Matthew Liberatore

P St. Louis Cardinals

Age 27 LHP 6'4" / 215 lbs MLB Svc 3.0 · Ctrl thru 2029 peak 0.9 · 2027

Overview

MLBSP40-MANArb-1FA 2030

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR
2024	24	MLBSTL	60	6	86	4.40	3.87	21.2%	7.0%	0.7
2025	25	MLBSTL	29	29	152	4.21	3.91	18.8%	6.2%	2.7
2026	26	MLBSTL	31	31	155	5.23	4.53	22.8%	8.2%	1.6
2027PROJ	27	MLBSTL	20	20	121	4.70	4.71	21.5%	7.5%	1.0
2028PROJ	28	MLBSTL	17	17	101	4.61	4.64	21.4%	7.7%	0.7
2029PROJ	29	MLBSTL	14	14	84	4.72	4.79	20.8%	7.9%	0.4

Last 3 seasons WAR 5.0 · Next 3 projected WAR 2.1Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2029Service3.837First FA2030

2027Arb-1$2M2028Arb-2$2M2029Arb-3$2M

Skills · percentileStatcast 2026

K%53

FB Velo47

xwOBA vs25

Form4.15 ERA (proj 4.70) · K 19.8% (proj 21.5%) · BB 9.0% (proj 7.5%) ▼ last 60d · 26 IP through Oct 27

CompsCasey Fossum (age 27) · Jorge De La Rosa (age 27) · Patrick Corbin (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 107115vR 123

ERA4.70

FIP4.71

K%21.5%

BB%7.5%

K-BB%14.0%

Proj IP121

Value2027 · WAR

Runs saved vs league avg · 121 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$10M ctrl surplus

Statcast · Contract

Statcast Percentiles

FB Velo

p4794.3

Whiff%

p4023.9%

p5322.8%

xwOBA vs

p250.341

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

Status Arb-1

MLB Debut 2022

Service 3.837 yrs.days

Team Control Through 2029

First FA Year 2030

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-1	$2M	+1.0	$8M	+$6M
2028	Arb-2	$2M	+0.7	$3M	+$0.4M
2029	Arb-3	$2M	+0.4	$1M	+$0.0M (cut)
Totals		$4M		$12M	+$6M

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	18	ROK MLE	Princeton Rays	9	9	33	127	37	13	0	100%	3.6	19.8%	12.8%	7.0%	0.0%	1.38	3.05	—
2018	18	ROK RAW	Princeton Rays	9	9	33	127	37	13	0	100%	3.6	29.1%	10.2%	18.9%	0.0%	1.38	2.03	—
2019	19	A MLE	Bowling Green Hot Rods	16	15	78	332	76	31	2	94%	4.9	16.9%	11.0%	5.9%	0.6%	3.10	3.40	—
2019	19	A RAW	Bowling Green Hot Rods	16	15	78	332	76	31	2	94%	4.9	22.9%	9.3%	13.6%	0.6%	3.10	2.68	—
2021	21	AAA MLE	Memphis Redbirds	22	18	125	520	123	33	19	82%	5.7	20.8%	6.7%	14.2%	4.2%	4.04	4.51	—
2021	21	AAA RAW	Memphis Redbirds	22	18	125	520	123	33	19	82%	5.7	23.7%	6.3%	17.3%	3.7%	4.04	3.90	—
2022	22	MIX MLE	2 levels	31	29	150	656	144	59	21	94%	4.8	19.8%	9.3%	10.5%	3.4%	5.35	4.46	+1.6
2022	22	MIX RAW	2 levels	31	29	150	656	144	59	21	94%	4.8	22.0%	9.0%	13.0%	3.2%	5.35	4.18	+2.2
2023	23	MIX MLE	2 levels	35	24	126	558	130	62	13	69%	3.6	21.2%	10.4%	10.8%	2.6%	4.70	4.07	+2.0
2023	23	MIX RAW	2 levels	35	24	126	558	130	62	13	69%	3.6	23.3%	11.1%	12.2%	2.3%	4.70	3.85	+2.3
2024	24	MLB MLE	St. Louis Cardinals	60	6	86	358	76	25	11	10%	1.4	21.2%	7.0%	14.2%	3.3%	4.40	4.01	+0.6
2024	24	MLB MLE	St. Louis Cardinals	60	6	86	358	76	25	11	10%	1.4	21.2%	7.0%	14.2%	3.3%	4.40	4.01	+0.6
2024	24	MLB RAW	St. Louis Cardinals	60	6	86	358	76	25	11	10%	1.4	21.2%	7.0%	14.2%	3.1%	4.40	3.87	+0.7
2025	25	MLB MLE	St. Louis Cardinals	29	29	152	648	122	40	19	100%	5.2	18.8%	6.2%	12.7%	3.2%	4.21	4.02	+2.5
2025	25	MLB MLE	St. Louis Cardinals	29	29	152	648	122	40	19	100%	5.2	18.8%	6.2%	12.7%	3.2%	4.21	4.02	+2.5
2025	25	MLB RAW	St. Louis Cardinals	29	29	152	648	122	40	19	100%	5.2	18.8%	6.2%	12.7%	2.9%	4.21	3.91	+2.7
2026	26	MLB MLE	St. Louis Cardinals	31	31	155	674	154	55	28	100%	5.0	22.8%	8.2%	14.7%	4.5%	5.23	4.66	+1.3
2026	26	MLB MLE	St. Louis Cardinals	31	31	155	674	154	55	28	100%	5.0	22.8%	8.2%	14.7%	4.5%	5.23	4.66	+1.3
2026	26	MLB RAW	St. Louis Cardinals	31	31	155	674	154	55	28	100%	5.0	22.8%	8.2%	14.7%	4.2%	5.23	4.53	+1.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			151	84	489	2116	426	162	68	56%	3.2	20.1%	7.7%	12.5%	3.2%	4.82	4.16	+7.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	STL	20	20	121	511	110	38	20	100%	6.0	21.5%	7.5%	14.0%	3.8%	4.70	4.71	+1.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	STL	17	17	101	426	91	33	17	100%	5.9	21.4%	7.7%	13.7%	3.9%	4.76	4.79	+0.7
2029	29	MLB MLE	STL	14	14	84	353	74	28	14	100%	6.0	20.8%	7.9%	12.9%	4.1%	4.88	4.95	+0.4
2030	30	MLB MLE	STL	11	11	69	291	58	24	12	100%	6.3	20.1%	8.2%	11.9%	4.3%	5.05	5.16	+0.2
2028	28	MLB CTX	STL	17	17	101	426	91	33	16	100%	5.9	21.4%	7.7%	13.7%	3.6%	4.61	4.64	+0.7
2029	29	MLB CTX	STL	14	14	84	355	74	28	13	100%	6.0	20.8%	7.9%	12.9%	3.8%	4.72	4.79	+0.4
2030	30	MLB CTX	STL	12	12	69	291	59	24	12	100%	5.8	20.1%	8.2%	11.9%	4.0%	4.89	5.00	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		193	126	742	3186	649	246	108	65%	3.8	20.4%	7.7%	12.6%	3.4%	4.79	4.23	+10.3
/ 200 IP	—	RAW		52	34	200	858	175	66	29	65%	3.8	20.4%	7.7%	12.6%	3.4%	4.79	4.23	+2.8
Career	—	MLE		233	161	904	3873	790	327	123	69%	3.9	20.4%	8.4%	12.0%	3.2%	4.44	4.19	+8.5
/ 200 IP	—	MLE		52	36	200	857	175	72	27	69%	3.9	20.4%	8.4%	12.0%	3.2%	4.44	4.19	+2.3

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.

2023 AAAMemphis Redbirds · 65 IPFIP 3.85 → 4.26 (+0.42)K% 29.7% → 25.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.68%	—	×0.860	25.53%
BB% (unintentional) /BF	13.43%	—	×0.900	12.08%
HR / BF /BF	2.83%	÷0.955	×1.100	3.26%

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 91).

Result: FIP 3.85 → 4.26, 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 AAAMemphis Redbirds · 115 IPFIP 3.94 → 4.32 (+0.38)K% 23.4% → 20.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.43%	—	×0.880	20.62%
BB% (unintentional) /BF	8.28%	—	×1.050	8.70%
HR / BF /BF	3.23%	÷1.048	×1.100	3.39%

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 3.94 → 4.32, 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).

2021 AAAMemphis Redbirds · 125 IPFIP 3.91 → 4.51 (+0.60)K% 23.7% → 20.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.65%	—	×0.880	20.82%
BB% (unintentional) /BF	6.35%	—	×1.050	6.66%
HR / BF /BF	3.65%	÷0.949	×1.100	4.24%

Result: FIP 3.91 → 4.51, 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 ABowling Green Hot Rods · 78 IPFIP 2.68 → 3.40 (+0.72)K% 22.9% → 16.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.89%	—	×0.740	16.94%
BB% (unintentional) /BF	9.34%	—	×1.180	11.02%
HR / BF /BF	0.60%	÷1.270	×1.300	0.62%

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 154).

Result: FIP 2.68 → 3.40, 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 ROKPrinceton Rays · 33 IPFIP 1.94 → 3.05 (+1.11)K% 29.1% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.13%	—	×0.680	19.81%
BB% (unintentional) /BF	10.24%	—	×1.250	12.80%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. 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 1.94 → 3.05, 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
Matthew Liberatore (OGILVIE)	—	—	—	—	—	3.8%	—	4.94	20.8%	13.0%	254	+0.23	—	—	—
Casey Fossum L 2005 · 4.19 FIP	27	SP-	4.19	17.7%	7.9%	2.9%	.287	4.77	14.9%	5.8%	247	+0.58	3.50	782	69
Jorge De La Rosa L 2008 · 3.77 FIP	27	SP-	3.77	22.4%	10.3%	2.3%	.310	3.70	23.0%	13.2%	366	-0.07	3.24	1,537	65
Patrick Corbin L 2016 · 4.54 FIP	27	SP-	4.54	18.7%	9.1%	3.4%	.317	3.12	27.0%	20.3%	592	-1.42	2.30	2,144	64
David Peterson L 2023 · 4.14 FIP	27	SP-	4.14	25.1%	10.7%	3.3%	.356	3.54	20.5%	11.2%	438	-0.60	2.81	1,078	63
Matthew Boyd L 2018 · 4.30 FIP	27	SP	4.30	22.4%	7.2%	4.0%	.252	4.32	26.2%	19.5%	324	+0.02	2.22	1,457	61
Daniel Lynch IV L 2024 · 4.14 FIP	27	SP-	4.14	18.1%	6.4%	3.2%	.268	4.53	15.7%	7.7%	154	+0.39	2.21	764	61
Manny Parra L 2010 · 4.19 FIP	27	SW	4.19	23.0%	10.7%	3.1%	.331	3.16	25.6%	15.3%	105	-1.03	2.43	710	59
Steven Brault L 2019 · 4.47 FIP	27	SP-	4.47	19.8%	10.1%	3.2%	.301	3.81	18.8%	8.2%	70	-0.66	3.12	691	59
Felix Doubront L 2015 · 3.92 FIP	27	SP	3.92	18.0%	8.4%	2.3%	.304	4.12	23.7%	14.7%	42	+0.20	3.44	719	57
Héctor Santiago L 2015 · 4.43 FIP	27	SP	4.43	20.9%	8.5%	3.7%	.245	5.13	19.2%	8.1%	378	+0.70	4.07	1,059	57
Danny Duffy L 2016 · 3.85 FIP	27	SP-	3.85	25.7%	5.7%	4.0%	.287	4.22	20.8%	12.4%	432	+0.37	3.02	1,222	56
Wandy Rodriguez L 2006 · 4.43 FIP	27	SP-	4.43	16.0%	9.2%	2.8%	.311	3.58	21.7%	14.6%	526	-0.85	3.37	1,572	55
Adam Conley L 2017 · 5.07 FIP	27	SP	5.07	14.6%	8.7%	3.8%	.293	4.43	18.9%	10.6%	151	-0.64	3.55	674	54
Ken Waldichuk L 2023 · 5.01 FIP	25	SP-	5.01	20.7%	11.0%	4.1%	.303	5.78	21.8%	6.9%	51	+0.77	3.51	432	54
Hogan Harris L 2024 · 4.46 FIP	27	SP-	4.46	20.3%	11.8%	2.9%	.312	3.42	26.7%	15.1%	150	-1.04	3.09	501	53
Steven Matz L 2018 · 4.33 FIP	27	SP	4.33	23.2%	8.6%	3.8%	.259	4.21	22.5%	15.9%	342	-0.12	3.19	1,226	53
Wade Miley L 2014 · 3.81 FIP	27	SP	3.81	21.1%	8.3%	2.6%	.313	4.15	18.8%	9.9%	517	+0.34	3.12	1,805	52
Ted Lilly L 2003 · 4.10 FIP	27	SP	4.10	19.0%	7.1%	3.1%	.283	4.64	19.2%	9.3%	505	+0.54	3.61	1,975	52
Dylan Dodd L 2024 · 4.71 FIP	26	SP-	4.71	17.5%	6.0%	4.2%	.338	3.97	26.5%	21.7%	123	-0.74	3.31	475	52
Tyler Anderson L 2017 · 4.02 FIP	27	SP-	4.02	22.4%	7.3%	3.4%	.315	4.35	20.7%	12.2%	256	+0.33	3.10	1,288	52

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	20.5%	7.8%	1.37	4.82
Hank Fischer ('62-'67, -1 WAR*)	2.7	91	19.8%*	8.2%*	1.33*	5.07*
Jerry Garvin ('77-'82, 4 WAR*)	3.0	101	19.3%*	8.4%*	1.44*	4.52*
Mark Grant ('84-'93, 0 WAR*)	3.2	91	18.0%*	8.5%*	1.41*	4.84*
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*
Drew Hutchison ('22)	2.9	84	19.2%	8.2%	1.29	4.89