Brandon Neeck

P Indianapolis Indians

Age 27 LHP 6'1" / 190 lbs AAA

Overview

AAAPROSPECT

ETA2028MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	A+LAD	38	0	60	2.85	2.88	27.8%	9.5%	—	K 21.4% · BB 11.0% · FIP 3.78
2025	25	AALAD	39	4	47	5.40	5.52	20.7%	15.2%	—	K 16.8% · BB 16.7% · FIP 6.34
2026	26	MIX2 levels	43	2	70	2.33	2.78	33.9%	15.8%	—	K 28.4% · BB 15.3% · FIP 3.24
2027PROJ	27	MLBPIT	7	0	7	5.10	5.10	24.2%	17.7%	-0.0
2028PROJ43% MLB	28	MLBPIT	21	0	22	5.08	5.11	24.0%	17.0%	-0.1
2029PROJ59% MLB	29	MLBPIT	25	0	26	5.12	5.18	23.7%	16.7%	-0.2

Next 3 projected WAR -0.4Projected 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 -0.2 / P90 0.5, comp-based) · star 0% · didn't stick 96%

CompsAaron Brown (age 27) · Matt Thornton (age 27) · Nick Hagadone (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 114122vR 130

ERA5.10

FIP5.10

K%24.2%

BB%17.7%

K-BB%6.4%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL2525

CMD3030

K†6060

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)
2023	23	MIX MLE	2 levels	23	0	29	137	42	16	2	0%	1.3	21.0%	13.9%	7.0%	2.0%	6.83	4.19	—
2023	23	MIX RAW	2 levels	23	0	29	137	42	16	2	0%	1.3	30.7%	11.7%	19.0%	1.5%	6.83	2.76	—
2024	24	A+ MLE	Great Lakes Loons	38	0	60	241	67	23	4	0%	1.6	21.4%	11.0%	10.4%	2.0%	2.85	3.78	—
2024	24	A+ MLE	Great Lakes Loons	38	0	60	241	67	23	4	0%	1.6	21.4%	11.0%	10.4%	2.0%	2.85	3.78	—
2024	24	A+ RAW	Great Lakes Loons	38	0	60	241	67	23	4	0%	1.6	27.8%	9.5%	18.3%	1.7%	2.85	2.88	—
2025	25	AA MLE	Tulsa Drillers	39	4	47	217	45	33	8	10%	1.2	16.8%	16.7%	0.1%	4.6%	5.40	6.34	—
2025	25	AA MLE	Tulsa Drillers	39	4	47	217	45	33	8	10%	1.2	16.8%	16.7%	0.1%	4.6%	5.40	6.34	—
2025	25	AA RAW	Tulsa Drillers	39	4	47	217	45	33	8	10%	1.2	20.7%	15.2%	5.5%	3.7%	5.40	5.52	—
2026	26	MIX MLE	2 levels	43	2	70	298	101	47	3	5%	1.6	28.4%	15.3%	13.2%	1.1%	2.33	3.24	—
2026	26	MIX MLE	2 levels	43	2	70	298	101	47	3	5%	1.6	28.4%	15.3%	13.2%	1.1%	2.33	3.24	—
2026	26	MIX RAW	2 levels	43	2	70	298	101	47	3	5%	1.6	33.9%	15.8%	18.1%	1.0%	2.33	2.78	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	PIT	7	0	7	30	7	5	1	0%	1.0	24.2%	17.7%	6.4%	2.6%	5.10	5.10	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	PIT	49	0	52	219	52	37	6	0%	1.1	24.0%	17.0%	6.9%	2.7%	5.08	5.11	-0.3
2029	29	MLB MLE	PIT	41	0	43	183	43	31	5	0%	1.1	23.7%	16.7%	7.0%	2.9%	5.12	5.18	-0.3
2028	28	MLB CTX	PIT	21	0	22	93	22	16	3	0%	1.0	24.0%	17.0%	6.9%	2.7%	5.08	5.11	-0.1
2029	29	MLB CTX	PIT	25	0	26	110	26	18	3	0%	1.0	23.7%	16.7%	7.0%	2.9%	5.12	5.18	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		45	0	48	201	48	34	6	0%	1.1	23.8%	16.8%	7.0%	2.8%	5.10	4.77	-0.1
/ 200 IP	—	RAW		190	0	200	844	201	143	25	0%	1.1	23.8%	16.8%	7.0%	2.8%	5.10	4.77	-0.5
Career	—	MLE		143	6	205	893	202	127	21	4%	1.4	22.6%	14.3%	8.3%	2.3%	3.81	4.28	-0.7
/ 200 IP	—	MLE		139	6	200	870	196	124	20	4%	1.4	22.6%	14.3%	8.3%	2.3%	3.81	4.28	-1.4

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 AAAIndianapolis Indians · 43 IPFIP 3.42 → 3.67 (+0.25)K% 31.7% → 27.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.72%	—	×0.860	27.28%
BB% (unintentional) /BF	16.67%	—	×0.900	15.00%
HR / BF /BF	1.61%	÷1.000	×1.100	1.77%

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 3.42 → 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).

2026 AAAltoona Curve · 27 IPFIP 1.74 → 2.53 (+0.78)K% 37.5% → 30.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.50%	—	×0.810	30.38%
BB% (unintentional) /BF	14.29%	—	×1.100	15.71%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 1.74 → 2.53, 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 AATulsa Drillers · 47 IPFIP 5.30 → 6.34 (+1.04)K% 20.7% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.74%	—	×0.810	16.80%
BB% (unintentional) /BF	15.21%	—	×1.100	16.73%
HR / BF /BF	3.69%	÷0.957	×1.200	4.62%

Result: FIP 5.30 → 6.34, 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 · 60 IPFIP 2.87 → 3.78 (+0.91)K% 27.8% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.80%	—	×0.770	21.41%
BB% (unintentional) /BF	9.54%	—	×1.150	10.98%
HR / BF /BF	1.66%	÷1.036	×1.250	2.00%

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 107).

Result: FIP 2.87 → 3.78, 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 · 27 IPFIP 3.07 → 4.19 (+1.12)K% 28.3% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.35%	—	×0.740	20.98%
BB% (unintentional) /BF	11.81%	—	×1.180	13.94%
HR / BF /BF	1.57%	÷1.025	×1.300	2.00%

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 3.07 → 4.19, 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 Neeck (OGILVIE)	—	—	5.10	24.2%	17.7%	2.6%	—	5.14	23.8%	7.0%	95	+0.04	—	—	—
Aaron Brown L 2019 · 4.04 FIP	27	SU	4.04	22.9%	13.5%	2.1%	.317	4.77	19.4%	6.7%	129	+0.73	4.04	269	82
Matt Thornton L 2004 · 4.18 FIP	27	SU	4.18	20.3%	16.2%	1.4%	.304	4.18	21.8%	11.5%	167	-0.00	1.71	663	81
Nick Hagadone L 2013 · 4.75 FIP	27	SU	4.75	22.6%	15.0%	3.0%	.253	3.34	25.9%	19.0%	51	-1.41	2.97	141	80
Trey Jeans L 2022 · 5.09 FIP	26	SU	5.09	22.3%	16.5%	3.3%	.291	—	—	—	—	—	2.74	111	79
Brian Marconi L 2022 · 5.02 FIP	25	SU	5.02	20.3%	18.2%	2.4%	.329	—	—	—	—	—	3.89	101	78
Stephen Randolph L 2003 · 4.83 FIP	29	SU	4.83	18.5%	14.8%	2.6%	.247	5.69	15.8%	-3.0%	82	+0.86	4.83	155	78
Brendan Cellucci L 2024 · 3.98 FIP	26	SU	3.98	26.3%	16.6%	1.8%	.288	4.38	21.7%	9.6%	79	+0.40	3.98	288	78
C.J. Widger L 2024 · 4.21 FIP	25	SU	4.21	26.0%	16.0%	2.3%	.258	5.75	18.1%	-0.7%	57	+1.54	3.83	105	77
Nick Lee L 2016 · 4.96 FIP	25	SU	4.96	19.0%	19.7%	1.8%	.286	—	—	—	—	—	3.77	102	76
Trey Cumbie L 2022 · 5.07 FIP	26	SU	5.07	23.3%	16.1%	3.4%	.215	—	—	—	—	—	3.44	152	76
Graeme Stinson L 2023 · 4.85 FIP	25	SU	4.85	19.5%	15.6%	2.6%	.302	—	—	—	—	—	3.56	146	75
Colton Johnson L 2024 · 3.92 FIP	26	SU	3.92	20.8%	11.0%	2.1%	.309	4.53	12.2%	-0.4%	48	+0.61	3.92	106	75
Brian Moran L 2015 · 4.50 FIP	26	SU	4.50	17.7%	14.1%	2.0%	.318	2.74	25.0%	17.4%	80	-1.76	1.80	421	74
Mitchell Tyranski L 2024 · 4.90 FIP	26	SU	4.90	21.0%	12.3%	3.7%	.234	3.46	20.5%	4.0%	57	-1.44	3.46	145	74
John Bale L 2001 · 4.41 FIP	27	SU	4.41	18.6%	15.0%	1.8%	.219	4.12	19.0%	13.9%	46	-0.29	2.49	168	74
Renyel Pinto L 2009 · 4.10 FIP	27	SU	4.10	21.1%	15.6%	1.5%	.288	3.58	20.8%	9.1%	17	-0.52	3.58	231	74
Luke Westphal L 2016 · 4.69 FIP	27	SU	4.69	21.2%	19.7%	1.6%	.353	—	—	—	—	—	2.97	294	73
Russell Smith L 2024 · 4.00 FIP	25	SU	4.00	19.0%	13.9%	1.4%	.266	—	—	—	—	—	4.00	175	73
Davis Schwab L 2022 · 5.70 FIP	25	SU	5.70	20.3%	18.7%	3.5%	.352	—	—	—	—	—	4.46	114	72
Sean Keselica L 2019 · 4.47 FIP	26	SU	4.47	18.0%	14.5%	1.9%	.314	—	—	—	—	—	2.79	235	72

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	55	24.0%	17.2%	1.05	5.10
Brian Bruney ('12)	1.3	43	21.2%	15.8%	0.94	4.68
Derrick Turnbow ('08)	1.3	64	23.4%	14.8%	0.87	4.30
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*
Doug Creek ('05)	1.4	58	22.2%	15.1%	1.52	5.32
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*
Ken Wright ('70-'74, -0 WAR*)	1.2	79	23.8%*	16.1%*	0.70*	5.24*