Sean Newcomb

P Chicago White Sox

Age 34 LHP 6'5" / 255 lbs MLB peak 0.8 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	31	MIX3 levels	11	1	16	5.06	5.16	18.3%	15.5%	-0.1	K 18.3% · BB 15.5% · FIP 5.06
2025	32	MLBOAK	48	5	92	2.73	2.78	23.3%	7.4%	2.0
2026	33	MLBCWS	60	6	90	3.09	2.85	22.6%	8.3%	1.9
2027PROJ	34	MLBCWS	66	0	69	3.58	3.58	22.6%	8.2%	0.8
2028PROJ	35	MLBCWS	50	0	52	3.64	3.67	23.6%	8.0%	0.6
2029PROJ	36	MLBCWS	31	0	33	3.88	4.04	22.6%	8.6%	0.2

Last 3 seasons WAR 3.7 · Next 3 projected WAR 1.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo55

K%52

xwOBA vs45

Form7.04 ERA (proj 3.58) · K 22.9% (proj 22.6%) · BB 10.0% (proj 8.2%) · last 60d · 15 IP through Oct 27

CompsHisanori Takahashi (age 35) · Alejandro Soto (age 33) · Luke Westphal (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 8896vR 104

ERA3.58

FIP3.58

K%22.6%

BB%8.2%

K-BB%14.4%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p5594.9

Whiff%

p4023.9%

p5222.6%

xwOBA vs

p450.317

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	22	MIX MLE	3 levels	27	27	136	575	168	76	5	100%	5.0	22.5%	15.1%	7.4%	1.1%	2.38	3.69	—
2015	22	MIX RAW	3 levels	27	27	136	575	168	76	5	100%	5.0	29.2%	13.2%	16.0%	0.9%	2.38	2.78	—
2016	23	AA MLE	Mississippi Braves	27	27	140	595	152	71	4	100%	5.2	20.7%	13.1%	7.6%	0.7%	3.86	3.42	—
2016	23	AA RAW	Mississippi Braves	27	27	140	595	152	71	4	100%	5.2	25.5%	11.9%	13.6%	0.7%	3.86	2.82	—
2017	24	MIX MLE	2 levels	30	30	158	705	182	84	13	100%	5.3	24.6%	12.1%	12.4%	1.9%	3.82	3.61	+3.4
2017	24	MIX RAW	2 levels	30	30	158	705	182	84	13	100%	5.3	25.8%	11.9%	13.9%	1.8%	3.82	3.46	+3.7
2018	25	MLB MLE	Atlanta Braves	31	30	164	696	160	80	18	97%	5.3	23.0%	11.5%	11.5%	2.6%	3.90	4.03	+2.7
2018	25	MLB RAW	Atlanta Braves	31	30	164	696	160	80	18	97%	5.3	23.0%	11.5%	11.5%	2.6%	3.90	4.04	+2.7
2019	26	MIX MLE	2 levels	59	7	89	373	85	33	9	12%	1.5	22.1%	8.9%	13.2%	2.5%	2.93	3.72	+0.9
2019	26	MIX RAW	2 levels	59	7	89	373	85	33	9	12%	1.5	22.8%	8.8%	13.9%	2.4%	2.93	3.62	+1.0
2020	27	MLB MLE	Atlanta Braves	4	4	14	70	10	6	4	100%	3.4	14.3%	8.6%	5.7%	5.7%	11.20	6.12	-0.1
2020	27	MLB RAW	Atlanta Braves	4	4	14	70	10	6	4	100%	3.4	14.3%	8.6%	5.7%	5.7%	11.20	6.76	-0.2
2021	28	MIX MLE	2 levels	47	0	49	214	71	30	2	0%	1.0	31.6%	14.1%	17.5%	1.0%	3.67	2.76	+1.1
2021	28	MIX RAW	2 levels	47	0	49	214	71	30	2	0%	1.0	33.2%	14.0%	19.2%	0.9%	3.67	2.57	+1.2
2022	29	MIX MLE	2 levels	32	2	52	235	59	37	9	6%	1.6	23.5%	16.1%	7.4%	4.0%	6.27	5.36	-0.5
2022	29	MIX RAW	2 levels	32	2	52	235	59	37	9	6%	1.6	25.1%	15.7%	9.4%	3.8%	6.27	5.23	-0.4
2023	30	MIX MLE	3 levels	27	4	49	204	62	29	3	15%	1.8	26.8%	14.1%	12.7%	1.7%	3.10	3.53	+0.6
2023	30	MIX RAW	3 levels	27	4	49	204	62	29	3	15%	1.8	30.4%	14.2%	16.2%	1.5%	3.10	3.14	+0.8
2024	31	MIX MLE	3 levels	11	1	16	71	13	11	2	9%	1.5	18.3%	15.5%	2.8%	2.8%	5.06	5.06	-0.1
2024	31	MIX MLE	3 levels	11	1	16	71	13	11	2	9%	1.5	18.3%	15.5%	2.8%	2.8%	5.06	5.06	-0.1
2024	31	MIX RAW	3 levels	11	1	16	71	13	11	2	9%	1.5	18.3%	15.5%	2.8%	2.8%	5.06	5.16	-0.1
2025	32	MLB MLE	Athletics	48	5	92	391	91	29	5	10%	1.9	23.3%	7.4%	15.9%	1.3%	2.73	2.79	+2.0
2025	32	MLB MLE	Athletics	48	5	92	391	91	29	5	10%	1.9	23.3%	7.4%	15.9%	1.3%	2.73	2.79	+2.0
2025	32	MLB RAW	Athletics	48	5	92	391	91	29	5	10%	1.9	23.3%	7.4%	15.9%	1.3%	2.73	2.78	+2.0
2026	33	MLB MLE	Chicago White Sox	60	6	90	372	84	31	4	10%	1.5	22.6%	8.3%	14.2%	1.1%	3.09	2.83	+1.9
2026	33	MLB MLE	Chicago White Sox	60	6	90	372	84	31	4	10%	1.5	22.6%	8.3%	14.2%	1.1%	3.09	2.83	+1.9
2026	33	MLB RAW	Chicago White Sox	60	6	90	372	84	31	4	10%	1.5	22.6%	8.3%	14.2%	1.1%	3.09	2.85	+1.9
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			283	71	614	2668	613	286	61	25%	2.2	23.0%	10.7%	12.3%	2.3%	4.03	3.79	+5.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	CWS	66	0	69	291	66	24	5	0%	1.0	22.6%	8.2%	14.4%	1.8%	3.58	3.58	+0.8
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	CWS	50	0	52	221	52	18	5	0%	1.0	23.6%	8.0%	15.7%	2.1%	3.62	3.65	+0.6
2029	36	MLB MLE	CWS	31	0	33	138	31	12	3	0%	1.1	22.6%	8.6%	14.0%	2.5%	3.86	4.02	+0.2
2028	35	MLB CTX	CWS	50	0	52	220	52	17	5	0%	1.0	23.6%	8.0%	15.7%	2.1%	3.64	3.67	+0.6
2029	36	MLB CTX	CWS	31	0	33	139	31	12	4	0%	1.1	22.6%	8.6%	14.0%	2.5%	3.88	4.04	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		364	71	699	3028	697	316	69	20%	1.9	23.0%	10.4%	12.6%	2.3%	4.00	3.73	+6.8
/ 200 IP	—	RAW		104	20	200	866	199	90	20	19%	1.9	23.0%	10.4%	12.6%	2.3%	4.00	3.73	+1.9
Career	—	MLE		403	143	1049	4501	1044	538	81	35%	2.6	23.2%	11.9%	11.3%	1.8%	3.61	3.64	+6.3
/ 200 IP	—	MLE		77	27	200	858	199	102	15	35%	2.6	23.2%	11.9%	11.3%	1.8%	3.61	3.64	+1.8

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 AAALas Vegas Aviators · 5 IPFIP 3.83 → 3.82 (−0.01)K% 17.4% → 15.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.39%	—	×0.860	14.96%
BB% (unintentional) /BF	17.39%	—	×0.900	15.65%
HR / BF /BF	0.00%	÷1.001	×1.100	0.00%

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 100).

Result: FIP 3.83 → 3.82, 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 AAASacramento River Cats · 31 IPFIP 3.29 → 3.50 (+0.20)K% 30.5% → 26.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.53%	—	×0.860	26.26%
BB% (unintentional) /BF	15.27%	—	×0.900	13.74%
HR / BF /BF	1.53%	÷1.057	×1.100	1.59%

Result: FIP 3.29 → 3.50, 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 AAAIowa Cubs · 24 IPFIP 3.31 → 3.79 (+0.48)K% 30.7% → 27.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.69%	—	×0.880	27.01%
BB% (unintentional) /BF	17.82%	—	×1.050	18.71%
HR / BF /BF	0.99%	÷0.996	×1.100	1.09%

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 3.31 → 3.79, 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 AAAGwinnett Stripers · 17 IPFIP 1.05 → 1.62 (+0.57)K% 43.8% → 38.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	43.75%	—	×0.880	38.50%
BB% (unintentional) /BF	6.25%	—	×1.050	6.56%
HR / BF /BF	1.56%	÷1.001	×1.100	1.72%

Result: FIP 1.05 → 1.62, 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 · 21 IPFIP 2.47 → 2.91 (+0.45)K% 25.0% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.880	22.00%
BB% (unintentional) /BF	6.25%	—	×1.050	6.56%
HR / BF /BF	1.25%	÷0.899	×1.100	1.53%

Result: FIP 2.47 → 2.91, 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 AAAGwinnett Braves · 58 IPFIP 2.93 → 3.40 (+0.47)K% 29.7% → 26.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.72%	—	×0.880	26.15%
BB% (unintentional) /BF	13.25%	—	×1.050	13.92%
HR / BF /BF	1.20%	÷0.972	×1.100	1.36%

Result: FIP 2.93 → 3.40, 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 AAMississippi Braves · 140 IPFIP 2.82 → 3.42 (+0.60)K% 25.5% → 20.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.55%	—	×0.810	20.69%
BB% (unintentional) /BF	11.93%	—	×1.100	13.13%
HR / BF /BF	0.67%	÷1.084	×1.200	0.74%

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 2.82 → 3.42, 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+Inland Empire 66ers · 66 IPFIP 2.45 → 3.41 (+0.96)K% 30.0% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.00%	—	×0.770	23.10%
BB% (unintentional) /BF	11.79%	—	×1.150	13.55%
HR / BF /BF	0.71%	÷0.896	×1.250	1.00%

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 79).

Result: FIP 2.45 → 3.41, 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
Sean Newcomb (OGILVIE)	—	—	—	—	—	1.8%	—	3.79	23.2%	15.0%	85	+0.21	—	—	—
Hisanori Takahashi L 2010 · 3.50 FIP	35	SW	3.50	22.1%	7.0%	2.5%	.292	3.81	21.1%	15.0%	118	+0.31	3.50	240	75
Alejandro Soto L 2019 · 4.03 FIP	33	SW	4.03	17.1%	6.9%	2.7%	.376	—	—	—	—	—	3.96	280	61
Luke Westphal L 2022 · 4.35 FIP	33	SW	4.35	24.2%	13.4%	2.9%	.302	5.19	15.7%	-0.7%	26	+0.84	2.97	294	61
Juan Pablo Perez L 2013 · 3.68 FIP	34	SU	3.68	25.2%	11.5%	2.3%	.250	3.68	26.5%	11.2%	51	-0.00	1.75	104	56
John Bale L 2008 · 3.22 FIP	34	SW	3.22	12.7%	5.5%	0.9%	.315	4.31	17.6%	5.8%	28	+1.09	2.49	168	55
Pedro Borbón L 2002 · 4.57 FIP	34	SU	4.57	21.6%	7.3%	4.3%	.277	—	—	—	—	—	2.26	264	55
Hideki Okajima L 2010 · 4.27 FIP	34	SU	4.27	15.5%	7.0%	2.9%	.333	—	—	—	—	—	3.05	238	55
Brandon Mann L 2018 · 3.59 FIP	34	SU	3.59	17.8%	11.4%	1.0%	.232	—	—	—	—	—	3.59	190	54
Clay Rapada L 2015 · 3.84 FIP	34	SU	3.84	14.3%	8.0%	1.7%	.299	—	—	—	—	—	3.00	120	51
Jamie Walker L 2005 · 3.81 FIP	34	SU	3.81	14.4%	4.8%	2.4%	.270	4.46	16.3%	12.2%	147	+0.65	3.48	442	50
Tom Martin L 2004 · 4.74 FIP	34	SU	4.74	14.7%	7.8%	3.4%	.278	3.96	14.7%	7.1%	86	-0.78	3.40	303	49
James Jones L 2023 · 4.67 FIP	34	SU	4.67	13.7%	11.5%	2.3%	.246	—	—	—	—	—	3.58	127	49
Heriberto Ruelas L 2016 · 3.75 FIP	34	SU	3.75	15.0%	8.9%	1.4%	.310	3.42	17.2%	10.5%	49	-0.33	2.95	117	48
Joey Eischen L 2004 · 3.63 FIP	34	SU	3.63	21.2%	7.5%	2.5%	.255	3.37	19.0%	9.1%	51	-0.26	2.13	294	48
Zac Rosscup L 2022 · 2.83 FIP	34	SU	2.83	24.1%	13.9%	0.0%	.303	—	—	—	—	—	2.56	173	47
Brian Shouse L 2003 · 2.38 FIP	34	SU	2.38	15.8%	3.2%	0.4%	.299	3.97	15.6%	8.5%	136	+1.59	2.32	339	46
Brooks Raley L 2022 · 2.39 FIP	34	SU	2.39	27.9%	6.8%	1.4%	.243	2.62	25.6%	17.4%	80	+0.23	1.74	294	46
Jonny Venters L 2018 · 3.04 FIP	33	SU	3.04	18.6%	9.0%	0.7%	.240	—	—	—	—	—	2.36	264	45
Brady Feigl L 2024 · 4.12 FIP	33	SU	4.12	23.7%	4.7%	4.4%	.312	3.70	22.2%	14.9%	14	-0.42	2.69	212	45
Kwang Hyun Kim L 2021 · 4.21 FIP	33	SP-	4.21	17.7%	8.2%	2.9%	.266	—	—	—	—	—	3.76	146	45

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	3.8	77	23.0%	10.7%	0.86	3.96
David Phelps ('22)	3.4	76	22.9%	9.4%	0.94	3.80
Joe Kelly ('24)	4.2	70	21.1%	9.8%	0.78	3.98
Dan Osinski ('62-'70, 4 WAR*)	2.9	84	20.1%*	10.4%*	0.88*	4.00*
Jeff Parrett ('86-'96, 6 WAR*)	3.6	72	24.8%*	11.0%*	1.02*	4.07*
George Frazier ('78-'87, 2 WAR*)	3.4	68	21.6%*	10.5%*	0.92*	4.42*
Juan Cruz ('12)	3.3	60	23.1%	12.1%	0.92	4.05