Mark Leiter Jr.

P Athletics

Age 36 RHP 6'0" / 210 lbs MLB peak 0.3 · 2027 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	33	MLBNYY	60	58	4.50	3.01	33.6%	8.2%	1.1
2025	34	MIX2 levels	60	49	4.74	3.32	24.2%	8.1%	0.7	K 24.7% · BB 7.8% · FIP 3.17
2026	35	MLBOAK	36	34	4.28	2.51	26.4%	6.9%	0.8
2027PROJ	36	MLBOAK	22	23	3.81	3.58	26.2%	7.6%	0.3
2028PROJ	37	MLBOAK	28	29	3.91	3.98	25.1%	8.2%	0.2

Last 3 seasons WAR 2.6 · Next 2 projected WAR 0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%73

xwOBA vs46

FB Velo18

CompsSeunghwan Oh (age 36) · Tony Barnette (age 34) · Rafael Martín (age 35)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10193vR 85

ERA3.81

FIP3.58

K%26.2%

BB%7.6%

K-BB%18.6%

Proj IP23

Value2027 · WAR

Runs saved vs league avg · 23 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1892.2

Whiff%

p8230.3%

p7326.4%

xwOBA vs

p460.316

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)
2015	24	MIX MLE	2 levels	27	21	143	590	121	33	7	78%	5.3	16.0%	6.3%	9.7%	1.4%	3.09	3.29	—
2015	24	MIX RAW	2 levels	27	21	143	590	121	33	7	78%	5.3	20.5%	5.6%	14.9%	1.2%	3.09	2.74	—
2016	25	AA MLE	Reading Fightin Phils	23	17	104	424	94	30	9	74%	4.5	18.0%	7.8%	10.2%	2.0%	3.39	3.67	—
2016	25	AA RAW	Reading Fightin Phils	23	17	104	424	94	30	9	74%	4.5	22.2%	7.1%	15.1%	2.1%	3.39	3.28	—
2017	26	MIX MLE	2 levels	34	16	121	519	122	35	23	47%	3.5	22.6%	6.8%	15.8%	4.2%	4.77	4.38	+0.2
2017	26	MIX RAW	2 levels	34	16	121	519	122	35	23	47%	3.5	23.5%	6.7%	16.8%	4.4%	4.77	4.43	+0.2
2018	27	MIX MLE	3 levels	43	0	57	267	61	22	10	0%	1.3	19.4%	8.6%	10.7%	4.2%	5.08	4.86	-0.2
2018	27	MIX RAW	3 levels	43	0	57	267	61	22	10	0%	1.3	22.8%	8.2%	14.6%	3.7%	5.08	4.41	+0.1
2021	30	MIX MLE	2 levels	25	19	115	472	145	31	14	76%	4.6	26.5%	7.0%	19.5%	3.2%	3.77	3.49	—
2021	30	MIX RAW	2 levels	25	19	115	472	145	31	14	76%	4.6	30.7%	6.6%	24.2%	3.0%	3.77	2.97	—
2022	31	MIX MLE	2 levels	41	10	90	376	105	29	14	24%	2.2	26.9%	7.8%	19.1%	3.9%	4.32	3.98	+0.6
2022	31	MIX RAW	2 levels	41	10	90	376	105	29	14	24%	2.2	27.9%	7.7%	20.2%	3.7%	4.32	3.76	+0.8
2023	32	MLB MLE	Chicago Cubs	69	0	64	269	77	24	7	0%	0.9	28.6%	8.9%	19.7%	2.7%	3.50	3.30	+1.0
2023	32	MLB RAW	Chicago Cubs	69	0	64	269	77	24	7	0%	0.9	28.6%	8.9%	19.7%	2.6%	3.50	3.24	+1.0
2024	33	MLB MLE	New York Yankees	60	0	58	256	86	21	8	0%	1.0	33.6%	8.2%	25.4%	2.9%	4.50	2.91	+1.1
2024	33	MLB MLE	New York Yankees	60	0	58	256	86	21	8	0%	1.0	33.6%	8.2%	25.4%	2.9%	4.50	2.91	+1.1
2024	33	MLB RAW	New York Yankees	60	0	58	256	86	21	8	0%	1.0	33.6%	8.2%	25.4%	3.1%	4.50	3.01	+1.1
2025	34	MIX MLE	2 levels	60	0	49	223	54	18	5	0%	0.8	24.7%	7.8%	16.9%	2.1%	4.74	3.17	+0.8
2025	34	MIX MLE	2 levels	60	0	49	223	54	18	5	0%	0.8	24.7%	7.8%	16.9%	2.1%	4.74	3.17	+0.8
2025	34	MIX RAW	2 levels	60	0	49	223	54	18	5	0%	0.8	24.2%	8.1%	16.1%	2.2%	4.74	3.32	+0.7
2026	35	MLB MLE	Athletics	36	0	34	144	38	10	2	0%	0.9	26.4%	6.9%	19.4%	1.4%	4.28	2.53	+0.8
2026	35	MLB MLE	Athletics	36	0	34	144	38	10	2	0%	0.9	26.4%	6.9%	19.4%	1.4%	4.28	2.53	+0.8
2026	35	MLB RAW	Athletics	36	0	34	144	38	10	2	0%	0.9	26.4%	6.9%	19.4%	1.4%	4.28	2.51	+0.8
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			306	15	386	1688	434	133	57	5%	1.3	25.7%	7.9%	17.8%	3.4%	4.57	3.80	+3.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	OAK	22	0	23	97	25	7	2	0%	1.0	26.2%	7.6%	18.6%	2.5%	3.81	3.58	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	OAK	27	0	29	122	31	10	3	0%	1.1	25.1%	8.2%	16.9%	2.9%	3.91	3.98	+0.2
2028	37	MLB CTX	OAK	28	0	29	122	31	10	4	0%	1.0	25.1%	8.2%	16.9%	2.9%	3.91	3.98	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		333	15	415	1810	465	143	60	5%	1.2	25.7%	7.9%	17.8%	3.3%	4.52	3.77	+3.8
/ 200 IP	—	RAW		161	7	200	873	224	69	29	4%	1.2	25.7%	7.9%	17.8%	3.3%	4.52	3.77	+1.9
Career	—	MLE		418	83	833	3540	822	263	101	20%	2.0	23.2%	7.4%	15.8%	2.9%	4.01	3.65	+3.6
/ 200 IP	—	MLE		100	20	200	850	197	63	24	20%	2.0	23.2%	7.4%	15.8%	2.9%	4.01	3.65	+1.7

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.

2022 AAAIowa Cubs · 22 IPFIP 3.37 → 4.00 (+0.63)K% 34.0% → 30.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.04%	—	×0.880	29.96%
BB% (unintentional) /BF	6.38%	—	×1.050	6.70%
HR / BF /BF	4.26%	÷0.996	×1.100	4.70%

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 3.37 → 4.00, 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 AAAToledo Mud Hens · 89 IPFIP 2.85 → 3.27 (+0.42)K% 30.5% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.47%	—	×0.880	26.81%
BB% (unintentional) /BF	6.37%	—	×1.050	6.69%
HR / BF /BF	2.77%	÷1.052	×1.100	2.90%

Result: FIP 2.85 → 3.27, 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 AAErie SeaWolves · 26 IPFIP 3.33 → 4.20 (+0.87)K% 31.5% → 25.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.53%	—	×0.810	25.54%
BB% (unintentional) /BF	7.21%	—	×1.100	7.93%
HR / BF /BF	3.60%	÷1.055	×1.200	4.10%

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 111).

Result: FIP 3.33 → 4.20, 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 AAALehigh Valley IronPigs · 28 IPFIP 3.60 → 4.10 (+0.50)K% 23.6% → 20.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.62%	—	×0.880	20.79%
BB% (unintentional) /BF	9.45%	—	×1.050	9.92%
HR / BF /BF	2.36%	÷0.954	×1.100	2.72%

Result: FIP 3.60 → 4.10, 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 AAALehigh Valley IronPigs · 30 IPFIP 3.34 → 3.80 (+0.46)K% 30.6% → 27.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.65%	—	×0.880	26.97%
BB% (unintentional) /BF	4.84%	—	×1.050	5.08%
HR / BF /BF	4.03%	÷1.043	×1.100	4.25%

Result: FIP 3.34 → 3.80, 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).

2016 AAReading Fightin Phils · 104 IPFIP 3.29 → 3.67 (+0.38)K% 22.2% → 18.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.17%	—	×0.810	17.96%
BB% (unintentional) /BF	7.08%	—	×1.100	7.78%
HR / BF /BF	2.12%	÷1.273	×1.200	2.00%

Result: FIP 3.29 → 3.67, 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 A+Clearwater Threshers · 96 IPFIP 2.61 → 3.21 (+0.60)K% 21.5% → 16.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.50%	—	×0.770	16.56%
BB% (unintentional) /BF	5.96%	—	×1.150	6.85%
HR / BF /BF	1.04%	÷1.117	×1.250	1.16%

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 123).

Result: FIP 2.61 → 3.21, 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).

2015 AAReading Fightin Phils · 47 IPFIP 2.96 → 3.46 (+0.50)K% 18.6% → 15.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.63%	—	×0.810	15.09%
BB% (unintentional) /BF	4.90%	—	×1.100	5.39%
HR / BF /BF	1.47%	÷1.021	×1.200	1.73%

Result: FIP 2.96 → 3.46, 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
Mark Leiter Jr. (OGILVIE)	—	—	—	—	—	2.5%	—	3.98	25.1%	16.9%	29	+0.40	—	—	—
Seunghwan Oh R 2018 · 2.83 FIP	36	SU	2.83	28.8%	5.8%	2.6%	.257	5.75	18.2%	11.4%	18	+2.92	1.87	226	71
Tony Barnette R 2018 · 2.61 FIP	34	SU	2.61	25.0%	4.8%	1.8%	.239	—	—	—	—	—	2.61	144	66
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	62
Kazuhiro Sasaki R 2003 · 3.30 FIP	35	SU	3.30	19.3%	8.7%	1.3%	.274	—	—	—	—	—	2.76	223	61
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	60
Juan Sandoval R 2017 · 3.42 FIP	36	SU	3.42	16.7%	7.2%	1.5%	.298	5.41	15.9%	8.7%	57	+1.99	3.24	225	59
Peter Moylan R 2015 · 3.11 FIP	36	SU	3.11	18.4%	8.2%	0.9%	.259	3.84	18.2%	9.1%	145	+0.73	2.54	431	59
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	57
Matt Bush R 2022 · 3.73 FIP	36	SU	3.73	30.3%	6.6%	4.3%	.224	3.79	26.2%	17.5%	36	+0.06	2.87	249	57
Scott Atchison R 2012 · 2.52 FIP	36	SU	2.52	18.0%	3.0%	1.0%	.256	3.67	15.9%	11.3%	137	+1.15	2.52	340	56
Salvador Valdez R 2019 · 4.30 FIP	36	SW	4.30	17.1%	8.2%	2.9%	.405	—	—	—	—	—	3.60	326	56
Roy Corcoran R 2015 · 2.87 FIP	35	SU	2.87	17.7%	8.2%	0.4%	.359	—	—	—	—	—	2.87	129	56
Akinori Otsuka R 2007 · 2.39 FIP	35	SU	2.39	17.6%	6.1%	0.0%	.260	—	—	—	—	—	2.39	232	56
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	54
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	53
Brendan Donnelly R 2007 · 2.40 FIP	36	SU	2.40	16.7%	5.6%	0.0%	.271	4.75	19.1%	6.0%	70	+2.35	2.23	385	53
Kazuhisa Makita R 2019 · 2.81 FIP	34	SU	2.81	18.9%	3.7%	1.5%	.291	—	—	—	—	—	2.81	132	52
Daniel Bard R 2021 · 3.62 FIP	36	SU	3.62	26.3%	11.5%	2.3%	.337	3.64	24.6%	10.3%	110	+0.02	2.56	456	52
Buddy Carlyle R 2014 · 2.57 FIP	36	SU	2.57	23.5%	4.2%	1.7%	.250	—	—	—	—	—	2.57	274	50
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	50

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	2.2	49	25.7%	8.4%	1.27	4.48
Trevor May ('23)	2.3	50	26.8%	8.5%	1.20	4.24
Michael Tonkin ('25)	1.6	55	23.2%	8.1%	1.28	4.23
Shane Greene ('23)	2.4	59	21.7%	8.6%	1.12	4.50
Bob Patterson ('85-'98, 4 WAR*)	3.1	51	23.0%*	6.7%*	1.32*	4.33*
Ed Nunez ('82-'94, 2 WAR*)	3.3	54	24.5%*	9.5%*	1.24*	4.37*
Buddy Schultz ('75-'79, 2 WAR*)	1.2	60	27.4%*	8.5%*	1.21*	4.14*