Mike Vasil

P Chicago White Sox

Age 27 RHP 6'5" / 225 lbs MLB ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	23	MIX2 levels	26	26	124	4.65	3.87	26.4%	8.8%	—	K 22.2% · BB 8.2% · FIP 4.51
2024	24	AAANYM	29	27	134	6.04	4.97	18.0%	8.6%	—	K 15.4% · BB 7.7% · FIP 5.03
2025	25	MLBCWS	47	3	101	2.50	3.90	19.4%	11.1%	0.8
2026	26	No MLB games played
2027PROJ	27	MLBCWS	9	9	54	4.51	4.93	19.0%	11.9%	0.3
2028PROJ91% MLB	28	MLBCWS	8	8	48	4.81	5.01	18.9%	12.1%	0.2
2029PROJ92% MLB	29	MLBCWS	5	5	28	5.03	5.17	18.3%	12.3%	0.1

Last 3 seasons WAR 0.8 · Next 3 projected WAR 0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

FB Velo51

xwOBA vs50

K%31

CompsClay Condrey (age 27) · Nolan Sanburn (age 26) · Ricky Castro (age 24)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 119111vR 103

ERA4.51

FIP4.93

K%19.0%

BB%11.9%

K-BB%7.1%

Proj IP61

Value2027 · WAR

Runs saved vs league avg · 61 IP

Grades · Statcast · Contract

Scouting Grades

STUF4545

CTRL3030

CMD3535

K†4545

Statcast Percentiles

FB Velo

p5194.6

Whiff%

p4124.0%

p3119.4%

xwOBA vs

p500.312

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	21	ROK MLE	FCL Mets	3	3	7	24	10	0	0	100%	2.3	41.7%	0.0%	41.7%	0.0%	1.29	-0.42	—
2021	21	ROK RAW	FCL Mets	3	3	7	24	10	0	0	100%	2.3	41.7%	0.0%	41.7%	0.0%	1.29	0.24	—
2022	22	MIX MLE	3 levels	18	17	71	291	85	26	4	94%	4.0	21.9%	10.5%	11.3%	1.9%	3.53	3.63	—
2022	22	MIX RAW	3 levels	18	17	71	291	85	26	4	94%	4.0	29.2%	8.9%	20.3%	1.4%	3.53	2.54	—
2023	23	MIX MLE	2 levels	26	26	124	522	138	46	18	100%	4.8	22.2%	8.2%	14.0%	4.1%	4.65	4.51	—
2023	23	MIX RAW	2 levels	26	26	124	522	138	46	18	100%	4.8	26.4%	8.8%	17.6%	3.4%	4.65	3.87	—
2024	24	AAA MLE	Syracuse Mets	29	27	134	607	109	52	24	93%	4.6	15.4%	7.7%	7.7%	4.1%	6.04	5.03	—
2024	24	AAA MLE	Syracuse Mets	29	27	134	607	109	52	24	93%	4.6	15.4%	7.7%	7.7%	4.1%	6.04	5.03	—
2024	24	AAA RAW	Syracuse Mets	29	27	134	607	109	52	24	93%	4.6	18.0%	8.6%	9.4%	4.0%	6.04	4.97	—
2025	25	MLB MLE	Chicago White Sox	47	3	101	423	82	47	8	6%	2.1	19.4%	11.1%	8.3%	1.9%	2.50	3.89	+0.8
2025	25	MLB MLE	Chicago White Sox	47	3	101	423	82	47	8	6%	2.1	19.4%	11.1%	8.3%	1.9%	2.50	3.89	+0.8
2025	25	MLB RAW	Chicago White Sox	47	3	101	423	82	47	8	6%	2.1	19.4%	11.1%	8.3%	1.9%	2.50	3.90	+0.8
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			47	3	101	423	82	47	8	6%	2.1	19.4%	11.1%	8.3%	1.9%	2.50	3.90	+0.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	CWS	9	9	54	228	43	27	6	100%	6.0	19.0%	11.9%	7.1%	2.8%	4.51	4.93	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	CWS	9	9	52	220	42	27	6	100%	5.8	18.9%	12.1%	6.8%	2.9%	4.81	5.01	+0.2
2029	29	MLB MLE	CWS	5	5	30	126	23	15	4	100%	6.0	18.3%	12.3%	6.0%	3.1%	5.03	5.17	+0.1
2030	30	MLB MLE	CWS	3	3	19	79	14	10	3	100%	6.2	17.6%	12.6%	5.0%	3.3%	5.24	5.38	+0.0
2028	28	MLB CTX	CWS	8	8	48	203	38	24	6	100%	6.0	18.9%	12.1%	6.8%	2.9%	4.81	5.01	+0.2
2029	29	MLB CTX	CWS	5	5	28	118	22	15	4	100%	5.6	18.3%	12.3%	6.0%	3.1%	5.03	5.17	+0.1
2030	30	MLB CTX	CWS	3	3	17	72	13	9	2	100%	5.7	17.6%	12.6%	5.0%	3.3%	5.24	5.38	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		62	18	194	814	154	95	20	29%	3.1	18.9%	11.7%	7.3%	2.4%	3.67	4.31	+0.5
/ 200 IP	—	RAW		65	19	200	841	159	98	21	30%	3.1	18.9%	11.7%	7.3%	2.4%	3.67	4.31	+0.6
Career	—	MLE		123	76	437	1867	365	167	60	62%	3.6	19.6%	9.0%	10.6%	3.2%	4.34	4.34	+2.1
/ 200 IP	—	MLE		56	35	200	854	167	77	27	62%	3.6	19.6%	9.0%	10.6%	3.2%	4.34	4.34	+2.1

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.

2024 AAASyracuse Mets · 134 IPFIP 4.84 → 5.03 (+0.19)K% 18.0% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.96%	—	×0.860	15.44%
BB% (unintentional) /BF	8.57%	—	×0.900	7.71%
HR / BF /BF	3.95%	÷1.059	×1.100	4.11%

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 112).

Result: FIP 4.84 → 5.03, 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 AAASyracuse Mets · 73 IPFIP 4.17 → 4.48 (+0.31)K% 24.9% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.92%	—	×0.860	21.43%
BB% (unintentional) /BF	11.69%	—	×0.900	10.52%
HR / BF /BF	3.08%	÷1.003	×1.100	3.38%

Result: FIP 4.17 → 4.48, 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).

2023 AABinghamton Rumble Ponies · 51 IPFIP 3.40 → 4.58 (+1.18)K% 28.9% → 23.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.93%	—	×0.810	23.44%
BB% (unintentional) /BF	4.06%	—	×1.100	4.47%
HR / BF /BF	4.06%	÷0.925	×1.200	5.27%

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 85).

Result: FIP 3.40 → 4.58, 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 ASt. Lucie Mets · 37 IPFIP 2.18 → 3.07 (+0.89)K% 26.5% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.53%	—	×0.740	19.63%
BB% (unintentional) /BF	7.48%	—	×1.180	8.83%
HR / BF /BF	0.68%	÷0.949	×1.300	0.93%

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 90).

Result: FIP 2.18 → 3.07, 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+Brooklyn Cyclones · 33 IPFIP 2.98 → 4.21 (+1.23)K% 31.4% → 24.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.43%	—	×0.770	24.20%
BB% (unintentional) /BF	10.71%	—	×1.150	12.32%
HR / BF /BF	2.14%	÷0.925	×1.250	2.89%

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 85).

Result: FIP 2.98 → 4.21, 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 ROKFCL Mets · 7 IPFIP -0.42 → 0.71 (+1.13)K% 41.7% → 28.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.67%	—	×0.680	28.33%
BB% (unintentional) /BF	0.00%	—	×1.250	0.00%
HR / BF /BF	0.00%	÷0.958	×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 92).

Result: FIP -0.42 → 0.71, 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
Mike Vasil (OGILVIE)	—	—	4.93	19.0%	11.9%	2.8%	—	5.13	18.5%	6.2%	101	+0.20	—	—	—
Clay Condrey R 2003 · 5.41 FIP	27	SP-	5.41	14.9%	10.1%	4.2%	.303	4.07	13.1%	7.4%	29	-1.34	3.18	250	76
Nolan Sanburn R 2017 · 4.55 FIP	26	SW	4.55	15.0%	10.4%	2.5%	.310	—	—	—	—	—	3.82	169	76
Ricky Castro R 2024 · 3.99 FIP	24	SP-	3.99	20.4%	8.6%	2.8%	.287	5.11	19.0%	10.6%	178	+1.12	3.99	241	75
Zach Stewart R 2015 · 4.43 FIP	28	SP-	4.43	14.4%	8.3%	2.7%	.322	5.17	11.7%	2.1%	51	+0.74	4.27	194	75
Alejandro Martinez R 2015 · 4.46 FIP	26	SP-	4.46	17.5%	10.9%	2.7%	.393	4.24	9.2%	3.9%	53	-0.22	4.24	166	75
Bryce Morrow R 2015 · 4.31 FIP	27	SP-	4.31	12.8%	7.9%	2.4%	.316	5.44	10.1%	-0.2%	50	+1.13	4.31	125	75
Aaron Northcraft R 2016 · 4.19 FIP	26	SW	4.19	16.1%	8.3%	2.5%	.309	3.32	24.1%	13.4%	34	-0.87	3.32	252	74
Lisalverto Bonilla R 2017 · 4.61 FIP	27	SW	4.61	18.2%	10.5%	3.1%	.304	4.70	15.8%	3.2%	11	+0.09	3.22	242	74
Shawn Dubin R 2023 · 4.87 FIP	27	SP-	4.87	20.0%	12.9%	3.3%	.292	3.97	21.8%	11.4%	79	-0.90	3.02	341	72
Mitch Neunborn R 2024 · 4.25 FIP	27	SP-	4.25	19.0%	12.0%	2.2%	.285	5.80	16.4%	6.5%	114	+1.55	3.65	248	72
Alfonso Sanchez R 2015 · 4.96 FIP	27	SP-	4.96	12.5%	9.1%	3.2%	.346	4.85	14.0%	5.3%	138	-0.11	4.51	224	72
Drake Fellows R 2024 · 4.97 FIP	26	SP-	4.97	16.1%	12.7%	2.9%	.293	4.85	14.2%	6.3%	207	-0.12	4.28	282	72
David Griffin R 2023 · 5.83 FIP	27	SP-	5.83	14.2%	9.2%	5.0%	.306	—	—	—	—	—	4.43	239	72
Mike Connolly R 2018 · 5.13 FIP	26	SW	5.13	13.2%	9.4%	3.5%	.321	—	—	—	—	—	3.94	328	71
Keyvius Sampson R 2017 · 5.08 FIP	26	SP-	5.08	19.6%	16.4%	2.8%	.333	—	—	—	—	—	4.10	316	71
Rorik Maltrud R 2024 · 3.91 FIP	24	SP-	3.91	20.4%	9.6%	2.4%	.300	4.40	18.6%	9.4%	193	+0.49	3.91	298	71
Dennis O'Grady R 2015 · 4.95 FIP	26	SW	4.95	13.5%	11.0%	2.9%	.339	—	—	—	—	—	3.62	157	71
Garrett Mock R 2009 · 4.06 FIP	26	SP-	4.06	17.1%	9.7%	2.1%	.350	—	—	—	—	—	3.57	132	71
Stolmy Pimentel R 2016 · 3.87 FIP	26	SP-	3.87	13.6%	10.5%	1.1%	.379	—	—	—	—	—	3.87	176	71
Edgar Alberto Garcia R 2015 · 5.24 FIP	27	SP-	5.24	11.6%	9.8%	3.4%	.263	4.28	15.3%	5.2%	167	-0.96	4.01	272	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	1.3	54	18.9%	12.2%	0.99	3.92
Rich Loiselle ('01)	1.1	56	17.2%	12.0%	0.88	4.38
Rich Garces ('02)	1.7	49	20.1%	11.1%	0.84	3.74
Mike James ('02)	1.6	63	18.1%	10.9%	0.86	3.67
Ray Searage ('81-'90, 4 WAR*)	1.4	41	21.0%*	10.8%*	0.84*	3.70*
Horacio Pina ('68-'78, 2 WAR*)	2.2	62	20.7%*	11.2%*	0.84*	4.01*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*