Michael Soroka

P Arizona Diamondbacks

Age 29 RHP 6'5" / 250 lbs MLB Svc 8.0 · Ctrl thru 2027 peak 1.7 · 2027

Overview

MLBSP40-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MIX2 levels	31	9	88	4.62	4.53	25.3%	11.9%	0.0	K 24.2% · BB 12.4% · FIP 4.65
2025	27	MIX3 levels	26	20	104	4.41	3.85	26.5%	7.8%	1.9	K 25.1% · BB 7.7% · FIP 3.76
2026	28	MIX2 levels	23	22	120	3.38	3.02	23.5%	6.1%	3.6	K 24.1% · BB 5.9% · FIP 3.04
2027PROJ	29	MLBARI	15	15	90	3.93	3.86	23.9%	7.0%	1.7
2028PROJ	30	MLBARI	14	14	85	3.92	3.98	23.2%	7.3%	1.3
2029PROJ	31	MLBARI	12	12	74	4.08	4.20	22.4%	7.6%	1.0

Last 3 seasons WAR 5.5 · Next 3 projected WAR 4.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service8.052First FA2028Options1

2027Ext / FA-deal$13M

Skills · percentileStatcast 2026

K%60

xwOBA vs50

FB Velo37

Form3.48 ERA (proj 3.93) · K 29.5% (proj 23.9%) · BB 6.4% (proj 7.0%) ▲▲ last 60d · 21 IP through Oct 27

CompsChase Anderson (age 29) · Kenta Maeda (age 29) · Tylor Megill (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10698vR 90

ERA3.93

FIP3.86

K%23.9%

BB%7.0%

K-BB%16.9%

Proj IP90

Value2027 · WAR

Runs saved vs league avg · 90 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p3793.6

Whiff%

p3423.0%

p6024.1%

xwOBA vs

p500.312

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

Status FA

MLB Debut 2018

Service 8.052 yrs.days

Team Control Through 2027

First FA Year 2028

OPT

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$13M	+1.7	$14M	+$0.5M
Totals		$13M		$14M	+$0.5M

Options · projected decision
2027	MUTUAL OPT	$10.0M / $1.0M 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)
2015	17	ROK MLE	Danville Braves	10	9	34	143	37	5	0	90%	3.4	17.6%	4.4%	13.2%	0.0%	3.18	2.17	—
2015	17	ROK RAW	Danville Braves	10	9	34	143	37	5	0	90%	3.4	25.9%	3.5%	22.4%	0.0%	3.18	1.36	—
2016	18	A MLE	Rome Braves	25	24	143	585	125	32	3	96%	5.7	15.8%	6.5%	9.4%	0.7%	3.02	2.96	—
2016	18	A RAW	Rome Braves	25	24	143	585	125	32	3	96%	5.7	21.4%	5.5%	15.9%	0.5%	3.02	2.30	—
2017	19	AA MLE	Mississippi Braves	26	26	154	627	125	34	10	100%	5.9	16.1%	6.0%	10.2%	2.1%	2.75	3.63	—
2017	19	AA RAW	Mississippi Braves	26	26	154	627	125	34	10	100%	5.9	19.9%	5.4%	14.5%	1.6%	2.75	2.98	—
2018	20	MIX MLE	3 levels	11	11	56	228	55	13	1	100%	5.1	22.2%	6.1%	16.1%	0.5%	2.56	2.25	+2.3
2018	20	MIX RAW	3 levels	11	11	56	228	55	13	1	100%	5.1	24.1%	5.7%	18.4%	0.4%	2.56	2.07	+2.4
2019	21	MIX MLE	2 levels	31	31	184	734	152	41	15	100%	5.9	20.3%	5.7%	14.6%	2.0%	2.74	3.21	+5.0
2019	21	MIX RAW	2 levels	31	31	184	734	152	41	15	100%	5.9	20.7%	5.6%	15.1%	2.0%	2.74	3.18	+5.1
2020	22	MLB MLE	Atlanta Braves	3	3	14	57	8	7	0	100%	4.6	14.0%	12.3%	1.8%	0.0%	3.95	3.47	+0.3
2020	22	MLB RAW	Atlanta Braves	3	3	14	57	8	7	0	100%	4.6	14.0%	12.3%	1.8%	0.0%	3.95	3.47	+0.3
2022	24	MIX MLE	2 levels	6	6	25	103	25	7	3	100%	4.2	16.8%	8.3%	8.6%	3.8%	5.40	4.80	—
2022	24	MIX RAW	2 levels	6	6	25	103	25	7	3	100%	4.2	24.3%	6.8%	17.5%	2.9%	5.40	3.50	—
2023	25	MIX MLE	2 levels	24	23	119	500	121	40	15	96%	5.0	21.6%	7.4%	14.2%	3.1%	4.22	3.94	+2.1
2023	25	MIX RAW	2 levels	24	23	119	500	121	40	15	96%	5.0	24.2%	8.0%	16.2%	3.0%	4.22	3.71	+2.4
2024	26	MIX MLE	2 levels	31	9	88	379	96	45	14	29%	2.8	24.2%	12.4%	11.8%	3.7%	4.62	4.65	-0.1
2024	26	MIX MLE	2 levels	31	9	88	379	96	45	14	29%	2.8	24.2%	12.4%	11.8%	3.7%	4.62	4.65	-0.1
2024	26	MIX RAW	2 levels	31	9	88	379	96	45	14	29%	2.8	25.3%	11.9%	13.5%	3.7%	4.62	4.53	+0.0
2025	27	MIX MLE	3 levels	26	20	104	438	116	34	16	77%	4.0	25.1%	7.7%	17.4%	3.3%	4.41	3.76	+2.0
2025	27	MIX MLE	3 levels	26	20	104	438	116	34	16	77%	4.0	25.1%	7.7%	17.4%	3.3%	4.41	3.76	+2.0
2025	27	MIX RAW	3 levels	26	20	104	438	116	34	16	77%	4.0	26.5%	7.8%	18.7%	3.7%	4.41	3.85	+1.9
2026	28	MIX MLE	2 levels	23	22	120	490	115	30	10	96%	5.2	24.1%	5.9%	18.2%	2.2%	3.38	3.04	+3.5
2026	28	MIX MLE	2 levels	23	22	120	490	115	30	10	96%	5.2	24.1%	5.9%	18.2%	2.2%	3.38	3.04	+3.5
2026	28	MIX RAW	2 levels	23	22	120	490	115	30	10	96%	5.2	23.5%	6.1%	17.3%	2.0%	3.38	3.02	+3.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			113	90	532	2215	493	166	59	80%	4.7	22.3%	7.5%	14.8%	2.7%	3.76	3.62	+11.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	ARI	15	15	90	380	91	26	11	100%	6.0	23.9%	7.0%	16.9%	2.8%	3.93	3.86	+1.7
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	ARI	14	14	85	358	83	26	11	100%	6.1	23.2%	7.3%	15.9%	3.0%	4.01	4.07	+1.3
2029	31	MLB MLE	ARI	12	12	74	312	70	24	10	100%	6.2	22.4%	7.6%	14.8%	3.2%	4.18	4.30	+1.0
2030	32	MLB MLE	ARI	10	10	61	258	56	21	9	100%	6.1	21.6%	8.0%	13.6%	3.4%	4.41	4.56	+0.6
2031	33	MLB MLE	ARI	10	10	60	252	57	19	9	100%	6.0	22.8%	7.7%	15.1%	3.7%	4.50	4.57	+0.6
2032	34	MLB MLE	ARI	7	7	44	185	41	15	7	100%	6.3	21.9%	8.2%	13.7%	4.0%	4.72	4.87	+0.3
2028	30	MLB CTX	ARI	14	14	85	359	83	26	10	100%	6.1	23.2%	7.3%	15.9%	2.8%	3.92	3.98	+1.3
2029	31	MLB CTX	ARI	12	12	74	312	70	24	9	100%	6.2	22.4%	7.6%	14.8%	3.0%	4.08	4.20	+1.0
2030	32	MLB CTX	ARI	10	10	61	258	56	21	8	100%	6.1	21.6%	8.0%	13.6%	3.3%	4.31	4.46	+0.6
2031	33	MLB CTX	ARI	10	10	60	253	58	19	9	100%	6.0	22.8%	7.7%	15.1%	3.5%	4.39	4.46	+0.6
2032	34	MLB CTX	ARI	7	7	44	186	41	15	7	100%	6.3	21.9%	8.2%	13.7%	3.8%	4.60	4.75	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		167	144	855	3580	800	271	103	86%	5.1	22.3%	7.6%	14.8%	2.9%	3.93	3.75	+17.0
/ 200 IP	—	RAW		39	34	200	837	187	63	24	86%	5.1	22.3%	7.6%	14.8%	2.9%	3.93	3.75	+4.0
Career	—	MLE		216	184	1041	4284	871	299	92	85%	4.8	20.3%	7.0%	13.4%	2.1%	3.43	3.44	+15.1
/ 200 IP	—	MLE		42	35	200	823	167	58	18	85%	4.8	20.3%	7.0%	13.4%	2.1%	3.43	3.44	+3.5

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 AAAIowa Cubs · 7 IPFIP 4.09 → 4.43 (+0.34)K% 46.7% → 40.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	46.67%	—	×0.860	40.13%
BB% (unintentional) /BF	10.00%	—	×0.900	9.00%
HR / BF /BF	6.67%	÷1.125	×1.100	6.52%

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 125).

Result: FIP 4.09 → 4.43, 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 AAHarrisburg Senators · 7 IPFIP 5.72 → 7.13 (+1.41)K% 24.1% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.14%	—	×0.810	19.55%
BB% (unintentional) /BF	6.90%	—	×1.100	7.59%
HR / BF /BF	6.90%	÷0.963	×1.200	8.59%

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 93).

Result: FIP 5.72 → 7.13, 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 AAACharlotte Knights · 8 IPFIP 2.44 → 2.95 (+0.51)K% 37.5% → 32.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.50%	—	×0.860	32.25%
BB% (unintentional) /BF	6.25%	—	×0.900	5.62%
HR / BF /BF	3.12%	÷1.016	×1.100	3.38%

Result: FIP 2.44 → 2.95, 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 AAAGwinnett Stripers · 87 IPFIP 2.84 → 3.15 (+0.32)K% 25.9% → 22.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.92%	—	×0.860	22.29%
BB% (unintentional) /BF	7.89%	—	×0.900	7.10%
HR / BF /BF	1.69%	÷0.984	×1.100	1.89%

Result: FIP 2.84 → 3.15, 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 AAAGwinnett Stripers · 21 IPFIP 4.33 → 4.80 (+0.47)K% 19.1% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.10%	—	×0.880	16.81%
BB% (unintentional) /BF	7.87%	—	×1.050	8.26%
HR / BF /BF	3.37%	÷0.981	×1.100	3.78%

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 96).

Result: FIP 4.33 → 4.80, 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 AAAGwinnett Stripers · 9 IPFIP 2.59 → 3.29 (+0.70)K% 30.3% → 26.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.30%	—	×0.880	26.67%
BB% (unintentional) /BF	3.03%	—	×1.050	3.18%
HR / BF /BF	3.03%	÷0.899	×1.100	3.71%

Result: FIP 2.59 → 3.29, 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 AAAGwinnett Stripers · 27 IPFIP 1.31 → 1.65 (+0.34)K% 29.8% → 26.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.81%	—	×0.880	26.23%
BB% (unintentional) /BF	5.77%	—	×1.050	6.06%
HR / BF /BF	0.00%	÷0.970	×1.100	0.00%

Result: FIP 1.31 → 1.65, 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 AAMississippi Braves · 154 IPFIP 2.98 → 3.63 (+0.65)K% 19.9% → 16.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.94%	—	×0.810	16.15%
BB% (unintentional) /BF	5.42%	—	×1.100	5.96%
HR / BF /BF	1.59%	÷0.925	×1.200	2.07%

Result: FIP 2.98 → 3.63, 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
Michael Soroka (OGILVIE)	—	—	—	—	—	2.8%	—	4.28	22.5%	14.9%	220	+0.42	—	—	—
Chase Anderson R 2017 · 3.30 FIP	29	SP	3.30	23.4%	7.0%	2.3%	.259	4.81	20.8%	12.5%	331	+1.51	3.30	1,260	71
Kenta Maeda R 2017 · 3.81 FIP	29	SP	3.81	25.1%	5.9%	3.8%	.273	3.24	28.7%	21.7%	346	-0.57	2.87	1,092	66
Tylor Megill R 2024 · 3.33 FIP	29	SP	3.33	27.0%	9.7%	2.4%	.301	3.33	27.4%	16.4%	83	+0.00	3.02	603	65
Jameson Taillon R 2021 · 4.09 FIP	29	SP	4.09	23.2%	7.1%	3.7%	.268	4.02	20.2%	15.0%	497	-0.07	3.12	1,401	65
Yu Darvish R 2016 · 2.89 FIP	29	SP	2.89	30.6%	7.6%	2.6%	.284	3.85	29.1%	21.2%	405	+0.96	1.97	1,798	65
Taylor Jungmann R 2017 · 3.88 FIP	27	SP-	3.88	18.8%	11.1%	1.8%	.279	—	—	—	—	—	3.59	435	62
Jimmy Nelson R 2017 · 2.76 FIP	28	SP	2.76	27.3%	6.5%	2.1%	.333	4.28	26.9%	12.3%	62	+1.52	1.32	720	62
Anthony DeSclafani R 2019 · 3.99 FIP	29	SP	3.99	24.0%	6.3%	3.9%	.268	3.98	21.1%	14.5%	220	-0.01	3.38	1,014	62
Asher Wojciechowski R 2018 · 4.60 FIP	29	SP-	4.60	22.4%	7.8%	4.4%	.267	5.05	22.0%	13.3%	234	+0.45	3.15	678	62
Brad Peacock R 2017 · 2.97 FIP	29	SP-	2.97	29.5%	10.4%	1.9%	.283	3.85	29.3%	21.5%	157	+0.88	2.97	748	61
Jose Samayoa R 2019 · 4.05 FIP	29	SP	4.05	19.4%	7.0%	3.1%	.314	—	—	—	—	—	3.44	262	61
Matt Harvey R 2018 · 4.17 FIP	29	SP	4.17	19.8%	5.3%	3.8%	.294	4.74	16.9%	9.2%	222	+0.57	1.87	1,044	60
Alexi Ogando R 2013 · 4.22 FIP	29	SP-	4.22	16.8%	9.3%	2.5%	.249	4.43	19.0%	8.4%	122	+0.21	2.83	538	60
Claudio Vargas R 2007 · 4.76 FIP	29	SP-	4.76	17.7%	8.4%	3.8%	.307	4.10	16.8%	8.2%	98	-0.66	3.66	765	60
Chris Bassitt R 2018 · 3.49 FIP	29	SP-	3.49	20.5%	8.1%	2.0%	.307	3.64	23.5%	16.8%	364	+0.15	2.92	1,596	59
Kevin Slowey R 2013 · 3.81 FIP	29	SP-	3.81	19.2%	4.6%	3.2%	.325	3.53	14.2%	9.5%	37	-0.28	3.53	662	59
Mario Gonzalez R 2016 · 3.94 FIP	29	SP	3.94	17.9%	5.7%	2.9%	.276	4.53	14.1%	9.1%	104	+0.59	3.94	368	59
Matt Shoemaker R 2016 · 3.29 FIP	29	SP	3.29	21.4%	4.3%	2.6%	.310	4.27	22.4%	14.0%	137	+0.98	3.12	728	59
Austin Bibens-Dirkx R 2015 · 3.97 FIP	30	SP	3.97	17.4%	7.1%	2.6%	.315	4.94	15.9%	8.7%	305	+0.97	3.97	567	59
Yariel Rodríguez R 2024 · 3.76 FIP	27	SP	3.76	24.9%	11.4%	2.4%	.275	3.72	24.1%	12.7%	89	-0.04	2.32	196	59

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	4.7	79	22.5%	7.6%	1.13	3.96
Joe Hesketh ('84-'94, 10 WAR*)	4.8	87	23.2%*	8.8%*	1.07*	3.95*
Daniel Hudson ('24)	4.3	71	22.8%	7.7%	1.01	3.74
Alejandro Peña ('81-'96, 15 WAR*)	5.3	81	24.7%*	7.5%*	0.96*	3.61*
Collin McHugh ('23)	5.0	90	23.3%	6.7%	0.96	3.72
Tom Niedenfuer ('81-'90, 8 WAR*)	3.3	65	23.1%*	8.1%*	1.19*	3.80*
Zach McAllister ('23)	3.0	85	21.1%	7.8%	1.07	4.15