George Soriano

P St. Louis Cardinals

Age 28 RHP 6'2" / 210 lbs MLB

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	46	0	68	5.40	5.13	25.3%	10.4%	-0.5	K 23.1% · BB 9.8% · FIP 5.59
2025	26	MIX2 levels	53	1	79	5.11	4.30	24.8%	9.3%	0.2	K 22.8% · BB 8.9% · FIP 4.58
2026	27	MLBSTL	70	0	66	4.23	4.57	22.8%	11.4%	-0.0
2027PROJ	28	MLBSTL	53	0	56	5.11	4.99	23.9%	11.2%	-0.3
2028PROJ95% MLB	29	MLBSTL	35	0	37	5.13	5.15	23.3%	11.5%	-0.2
2029PROJ95% MLB	30	MLBSTL	25	0	26	5.26	5.35	22.6%	11.8%	-0.2

Last 3 seasons WAR -0.2 · Next 3 projected WAR -0.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo79

K%53

xwOBA vs37

Form6.27 ERA (proj 5.11) · K 21.9% (proj 23.9%) · BB 18.8% (proj 11.2%) ▼▼ last 90d · 19 IP through Oct 27

CompsLuis Santos (age 28) · Brandon Cunniff (age 28) · Cody Tucker (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 124115vR 107

ERA5.11

FIP4.99

K%23.9%

BB%11.2%

K-BB%12.7%

Proj IP56

Value2027 · WAR

Runs saved vs league avg · 56 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p7996.6

Whiff%

p7429.0%

p5322.8%

xwOBA vs

p370.327

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)
2016	17	ROK MLE	DSL Marlins	17	9	56	250	56	28	3	53%	3.3	15.2%	14.0%	1.2%	1.7%	3.56	4.51	—
2016	17	ROK RAW	DSL Marlins	17	9	56	250	56	28	3	53%	3.3	22.4%	11.2%	11.2%	1.2%	3.56	3.30	—
2018	19	ROK MLE	GCL Marlins	11	3	42	167	36	9	0	27%	3.8	14.7%	6.7%	7.9%	0.0%	1.91	2.72	—
2018	19	ROK RAW	GCL Marlins	11	3	42	167	36	9	0	27%	3.8	21.6%	5.4%	16.2%	0.0%	1.91	2.04	—
2019	20	A MLE	Clinton LumberKings	23	20	120	518	99	50	8	87%	5.2	14.1%	11.4%	2.8%	1.9%	3.91	4.36	—
2019	20	A RAW	Clinton LumberKings	23	20	120	518	99	50	8	87%	5.2	19.1%	9.7%	9.5%	1.5%	3.91	3.57	—
2021	22	MIX MLE	2 levels	18	18	89	391	114	37	8	100%	5.0	22.1%	11.0%	11.1%	2.6%	3.43	4.06	—
2021	22	MIX RAW	2 levels	18	18	89	391	114	37	8	100%	5.0	29.2%	9.5%	19.7%	2.0%	3.43	2.95	—
2022	23	MIX MLE	2 levels	40	6	76	325	85	40	4	15%	1.9	22.2%	13.2%	9.1%	1.4%	2.72	3.64	—
2022	23	MIX RAW	2 levels	40	6	76	325	85	40	4	15%	1.9	26.2%	12.3%	13.8%	1.2%	2.72	3.13	—
2023	24	MIX MLE	2 levels	43	6	77	349	79	36	9	14%	1.8	21.6%	9.9%	11.6%	2.7%	4.31	4.03	+0.5
2023	24	MIX RAW	2 levels	43	6	77	349	79	36	9	14%	1.8	22.6%	10.3%	12.3%	2.6%	4.31	3.97	+0.5
2024	25	MIX MLE	2 levels	46	0	68	289	73	30	15	0%	1.5	23.1%	9.8%	13.3%	5.8%	5.40	5.59	-0.8
2024	25	MIX MLE	2 levels	46	0	68	289	73	30	15	0%	1.5	23.1%	9.8%	13.3%	5.8%	5.40	5.59	-0.8
2024	25	MIX RAW	2 levels	46	0	68	289	73	30	15	0%	1.5	25.3%	10.4%	14.9%	5.2%	5.40	5.13	-0.5
2025	26	MIX MLE	2 levels	53	1	79	343	85	32	13	2%	1.5	22.8%	8.9%	13.9%	4.1%	5.11	4.58	-0.0
2025	26	MIX MLE	2 levels	53	1	79	343	85	32	13	2%	1.5	22.8%	8.9%	13.9%	4.1%	5.11	4.58	-0.0
2025	26	MIX RAW	2 levels	53	1	79	343	85	32	13	2%	1.5	24.8%	9.3%	15.5%	3.8%	5.11	4.30	+0.2
2026	27	MLB MLE	St. Louis Cardinals	70	0	66	290	66	33	10	0%	0.9	22.8%	11.4%	11.4%	3.7%	4.23	4.65	-0.1
2026	27	MLB MLE	St. Louis Cardinals	70	0	66	290	66	33	10	0%	0.9	22.8%	11.4%	11.4%	3.7%	4.23	4.65	-0.1
2026	27	MLB RAW	St. Louis Cardinals	70	0	66	290	66	33	10	0%	0.9	22.8%	11.4%	11.4%	3.4%	4.23	4.57	-0.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			142	1	184	822	183	86	33	1%	1.3	22.3%	10.5%	11.8%	4.0%	5.33	4.84	-0.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	STL	53	0	56	236	57	27	9	0%	1.1	23.9%	11.2%	12.7%	3.8%	5.11	4.99	-0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	STL	37	0	38	163	38	19	6	0%	1.0	23.3%	11.5%	11.9%	4.0%	5.13	5.15	-0.3
2029	30	MLB MLE	STL	26	0	27	114	26	13	5	0%	1.0	22.6%	11.8%	10.9%	4.2%	5.26	5.35	-0.2
2028	29	MLB CTX	STL	35	0	37	156	36	18	6	0%	1.1	23.3%	11.5%	11.9%	4.0%	5.13	5.15	-0.2
2029	30	MLB CTX	STL	25	0	26	110	25	13	5	0%	1.0	22.6%	11.8%	10.9%	4.2%	5.26	5.35	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		201	1	246	1085	244	116	44	0%	1.2	22.5%	10.7%	11.7%	4.0%	5.29	4.77	-0.6
/ 200 IP	—	RAW		163	1	200	881	198	94	36	0%	1.2	22.5%	10.7%	11.7%	4.0%	5.29	4.77	-0.5
Career	—	MLE		321	63	674	2922	581	318	80	20%	2.1	19.9%	10.9%	9.0%	2.7%	3.93	4.30	-1.2
/ 200 IP	—	MLE		95	19	200	867	172	94	24	20%	2.1	19.9%	10.9%	9.0%	2.7%	3.93	4.30	-0.9

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.

2025 AAAJacksonville Jumbo Shrimp · 43 IPFIP 2.68 → 3.13 (+0.45)K% 28.8% → 24.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.82%	—	×0.860	24.79%
BB% (unintentional) /BF	8.24%	—	×0.900	7.41%
HR / BF /BF	1.76%	÷0.903	×1.100	2.15%

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 81).

Result: FIP 2.68 → 3.13, 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 AAAJacksonville Jumbo Shrimp · 39 IPFIP 4.89 → 5.61 (+0.72)K% 27.8% → 23.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.85%	—	×0.860	23.95%
BB% (unintentional) /BF	10.76%	—	×0.900	9.68%
HR / BF /BF	5.06%	÷0.925	×1.100	6.02%

Result: FIP 4.89 → 5.61, 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 AAAJacksonville Jumbo Shrimp · 25 IPFIP 4.04 → 4.25 (+0.21)K% 22.3% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.31%	—	×0.860	19.19%
BB% (unintentional) /BF	11.57%	—	×0.900	10.41%
HR / BF /BF	2.48%	÷1.031	×1.100	2.65%

Result: FIP 4.04 → 4.25, 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 AAAJacksonville Jumbo Shrimp · 47 IPFIP 3.03 → 3.41 (+0.37)K% 25.7% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.65%	—	×0.880	22.58%
BB% (unintentional) /BF	12.04%	—	×1.050	12.64%
HR / BF /BF	1.05%	÷1.032	×1.100	1.12%

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 106).

Result: FIP 3.03 → 3.41, 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 AAPensacola Blue Wahoos · 29 IPFIP 3.26 → 3.97 (+0.71)K% 26.9% → 21.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.87%	—	×0.810	21.76%
BB% (unintentional) /BF	12.69%	—	×1.100	13.96%
HR / BF /BF	1.49%	÷1.048	×1.200	1.71%

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 110).

Result: FIP 3.26 → 3.97, 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 A+Beloit Snappers · 55 IPFIP 2.89 → 3.76 (+0.87)K% 27.8% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.80%	—	×0.770	21.41%
BB% (unintentional) /BF	7.88%	—	×1.150	9.07%
HR / BF /BF	2.07%	÷1.082	×1.250	2.40%

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 116).

Result: FIP 2.89 → 3.76, 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).

2021 AJupiter Hammerheads · 34 IPFIP 3.07 → 4.54 (+1.47)K% 31.3% → 23.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.33%	—	×0.740	23.19%
BB% (unintentional) /BF	12.00%	—	×1.180	14.16%
HR / BF /BF	2.00%	÷0.891	×1.300	2.92%

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 78).

Result: FIP 3.07 → 4.54, 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 AClinton LumberKings · 120 IPFIP 3.56 → 4.36 (+0.81)K% 19.1% → 14.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.11%	—	×0.740	14.14%
BB% (unintentional) /BF	9.65%	—	×1.180	11.39%
HR / BF /BF	1.54%	÷1.085	×1.300	1.85%

Result: FIP 3.56 → 4.36, 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
George Soriano (OGILVIE)	—	—	—	—	—	3.8%	—	5.23	23.1%	11.5%	66	+0.24	—	—	—
Luis Santos R 2019 · 4.31 FIP	28	SU	4.31	22.9%	10.0%	3.4%	.312	—	—	—	—	—	3.53	472	76
Brandon Cunniff R 2017 · 4.79 FIP	28	SU	4.79	20.1%	11.6%	3.5%	.275	6.80	13.9%	-1.9%	30	+2.01	3.89	180	76
Cody Tucker R 2024 · 4.97 FIP	25	SU	4.97	22.0%	12.0%	4.0%	.272	5.36	15.8%	-1.9%	40	+0.39	4.97	105	75
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	74
Greg Aquino R 2006 · 4.41 FIP	28	SU	4.41	23.2%	10.0%	3.6%	.331	4.39	17.4%	5.6%	30	-0.02	4.10	154	74
Coleman Huntley III R 2021 · 3.85 FIP	28	SW	3.85	20.2%	7.4%	2.8%	.348	3.56	23.4%	13.2%	86	-0.29	2.38	160	74
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	73
Steve Geltz R 2016 · 5.47 FIP	28	SU	5.47	22.0%	10.2%	5.4%	.248	3.57	22.6%	12.4%	27	-1.90	3.57	157	73
Spencer Bivens R 2022 · 4.86 FIP	28	SU	4.86	19.8%	13.5%	3.1%	.265	3.85	18.1%	10.3%	272	-1.01	3.52	391	73
Tyler Yates R 2006 · 4.17 FIP	28	SU	4.17	21.2%	10.6%	2.8%	.254	3.70	20.7%	11.1%	151	-0.47	3.23	248	72
Hunter Parsons R 2023 · 4.84 FIP	26	SU	4.84	22.5%	10.0%	4.3%	.274	6.70	25.5%	9.0%	29	+1.86	4.73	183	72
Emmanuel Chapman R 2024 · 4.08 FIP	25	SW	4.08	19.7%	10.6%	2.4%	.256	4.52	17.8%	1.3%	117	+0.44	3.81	198	72
Connor Brogdon R 2023 · 4.53 FIP	28	SU	4.53	22.0%	10.6%	3.6%	.273	5.17	24.0%	17.1%	98	+0.64	2.98	402	72
Neil Ramírez R 2017 · 4.66 FIP	28	SU	4.66	27.1%	12.5%	4.1%	.389	4.86	29.1%	19.7%	116	+0.20	2.43	264	72
Fernando Rodriguez Jr. R 2012 · 3.90 FIP	28	SU	3.90	25.2%	8.7%	3.3%	.299	3.34	26.5%	16.9%	75	-0.56	3.34	335	72
Matt Pushard R 2024 · 3.87 FIP	26	SU	3.87	24.1%	8.9%	3.0%	.242	3.29	22.2%	14.0%	115	-0.58	2.84	220	71
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	71
Josh Lueke R 2013 · 4.09 FIP	28	SU	4.09	25.3%	11.1%	3.1%	.333	3.28	24.6%	20.9%	90	-0.81	2.29	191	71
Luis Mateo R 2017 · 4.60 FIP	27	SU	4.60	17.6%	11.2%	2.9%	.309	5.55	8.6%	-4.8%	43	+0.95	3.48	160	71
Grant Sides R 2016 · 3.83 FIP	27	SU	3.83	22.4%	11.9%	2.0%	.247	3.31	21.7%	11.9%	47	-0.52	3.31	159	71

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	1.5	44	22.7%	11.1%	1.54	5.26
Scott Proctor ('11)	1.7	57	19.0%	10.9%	1.52	4.78
Scott Service ('04)	2.1	46	22.2%	9.9%	1.23	5.04
Buck Farmer ('24)	2.6	51	21.6%	10.5%	1.24	4.71
Phil Hennigan ('69-'73, -0 WAR*)	1.4	70	20.9%*	10.4%*	1.50*	4.95*
Jeff Jones ('80-'84, -2 WAR*)	1.0	41	22.0%*	12.4%*	1.48*	4.53*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*