Matt Svanson

P St. Louis Cardinals

Age 28 RHP 6'5" / 235 lbs MLB peak 0.3 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	AASTL	53	0	64	2.69	3.19	20.8%	8.5%	—	K 16.9% · BB 9.3% · FIP 3.53
2025	26	MIX2 levels	54	0	82	2.30	2.60	27.1%	8.7%	1.9	K 26.2% · BB 8.5% · FIP 2.70
2026	27	MIX2 levels	63	1	67	5.26	3.18	23.1%	8.7%	1.1	K 21.8% · BB 8.5% · FIP 3.33
2027PROJ	28	MLBSTL	41	0	43	3.98	3.94	22.9%	8.2%	0.3
2028PROJ91% MLB	29	MLBSTL	33	0	35	4.05	4.10	22.4%	8.4%	0.2
2029PROJ92% MLB	30	MLBSTL	27	0	28	4.21	4.31	21.7%	8.7%	0.1

Last 3 seasons WAR 3.0 · Next 3 projected WAR 0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo77

K%34

xwOBA vs10

CompsRyan Brasier (age 28) · Blake Treinen (age 28) · Matt Ramsey (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 121113vR 104

ERA3.98

FIP3.94

K%22.9%

BB%8.2%

K-BB%14.8%

Proj IP48

Value2027 · WAR

Runs saved vs league avg · 48 IP

Grades · Statcast · Contract

Scouting Grades

STUF4545

CTRL5050

CMD6060

K†5555

Statcast Percentiles

FB Velo

p7796.4

Whiff%

p1018.8%

p3419.8%

xwOBA vs

p100.369

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)
2021	22	A MLE	Dunedin Blue Jays	11	0	16	66	23	8	0	0%	1.4	25.8%	14.3%	11.5%	0.0%	2.30	2.73	—
2021	22	A RAW	Dunedin Blue Jays	11	0	16	66	23	8	0	0%	1.4	34.8%	12.1%	22.7%	0.0%	2.30	1.70	—
2022	23	MIX MLE	2 levels	28	9	82	348	83	23	10	32%	2.9	17.8%	7.8%	10.1%	4.0%	4.15	4.78	—
2022	23	MIX RAW	2 levels	28	9	82	348	83	23	10	32%	2.9	23.9%	6.6%	17.2%	2.9%	4.15	3.50	—
2023	24	MIX MLE	3 levels	41	0	53	212	64	15	0	0%	1.3	23.9%	8.5%	15.4%	0.0%	1.86	2.16	—
2023	24	MIX RAW	3 levels	41	0	53	212	64	15	0	0%	1.3	30.2%	7.1%	23.1%	0.0%	1.86	1.54	—
2024	25	AA MLE	Springfield Cardinals	53	0	64	283	59	24	4	0%	1.2	16.9%	9.3%	7.6%	1.2%	2.69	3.53	—
2024	25	AA MLE	Springfield Cardinals	53	0	64	283	59	24	4	0%	1.2	16.9%	9.3%	7.6%	1.2%	2.69	3.53	—
2024	25	AA RAW	Springfield Cardinals	53	0	64	283	59	24	4	0%	1.2	20.8%	8.5%	12.4%	1.4%	2.69	3.19	—
2025	26	MIX MLE	2 levels	54	0	82	332	90	29	4	0%	1.5	26.2%	8.5%	17.7%	1.4%	2.30	2.70	+1.8
2025	26	MIX MLE	2 levels	54	0	82	332	90	29	4	0%	1.5	26.2%	8.5%	17.7%	1.4%	2.30	2.70	+1.8
2025	26	MIX RAW	2 levels	54	0	82	332	90	29	4	0%	1.5	27.1%	8.7%	18.4%	1.2%	2.30	2.60	+1.9
2026	27	MIX MLE	2 levels	63	1	67	299	69	26	5	2%	1.1	21.8%	8.5%	13.2%	1.8%	5.26	3.33	+1.0
2026	27	MIX MLE	2 levels	63	1	67	299	69	26	5	2%	1.1	21.8%	8.5%	13.2%	1.8%	5.26	3.33	+1.0
2026	27	MIX RAW	2 levels	63	1	67	299	69	26	5	2%	1.1	23.1%	8.7%	14.4%	1.7%	5.26	3.18	+1.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			80	1	104	441	109	41	8	1%	1.3	24.7%	9.3%	15.4%	1.8%	4.17	3.19	+1.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	STL	41	0	43	182	42	15	5	0%	1.0	22.9%	8.2%	14.8%	2.5%	3.98	3.94	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	STL	37	0	38	163	36	14	4	0%	1.0	22.4%	8.4%	14.0%	2.6%	4.05	4.10	+0.2
2029	30	MLB MLE	STL	28	0	30	126	27	11	4	0%	1.1	21.7%	8.7%	13.0%	2.8%	4.21	4.31	+0.1
2028	29	MLB CTX	STL	33	0	35	148	33	12	4	0%	1.1	22.4%	8.4%	14.0%	2.6%	4.05	4.10	+0.2
2029	30	MLB CTX	STL	27	0	28	118	26	10	3	0%	1.0	21.7%	8.7%	13.0%	2.8%	4.21	4.31	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		140	1	166	706	167	64	15	1%	1.2	23.7%	9.0%	14.7%	2.2%	4.15	3.42	+2.2
/ 200 IP	—	RAW		168	1	200	848	201	77	18	1%	1.2	23.7%	9.0%	14.7%	2.2%	4.15	3.42	+2.7
Career	—	MLE		250	10	364	1540	330	134	27	4%	1.5	21.4%	8.7%	12.7%	1.8%	3.27	3.37	+2.0
/ 200 IP	—	MLE		137	5	200	847	181	74	15	4%	1.5	21.4%	8.7%	12.7%	1.8%	3.27	3.37	+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.

2026 AAAMemphis Redbirds · 23 IPFIP 1.22 → 1.51 (+0.29)K% 30.4% → 26.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.43%	—	×0.860	26.17%
BB% (unintentional) /BF	5.43%	—	×0.900	4.89%
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 1.22 → 1.51, 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).

2025 AAAMemphis Redbirds · 22 IPFIP 2.93 → 3.23 (+0.30)K% 22.4% → 19.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.45%	—	×0.860	19.31%
BB% (unintentional) /BF	9.18%	—	×0.900	8.27%
HR / BF /BF	1.02%	÷0.869	×1.100	1.29%

Result: FIP 2.93 → 3.23, 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 AASpringfield Cardinals · 64 IPFIP 3.19 → 3.53 (+0.34)K% 20.8% → 16.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.85%	—	×0.810	16.89%
BB% (unintentional) /BF	8.48%	—	×1.100	9.33%
HR / BF /BF	1.41%	÷1.386	×1.200	1.22%

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 177).

Result: FIP 3.19 → 3.53, 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 A+Vancouver Canadians · 29 IPFIP 1.67 → 2.46 (+0.79)K% 31.3% → 24.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.30%	—	×0.770	24.10%
BB% (unintentional) /BF	9.57%	—	×1.150	11.00%
HR / BF /BF	0.00%	÷1.253	×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 151).

Result: FIP 1.67 → 2.46, 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 AASpringfield Cardinals · 21 IPFIP 1.23 → 1.76 (+0.53)K% 29.1% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.07%	—	×0.810	23.55%
BB% (unintentional) /BF	4.65%	—	×1.100	5.12%
HR / BF /BF	0.00%	÷1.080	×1.200	0.00%

Result: FIP 1.23 → 1.76, 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 ADunedin Blue Jays · 60 IPFIP 3.83 → 5.24 (+1.41)K% 23.4% → 17.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.44%	—	×0.740	17.34%
BB% (unintentional) /BF	7.81%	—	×1.180	9.22%
HR / BF /BF	3.12%	÷0.916	×1.300	4.43%

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 83).

Result: FIP 3.83 → 5.24, 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 A+Vancouver Canadians · 23 IPFIP 2.60 → 3.52 (+0.92)K% 25.0% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.770	19.25%
BB% (unintentional) /BF	3.26%	—	×1.150	3.75%
HR / BF /BF	2.17%	÷0.952	×1.250	2.86%

Result: FIP 2.60 → 3.52, 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 ADunedin Blue Jays · 16 IPFIP 1.69 → 2.73 (+1.04)K% 34.8% → 25.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.85%	—	×0.740	25.79%
BB% (unintentional) /BF	12.12%	—	×1.180	14.30%
HR / BF /BF	0.00%	÷1.010	×1.300	0.00%

Result: FIP 1.69 → 2.73, 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
Matt Svanson (OGILVIE)	—	—	3.94	22.9%	8.2%	2.5%	—	4.19	22.1%	13.5%	68	+0.25	—	—	—
Ryan Brasier R 2016 · 3.68 FIP	28	SU	3.68	25.0%	7.7%	3.1%	.289	3.09	24.2%	17.9%	130	-0.59	2.31	426	83
Blake Treinen R 2016 · 3.32 FIP	28	SU	3.32	24.0%	9.5%	1.9%	.271	3.04	26.0%	17.7%	215	-0.28	1.53	601	83
Matt Ramsey R 2018 · 3.78 FIP	28	SU	3.78	24.9%	8.8%	3.0%	.276	2.42	21.7%	12.6%	34	-1.36	2.42	125	82
Jason Motte R 2010 · 3.24 FIP	28	SU	3.24	26.0%	7.2%	2.6%	.269	2.69	27.3%	21.8%	140	-0.55	2.22	387	82
Robert Stock R 2018 · 2.91 FIP	28	SU	2.91	22.2%	8.5%	1.1%	.262	4.51	24.1%	11.9%	88	+1.60	2.74	378	81
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	81
Michael Mariot R 2017 · 3.51 FIP	28	SU	3.51	22.6%	9.0%	2.1%	.327	4.79	20.9%	11.8%	74	+1.28	2.40	701	80
Andrew Robinson R 2016 · 3.19 FIP	28	SU	3.19	22.2%	7.9%	1.8%	.247	4.32	23.4%	14.6%	39	+1.13	3.19	160	80
Taylor Williams R 2019 · 4.15 FIP	28	SU	4.15	21.9%	8.4%	3.3%	.275	3.85	22.1%	12.1%	103	-0.30	2.51	309	80
Santiago Casilla R 2008 · 3.71 FIP	28	SU	3.71	18.8%	7.9%	2.2%	.337	3.37	20.6%	10.4%	155	-0.34	2.76	647	80
Fernando Rodney R 2005 · 3.62 FIP	28	SU	3.62	22.7%	7.6%	2.7%	.274	3.54	23.4%	12.9%	163	-0.08	1.85	933	80
Gerardo Sanchez R 2017 · 3.47 FIP	28	SU	3.47	21.6%	8.4%	2.1%	.355	3.58	20.5%	15.1%	56	+0.11	2.65	137	79
Pedro Strop R 2013 · 3.23 FIP	28	SU	3.23	26.0%	9.4%	2.1%	.252	2.51	30.3%	21.8%	176	-0.72	2.25	494	79
Dayan Díaz R 2017 · 3.45 FIP	28	SU	3.45	25.1%	8.7%	2.5%	.358	3.96	29.4%	19.3%	16	+0.51	3.08	205	79
Jumbo Diaz R 2014 · 2.87 FIP	30	SU	2.87	26.1%	7.0%	2.0%	.283	3.64	23.0%	15.0%	186	+0.77	2.80	319	78
Logan Ondrusek R 2013 · 3.74 FIP	28	SU	3.74	22.7%	6.4%	3.2%	.287	3.57	22.2%	14.3%	41	-0.17	3.57	409	78
Marcos Mateo R 2011 · 3.40 FIP	27	SU	3.40	25.5%	10.2%	2.1%	.361	—	—	—	—	—	3.12	104	78
Ryan Tepera R 2016 · 3.11 FIP	28	SU	3.11	22.6%	8.9%	1.4%	.266	3.81	24.3%	15.9%	164	+0.70	2.35	445	78
Mike Fyhrie R 2000 · 3.08 FIP	30	SU	3.08	19.5%	5.0%	1.8%	.309	3.87	13.7%	4.4%	69	+0.79	3.08	173	78
Miguel Mejia R 2016 · 3.37 FIP	28	SU	3.37	19.6%	7.2%	1.8%	.359	5.21	12.8%	2.8%	47	+1.84	3.37	108	78

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,234 reliever careers (754 from 1990-2025 + 480 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	1.1	44	23.5%	8.8%	0.87	4.11
David Carpenter ('19)	1.1	43	23.5%	8.4%	0.92	3.69
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*
Carlos Diaz ('82-'86, 2 WAR*)	1.3	52	25.1%*	8.7%*	0.91*	3.84*
Ed Vosberg ('86-'02, 1 WAR*)	1.2	47	21.0%*	9.6%*	0.86*	4.06*
Kevin Quackenbush ('21)	1.0	52	21.0%	9.2%	1.04	4.41
Charlie Furbush ('15)	1.3	52	24.5%	8.1%	1.04	3.97