Brandon Dufault

P Inland Empire 66ers

Age 28 RHP 6'5" / 204 lbs A

Overview

APROSPECT

ETA2029MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	23	A+LAA	34	0	46	4.93	3.52	31.0%	13.3%	—	K 23.8% · BB 15.3% · FIP 5.04
2023	24	AALAA	16	0	21	5.66	4.02	18.1%	18.1%	—	K 14.7% · BB 19.9% · FIP 4.38
2025	26	MIX2 levels	22	14	70	4.89	4.47	16.7%	16.7%	—	K 12.2% · BB 20.1% · FIP 5.22
2026	27	No MLB games played
2027PROJ	28	MLBSEA	—	—	0	6.61	6.61	11.5%	20.0%	—
2028PROJ30% MLB	29	MLBSEA	13	0	14	6.46	6.51	12.4%	19.1%	-0.3
2029PROJ50% MLB	30	MLBSEA	19	0	20	6.43	6.53	12.9%	18.7%	-0.4

Next 3 projected WAR -0.7Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff25Control25Command20

CompsMike Hepple (age 26) · Alex Caldera (age 29) · Oscar Verdugo (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 159151vR 142

ERA6.61

FIP6.61

K%11.5%

BB%20.0%

K-BB%-8.5%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 IP

Grades · Contract

Scouting Grades

STUF2525

CTRL2525

CMD2020

K†3030

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	11	0	17	77	24	10	3	0%	1.6	22.1%	15.9%	6.2%	3.8%	4.67	5.32	—
2021	22	MIX RAW	2 levels	11	0	17	77	24	10	3	0%	1.6	31.2%	13.0%	18.2%	3.9%	4.67	4.31	—
2022	23	A+ MLE	Tri-City Dust Devils	34	0	46	210	65	28	5	0%	1.3	23.8%	15.3%	8.5%	3.7%	4.93	5.04	—
2022	23	A+ RAW	Tri-City Dust Devils	34	0	46	210	65	28	5	0%	1.3	31.0%	13.3%	17.6%	2.4%	4.93	3.52	—
2023	24	AA MLE	Rocket City Trash Pandas	16	0	21	105	19	19	0	0%	1.3	14.7%	19.9%	-5.2%	0.0%	5.66	4.38	—
2023	24	AA RAW	Rocket City Trash Pandas	16	0	21	105	19	19	0	0%	1.3	18.1%	18.1%	0.0%	0.0%	5.66	4.02	—
2025	26	MIX MLE	2 levels	22	14	70	341	57	57	3	64%	3.2	12.2%	20.1%	-7.9%	1.1%	4.89	5.22	—
2025	26	MIX MLE	2 levels	22	14	70	341	57	57	3	64%	3.2	12.2%	20.1%	-7.9%	1.1%	4.89	5.22	—
2025	26	MIX RAW	2 levels	22	14	70	341	57	57	3	64%	3.2	16.7%	16.7%	0.0%	0.9%	4.89	4.47	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	SEA	—	—	0	—	—	—	—	—	—	11.5%	20.0%	-8.5%	2.9%	6.61	6.61	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	SEA	46	0	48	203	25	39	6	0%	1.0	12.4%	19.1%	-6.7%	3.0%	6.46	6.51	-1.0
2029	30	MLB MLE	SEA	37	0	39	164	21	31	5	0%	1.0	12.9%	18.7%	-5.8%	3.2%	6.43	6.53	-0.8
2028	29	MLB CTX	SEA	13	0	14	59	7	11	2	0%	1.1	12.4%	19.1%	-6.7%	3.0%	6.46	6.51	-0.3
2029	30	MLB CTX	SEA	19	0	20	84	11	16	3	0%	1.1	12.9%	18.7%	-5.8%	3.2%	6.43	6.53	-0.4
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		32	0	34	143	18	27	4	0%	1.1	12.7%	18.9%	-6.2%	3.1%	6.44	6.14	-0.6
/ 200 IP	—	RAW		190	0	200	844	106	159	24	0%	1.1	12.7%	18.9%	-6.2%	3.1%	6.44	6.14	-3.7
Career	—	MLE		83	14	154	733	124	134	14	17%	1.9	16.9%	18.2%	-1.3%	2.0%	4.98	5.06	-1.9
/ 200 IP	—	MLE		108	18	200	954	161	174	19	17%	1.9	16.9%	18.2%	-1.3%	2.0%	4.98	5.06	-4.5

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.

2025 AInland Empire 66ers · 60 IPFIP 4.12 → 4.96 (+0.85)K% 16.7% → 12.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.67%	—	×0.740	12.33%
BB% (unintentional) /BF	14.54%	—	×1.180	17.16%
HR / BF /BF	1.06%	÷1.036	×1.300	1.33%

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 107).

Result: FIP 4.12 → 4.96, 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).

2025 ROKACL Angels · 10 IPFIP 5.10 → 6.42 (+1.32)K% 16.9% → 11.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.95%	—	×0.680	11.53%
BB% (unintentional) /BF	27.12%	—	×1.250	33.90%
HR / BF /BF	0.00%	÷0.873	×1.400	0.00%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 75).

Result: FIP 5.10 → 6.42, 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).

2023 AARocket City Trash Pandas · 21 IPFIP 3.86 → 4.38 (+0.52)K% 18.1% → 14.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.10%	—	×0.810	14.66%
BB% (unintentional) /BF	18.10%	—	×1.100	19.90%
HR / BF /BF	0.00%	÷0.970	×1.200	0.00%

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 94).

Result: FIP 3.86 → 4.38, 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+Tri-City Dust Devils · 46 IPFIP 3.48 → 5.04 (+1.55)K% 31.0% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.95%	—	×0.770	23.83%
BB% (unintentional) /BF	13.33%	—	×1.150	15.33%
HR / BF /BF	2.38%	÷0.814	×1.250	3.65%

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 63).

Result: FIP 3.48 → 5.04, 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 AInland Empire 66ers · 15 IPFIP 3.92 → 5.32 (+1.41)K% 29.9% → 22.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.85%	—	×0.740	22.09%
BB% (unintentional) /BF	13.43%	—	×1.180	15.85%
HR / BF /BF	2.99%	÷1.023	×1.300	3.79%

Result: FIP 3.92 → 5.32, 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
Brandon Dufault (OGILVIE)	—	—	6.61	11.5%	20.0%	2.9%	—	6.52	12.6%	-6.3%	87	-0.09	—	—	—
Mike Hepple R 2016 · 5.75 FIP	26	SU	5.75	11.1%	18.5%	2.3%	.271	—	—	—	—	—	4.46	116	81
Alex Caldera R 2015 · 5.57 FIP	29	SW	5.57	10.4%	13.1%	3.1%	.333	4.54	11.9%	0.8%	84	-1.03	4.54	120	77
Oscar Verdugo R 2017 · 6.31 FIP	27	SU	6.31	10.3%	13.8%	4.2%	.277	—	—	—	—	—	5.01	144	75
Dylan Rheault R 2021 · 5.76 FIP	29	SU	5.76	12.1%	18.3%	2.5%	.357	—	—	—	—	—	3.88	198	72
Hunter Dollander R 2023 · 6.77 FIP	26	SU	6.77	17.6%	18.3%	5.2%	.329	—	—	—	—	—	3.92	106	71
Matt Eckelman R 2022 · 5.72 FIP	28	SU	5.72	12.4%	13.2%	3.6%	.289	6.65	6.6%	-15.4%	27	+0.93	4.07	386	69
Chris Jefferson R 2024 · 5.65 FIP	27	SU	5.65	16.4%	13.6%	4.0%	.308	—	—	—	—	—	3.53	140	69
Ted Stuka R 2023 · 7.45 FIP	26	SU	7.45	15.2%	36.8%	1.8%	.250	—	—	—	—	—	5.36	105	68
Connor Law R 2021 · 6.15 FIP	27	SU	6.15	16.2%	17.2%	4.1%	.300	—	—	—	—	—	3.19	110	68
Carlos Frías R 2017 · 6.07 FIP	27	SU	6.07	10.4%	13.0%	4.0%	.299	4.42	16.9%	5.8%	31	-1.65	3.40	236	68
Cre Finfrock R 2022 · 6.31 FIP	26	SU	6.31	16.7%	25.2%	2.6%	.309	—	—	—	—	—	4.27	103	67
Brad Allen R 2016 · 5.82 FIP	27	SW	5.82	14.7%	13.2%	4.2%	.272	—	—	—	—	—	4.25	149	67
Jesus Barraza R 2019 · 5.96 FIP	28	SU	5.96	8.7%	13.5%	3.4%	.328	—	—	—	—	—	3.24	164	67
Ryan Olson R 2022 · 6.71 FIP	27	SU	6.71	9.0%	26.2%	1.9%	.275	—	—	—	—	—	3.19	102	66
Luis Romero R 2022 · 5.72 FIP	28	SU	5.72	11.1%	12.4%	3.6%	.344	5.56	13.9%	-1.9%	15	-0.16	4.00	293	65
Victor Mateo R 2016 · 5.45 FIP	27	SW	5.45	10.2%	12.2%	3.0%	.370	—	—	—	—	—	4.32	199	64
Enrique Gonzalez R 2010 · 6.23 FIP	28	SU	6.23	12.1%	15.9%	3.9%	.233	—	—	—	—	—	4.49	132	64
Gabe Klobosits R 2023 · 6.12 FIP	28	SU	6.12	12.6%	13.2%	4.4%	.255	3.39	23.1%	11.9%	33	-2.73	2.60	129	64
Stevie Branche R 2024 · 5.67 FIP	27	SU	5.67	19.3%	17.6%	3.6%	.320	—	—	—	—	—	3.23	162	64
Harrison Cooney R 2018 · 6.60 FIP	26	SU	6.60	18.8%	21.9%	4.2%	.237	—	—	—	—	—	4.65	186	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	0.8	52	12.1%	19.4%	1.16	6.52
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
Doug Creek ('05)	1.4	58	22.2%	15.1%	1.52	5.32
Matt Perisho ('05)	1.4	69	15.2%	12.2%	1.37	6.39
Lloyd Allen ('69-'75, -5 WAR*)	1.5	59	19.8%*	13.9%*	0.79*	5.99*
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*