Brock Stewart

P Los Angeles Dodgers

Age 35 RHP 6'3" / 220 lbs MLB peak 0.5 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	32	MIX2 levels	20	0	20	4.58	3.76	34.1%	12.2%	0.2	K 29.9% · BB 11.9% · FIP 3.72
2025	33	MIX3 levels	48	0	42	2.36	2.48	28.9%	7.2%	1.0	K 27.7% · BB 6.9% · FIP 2.63
2026	34	MIX3 levels	40	1	37	2.19	2.72	29.5%	7.5%	0.8	K 24.3% · BB 7.8% · FIP 3.57
2027PROJ	35	MLBLAD	56	0	59	3.63	3.67	27.1%	7.8%	0.6
2028PROJ91% MLB	36	MLBLAD	36	0	38	3.87	4.03	26.1%	8.4%	0.2
2029PROJ82% MLB	37	MLBLAD	21	0	22	4.21	4.43	25.0%	9.1%	0.0

Last 3 seasons WAR 2.0 · Next 3 projected WAR 0.9Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs90

FB Velo70

K%61

CompsJumbo Diaz (age 35) · Jean Machi (age 35) · Neil Wagner (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10395vR 87

ERA3.63

FIP3.67

K%27.1%

BB%7.8%

K-BB%19.3%

Proj IP59

Value2027 · WAR

Runs saved vs league avg · 59 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p7095.9

Whiff%

p6928.2%

p6124.3%

xwOBA vs

p900.248

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	23	MIX MLE	2 levels	25	19	101	437	103	24	10	76%	4.0	17.9%	6.4%	11.5%	3.2%	4.46	4.17	—
2015	23	MIX RAW	2 levels	25	19	101	437	103	24	10	76%	4.0	23.6%	5.5%	18.1%	2.3%	4.46	3.06	—
2016	24	MIX MLE	4 levels	28	26	149	589	154	30	11	93%	5.3	22.8%	5.3%	17.4%	2.1%	2.54	2.99	+4.5
2016	24	MIX RAW	4 levels	28	26	149	589	154	30	11	93%	5.3	26.1%	5.1%	21.1%	1.9%	2.54	2.60	+5.3
2017	25	MIX MLE	3 levels	23	10	52	225	55	21	6	43%	2.3	23.3%	9.2%	14.1%	2.8%	3.63	3.82	+0.5
2017	25	MIX RAW	3 levels	23	10	52	225	55	21	6	43%	2.3	24.4%	9.3%	15.1%	2.7%	3.63	3.70	+0.5
2018	26	MIX MLE	2 levels	28	21	114	485	94	35	11	75%	4.1	17.4%	7.5%	9.9%	2.3%	3.47	3.87	+2.1
2018	26	MIX RAW	2 levels	28	21	114	485	94	35	11	75%	4.1	19.4%	7.2%	12.2%	2.3%	3.47	3.63	+2.4
2019	27	MIX MLE	2 levels	32	17	110	528	92	51	33	53%	3.4	15.8%	10.1%	5.7%	6.7%	7.94	6.70	-1.6
2019	27	MIX RAW	2 levels	32	17	110	528	92	51	33	53%	3.4	17.4%	9.7%	7.8%	6.2%	7.94	6.72	-1.6
2022	30	MIX MLE	3 levels	11	2	14	63	16	4	4	18%	1.3	25.4%	6.3%	19.0%	6.3%	7.71	5.24	—
2022	30	MIX RAW	3 levels	11	2	14	63	16	4	4	18%	1.3	25.4%	6.3%	19.0%	6.3%	7.71	5.39	—
2023	31	MIX MLE	2 levels	38	0	39	155	61	12	1	0%	1.0	35.8%	7.3%	28.4%	0.9%	0.92	1.51	+1.4
2023	31	MIX RAW	2 levels	38	0	39	155	61	12	1	0%	1.0	39.4%	7.7%	31.6%	0.6%	0.92	1.24	+1.6
2024	32	MIX MLE	2 levels	20	0	20	82	28	10	3	0%	1.0	29.9%	11.9%	17.9%	3.0%	4.58	3.72	+0.2
2024	32	MIX MLE	2 levels	20	0	20	82	28	10	3	0%	1.0	29.9%	11.9%	17.9%	3.0%	4.58	3.72	+0.2
2024	32	MIX RAW	2 levels	20	0	20	82	28	10	3	0%	1.0	34.1%	12.2%	22.0%	3.7%	4.58	3.76	+0.2
2025	33	MIX MLE	3 levels	48	0	42	180	52	13	3	0%	0.9	27.7%	6.9%	20.8%	1.8%	2.36	2.63	+1.0
2025	33	MIX MLE	3 levels	48	0	42	180	52	13	3	0%	0.9	27.7%	6.9%	20.8%	1.8%	2.36	2.63	+1.0
2025	33	MIX RAW	3 levels	48	0	42	180	52	13	3	0%	0.9	28.9%	7.2%	21.7%	1.7%	2.36	2.48	+1.0
2026	34	MIX MLE	3 levels	40	1	37	146	43	11	3	2%	0.9	24.3%	7.8%	16.5%	2.8%	2.19	3.57	+0.4
2026	34	MIX MLE	3 levels	40	1	37	146	43	11	3	2%	0.9	24.3%	7.8%	16.5%	2.8%	2.19	3.57	+0.4
2026	34	MIX RAW	3 levels	40	1	37	146	43	11	3	2%	0.9	29.5%	7.5%	21.9%	2.1%	2.19	2.72	+0.8
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			161	12	213	925	215	77	35	7%	1.3	23.2%	8.3%	14.9%	3.8%	4.26	4.30	+0.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	35	MLB	LAD	56	0	59	249	68	19	7	0%	1.1	27.1%	7.8%	19.3%	2.7%	3.63	3.67	+0.6
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	36	MLB MLE	LAD	40	0	42	177	46	15	5	0%	1.1	26.1%	8.4%	17.7%	3.1%	3.87	4.03	+0.3
2029	37	MLB MLE	LAD	25	0	27	112	28	10	4	0%	1.1	25.0%	9.1%	15.9%	3.5%	4.21	4.43	+0.0
2030	38	MLB MLE	LAD	14	0	14	60	14	6	2	0%	1.0	23.9%	9.8%	14.1%	3.9%	4.60	4.87	-0.1
2028	36	MLB CTX	LAD	36	0	38	160	42	14	5	0%	1.1	26.1%	8.4%	17.7%	3.1%	3.87	4.03	+0.2
2029	37	MLB CTX	LAD	21	0	22	93	23	8	3	0%	1.0	25.0%	9.1%	15.9%	3.5%	4.21	4.43	+0.0
2030	38	MLB CTX	LAD	10	0	10	42	10	4	2	0%	1.0	23.9%	9.8%	14.1%	3.9%	4.60	4.87	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		227	12	283	1220	290	103	45	5%	1.2	23.8%	8.4%	15.3%	3.7%	4.22	4.18	+1.2
/ 200 IP	—	RAW		161	8	200	862	205	73	32	5%	1.2	23.8%	8.4%	15.3%	3.7%	4.22	4.18	+0.9
Career	—	MLE		293	96	678	2890	613	219	94	33%	2.3	21.2%	7.6%	13.7%	3.3%	3.98	4.06	+0.9
/ 200 IP	—	MLE		86	28	200	853	181	64	28	33%	2.3	21.2%	7.6%	13.7%	3.3%	3.98	4.06	+0.6

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.

2026 AOntario Tower Buzzers · 6 IPFIP 0.16 → 0.93 (+0.76)K% 34.8% → 25.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.78%	—	×0.740	25.74%
BB% (unintentional) /BF	0.00%	—	×1.180	0.00%
HR / BF /BF	0.00%	÷1.000	×1.300	0.00%

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 100).

Result: FIP 0.16 → 0.93, 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).

2026 AAAOklahoma City Comets · 5 IPFIP 0.78 → 1.18 (+0.40)K% 50.0% → 43.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	50.00%	—	×0.860	43.00%
BB% (unintentional) /BF	15.00%	—	×0.900	13.50%
HR / BF /BF	0.00%	÷1.000	×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 0.78 → 1.18, 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 AAASt. Paul Saints · 12 IPFIP 0.16 → 0.62 (+0.46)K% 47.8% → 41.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	47.83%	—	×0.860	41.13%
BB% (unintentional) /BF	8.70%	—	×0.900	7.83%
HR / BF /BF	0.00%	÷1.009	×1.100	0.00%

Result: FIP 0.16 → 0.62, 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).

2022 AAASt. Paul Saints · 7 IPFIP 3.97 → 5.12 (+1.15)K% 32.4% → 28.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.35%	—	×0.880	28.47%
BB% (unintentional) /BF	2.94%	—	×1.050	3.09%
HR / BF /BF	5.88%	÷0.881	×1.100	7.34%

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 76).

Result: FIP 3.97 → 5.12, 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).

2022 AFort Myers Mighty Mussels · 5 IPFIP 9.22 → 11.54 (+2.32)K% 15.0% → 11.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.00%	—	×0.740	11.10%
BB% (unintentional) /BF	15.00%	—	×1.180	17.70%
HR / BF /BF	10.00%	÷1.000	×1.300	13.00%

Result: FIP 9.22 → 11.54, 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).

2019 AAABuffalo Bisons · 84 IPFIP 5.91 → 6.46 (+0.55)K% 18.1% → 15.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.07%	—	×0.880	15.90%
BB% (unintentional) /BF	10.64%	—	×1.050	11.18%
HR / BF /BF	5.45%	÷1.000	×1.100	5.99%

Result: FIP 5.91 → 6.46, 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).

2018 AAAOklahoma City Dodgers · 96 IPFIP 3.29 → 3.62 (+0.33)K% 20.3% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.25%	—	×0.880	17.82%
BB% (unintentional) /BF	7.34%	—	×1.050	7.71%
HR / BF /BF	1.77%	÷1.020	×1.100	1.91%

Result: FIP 3.29 → 3.62, 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).

2017 AAAOklahoma City Dodgers · 17 IPFIP 2.22 → 2.77 (+0.55)K% 34.7% → 30.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.72%	—	×0.880	30.56%
BB% (unintentional) /BF	4.17%	—	×1.050	4.38%
HR / BF /BF	2.78%	÷0.989	×1.100	3.09%

Result: FIP 2.22 → 2.77, 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
Brock Stewart (OGILVIE)	—	—	—	—	—	2.7%	—	4.30	25.4%	16.5%	83	+0.63	—	—	—
Jumbo Diaz R 2019 · 2.98 FIP	35	SU	2.98	25.0%	7.7%	1.8%	.290	—	—	—	—	—	2.80	319	67
Jean Machi R 2017 · 4.12 FIP	35	SU	4.12	18.6%	6.6%	3.2%	.285	—	—	—	—	—	2.16	306	64
Neil Wagner R 2017 · 3.11 FIP	33	SU	3.11	20.7%	8.6%	1.2%	.257	—	—	—	—	—	3.11	135	62
Huascar Brazobán R 2024 · 3.08 FIP	34	SU	3.08	23.5%	11.5%	0.9%	.259	3.71	21.3%	11.7%	144	+0.63	3.08	370	61
Tony Pena Jr. R 2016 · 2.87 FIP	35	SU	2.87	21.5%	4.3%	1.9%	.249	3.43	10.9%	6.6%	22	+0.56	2.80	128	59
Tony Barnette R 2018 · 2.61 FIP	34	SU	2.61	25.0%	4.8%	1.8%	.239	—	—	—	—	—	2.61	144	58
Toby Borland R 2004 · 4.28 FIP	35	SU	4.28	20.9%	8.1%	3.5%	.259	—	—	—	—	—	2.92	248	58
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	58
Yoshihisa Hirano R 2019 · 3.72 FIP	35	SU	3.72	26.2%	8.6%	3.2%	.303	5.02	17.5%	4.8%	12	+1.30	3.45	132	57
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	57
Rodolfo Aguirre R 2019 · 4.50 FIP	34	SU	4.50	21.3%	5.1%	4.7%	.244	—	—	—	—	—	3.39	212	56
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	55
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	55
Fernando Cruz R 2024 · 2.94 FIP	34	SU	2.94	37.8%	11.5%	2.9%	.328	3.39	32.1%	19.6%	103	+0.45	2.50	371	54
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	54
Kazuhiro Sasaki R 2003 · 3.30 FIP	35	SU	3.30	19.3%	8.7%	1.3%	.274	—	—	—	—	—	2.76	223	53
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	52
Daniel Bard R 2020 · 2.82 FIP	35	SU	2.82	25.5%	7.5%	1.7%	.290	3.63	25.3%	12.0%	175	+0.81	2.56	456	52
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	52
Seunghwan Oh R 2017 · 3.90 FIP	35	SU	3.90	20.5%	2.3%	4.1%	.299	3.45	26.6%	20.5%	87	-0.45	1.87	226	51

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	1.8	36	24.4%	9.2%	1.36	4.12
Michael Tonkin ('25)	1.6	55	23.2%	8.1%	1.28	4.23
Chasen Shreve ('24)	1.8	45	25.2%	10.8%	1.54	3.96
Trevor May ('23)	2.3	50	26.8%	8.5%	1.20	4.24
Bob Patterson ('85-'98, 4 WAR*)	3.1	51	23.0%*	6.7%*	1.32*	4.33*
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*