Alan Busenitz

P Louisville Bats

Age 36 RHP 6'1" / 180 lbs AAA

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	32	MIX2 levels	53	0	58	4.66	4.01	21.4%	9.3%	0.4	K 18.9% · BB 9.5% · FIP 4.47
2024	33	MIX2 levels	52	2	70	4.61	3.50	21.1%	7.0%	0.9	K 18.6% · BB 6.8% · FIP 3.57
2025	34	AAACIN	18	0	25	6.75	7.01	18.8%	7.1%	—	K 16.1% · BB 6.4% · FIP 7.93
2026	35	No MLB games played
2027PROJ	36	MLBCIN	5	0	5	4.85	4.91	21.4%	8.9%	-0.0
2028PROJMLE	37	MLBCIN	—	—	0	5.07	5.25	20.5%	9.6%	—

Last 3 seasons WAR 1.2 · Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2018

FB Velo61

K%39

xwOBA vs10

CompsKeiichi Yabu (age 36) · Rudy Gonzalez (age 36) · Joe Nelson (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 126118vR 110

ERA4.85

FIP4.91

K%21.4%

BB%8.9%

K-BB%12.4%

Proj IP51

Value2027 · WAR

Runs saved vs league avg · 51 IP

Grades · Statcast · Contract

Scouting Grades

STUF4545

CTRL4545

CMD4545

K†5050

Statcast Percentiles

FB Velo

p6195.3

Whiff%

p6026.9%

p3920.6%

xwOBA vs

p100.389

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	24	MIX MLE	2 levels	37	8	100	446	82	32	9	22%	2.7	14.5%	8.1%	6.4%	2.5%	5.15	4.25	—
2015	24	MIX RAW	2 levels	37	8	100	446	82	32	9	22%	2.7	18.4%	7.2%	11.2%	2.0%	5.15	3.59	—
2016	25	MIX MLE	2 levels	45	0	61	255	55	13	3	0%	1.4	18.0%	5.5%	12.5%	1.2%	3.54	2.92	—
2016	25	MIX RAW	2 levels	45	0	61	255	55	13	3	0%	1.4	21.6%	5.1%	16.5%	1.2%	3.54	2.58	—
2017	26	MIX MLE	2 levels	52	0	67	253	62	19	4	0%	1.3	22.7%	7.7%	14.9%	1.6%	1.88	3.03	+1.2
2017	26	MIX RAW	2 levels	52	0	67	253	62	19	4	0%	1.3	24.5%	7.5%	17.0%	1.6%	1.88	2.88	+1.3
2018	27	MIX MLE	2 levels	50	1	65	283	71	21	11	2%	1.3	23.2%	7.5%	15.6%	4.1%	4.55	4.37	+0.1
2018	27	MIX RAW	2 levels	50	1	65	283	71	21	11	2%	1.3	25.1%	7.4%	17.7%	3.9%	4.55	4.08	+0.4
2023	32	MIX MLE	2 levels	53	0	58	257	55	24	7	0%	1.1	18.9%	9.5%	9.4%	3.2%	4.66	4.47	+0.1
2023	32	MIX RAW	2 levels	53	0	58	257	55	24	7	0%	1.1	21.4%	9.3%	12.1%	2.7%	4.66	4.01	+0.4
2024	33	MIX MLE	2 levels	52	2	70	299	63	21	7	4%	1.4	18.6%	6.8%	11.8%	2.1%	4.61	3.57	+0.8
2024	33	MIX MLE	2 levels	52	2	70	299	63	21	7	4%	1.4	18.6%	6.8%	11.8%	2.1%	4.61	3.57	+0.8
2024	33	MIX RAW	2 levels	52	2	70	299	63	21	7	4%	1.4	21.1%	7.0%	14.0%	2.3%	4.61	3.50	+0.9
2025	34	AAA MLE	Louisville Bats	18	0	25	112	21	8	9	0%	1.4	16.1%	6.4%	9.7%	9.8%	6.75	7.93	—
2025	34	AAA MLE	Louisville Bats	18	0	25	112	21	8	9	0%	1.4	16.1%	6.4%	9.7%	9.8%	6.75	7.93	—
2025	34	AAA RAW	Louisville Bats	18	0	25	112	21	8	9	0%	1.4	18.8%	7.1%	11.6%	8.0%	6.75	7.01	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			60	0	68	297	57	23	13	0%	1.1	19.2%	7.7%	11.4%	4.4%	4.90	4.92	-0.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	CIN	5	0	5	21	5	2	1	0%	1.0	21.4%	8.9%	12.4%	3.8%	4.85	4.91	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	CIN	33	0	34	144	30	14	6	0%	1.0	20.5%	9.6%	10.9%	4.2%	5.07	5.25	-0.3
2028	37	MLB CTX	CIN	—	—	0	—	—	—	—	—	—	20.5%	9.6%	10.9%	4.2%	5.07	5.25	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		60	0	68	298	57	23	13	0%	1.1	19.2%	7.8%	11.4%	4.4%	4.90	4.86	-0.3
/ 200 IP	—	RAW		177	0	200	873	167	67	38	0%	1.1	19.2%	7.8%	11.4%	4.4%	4.90	4.86	-0.7
Career	—	MLE		307	11	447	1905	355	143	55	4%	1.5	18.7%	7.5%	11.2%	2.9%	4.29	4.07	-0.6
/ 200 IP	—	MLE		137	5	200	853	159	64	25	4%	1.5	18.7%	7.5%	11.2%	2.9%	4.29	4.07	-1.1

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 AAALouisville Bats · 25 IPFIP 6.83 → 7.93 (+1.10)K% 18.8% → 16.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.75%	—	×0.860	16.12%
BB% (unintentional) /BF	7.14%	—	×0.900	6.43%
HR / BF /BF	8.04%	÷0.901	×1.100	9.81%

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 80).

Result: FIP 6.83 → 7.93, 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).

2024 AAALouisville Bats · 66 IPFIP 3.42 → 3.57 (+0.15)K% 21.6% → 18.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.58%	—	×0.860	18.56%
BB% (unintentional) /BF	7.55%	—	×0.900	6.80%
HR / BF /BF	2.16%	÷1.111	×1.100	2.14%

Result: FIP 3.42 → 3.57, 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 AAALouisville Bats · 51 IPFIP 4.27 → 4.47 (+0.20)K% 21.9% → 18.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.93%	—	×0.860	18.86%
BB% (unintentional) /BF	10.53%	—	×0.900	9.47%
HR / BF /BF	3.07%	÷1.054	×1.100	3.21%

Result: FIP 4.27 → 4.47, 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 AAARochester Red Wings · 40 IPFIP 2.29 → 2.88 (+0.58)K% 28.7% → 25.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.66%	—	×0.880	25.22%
BB% (unintentional) /BF	4.46%	—	×1.050	4.68%
HR / BF /BF	1.91%	÷0.879	×1.100	2.39%

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 2.29 → 2.88, 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 AAARochester Red Wings · 35 IPFIP 1.56 → 1.91 (+0.35)K% 29.5% → 26.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.55%	—	×0.880	26.00%
BB% (unintentional) /BF	7.58%	—	×1.050	7.95%
HR / BF /BF	0.00%	÷0.956	×1.100	0.00%

Result: FIP 1.56 → 1.91, 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).

2016 AAChattanooga Lookouts · 40 IPFIP 2.30 → 2.67 (+0.37)K% 23.4% → 19.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.42%	—	×0.810	18.97%
BB% (unintentional) /BF	3.80%	—	×1.100	4.18%
HR / BF /BF	1.27%	÷1.301	×1.200	1.17%

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 160).

Result: FIP 2.30 → 2.67, 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).

2016 AAARochester Red Wings · 21 IPFIP 3.01 → 3.34 (+0.32)K% 18.6% → 16.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.56%	—	×0.880	16.33%
BB% (unintentional) /BF	7.22%	—	×1.050	7.58%
HR / BF /BF	1.03%	÷0.951	×1.100	1.19%

Result: FIP 3.01 → 3.34, 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).

2015 AAArkansas Travelers · 53 IPFIP 4.18 → 4.78 (+0.60)K% 15.4% → 12.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.38%	—	×0.810	12.46%
BB% (unintentional) /BF	6.48%	—	×1.100	7.13%
HR / BF /BF	2.83%	÷1.022	×1.200	3.33%

Result: FIP 4.18 → 4.78, 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).

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
Alan Busenitz (OGILVIE)	—	—	4.91	21.4%	8.9%	3.8%	—	5.25	20.5%	10.9%	34	+0.34	—	—	—
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	77
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	71
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	68
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	66
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	66
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	66
Salvador Valdez R 2019 · 4.30 FIP	36	SW	4.30	17.1%	8.2%	2.9%	.405	—	—	—	—	—	3.60	326	66
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	65
Jesus Adrian Castillo R 2019 · 5.13 FIP	35	SU	5.13	13.1%	7.8%	3.9%	.319	—	—	—	—	—	2.23	173	65
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	65
Jim Miller R 2016 · 5.43 FIP	34	SU	5.43	20.4%	14.1%	4.1%	.347	—	—	—	—	—	3.95	140	64
Jay Jackson R 2024 · 5.31 FIP	36	SU	5.31	25.4%	7.9%	6.1%	.304	—	—	—	—	—	2.36	261	64
Daniel Guerrero R 2019 · 5.59 FIP	34	SW	5.59	14.7%	11.1%	4.2%	.353	—	—	—	—	—	4.61	269	61
Francisco Del Rosario R 2017 · 4.15 FIP	36	SU	4.15	16.4%	10.0%	2.1%	.267	6.35	11.9%	-0.6%	77	+2.20	3.93	194	60
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	56
Brian Sweeney R 2010 · 4.63 FIP	36	SU	4.63	9.5%	3.4%	3.5%	.226	—	—	—	—	—	3.03	108	56
Pete Walker R 2005 · 4.79 FIP	36	SU	4.79	12.0%	9.2%	2.8%	.261	4.45	19.6%	11.6%	30	-0.34	4.45	327	50
Leo Rosales R 2017 · 4.24 FIP	36	SU	4.24	7.8%	8.2%	1.4%	.203	—	—	—	—	—	3.85	130	50
Yoshihisa Hirano R 2020 · 5.02 FIP	36	SU	5.02	17.5%	12.7%	3.3%	.381	—	—	—	—	—	3.45	132	44
Brian Shouse L 2005 · 4.24 FIP	36	SU	4.24	15.0%	6.0%	3.0%	.271	3.35	15.0%	9.6%	137	-0.89	2.32	339	36

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	38	20.2%	8.7%	1.61	4.92
Mike Mayers ('23)	1.3	53	23.0%	8.3%	1.61	5.21
Josh Osich ('21)	1.1	55	20.7%	9.0%	1.84	5.02
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Steve Kealey ('68-'73, -1 WAR*)	1.1	54	18.5%*	7.2%*	1.32*	5.26*
Tom Dukes ('67-'72, -2 WAR*)	1.1	43	22.7%*	8.7%*	1.16*	5.37*