Maddux Bruns

P Tulsa Drillers

Age 25 LHP 6'2" / 205 lbs AA

Overview

AAPROSPECT

ETA2028MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	22	A+LAD	10	10	28	2.22	2.61	28.9%	15.6%	—	K 22.3% · BB 18.0% · FIP 3.50
2025	23	MIX2 levels	16	16	56	6.95	3.66	22.4%	15.5%	—	K 17.1% · BB 17.8% · FIP 4.49
2026	24	MIX2 levels	20	0	22	10.48	5.38	25.0%	26.6%	—	K 16.4% · BB 33.3% · FIP 6.61
2027PROJ	25	MLBLAD	1	1	1	6.06	6.06	16.5%	20.0%	-0.0
2028PROJ44% MLB	26	MLBLAD	3	3	20	5.86	5.85	17.5%	18.9%	-0.1
2029PROJ63% MLB	27	MLBLAD	4	4	24	5.76	5.77	18.0%	18.2%	-0.1

Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control25Command30

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsNate Savino (age 22) · Brooks Gosswein (age 24) · Colby Langford (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 132140vR 148

ERA6.06

FIP6.06

K%16.5%

BB%20.0%

K-BB%-3.5%

Proj IP60

Value2027 · WAR

Runs saved vs league avg · 60 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL2525

CMD3030

K†4040

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	19	ROK MLE	ACL Dodgers	4	4	5	30	5	7	2	100%	1.2	16.7%	23.3%	-6.7%	6.7%	16.20	8.31	—
2021	19	ROK RAW	ACL Dodgers	4	4	5	30	5	7	2	100%	1.2	16.7%	23.3%	-6.7%	6.7%	16.20	10.50	—
2022	20	A MLE	Rancho Cucamonga Quakes	21	21	44	216	67	45	1	100%	2.1	23.0%	24.6%	-1.6%	0.5%	5.68	4.54	—
2022	20	A RAW	Rancho Cucamonga Quakes	21	21	44	216	67	45	1	100%	2.1	31.0%	20.8%	10.2%	0.5%	5.68	3.42	—
2023	21	MIX MLE	2 levels	26	26	97	430	126	67	7	100%	3.7	22.3%	18.0%	4.3%	2.1%	3.99	4.67	—
2023	21	MIX RAW	2 levels	26	26	97	430	126	67	7	100%	3.7	29.3%	15.6%	13.7%	1.6%	3.99	3.51	—
2024	22	A+ MLE	Great Lakes Loons	10	10	28	128	37	20	0	100%	2.8	22.3%	18.0%	4.3%	0.0%	2.22	3.50	—
2024	22	A+ MLE	Great Lakes Loons	10	10	28	128	37	20	0	100%	2.8	22.3%	18.0%	4.3%	0.0%	2.22	3.50	—
2024	22	A+ RAW	Great Lakes Loons	10	10	28	128	37	20	0	100%	2.8	28.9%	15.6%	13.3%	0.0%	2.22	2.61	—
2025	23	MIX MLE	2 levels	16	16	56	277	62	43	2	100%	3.5	17.1%	17.8%	-0.7%	1.1%	6.95	4.49	—
2025	23	MIX MLE	2 levels	16	16	56	277	62	43	2	100%	3.5	17.1%	17.8%	-0.7%	1.1%	6.95	4.49	—
2025	23	MIX RAW	2 levels	16	16	56	277	62	43	2	100%	3.5	22.4%	15.5%	6.9%	0.7%	6.95	3.66	—
2026	24	MIX MLE	2 levels	20	0	22	128	32	34	1	0%	1.1	16.4%	33.3%	-17.0%	1.2%	10.48	6.61	—
2026	24	MIX MLE	2 levels	20	0	22	128	32	34	1	0%	1.1	16.4%	33.3%	-17.0%	1.2%	10.48	6.61	—
2026	24	MIX RAW	2 levels	20	0	22	128	32	34	1	0%	1.1	25.0%	26.6%	-1.6%	0.8%	10.48	5.38	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	LAD	1	1	1	4	1	1	0	100%	1.0	16.5%	20.0%	-3.5%	2.6%	6.06	6.06	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	LAD	7	7	45	188	33	36	5	100%	6.4	17.5%	18.9%	-1.3%	2.7%	5.86	5.85	-0.2
2029	27	MLB MLE	LAD	6	6	38	163	29	30	4	100%	6.4	18.0%	18.2%	-0.3%	2.7%	5.76	5.77	-0.2
2028	26	MLB CTX	LAD	3	3	20	84	15	16	2	100%	6.7	17.5%	18.9%	-1.3%	2.7%	5.86	5.85	-0.1
2029	27	MLB CTX	LAD	4	4	24	101	18	18	3	100%	6.0	18.0%	18.2%	-0.3%	2.7%	5.76	5.77	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		7	7	44	186	33	34	5	100%	6.3	17.8%	18.5%	-0.7%	2.7%	5.80	5.42	-0.0
/ 200 IP	—	RAW		33	33	200	844	150	155	23	100%	6.0	17.8%	18.5%	-0.7%	2.7%	5.80	5.42	-0.1
Career	—	MLE		97	77	253	1209	247	253	17	79%	2.6	20.5%	20.9%	-0.4%	1.4%	5.56	4.78	-0.4
/ 200 IP	—	MLE		77	61	200	957	196	200	13	79%	2.6	20.5%	20.9%	-0.4%	1.4%	5.56	4.78	-0.9

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 AATulsa Drillers · 16 IPFIP 5.79 → 6.61 (+0.82)K% 20.2% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.20%	—	×0.810	16.36%
BB% (unintentional) /BF	30.30%	—	×1.100	33.33%
HR / BF /BF	1.01%	÷1.000	×1.200	1.21%

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 100).

Result: FIP 5.79 → 6.61, 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 A+Great Lakes Loons · 7 IPFIP 1.35 → 2.42 (+1.07)K% 41.4% → 31.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.38%	—	×0.770	31.86%
BB% (unintentional) /BF	13.79%	—	×1.150	15.86%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 1.35 → 2.42, 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).

2025 A+Great Lakes Loons · 49 IPFIP 3.65 → 4.49 (+0.84)K% 22.2% → 17.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.18%	—	×0.770	17.08%
BB% (unintentional) /BF	15.48%	—	×1.150	17.80%
HR / BF /BF	0.84%	÷0.992	×1.250	1.05%

Result: FIP 3.65 → 4.49, 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 Dodgers · 6 IPFIP 3.10 → 4.24 (+1.14)K% 23.7% → 16.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.68%	—	×0.680	16.11%
BB% (unintentional) /BF	15.79%	—	×1.250	19.74%
HR / BF /BF	0.00%	÷1.187	×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 137).

Result: FIP 3.10 → 4.24, 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).

2024 A+Great Lakes Loons · 28 IPFIP 2.64 → 3.50 (+0.86)K% 28.9% → 22.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.91%	—	×0.770	22.26%
BB% (unintentional) /BF	15.62%	—	×1.150	17.97%
HR / BF /BF	0.00%	÷1.036	×1.250	0.00%

Result: FIP 2.64 → 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).

2023 A+Great Lakes Loons · 76 IPFIP 3.93 → 5.11 (+1.18)K% 27.2% → 20.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.19%	—	×0.770	20.94%
BB% (unintentional) /BF	15.79%	—	×1.150	18.16%
HR / BF /BF	2.05%	÷0.951	×1.250	2.69%

Result: FIP 3.93 → 5.11, 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 ARancho Cucamonga Quakes · 21 IPFIP 1.80 → 2.96 (+1.16)K% 37.5% → 27.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.50%	—	×0.740	27.75%
BB% (unintentional) /BF	14.77%	—	×1.180	17.43%
HR / BF /BF	0.00%	÷1.025	×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 105).

Result: FIP 1.80 → 2.96, 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).

2022 ARancho Cucamonga Quakes · 44 IPFIP 3.37 → 4.54 (+1.17)K% 31.0% → 23.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.02%	—	×0.740	22.95%
BB% (unintentional) /BF	20.83%	—	×1.180	24.58%
HR / BF /BF	0.46%	÷1.247	×1.300	0.48%

Result: FIP 3.37 → 4.54, 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).

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
Maddux Bruns (OGILVIE)	—	—	6.06	16.5%	20.0%	2.6%	—	5.81	17.7%	-0.8%	83	-0.25	—	—	—
Nate Savino L 2024 · 5.85 FIP	22	SP	5.85	16.8%	18.8%	3.2%	.244	4.83	14.9%	2.0%	130	-1.02	4.26	176	78
Brooks Gosswein L 2023 · 5.61 FIP	24	SP-	5.61	15.2%	17.9%	2.8%	.301	—	—	—	—	—	5.13	165	72
Colby Langford L 2024 · 5.34 FIP	22	SW	5.34	21.6%	22.5%	2.2%	.273	6.01	22.2%	-1.1%	110	+0.67	4.92	168	71
Erik Rivera L 2024 · 5.71 FIP	23	SP-	5.71	19.0%	14.6%	4.3%	.255	4.74	23.9%	6.3%	106	-0.97	4.42	141	69
Garrett Schoenle L 2023 · 5.38 FIP	25	SP-	5.38	20.5%	15.0%	3.9%	.307	3.58	20.9%	12.1%	174	-1.80	2.32	362	68
Luke Fox L 2024 · 5.24 FIP	22	SP	5.24	21.8%	19.2%	2.8%	.284	4.16	21.4%	8.1%	125	-1.08	3.60	156	68
Bryce Hubbart L 2024 · 5.45 FIP	23	SP-	5.45	15.5%	13.8%	3.5%	.313	5.14	19.9%	6.3%	82	-0.31	4.79	194	67
Tim Berry L 2016 · 5.66 FIP	25	SP-	5.66	11.3%	13.5%	3.3%	.380	4.04	20.0%	1.8%	44	-1.62	4.04	196	66
Adam Loewen L 2008 · 6.87 FIP	24	SP-	6.87	13.7%	17.6%	4.9%	.308	—	—	—	—	—	2.96	340	66
Nathan Kirby L 2018 · 5.12 FIP	24	SW	5.12	17.7%	16.2%	2.7%	.318	3.84	25.3%	8.7%	38	-1.28	3.84	145	65
Jorge De La Rosa L 2006 · 5.48 FIP	25	SW	5.48	18.3%	14.4%	3.8%	.288	4.04	20.7%	11.2%	445	-1.44	3.24	1,537	63
Zach King L 2023 · 5.02 FIP	25	SP-	5.02	14.1%	13.0%	2.7%	.343	—	—	—	—	—	3.31	278	63
Nick Dombkowski L 2024 · 4.92 FIP	25	SW	4.92	16.5%	10.9%	3.3%	.273	5.17	18.2%	10.6%	183	+0.25	3.71	425	63
Brett Adcock L 2019 · 5.34 FIP	23	SP	5.34	17.4%	13.6%	3.6%	.295	—	—	—	—	—	4.02	301	62
Nate Peterson L 2024 · 5.51 FIP	24	SP-	5.51	19.2%	11.4%	4.7%	.296	4.75	16.0%	3.7%	148	-0.76	4.27	315	59
Cole Kirschsieper L 2023 · 5.07 FIP	22	SP-	5.07	15.2%	12.0%	3.2%	.268	—	—	—	—	—	5.07	105	59
Konnor Pilkington L 2023 · 6.25 FIP	25	SP-	6.25	17.8%	15.2%	5.0%	.338	4.50	20.7%	6.9%	189	-1.75	3.92	622	58
Manny Banuelos L 2016 · 5.18 FIP	25	SP	5.18	15.1%	14.2%	2.8%	.322	4.03	20.2%	9.6%	254	-1.15	2.95	486	57
Aliangel Lopez L 2017 · 6.36 FIP	23	SW	6.36	13.0%	13.9%	4.7%	.371	—	—	—	—	—	4.36	260	56
Miguel Cienfuegos L 2023 · 5.12 FIP	26	SP	5.12	13.6%	10.5%	3.4%	.257	4.54	14.3%	5.8%	242	-0.58	2.95	313	56

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	0.7	48	17.2%	19.2%	1.03	5.92
Brian Bruney ('12)	1.3	43	21.2%	15.8%	0.94	4.68
John Parrish ('10)	1.4	46	17.6%	14.8%	0.88	4.51
Doug Creek ('05)	1.4	58	22.2%	15.1%	1.52	5.32
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*
Ken Wright ('70-'74, -0 WAR*)	1.2	79	23.8%*	16.1%*	0.70*	5.24*