Ryne Stanek

P St. Louis Cardinals

Age 36 RHP 6'4" / 226 lbs MLB

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR
2024	33	MLBNYM	63	55	4.88	3.80	27.8%	9.5%	0.5
2025	34	MLBNYM	65	56	5.30	4.37	22.7%	12.5%	0.1
2026	35	MLBSTL	70	63	4.02	4.38	24.3%	11.6%	0.1
2027PROJ	36	MLBSTL	45	47	4.55	4.55	25.8%	11.5%	0.0
2028PROJ	37	MLBSTL	24	25	4.79	4.95	24.7%	12.2%	-0.1

Last 3 seasons WAR 0.7 · Next 2 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo90

K%61

xwOBA vs51

Form3.38 ERA (proj 4.55) · K 23.5% (proj 25.8%) · BB 8.2% (proj 11.5%) · last 90d · 21 IP through Oct 27

CompsHirokazu Sawamura (age 34) · Joe Nelson (age 34) · Keiichi Yabu (age 36)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 114106vR 98

ERA4.55

FIP4.55

K%25.8%

BB%11.5%

K-BB%14.3%

Proj IP47

Value2027 · WAR

Runs saved vs league avg · 47 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p9098.0

Whiff%

p7829.7%

p6124.3%

xwOBA vs

p510.311

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)
2015	24	MIX MLE	2 levels	25	17	112	452	79	46	9	68%	4.5	13.8%	11.4%	2.5%	2.6%	3.04	4.78	—
2015	24	MIX RAW	2 levels	25	17	112	452	79	46	9	68%	4.5	17.5%	10.2%	7.3%	2.0%	3.04	3.96	—
2016	25	MIX MLE	2 levels	34	11	103	430	113	48	9	32%	3.0	21.6%	12.1%	9.5%	2.2%	4.30	4.02	—
2016	25	MIX RAW	2 levels	34	11	103	430	113	48	9	32%	3.0	26.3%	11.2%	15.1%	2.1%	4.30	3.44	—
2017	26	MIX MLE	2 levels	58	0	65	269	89	26	6	0%	1.1	30.4%	10.0%	20.4%	2.3%	2.64	3.05	+1.2
2017	26	MIX RAW	2 levels	58	0	65	269	89	26	6	0%	1.1	33.1%	9.7%	23.4%	2.2%	2.64	2.76	+1.4
2018	27	MIX MLE	2 levels	69	29	76	303	98	32	9	42%	1.1	30.8%	9.9%	20.9%	3.1%	2.84	3.47	+1.0
2018	27	MIX RAW	2 levels	69	29	76	303	98	32	9	42%	1.1	32.3%	10.6%	21.8%	3.0%	2.84	3.32	+1.1
2019	28	MLB MLE	Miami Marlins	63	27	77	327	89	36	11	43%	1.2	27.2%	11.0%	16.2%	3.5%	3.97	4.14	+0.4
2019	28	MLB RAW	Miami Marlins	63	27	77	327	89	36	11	43%	1.2	27.2%	11.0%	16.2%	3.4%	3.97	4.05	+0.5
2020	29	MLB MLE	Miami Marlins	9	0	10	48	11	7	3	0%	1.1	22.9%	14.6%	8.3%	6.2%	7.20	6.44	-0.2
2020	29	MLB RAW	Miami Marlins	9	0	10	48	11	7	3	0%	1.1	22.9%	14.6%	8.3%	6.2%	7.20	6.90	-0.3
2021	30	MLB MLE	Houston Astros	72	0	68	290	83	34	8	0%	0.9	28.6%	11.7%	16.9%	2.8%	3.42	3.73	+0.7
2021	30	MLB RAW	Houston Astros	72	0	68	290	83	34	8	0%	0.9	28.6%	11.7%	16.9%	2.8%	3.42	3.69	+0.7
2022	31	MLB MLE	Houston Astros	59	0	55	224	62	30	2	0%	0.9	27.7%	13.4%	14.3%	0.9%	1.15	2.96	+1.0
2022	31	MLB RAW	Houston Astros	59	0	55	224	62	30	2	0%	0.9	27.7%	13.4%	14.3%	0.9%	1.15	2.95	+1.0
2023	32	MIX MLE	2 levels	56	0	52	216	51	20	8	0%	0.9	23.9%	9.4%	14.6%	3.9%	4.01	4.39	+0.1
2023	32	MIX RAW	2 levels	56	0	52	216	51	20	8	0%	0.9	23.6%	9.3%	14.4%	3.7%	4.01	4.30	+0.2
2024	33	MLB MLE	New York Mets	63	0	55	241	67	23	8	0%	0.9	27.8%	9.5%	18.3%	3.3%	4.88	3.79	+0.5
2024	33	MLB MLE	New York Mets	63	0	55	241	67	23	8	0%	0.9	27.8%	9.5%	18.3%	3.3%	4.88	3.79	+0.5
2024	33	MLB RAW	New York Mets	63	0	55	241	67	23	8	0%	0.9	27.8%	9.5%	18.3%	3.3%	4.88	3.80	+0.5
2025	34	MLB MLE	New York Mets	65	0	56	255	58	32	7	0%	0.9	22.7%	12.5%	10.2%	2.8%	5.30	4.28	+0.2
2025	34	MLB MLE	New York Mets	65	0	56	255	58	32	7	0%	0.9	22.7%	12.5%	10.2%	2.8%	5.30	4.28	+0.2
2025	34	MLB RAW	New York Mets	65	0	56	255	58	32	7	0%	0.9	22.7%	12.5%	10.2%	2.7%	5.30	4.37	+0.1
2026	35	MLB MLE	St. Louis Cardinals	70	0	63	267	65	31	9	0%	0.9	24.3%	11.6%	12.7%	3.6%	4.02	4.50	+0.0
2026	35	MLB MLE	St. Louis Cardinals	70	0	63	267	65	31	9	0%	0.9	24.3%	11.6%	12.7%	3.6%	4.02	4.50	+0.0
2026	35	MLB RAW	St. Louis Cardinals	70	0	63	267	65	31	9	0%	0.9	24.3%	11.6%	12.7%	3.4%	4.02	4.38	+0.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			536	56	521	2223	596	249	70	10%	1.0	26.8%	11.2%	15.6%	3.1%	3.87	3.99	+3.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	STL	45	0	47	198	51	23	6	0%	1.0	25.8%	11.5%	14.3%	3.3%	4.55	4.55	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	STL	24	0	25	106	26	13	4	0%	1.1	24.7%	12.2%	12.5%	3.7%	4.79	4.95	-0.1
2028	37	MLB CTX	STL	24	0	25	106	26	13	4	0%	1.0	24.7%	12.2%	12.5%	3.7%	4.79	4.95	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		560	56	546	2329	622	262	74	10%	1.0	26.7%	11.2%	15.5%	3.2%	3.91	4.01	+3.5
/ 200 IP	—	RAW		205	21	200	853	228	96	27	10%	1.0	26.7%	11.2%	15.5%	3.2%	3.91	4.01	+1.3
Career	—	MLE		643	84	791	3322	817	374	95	13%	1.2	24.6%	11.2%	13.4%	2.8%	3.63	4.01	+3.3
/ 200 IP	—	MLE		163	21	200	840	207	94	24	13%	1.2	24.6%	11.2%	13.4%	2.8%	3.63	4.01	+1.2

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.

2018 AAADurham Bulls · 10 IPFIP 2.78 → 3.49 (+0.71)K% 42.5% → 37.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	42.50%	—	×0.880	37.40%
BB% (unintentional) /BF	15.00%	—	×1.050	15.75%
HR / BF /BF	2.50%	÷0.970	×1.100	2.84%

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 94).

Result: FIP 2.78 → 3.49, 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 · 45 IPFIP 1.35 → 1.76 (+0.41)K% 34.5% → 30.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.48%	—	×0.880	30.34%
BB% (unintentional) /BF	9.20%	—	×1.050	9.66%
HR / BF /BF	0.00%	÷1.049	×1.100	0.00%

Result: FIP 1.35 → 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).

2016 AAMontgomery Biscuits · 78 IPFIP 3.11 → 3.81 (+0.70)K% 28.2% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.17%	—	×0.810	22.82%
BB% (unintentional) /BF	10.84%	—	×1.100	11.92%
HR / BF /BF	1.86%	÷1.081	×1.200	2.06%

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 116).

Result: FIP 3.11 → 3.81, 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 · 24 IPFIP 4.44 → 4.64 (+0.20)K% 20.6% → 18.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.56%	—	×0.880	18.09%
BB% (unintentional) /BF	12.15%	—	×1.050	12.76%
HR / BF /BF	2.80%	÷1.167	×1.100	2.64%

Result: FIP 4.44 → 4.64, 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 · 62 IPFIP 4.75 → 5.48 (+0.73)K% 15.7% → 12.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.71%	—	×0.810	12.72%
BB% (unintentional) /BF	11.88%	—	×1.100	13.07%
HR / BF /BF	2.68%	÷0.983	×1.200	3.27%

Result: FIP 4.75 → 5.48, 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 A+Charlotte Stone Crabs · 51 IPFIP 2.99 → 3.82 (+0.84)K% 19.9% → 15.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.90%	—	×0.770	15.32%
BB% (unintentional) /BF	7.85%	—	×1.150	9.03%
HR / BF /BF	1.05%	÷0.822	×1.250	1.59%

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 64).

Result: FIP 2.99 → 3.82, 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
Ryne Stanek (OGILVIE)	—	—	—	—	—	3.3%	—	4.95	24.7%	12.5%	25	+0.40	—	—	—
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	65
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	65
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	61
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	60
Daniel Bard R 2021 · 3.62 FIP	36	SU	3.62	26.3%	11.5%	2.3%	.337	3.64	24.6%	10.3%	110	+0.02	2.56	456	60
Juan Sandoval R 2017 · 3.42 FIP	36	SU	3.42	16.7%	7.2%	1.5%	.298	5.41	15.9%	8.7%	57	+1.99	3.24	225	58
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	58
Matt Bush R 2022 · 3.73 FIP	36	SU	3.73	30.3%	6.6%	4.3%	.224	3.79	26.2%	17.5%	36	+0.06	2.87	249	56
Jim Miller R 2016 · 5.43 FIP	34	SU	5.43	20.4%	14.1%	4.1%	.347	—	—	—	—	—	3.95	140	56
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	54
Salvador Valdez R 2019 · 4.30 FIP	36	SW	4.30	17.1%	8.2%	2.9%	.405	—	—	—	—	—	3.60	326	53
Jay Jackson R 2024 · 5.31 FIP	36	SU	5.31	25.4%	7.9%	6.1%	.304	—	—	—	—	—	2.36	261	52
Francisco Del Rosario R 2017 · 4.15 FIP	36	SU	4.15	16.4%	10.0%	2.1%	.267	6.35	11.9%	-0.6%	77	+2.20	3.93	194	51
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	50
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	49
Daniel Guerrero R 2019 · 5.59 FIP	34	SW	5.59	14.7%	11.1%	4.2%	.353	—	—	—	—	—	4.61	269	49
Jesus Adrian Castillo R 2019 · 5.13 FIP	35	SU	5.13	13.1%	7.8%	3.9%	.319	—	—	—	—	—	2.23	173	48
Erubiel Gonzalez R 2015 · 3.43 FIP	36	SU	3.43	12.4%	6.0%	1.1%	.328	3.26	14.8%	10.4%	69	-0.17	2.99	119	46
Pete Walker R 2005 · 4.79 FIP	36	SU	4.79	12.0%	9.2%	2.8%	.261	4.45	19.6%	11.6%	30	-0.34	4.45	327	44
Yoshihisa Hirano R 2020 · 5.02 FIP	36	SU	5.02	17.5%	12.7%	3.3%	.381	—	—	—	—	—	3.45	132	42

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	3.0	54	26.6%	11.9%	1.23	3.96
Brad Boxberger ('23)	2.4	43	28.7%	11.5%	1.19	3.50
Tony Sipp ('19)	2.5	46	25.2%	10.5%	1.32	3.72
Antonio Bastardo ('17)	2.0	56	28.0%	11.4%	1.01	4.01
Tim Stoddard ('75-'89, 4 WAR*)	3.6	66	26.2%*	11.2%*	1.14*	4.24*
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Jeff Parrett ('86-'96, 6 WAR*)	3.6	72	24.8%*	11.0%*	1.02*	4.07*