Jordan Leasure

P Chicago White Sox

Age 28 RHP 6'3" / 220 lbs MLB ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	44	0	41	6.15	5.22	20.9%	13.2%	-0.3	K 18.3% · BB 12.7% · FIP 5.44
2025	26	MLBCWS	68	1	64	3.92	4.36	30.1%	10.8%	0.1
2026	27	MIX2 levels	22	1	23	5.48	5.53	24.5%	8.5%	-0.3	K 23.1% · BB 9.0% · FIP 6.44
2027PROJ	28	MLBCWS	31	0	33	4.63	4.80	27.9%	10.8%	-0.1
2028PROJ93% MLB	29	MLBCWS	40	0	42	4.83	4.96	27.3%	11.0%	-0.2
2029PROJ94% MLB	30	MLBCWS	31	0	33	5.03	5.17	26.6%	11.3%	-0.2

Last 3 seasons WAR -0.4 · Next 3 projected WAR -0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo68

K%55

xwOBA vs10

CompsJason Bulger (age 29) · Josh Lueke (age 28) · Matt Ramsey (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 124116vR 108

ERA4.63

FIP4.80

K%27.9%

BB%10.8%

K-BB%17.1%

Proj IP36

Value2027 · WAR

Runs saved vs league avg · 36 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL3535

CMD5050

K†6565

Statcast Percentiles

FB Velo

p6895.8

Whiff%

p5826.5%

p5523.1%

xwOBA vs

p100.406

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	22	MIX MLE	2 levels	8	0	10	42	13	3	3	0%	1.3	31.0%	7.1%	23.8%	7.1%	5.23	5.31	—
2021	22	MIX RAW	2 levels	8	0	10	42	13	3	3	0%	1.3	31.0%	7.1%	23.8%	7.1%	5.23	5.23	—
2022	23	MIX MLE	2 levels	49	0	59	241	84	21	8	0%	1.2	25.0%	9.2%	15.8%	4.7%	3.37	4.75	—
2022	23	MIX RAW	2 levels	49	0	59	241	84	21	8	0%	1.2	34.9%	8.7%	26.1%	3.3%	3.37	3.08	—
2023	24	MIX MLE	2 levels	44	0	48	206	79	23	9	0%	1.1	31.6%	11.5%	20.1%	4.6%	3.91	4.42	—
2023	24	MIX RAW	2 levels	44	0	48	206	79	23	9	0%	1.1	38.3%	11.2%	27.2%	4.4%	3.91	3.68	—
2024	25	MIX MLE	2 levels	44	0	41	182	38	24	7	0%	0.9	18.3%	12.7%	5.6%	4.2%	6.15	5.44	-0.4
2024	25	MIX MLE	2 levels	44	0	41	182	38	24	7	0%	0.9	18.3%	12.7%	5.6%	4.2%	6.15	5.44	-0.4
2024	25	MIX RAW	2 levels	44	0	41	182	38	24	7	0%	0.9	20.9%	13.2%	7.7%	3.8%	6.15	5.22	-0.3
2025	26	MLB MLE	Chicago White Sox	68	1	64	269	81	29	12	1%	0.9	30.1%	10.8%	19.3%	4.4%	3.92	4.33	+0.2
2025	26	MLB MLE	Chicago White Sox	68	1	64	269	81	29	12	1%	0.9	30.1%	10.8%	19.3%	4.4%	3.92	4.33	+0.2
2025	26	MLB RAW	Chicago White Sox	68	1	64	269	81	29	12	1%	0.9	30.1%	10.8%	19.3%	4.5%	3.92	4.36	+0.1
2026	27	MIX MLE	2 levels	22	1	23	94	23	8	6	5%	1.0	23.1%	9.0%	14.1%	7.6%	5.48	6.44	-0.5
2026	27	MIX MLE	2 levels	22	1	23	94	23	8	6	5%	1.0	23.1%	9.0%	14.1%	7.6%	5.48	6.44	-0.5
2026	27	MIX RAW	2 levels	22	1	23	94	23	8	6	5%	1.0	24.5%	8.5%	16.0%	6.4%	5.48	5.53	-0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			119	2	114	489	125	54	24	2%	1.0	25.6%	11.0%	14.5%	4.9%	4.96	5.06	-0.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	CWS	31	0	33	139	39	15	6	0%	1.1	27.9%	10.8%	17.1%	4.2%	4.63	4.80	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	CWS	43	0	46	193	53	21	8	0%	1.1	27.3%	11.0%	16.3%	4.4%	4.83	4.96	-0.2
2029	30	MLB MLE	CWS	34	0	36	150	40	17	7	0%	1.0	26.6%	11.3%	15.3%	4.6%	5.03	5.17	-0.2
2028	29	MLB CTX	CWS	40	0	42	177	48	20	8	0%	1.1	27.3%	11.0%	16.3%	4.4%	4.83	4.96	-0.2
2029	30	MLB CTX	CWS	31	0	33	139	37	16	6	0%	1.1	26.6%	11.3%	15.3%	4.6%	5.03	5.17	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		191	2	190	808	211	90	38	1%	1.0	26.1%	11.1%	15.1%	4.7%	4.94	4.89	-0.8
/ 200 IP	—	RAW		201	2	200	851	222	95	40	1%	1.0	26.1%	11.1%	15.1%	4.7%	4.94	4.89	-0.8
Career	—	MLE		235	2	246	1034	274	109	50	1%	1.0	26.5%	10.6%	16.0%	4.9%	4.36	4.87	-1.2
/ 200 IP	—	MLE		191	2	200	842	223	89	41	1%	1.0	26.5%	10.6%	16.0%	4.9%	4.36	4.87	-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.

2024 AAACharlotte Knights · 10 IPFIP 3.84 → 4.12 (+0.28)K% 30.0% → 25.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.00%	—	×0.860	25.80%
BB% (unintentional) /BF	15.00%	—	×0.900	13.50%
HR / BF /BF	2.50%	÷1.016	×1.100	2.71%

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 103).

Result: FIP 3.84 → 4.12, 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 AATulsa Drillers · 35 IPFIP 3.43 → 4.45 (+1.03)K% 39.7% → 32.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.72%	—	×0.810	32.17%
BB% (unintentional) /BF	10.64%	—	×1.100	11.70%
HR / BF /BF	4.26%	÷1.083	×1.200	4.72%

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 117).

Result: FIP 3.43 → 4.45, 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 AAACharlotte Knights · 13 IPFIP 4.20 → 4.35 (+0.15)K% 35.4% → 30.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.38%	—	×0.860	30.43%
BB% (unintentional) /BF	12.31%	—	×0.900	11.08%
HR / BF /BF	4.62%	÷1.152	×1.100	4.41%

Result: FIP 4.20 → 4.35, 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 AATulsa Drillers · 49 IPFIP 3.70 → 4.75 (+1.05)K% 30.9% → 25.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.88%	—	×0.810	25.01%
BB% (unintentional) /BF	8.33%	—	×1.100	9.17%
HR / BF /BF	3.92%	÷0.993	×1.200	4.74%

Result: FIP 3.70 → 4.75, 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+Great Lakes Loons · 9 IPFIP -0.32 → 0.98 (+1.31)K% 56.8% → 43.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	56.76%	—	×0.770	43.70%
BB% (unintentional) /BF	10.81%	—	×1.150	12.43%
HR / BF /BF	0.00%	÷1.013	×1.250	0.00%

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 103).

Result: FIP -0.32 → 0.98, 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 ARancho Cucamonga Quakes · 6 IPFIP 6.98 → 9.31 (+2.33)K% 24.0% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.00%	—	×0.740	17.76%
BB% (unintentional) /BF	12.00%	—	×1.180	14.16%
HR / BF /BF	8.00%	÷0.965	×1.300	10.78%

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 93).

Result: FIP 6.98 → 9.31, 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
Jordan Leasure (OGILVIE)	—	—	4.80	27.9%	10.8%	4.2%	—	5.05	27.0%	15.9%	81	+0.25	—	—	—
Jason Bulger R 2008 · 4.60 FIP	29	SU	4.60	27.4%	12.3%	4.1%	.293	3.94	25.1%	13.3%	90	-0.66	3.78	106	81
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	77
Matt Ramsey R 2018 · 3.78 FIP	28	SU	3.78	24.9%	8.8%	3.0%	.276	2.42	21.7%	12.6%	34	-1.36	2.42	125	75
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	75
Michael Flynn R 2024 · 3.99 FIP	27	SU	3.99	27.6%	8.3%	3.9%	.277	4.68	16.2%	3.7%	50	+0.69	3.89	168	75
Al Alburquerque R 2014 · 3.62 FIP	28	SU	3.62	26.7%	8.5%	3.1%	.267	3.27	21.8%	11.6%	147	-0.35	1.73	391	74
Ryan Brasier R 2016 · 3.68 FIP	28	SU	3.68	25.0%	7.7%	3.1%	.289	3.09	24.2%	17.9%	130	-0.59	2.31	426	74
Trevor May R 2018 · 3.74 FIP	28	SU	3.74	26.1%	9.8%	2.9%	.291	3.47	31.9%	23.6%	150	-0.27	3.05	477	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	73
Steven Wilson R 2023 · 4.12 FIP	28	SU	4.12	26.0%	11.9%	3.1%	.217	4.64	20.6%	10.8%	121	+0.52	3.64	331	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
Brooks Kriske R 2021 · 4.95 FIP	27	SU	4.95	28.6%	12.1%	5.0%	.261	4.27	30.0%	17.8%	88	-0.68	3.09	246	72
Justin Sterner R 2024 · 3.92 FIP	27	SU	3.92	27.0%	8.0%	3.8%	.262	4.52	24.5%	17.6%	108	+0.60	3.90	294	71
Kerry Ligtenberg R 2000 · 4.00 FIP	29	SU	4.00	23.5%	8.8%	3.2%	.257	3.79	19.6%	11.6%	186	-0.21	2.94	381	71
Kyle Barraclough R 2018 · 4.52 FIP	28	SU	4.52	24.5%	12.7%	3.4%	.219	5.02	30.1%	17.0%	86	+0.50	1.95	523	71
Peyton Gray R 2021 · 4.27 FIP	26	SU	4.27	29.2%	14.1%	3.4%	.307	—	—	—	—	—	3.62	160	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
Alan Busenitz R 2018 · 4.37 FIP	27	SU	4.37	23.2%	7.5%	4.1%	.322	—	—	—	—	—	2.92	436	70
Yennier Cano R 2022 · 4.46 FIP	28	SU	4.46	23.2%	11.8%	3.3%	.325	3.19	23.4%	16.2%	191	-1.27	2.43	381	70
Scott Atchison R 2004 · 3.61 FIP	28	SU	3.61	27.1%	9.0%	3.0%	.309	4.55	19.1%	11.5%	31	+0.94	2.52	340	70

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	1.2	47	26.5%	11.2%	1.79	4.89
Robert Stephenson ('25)	1.9	62	25.9%	10.1%	1.54	4.59
Amir Garrett ('24)	1.7	55	26.7%	13.3%	1.52	4.95
Michael Feliz ('22)	1.2	50	29.9%	9.9%	1.55	5.29
Jeff Jones ('80-'84, -2 WAR*)	1.0	41	22.0%*	12.4%*	1.48*	4.53*
Phil Hennigan ('69-'73, -0 WAR*)	1.4	70	20.9%*	10.4%*	1.50*	4.95*
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*