Dominic Leone

P Chicago White Sox

Age 35 RHP 5'10" / 215 lbs MLB peak 0.1 · 2027

Overview

MLBRP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	30	MLBSF	55	0	49	4.01	3.73	23.4%	8.6%	0.5
2023	31	MIX2 levels	59	0	65	4.13	5.17	24.5%	9.2%	-0.5	K 23.0% · BB 10.6% · FIP 5.86
2024	32	MIX2 levels	27	0	23	6.26	4.97	22.6%	12.3%	-0.1	K 19.1% · BB 14.6% · FIP 5.76
2025	33	No MLB games played
2026	34	No MLB games played
2027PROJ	35	MLBCWS	47	0	49	4.48	4.39	24.0%	9.7%	0.1
2028PROJ	36	MLBCWS	34	0	36	4.65	4.76	23.0%	10.3%	-0.1

Last 3 seasons WAR -0.1 · Next 2 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2024

FB Velo55

K%29

xwOBA vs10

CompsMark Serrano (age 33) · Brendan Donnelly (age 35) · Keiichi Yabu (age 36)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 117108vR 100

ERA4.48

FIP4.39

K%24.0%

BB%9.7%

K-BB%14.3%

Proj IP49

Value2027 · WAR

Runs saved vs league avg · 49 IP

Grades · Statcast · Contract

Scouting Grades

STUF7070

CTRL3535

CMD4545

K†6060

Statcast Percentiles

FB Velo

p5594.9

Whiff%

p9038.0%

p2919.1%

xwOBA vs

p100.372

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)
2014	22	MLB MLE	Seattle Mariners	57	0	66	272	70	22	4	0%	1.2	25.7%	8.1%	17.6%	1.5%	2.17	2.78	+1.4
2014	22	MLB RAW	Seattle Mariners	57	0	66	272	70	22	4	0%	1.2	25.7%	8.1%	17.6%	1.5%	2.17	2.77	+1.4
2015	23	MIX MLE	3 levels	40	0	52	233	45	23	4	0%	1.3	16.6%	10.0%	6.6%	1.6%	5.88	3.85	+0.4
2015	23	MIX RAW	3 levels	40	0	52	233	45	23	4	0%	1.3	19.3%	9.9%	9.4%	1.7%	5.88	3.70	+0.5
2016	24	MIX MLE	2 levels	58	0	62	268	59	19	11	0%	1.1	20.4%	7.2%	13.2%	4.1%	4.65	4.54	+0.0
2016	24	MIX RAW	2 levels	58	0	62	268	59	19	11	0%	1.1	22.0%	7.1%	14.9%	4.1%	4.65	4.42	+0.1
2017	25	MIX MLE	2 levels	69	0	74	295	85	21	6	0%	1.1	29.0%	7.2%	21.9%	2.2%	2.66	2.74	+1.6
2017	25	MIX RAW	2 levels	69	0	74	295	85	21	6	0%	1.1	28.8%	7.1%	21.7%	2.0%	2.66	2.71	+1.6
2018	26	MIX MLE	2 levels	39	0	34	155	33	11	6	0%	0.9	24.5%	4.7%	19.8%	3.0%	5.29	3.30	+0.5
2018	26	MIX RAW	2 levels	39	0	34	155	33	11	6	0%	0.9	21.3%	7.1%	14.2%	3.9%	5.29	4.42	+0.1
2019	27	MIX MLE	2 levels	63	0	72	310	88	34	12	0%	1.1	26.8%	11.2%	15.6%	4.2%	4.35	4.57	-0.0
2019	27	MIX RAW	2 levels	63	0	72	310	88	34	12	0%	1.1	28.4%	11.0%	17.4%	3.9%	4.35	4.23	+0.3
2020	28	MLB MLE	Cleveland Indians	12	0	10	47	16	5	3	0%	0.8	34.0%	10.6%	23.4%	6.4%	8.38	5.08	-0.1
2020	28	MLB RAW	Cleveland Indians	12	0	10	47	16	5	3	0%	0.8	34.0%	10.6%	23.4%	6.4%	8.38	5.38	-0.1
2021	29	MIX MLE	2 levels	64	5	63	253	66	24	2	8%	1.0	22.8%	9.6%	13.2%	1.0%	1.44	2.93	+1.2
2021	29	MIX RAW	2 levels	64	5	63	253	66	24	2	8%	1.0	26.1%	9.5%	16.6%	0.8%	1.44	2.56	+1.5
2022	30	MLB MLE	San Francisco Giants	55	0	49	222	52	19	6	0%	0.9	23.4%	8.6%	14.9%	2.9%	4.01	3.81	+0.4
2022	30	MLB RAW	San Francisco Giants	55	0	49	222	52	19	6	0%	0.9	23.4%	8.6%	14.9%	2.7%	4.01	3.73	+0.5
2023	31	MIX MLE	2 levels	59	0	65	282	69	26	15	0%	1.1	23.0%	10.6%	12.3%	6.1%	4.13	5.86	-1.0
2023	31	MIX RAW	2 levels	59	0	65	282	69	26	15	0%	1.1	24.5%	9.2%	15.2%	5.3%	4.13	5.17	-0.5
2024	32	MIX MLE	2 levels	27	0	23	106	24	13	4	0%	0.9	19.1%	14.6%	4.5%	4.4%	6.26	5.76	-0.3
2024	32	MIX MLE	2 levels	27	0	23	106	24	13	4	0%	0.9	19.1%	14.6%	4.5%	4.4%	6.26	5.76	-0.3
2024	32	MIX RAW	2 levels	27	0	23	106	24	13	4	0%	0.9	22.6%	12.3%	10.4%	3.8%	6.26	4.97	-0.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			427	4	429	1854	444	168	60	1%	1.0	23.9%	9.1%	14.9%	3.2%	3.94	4.02	+2.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	35	MLB	CWS	47	0	49	207	50	20	6	0%	1.0	24.0%	9.7%	14.3%	3.1%	4.48	4.39	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	36	MLB MLE	CWS	34	0	36	150	35	16	5	0%	1.0	23.0%	10.3%	12.6%	3.5%	4.65	4.76	-0.1
2028	36	MLB CTX	CWS	34	0	36	152	35	16	5	0%	1.1	23.0%	10.3%	12.6%	3.5%	4.65	4.76	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		461	4	465	2004	479	184	65	1%	1.0	23.9%	9.2%	14.7%	3.3%	4.00	4.03	+2.9
/ 200 IP	—	RAW		198	2	200	863	206	79	28	1%	1.0	23.9%	9.2%	14.7%	3.3%	4.00	4.03	+1.2
Career	—	MLE		543	5	571	2443	581	222	77	1%	1.1	23.8%	9.1%	14.7%	3.1%	3.88	3.97	+2.6
/ 200 IP	—	MLE		190	2	200	856	203	78	27	1%	1.1	23.8%	9.1%	14.7%	3.1%	3.88	3.97	+1.1

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.

2023 AAARound Rock Express · 11 IPFIP 1.84 → 2.27 (+0.42)K% 31.9% → 27.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.91%	—	×0.860	27.45%
BB% (unintentional) /BF	2.13%	—	×0.900	1.91%
HR / BF /BF	2.13%	÷1.035	×1.100	2.26%

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 107).

Result: FIP 1.84 → 2.27, 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 AAASacramento River Cats · 9 IPFIP 0.24 → 0.78 (+0.53)K% 47.1% → 41.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	47.06%	—	×0.880	41.41%
BB% (unintentional) /BF	8.82%	—	×1.050	9.26%
HR / BF /BF	0.00%	÷0.995	×1.100	0.00%

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 99).

Result: FIP 0.24 → 0.78, 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 AAAMemphis Redbirds · 32 IPFIP 3.00 → 3.55 (+0.55)K% 32.3% → 28.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.31%	—	×0.880	28.43%
BB% (unintentional) /BF	10.77%	—	×1.050	11.31%
HR / BF /BF	2.31%	÷0.982	×1.100	2.58%

Result: FIP 3.00 → 3.55, 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 AAAMemphis Redbirds · 10 IPFIP 6.81 → 7.73 (+0.93)K% 14.3% → 12.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.29%	—	×0.880	12.57%
BB% (unintentional) /BF	12.24%	—	×1.050	12.86%
HR / BF /BF	6.12%	÷0.909	×1.100	7.40%

Result: FIP 6.81 → 7.73, 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).

2016 AAAReno Aces · 35 IPFIP 3.22 → 3.54 (+0.31)K% 26.3% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.28%	—	×0.880	23.12%
BB% (unintentional) /BF	5.84%	—	×1.050	6.13%
HR / BF /BF	2.92%	÷1.092	×1.100	2.94%

Result: FIP 3.22 → 3.54, 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).

2015 AAMobile BayBears · 28 IPFIP 2.74 → 3.29 (+0.55)K% 23.9% → 19.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.93%	—	×0.810	19.38%
BB% (unintentional) /BF	9.40%	—	×1.100	10.34%
HR / BF /BF	0.85%	÷1.098	×1.200	0.93%

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 120).

Result: FIP 2.74 → 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).

2015 AAATacoma Rainiers · 9 IPFIP 4.31 → 4.54 (+0.24)K% 19.0% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.05%	—	×0.880	16.76%
BB% (unintentional) /BF	11.90%	—	×1.050	12.50%
HR / BF /BF	2.38%	÷1.127	×1.100	2.32%

Result: FIP 4.31 → 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).

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
Dominic Leone (OGILVIE)	—	—	4.39	24.0%	9.7%	3.1%	—	4.76	23.0%	12.6%	36	+0.37	—	—	—
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	77
Brendan Donnelly R 2006 · 4.21 FIP	35	SU	4.21	19.1%	9.0%	2.9%	.260	3.19	18.6%	10.1%	60	-1.02	2.23	385	75
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	75
Jean Machi R 2017 · 4.12 FIP	35	SU	4.12	18.6%	6.6%	3.2%	.285	—	—	—	—	—	2.16	306	74
Toby Borland R 2004 · 4.28 FIP	35	SU	4.28	20.9%	8.1%	3.5%	.259	—	—	—	—	—	2.92	248	73
Juan Sandoval R 2016 · 3.24 FIP	35	SU	3.24	18.2%	10.2%	0.7%	.288	4.40	16.3%	9.1%	116	+1.16	3.24	225	72
Leo Rosales R 2015 · 3.99 FIP	34	SU	3.99	18.1%	10.8%	1.9%	.261	4.24	7.8%	-0.4%	22	+0.25	3.85	130	71
Hector Navarro R 2015 · 4.35 FIP	35	SU	4.35	15.0%	5.4%	3.3%	.281	3.00	15.2%	9.0%	81	-1.35	2.30	126	70
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	70
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	69
Spencer Patton R 2023 · 4.33 FIP	35	SU	4.33	18.9%	9.7%	2.9%	.295	—	—	—	—	—	2.79	239	68
Brian Schlitter R 2021 · 4.70 FIP	35	SU	4.70	14.9%	9.1%	3.1%	.318	—	—	—	—	—	3.27	300	68
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	67
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	67
Kazuhiro Sasaki R 2003 · 3.30 FIP	35	SU	3.30	19.3%	8.7%	1.3%	.274	—	—	—	—	—	2.76	223	65
Fernando Rodriguez Jr. R 2019 · 5.11 FIP	35	SW	5.11	25.0%	11.2%	4.9%	.312	—	—	—	—	—	3.34	335	65
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	65
Rodolfo Aguirre R 2019 · 4.50 FIP	34	SU	4.50	21.3%	5.1%	4.7%	.244	—	—	—	—	—	3.39	212	64
Jim Miller R 2016 · 5.43 FIP	34	SU	5.43	20.4%	14.1%	4.1%	.347	—	—	—	—	—	3.95	140	64
Chris Nichting R 2001 · 4.11 FIP	35	SU	4.11	21.2%	3.7%	4.2%	.351	4.67	16.6%	13.3%	36	+0.56	4.11	103	63

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	2.6	51	23.9%	10.3%	1.25	4.04
Tony Sipp ('19)	2.5	46	25.2%	10.5%	1.32	3.72
Hansel Robles ('22)	2.1	61	25.3%	10.2%	1.20	4.11
Al Reyes ('08)	2.1	54	23.2%	10.7%	1.11	3.84
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Ed Nunez ('82-'94, 2 WAR*)	3.3	54	24.5%*	9.5%*	1.24*	4.37*
Xavier Hernandez ('89-'98, 3 WAR*)	3.4	67	23.9%*	9.1%*	1.12*	4.20*