Casey Mize

P San Diego Padres

Age 30 RHP 6'3" / 212 lbs MLB Svc 6.0 · Ctrl thru 2027 peak 1.2 · 2027

Overview

MLBSP40-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MIX2 levels	26	24	116	4.27	3.55	18.8%	6.5%	2.6	K 18.3% · BB 6.4% · FIP 3.62
2025	28	MLBDET	28	28	149	3.87	3.77	22.2%	5.6%	2.9
2026	29	MIX2 levels	27	27	136	4.22	4.08	20.3%	6.9%	2.1	K 20.0% · BB 6.9% · FIP 4.04
2027PROJ	30	MLBSD	16	16	98	4.25	4.31	20.8%	6.5%	1.3
2028PROJ	31	MLBSD	14	14	83	4.47	4.59	20.0%	6.8%	0.8
2029PROJ	32	MLBSD	11	11	66	4.69	4.84	19.2%	7.2%	0.5

Last 3 seasons WAR 7.7 · Next 3 projected WAR 2.5Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service6.645First FA2028Options2

2027Ext / FA-deal$10M

Skills · percentileStatcast 2026

xwOBA vs59

K%35

FB Velo33

Form8.72 ERA (proj 4.25) · K 13.6% (proj 20.8%) · BB 10.7% (proj 6.5%) ▼▼ last 60d · 22 IP through Oct 27

CompsChase Anderson (age 30) · Miguel González (age 30) · Rolando Arrojo (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 110101vR 93

ERA4.25

FIP4.31

K%20.8%

BB%6.5%

K-BB%14.3%

Proj IP98

Value2027 · WAR

Runs saved vs league avg · 98 IP

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

Statcast · Contract

Statcast Percentiles

FB Velo

p3393.3

Whiff%

p3523.2%

p3520.0%

xwOBA vs

p590.303

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

Status FA

MLB Debut 2020

Service 6.645 yrs.days

Team Control Through 2027

First FA Year 2028

OPT

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$10M	+1.3	$10M	+$0.0M
Totals		$10M		$10M	+$0.0M

Options · projected decision
2027	CLUB OPT	$10.4M / $0.0M buyout	DECLINE
2028	CLUB OPT	$3.1M / $0.0M buyout	DECLINE

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	21	MIX MLE	2 levels	5	5	14	55	14	3	2	100%	2.7	25.5%	5.5%	20.0%	3.6%	3.95	3.64	—
2018	21	MIX RAW	2 levels	5	5	14	55	14	3	2	100%	2.7	25.5%	5.5%	20.0%	3.6%	3.95	3.61	—
2019	22	MIX MLE	2 levels	21	21	109	430	106	23	5	100%	5.2	19.7%	5.9%	13.7%	1.1%	2.55	2.78	—
2019	22	MIX RAW	2 levels	21	21	109	430	106	23	5	100%	5.2	24.7%	5.3%	19.3%	1.2%	2.55	2.39	—
2020	23	MLB MLE	Detroit Tigers	7	7	28	133	26	13	7	100%	4.0	19.5%	9.8%	9.8%	5.5%	6.99	5.70	-0.1
2020	23	MLB RAW	Detroit Tigers	7	7	28	133	26	13	7	100%	4.0	19.5%	9.8%	9.8%	5.3%	6.99	5.85	-0.1
2021	24	MLB MLE	Detroit Tigers	30	30	150	612	118	41	24	100%	5.0	19.3%	6.7%	12.6%	4.1%	3.71	4.57	+1.5
2021	24	MLB RAW	Detroit Tigers	30	30	150	612	118	41	24	100%	5.0	19.3%	6.7%	12.6%	3.9%	3.71	4.42	+1.7
2022	25	MIX MLE	2 levels	3	3	11	52	4	2	2	100%	3.6	7.7%	3.8%	3.8%	3.8%	7.59	5.05	+0.0
2022	25	MIX RAW	2 levels	3	3	11	52	4	2	2	100%	3.6	7.7%	3.8%	3.8%	3.8%	7.59	5.35	+0.0
2024	27	MIX MLE	2 levels	26	24	116	506	95	33	11	92%	4.5	18.3%	6.4%	11.9%	2.3%	4.27	3.62	+2.5
2024	27	MIX MLE	2 levels	26	24	116	506	95	33	11	92%	4.5	18.3%	6.4%	11.9%	2.3%	4.27	3.62	+2.5
2024	27	MIX RAW	2 levels	26	24	116	506	95	33	11	92%	4.5	18.8%	6.5%	12.3%	2.2%	4.27	3.55	+2.6
2025	28	MLB MLE	Detroit Tigers	28	28	149	627	139	35	21	100%	5.3	22.2%	5.6%	16.6%	3.5%	3.87	3.85	+2.8
2025	28	MLB MLE	Detroit Tigers	28	28	149	627	139	35	21	100%	5.3	22.2%	5.6%	16.6%	3.5%	3.87	3.85	+2.8
2025	28	MLB RAW	Detroit Tigers	28	28	149	627	139	35	21	100%	5.3	22.2%	5.6%	16.6%	3.3%	3.87	3.77	+2.9
2026	29	MIX MLE	2 levels	27	27	136	567	115	39	19	100%	5.0	20.0%	6.9%	13.1%	3.2%	4.22	4.04	+2.2
2026	29	MIX MLE	2 levels	27	27	136	567	115	39	19	100%	5.0	20.0%	6.9%	13.1%	3.2%	4.22	4.04	+2.2
2026	29	MIX RAW	2 levels	27	27	136	567	115	39	19	100%	5.0	20.3%	6.9%	13.4%	3.4%	4.22	4.08	+2.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			115	113	571	2418	475	158	82	98%	5.0	19.6%	6.5%	13.1%	3.4%	4.22	4.13	+8.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	SD	16	16	98	414	86	27	13	100%	6.1	20.8%	6.5%	14.3%	3.2%	4.25	4.31	+1.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	SD	14	14	83	350	70	24	12	100%	5.9	20.0%	6.8%	13.2%	3.4%	4.42	4.54	+0.8
2029	32	MLB MLE	SD	11	11	66	281	54	20	10	100%	6.0	19.2%	7.2%	12.0%	3.7%	4.64	4.79	+0.5
2030	33	MLB MLE	SD	8	8	50	212	39	16	8	100%	6.3	18.4%	7.7%	10.7%	4.0%	4.90	5.07	+0.2
2028	31	MLB CTX	SD	14	14	83	350	70	24	12	100%	5.9	20.0%	6.8%	13.2%	3.5%	4.47	4.59	+0.8
2029	32	MLB CTX	SD	11	11	66	279	54	20	10	100%	6.0	19.2%	7.2%	12.0%	3.8%	4.69	4.84	+0.5
2030	33	MLB CTX	SD	8	8	50	211	39	16	9	100%	6.2	18.4%	7.7%	10.7%	4.0%	4.95	5.12	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		148	146	771	3261	638	219	113	99%	5.2	19.6%	6.7%	12.9%	3.5%	4.34	4.21	+10.8
/ 200 IP	—	RAW		38	38	200	846	166	57	29	99%	5.2	19.6%	6.7%	12.9%	3.5%	4.34	4.21	+2.8
Career	—	MLE		147	145	714	2982	592	191	93	99%	4.9	19.8%	6.4%	13.4%	3.1%	3.95	3.94	+10.0
/ 200 IP	—	MLE		41	41	200	836	166	54	26	99%	4.9	19.8%	6.4%	13.4%	3.1%	3.95	3.94	+2.6

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.

2024 AAAToledo Mud Hens · 14 IPFIP 1.38 → 1.66 (+0.28)K% 31.5% → 27.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.48%	—	×0.860	27.07%
BB% (unintentional) /BF	7.41%	—	×0.900	6.67%
HR / BF /BF	0.00%	÷0.792	×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 58).

Result: FIP 1.38 → 1.66, 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 AAErie SeaWolves · 79 IPFIP 2.67 → 3.06 (+0.39)K% 23.5% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.53%	—	×0.810	19.06%
BB% (unintentional) /BF	5.57%	—	×1.100	6.13%
HR / BF /BF	1.55%	÷1.294	×1.200	1.44%

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 159).

Result: FIP 2.67 → 3.06, 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 A+Lakeland Flying Tigers · 31 IPFIP 1.32 → 1.96 (+0.63)K% 28.0% → 21.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.04%	—	×0.770	21.59%
BB% (unintentional) /BF	4.67%	—	×1.150	5.37%
HR / BF /BF	0.00%	÷0.963	×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 93).

Result: FIP 1.32 → 1.96, 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+Lakeland Flying Tigers · 12 IPFIP 4.16 → 4.59 (+0.44)K% 20.8% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.83%	—	×0.770	16.04%
BB% (unintentional) /BF	4.17%	—	×1.150	4.79%
HR / BF /BF	4.17%	÷1.277	×1.250	4.08%

Result: FIP 4.16 → 4.59, 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
Casey Mize (OGILVIE)	—	—	—	—	—	3.2%	—	4.76	19.3%	12.1%	200	+0.45	—	—	—
Chase Anderson R 2018 · 4.98 FIP	30	SP	4.98	19.9%	8.9%	4.4%	.235	4.93	20.1%	11.9%	253	-0.05	3.30	1,260	70
Miguel González R 2014 · 4.49 FIP	30	SP	4.49	16.5%	7.5%	3.4%	.268	4.26	16.6%	9.5%	457	-0.23	3.72	905	68
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	67
Tom Koehler R 2016 · 4.38 FIP	30	SP	4.38	19.0%	9.8%	3.0%	.291	4.66	22.4%	13.4%	110	+0.28	3.76	822	66
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
Matt Shoemaker R 2017 · 4.88 FIP	30	SP	4.88	21.2%	8.6%	4.5%	.271	4.29	23.5%	15.5%	88	-0.59	3.12	728	60
Marco Estrada R 2013 · 3.81 FIP	30	SP	3.81	23.0%	5.7%	3.5%	.260	4.34	20.4%	12.6%	508	+0.53	3.28	1,244	60
Lance Lynn R 2017 · 4.68 FIP	30	SP	4.68	19.7%	9.4%	3.7%	.237	3.25	25.9%	17.8%	449	-1.43	2.85	2,006	59
Masahiro Tanaka R 2019 · 4.01 FIP	30	SP	4.01	19.6%	5.3%	3.5%	.292	4.08	22.3%	18.2%	48	+0.07	2.82	1,054	59
Orlando Hernandez R 2000 · 4.68 FIP	30	SP	4.68	17.2%	6.0%	4.2%	.255	4.38	18.6%	11.3%	241	-0.30	3.35	1,315	58
Cory Lidle R 2002 · 3.67 FIP	30	SP	3.67	13.9%	4.5%	2.1%	.275	4.13	14.1%	8.3%	589	+0.46	3.48	1,318	58
Tanner Roark R 2017 · 3.88 FIP	30	SP	3.88	21.4%	7.6%	3.0%	.294	4.48	20.3%	13.2%	393	+0.60	2.40	1,194	57
Adrian Sampson R 2022 · 4.22 FIP	30	SP	4.22	16.1%	6.2%	3.1%	.278	4.88	14.4%	7.0%	244	+0.66	3.23	1,012	57
Mike Fiers R 2015 · 3.86 FIP	30	SP	3.86	23.7%	7.8%	3.2%	.277	4.73	19.9%	13.3%	494	+0.87	2.83	1,140	57
Rodrigo Lopez R 2006 · 4.67 FIP	30	SP-	4.67	16.1%	6.7%	3.8%	.325	4.30	13.2%	7.9%	109	-0.37	4.06	1,344	57
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	57
Chris Bassitt R 2019 · 4.20 FIP	30	SP	4.20	23.0%	7.7%	3.8%	.258	3.35	23.2%	16.9%	402	-0.85	2.92	1,596	56
Jeremy Guthrie R 2009 · 5.09 FIP	30	SP	5.09	12.6%	6.8%	4.0%	.282	4.41	13.7%	7.5%	599	-0.68	4.08	1,834	56
Christian Bergman R 2018 · 4.37 FIP	30	SP	4.37	15.7%	6.3%	3.3%	.327	7.36	13.2%	6.6%	26	+2.99	3.99	521	56
Kyle Gibson R 2018 · 3.97 FIP	30	SP	3.97	21.7%	9.3%	2.8%	.282	3.91	21.2%	12.9%	409	-0.06	3.56	1,920	56

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	96	19.7%	6.7%	1.33	4.31
Scott Bankhead ('86-'95, 10 WAR*)	4.5	100	21.2%*	7.3%*	1.36*	4.16*
Lee Stange ('61-'70, 9 WAR*)	6.1	135	17.8%*	6.6%*	1.36*	4.14*
Mark Leiter ('90-'01, 5 WAR*)	5.9	118	20.7%*	7.8%*	1.36*	4.61*
Chris Capuano ('16)	7.1	119	19.5%	7.5%	1.23	4.38
Matt Andriese ('24)	2.6	74	21.8%	6.7%	1.36	4.65
Carlos Villanueva ('16)	5.0	91	20.4%	7.6%	1.25	4.31