.7%	6.6%	20.1%	3.9%	4.23	3.85	+2.5
2024	28	MLB MLE	Los Angeles Angels	32	31	172	739	130	65	31	97%	5.4	17.6%	8.8%	8.8%	4.1%	5.19	4.99	+0.8
2024	28	MLB MLE	Los Angeles Angels	32	31	172	739	130	65	31	97%	5.4	17.6%	8.8%	8.8%	4.1%	5.19	4.99	+0.8
2024	28	MLB RAW	Los Angeles Angels	32	31	172	739	130	65	31	97%	5.4	17.6%	8.8%	8.8%	4.2%	5.19	5.07	+0.6
2025	29	MLB MLE	New York Mets	16	16	76	328	70	35	8	100%	4.8	21.3%	10.7%	10.7%	2.4%	3.77	3.99	+1.3
2025	29	MLB MLE	New York Mets	16	16	76	328	70	35	8	100%	4.8	21.3%	10.7%	10.7%	2.4%	3.77	3.99	+1.3
2025	29	MLB RAW	New York Mets	16	16	76	328	70	35	8	100%	4.8	21.3%	10.7%	10.7%	2.4%	3.77	4.00	+1.3
2026	30	MIX MLE	2 levels	35	16	104	460	105	53	16	46%	3.0	22.3%	11.3%	11.0%	3.4%	5.38	4.54	+0.0
2026	30	MIX MLE	2 levels	35	16	104	460	105	53	16	46%	3.0	22.3%	11.3%	11.0%	3.4%	5.38	4.54	+0.0
2026	30	MIX RAW	2 levels	35	16	104	460	105	53	16	46%	3.0	22.8%	11.5%	11.3%	3.5%	5.38	4.61	-0.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			145	121	673	2893	640	257	111	83%	4.6	22.1%	8.9%	13.2%	3.8%	4.79	4.49	+7.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	SD	12	12	70	296	63	31	10	100%	5.8	21.3%	10.5%	10.7%	3.3%	4.82	4.81	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	SD	11	11	66	278	57	30	10	100%	6.0	20.5%	10.9%	9.6%	3.5%	4.97	5.07	+0.2
2029	33	MLB MLE	SD	8	8	50	212	42	24	8	100%	6.3	19.6%	11.4%	8.2%	3.8%	5.20	5.35	+0.0
2028	32	MLB CTX	SD	11	11	66	279	57	30	10	100%	6.0	20.5%	10.9%	9.6%	3.5%	4.97	5.07	+0.2
2029	33	MLB CTX	SD	8	8	50	211	41	24	8	100%	6.2	19.6%	11.4%	8.2%	3.8%	5.20	5.35	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		164	140	789	3383	739	311	129	85%	4.8	21.8%	9.2%	12.6%	3.8%	4.83	4.51	+8.1
/ 200 IP	—	RAW		42	36	200	857	187	79	33	85%	4.8	21.8%	9.2%	12.6%	3.8%	4.83	4.51	+2.1
Career	—	MLE		180	156	824	3534	783	320	123	87%	4.6	22.2%	9.1%	13.1%	3.5%	4.56	4.29	+7.4
/ 200 IP	—	MLE		44	38	200	857	190	78	30	87%	4.6	22.2%	9.1%	13.1%	3.5%	4.56	4.29	+1.9

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 AAAEl Paso Chihuahuas · 15 IPFIP 4.69 → 4.94 (+0.25)K% 26.1% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.09%	—	×0.860	22.43%
BB% (unintentional) /BF	17.39%	—	×0.900	15.65%
HR / BF /BF	2.90%	÷1.000	×1.100	3.19%

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 4.69 → 4.94, 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 AInland Empire 66ers · 5 IPFIP 0.41 → 1.62 (+1.21)K% 45.5% → 33.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	45.45%	—	×0.740	33.64%
BB% (unintentional) /BF	9.09%	—	×1.180	10.73%
HR / BF /BF	0.00%	÷0.897	×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 79).

Result: FIP 0.41 → 1.62, 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).

2019 AAASalt Lake Bees · 16 IPFIP 1.13 → 1.44 (+0.31)K% 28.3% → 24.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.33%	—	×0.880	24.93%
BB% (unintentional) /BF	3.33%	—	×1.050	3.50%
HR / BF /BF	0.00%	÷1.059	×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 112).

Result: FIP 1.13 → 1.44, 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).

2018 AAASalt Lake Bees · 59 IPFIP 3.36 → 3.85 (+0.49)K% 24.5% → 21.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.52%	—	×0.880	21.58%
BB% (unintentional) /BF	8.43%	—	×1.050	8.85%
HR / BF /BF	2.30%	÷0.958	×1.100	2.64%

Result: FIP 3.36 → 3.85, 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).

2018 AAMobile BayBears · 46 IPFIP 2.75 → 3.47 (+0.72)K% 27.2% → 22.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.22%	—	×0.810	22.05%
BB% (unintentional) /BF	10.56%	—	×1.100	11.61%
HR / BF /BF	1.11%	÷0.959	×1.200	1.39%

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 92).

Result: FIP 2.75 → 3.47, 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).

2018 A+Inland Empire 66ers · 9 IPFIP 1.24 → 2.09 (+0.85)K% 35.3% → 27.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.29%	—	×0.770	27.18%
BB% (unintentional) /BF	8.82%	—	×1.150	10.15%
HR / BF /BF	0.00%	÷0.978	×1.250	0.00%

Factors used: pitcher A+ level factors — K ×0.77, BB ×1.15, HR ×1.25. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 96).

Result: FIP 1.24 → 2.09, 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
Griffin Canning (OGILVIE)	—	—	—	—	—	3.3%	—	5.19	20.1%	9.0%	116	+0.38	—	—	—
Chase Anderson R 2019 · 4.39 FIP	31	SP	4.39	20.9%	8.1%	3.7%	.259	5.39	19.2%	10.0%	218	+1.00	3.30	1,260	68
Daisuke Matsuzaka R 2012 · 5.55 FIP	31	SP	5.55	19.1%	9.3%	5.2%	.329	3.83	21.1%	9.5%	122	-1.72	3.77	790	68
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	63
Miguel González R 2015 · 4.53 FIP	31	SP	4.53	17.5%	7.9%	3.5%	.289	4.23	15.9%	9.0%	325	-0.30	3.72	905	63
Hideki Irabu R 2000 · 4.38 FIP	31	SP	4.38	17.0%	5.7%	3.6%	.374	5.19	17.2%	11.0%	64	+0.81	3.78	514	61
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	748	61
Orlando Hernandez R 2001 · 5.30 FIP	31	SP	5.30	18.6%	9.9%	4.6%	.256	3.78	20.4%	13.1%	231	-1.52	3.35	1,315	59
Luke Hudson R 2006 · 3.81 FIP	29	SP-	3.81	14.5%	8.4%	1.6%	.307	—	—	—	—	—	3.81	235	59
Joe Biagini R 2021 · 4.80 FIP	31	SP	4.80	18.0%	10.6%	3.4%	.309	4.53	16.4%	6.6%	39	-0.27	2.66	624	59
Scott Carroll R 2016 · 4.94 FIP	31	SP	4.94	10.5%	8.6%	3.0%	.289	5.71	14.4%	5.8%	22	+0.77	3.92	377	58
Chris Heston R 2017 · 5.88 FIP	29	SP-	5.88	13.6%	10.0%	4.9%	.368	—	—	—	—	—	3.81	321	58
Yu Darvish R 2018 · 4.50 FIP	31	SP	4.50	27.2%	11.7%	4.0%	.282	3.48	30.5%	24.0%	421	-1.02	1.97	1,798	57
Zack Segovia R 2015 · 4.78 FIP	32	SP	4.78	15.0%	8.3%	3.4%	.314	3.33	20.2%	14.3%	39	-1.45	3.33	144	57
Jeremy Hefner R 2016 · 4.64 FIP	30	SP	4.64	16.8%	9.1%	3.3%	.305	—	—	—	—	—	3.56	322	57
Chuck Smith R 2001 · 3.99 FIP	31	SP	3.99	18.4%	8.1%	2.6%	.289	—	—	—	—	—	3.08	211	57
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	57
Mike Wright Jr. R 2021 · 3.89 FIP	31	SP-	3.89	19.1%	8.8%	2.4%	.237	4.79	14.4%	1.1%	56	+0.90	3.76	725	56
Rolando Arrojo R 2000 · 4.47 FIP	32	SP	4.47	16.1%	8.0%	3.1%	.291	3.68	16.4%	9.2%	185	-0.79	3.50	700	55
Kenta Maeda R 2019 · 3.68 FIP	31	SP-	3.68	27.1%	8.0%	3.4%	.240	3.44	27.8%	22.0%	173	-0.24	2.87	1,092	55
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	55

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	4.3	86	21.8%	9.4%	1.46	4.83
Brad Havens ('81-'89, 2 WAR*)	3.0	84	21.0%*	9.5%*	1.43*	4.96*
Daniel Norris ('23)	2.9	73	21.5%	8.9%	1.39	4.73
Vince Velasquez ('15-'23, 2 WAR*)	3.8	85	21.9%*	9.2%*	1.37*	4.99*
Scott Sanders ('99)	3.4	97	21.2%	9.3%	1.23	4.86
John Boozer ('62-'69, -2 WAR*)	2.0	66	21.1%*	9.0%*	1.46*	5.15*
Vicente Palacios ('87-'00, 1 WAR*)	1.9	62	21.0%*	10.0%*	1.41*	4.86*