Jared Koenig

P Nashville Sounds

Age 33 LHP 6'5" / 244 lbs AAA peak 0.4 · 2027 ILForty Man (40M)

Overview

AAARP40M40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	30	MIX2 levels	61	6	69	2.36	2.62	25.7%	7.3%	1.6	K 23.8% · BB 7.2% · FIP 2.79
2025	31	MLBMIL	72	0	66	2.86	3.08	25.4%	7.1%	1.2
2026	32	MIX2 levels	32	0	27	3.95	3.25	19.5%	10.6%	0.4	K 17.8% · BB 9.9% · FIP 2.85
2027PROJ	33	MLBMIL	49	0	51	3.62	3.86	22.6%	7.7%	0.4
2028PROJ95% MLB	34	MLBMIL	35	0	37	3.95	4.16	21.7%	8.2%	0.2
2029PROJ91% MLB	35	MLBMIL	21	0	22	4.28	4.50	20.7%	8.7%	0.0

Last 3 seasons WAR 3.2 · Next 3 projected WAR 0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

xwOBA vs90

FB Velo78

K%67

CompsHideki Okajima (age 33) · Grant Dayton (age 33) · Scott Sauerbeck (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 7886vR 95

ERA3.62

FIP3.86

K%22.6%

BB%7.7%

K-BB%14.9%

Proj IP51

Value2027 · WAR

Runs saved vs league avg · 51 IP

Grades · Statcast · Contract

Scouting Grades

STUF4545

CTRL5050

CMD5555

K†5555

Statcast Percentiles

FB Velo

p7896.5

Whiff%

p3322.9%

p6725.4%

xwOBA vs

p900.263

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	27	AA MLE	Midland RockHounds	24	21	121	505	100	43	14	88%	5.1	16.0%	9.4%	6.7%	4.0%	3.26	5.11	—
2021	27	AA RAW	Midland RockHounds	24	21	121	505	100	43	14	88%	5.1	19.8%	8.5%	11.3%	2.8%	3.26	4.01	—
2022	28	MIX MLE	2 levels	30	23	146	627	126	45	17	77%	4.9	18.1%	7.4%	10.7%	2.8%	4.98	4.06	+2.3
2022	28	MIX RAW	2 levels	30	23	146	627	126	45	17	77%	4.9	20.1%	7.2%	12.9%	2.7%	4.98	3.81	+2.8
2023	29	MIX MLE	2 levels	48	1	59	278	70	27	8	2%	1.2	21.3%	9.2%	12.1%	3.0%	3.81	4.12	—
2023	29	MIX RAW	2 levels	48	1	59	278	70	27	8	2%	1.2	25.2%	9.7%	15.5%	2.9%	3.81	3.86	—
2024	30	MIX MLE	2 levels	61	6	69	288	74	21	4	10%	1.1	23.8%	7.2%	16.6%	1.4%	2.36	2.79	+1.4
2024	30	MIX MLE	2 levels	61	6	69	288	74	21	4	10%	1.1	23.8%	7.2%	16.6%	1.4%	2.36	2.79	+1.4
2024	30	MIX RAW	2 levels	61	6	69	288	74	21	4	10%	1.1	25.7%	7.3%	18.4%	1.4%	2.36	2.62	+1.6
2025	31	MLB MLE	Milwaukee Brewers	72	0	66	268	68	19	6	0%	0.9	25.4%	7.1%	18.3%	2.1%	2.86	3.03	+1.2
2025	31	MLB MLE	Milwaukee Brewers	72	0	66	268	68	19	6	0%	0.9	25.4%	7.1%	18.3%	2.1%	2.86	3.03	+1.2
2025	31	MLB RAW	Milwaukee Brewers	72	0	66	268	68	19	6	0%	0.9	25.4%	7.1%	18.3%	2.2%	2.86	3.08	+1.2
2026	32	MIX MLE	2 levels	32	0	27	123	24	13	1	0%	0.9	17.8%	9.9%	8.0%	0.0%	3.95	2.85	+0.6
2026	32	MIX MLE	2 levels	32	0	27	123	24	13	1	0%	0.9	17.8%	9.9%	8.0%	0.0%	3.95	2.85	+0.6
2026	32	MIX RAW	2 levels	32	0	27	123	24	13	1	0%	0.9	19.5%	10.6%	8.9%	0.8%	3.95	3.25	+0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			146	11	174	751	160	57	15	8%	1.2	21.3%	7.6%	13.7%	2.0%	3.61	3.36	+2.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	MIL	49	0	51	215	49	17	5	0%	1.0	22.6%	7.7%	14.9%	2.4%	3.62	3.86	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	MIL	37	0	39	165	36	13	4	0%	1.1	21.7%	8.2%	13.5%	2.7%	3.95	4.16	+0.2
2029	35	MLB MLE	MIL	23	0	24	100	21	9	3	0%	1.0	20.7%	8.7%	12.0%	3.0%	4.28	4.50	+0.0
2030	36	MLB MLE	MIL	13	0	13	56	11	5	2	0%	1.0	19.7%	9.3%	10.4%	3.4%	4.63	4.87	-0.0
2028	34	MLB CTX	MIL	35	0	37	156	34	13	4	0%	1.1	21.7%	8.2%	13.5%	2.7%	3.95	4.16	+0.2
2029	35	MLB CTX	MIL	21	0	22	93	19	8	3	0%	1.0	20.7%	8.7%	12.0%	3.0%	4.28	4.50	+0.0
2030	36	MLB CTX	MIL	10	0	11	46	9	4	2	0%	1.1	19.7%	9.3%	10.4%	3.4%	4.63	4.87	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		212	11	244	1045	222	82	24	5%	1.2	21.2%	7.9%	13.4%	2.3%	3.77	3.54	+2.9
/ 200 IP	—	RAW		174	9	200	857	182	67	20	5%	1.1	21.2%	7.9%	13.4%	2.3%	3.77	3.54	+2.4
Career	—	MLE		267	51	489	2089	412	171	56	19%	1.8	19.7%	8.2%	11.5%	2.7%	3.70	3.94	+2.6
/ 200 IP	—	MLE		109	21	200	855	169	70	23	19%	1.8	19.7%	8.2%	11.5%	2.7%	3.70	3.94	+2.1

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.

2026 AAANashville Sounds · 20 IPFIP 2.74 → 2.85 (+0.11)K% 20.7% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.73%	—	×0.860	17.83%
BB% (unintentional) /BF	10.98%	—	×0.900	9.88%
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 2.74 → 2.85, 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 AAANashville Sounds · 7 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%	÷0.909	×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).

2023 AAAEl Paso Chihuahuas · 45 IPFIP 4.46 → 4.69 (+0.23)K% 21.8% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.82%	—	×0.860	18.76%
BB% (unintentional) /BF	9.55%	—	×0.900	8.59%
HR / BF /BF	3.64%	÷1.052	×1.100	3.80%

Result: FIP 4.46 → 4.69, 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 AASan Antonio Missions · 14 IPFIP 1.21 → 1.95 (+0.74)K% 37.9% → 30.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.93%	—	×0.810	30.72%
BB% (unintentional) /BF	10.34%	—	×1.100	11.38%
HR / BF /BF	0.00%	÷0.820	×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 64).

Result: FIP 1.21 → 1.95, 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 AAALas Vegas Aviators · 107 IPFIP 3.58 → 3.89 (+0.31)K% 23.1% → 20.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.11%	—	×0.880	20.34%
BB% (unintentional) /BF	6.67%	—	×1.050	7.00%
HR / BF /BF	2.89%	÷1.075	×1.100	2.96%

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 115).

Result: FIP 3.58 → 3.89, 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 AAMidland RockHounds · 121 IPFIP 4.03 → 5.11 (+1.08)K% 19.8% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.80%	—	×0.810	16.04%
BB% (unintentional) /BF	8.51%	—	×1.100	9.37%
HR / BF /BF	2.77%	÷0.838	×1.200	3.97%

Result: FIP 4.03 → 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).

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
Jared Koenig (OGILVIE)	—	—	3.86	22.6%	7.7%	2.4%	—	4.39	21.0%	12.5%	76	+0.53	—	—	—
Hideki Okajima L 2009 · 3.95 FIP	33	SU	3.95	20.5%	7.0%	3.1%	.268	4.27	15.5%	8.5%	46	+0.32	3.05	238	71
Grant Dayton L 2021 · 4.00 FIP	33	SU	4.00	23.0%	8.2%	3.3%	.325	3.80	23.2%	13.5%	49	-0.20	1.63	277	68
Scott Sauerbeck L 2005 · 3.75 FIP	33	SU	3.75	22.3%	8.9%	2.5%	.298	5.05	14.0%	0.0%	25	+1.30	2.79	386	68
Brian Moran L 2022 · 4.20 FIP	33	SU	4.20	21.7%	7.0%	3.7%	.304	3.72	21.5%	14.5%	152	-0.48	1.80	421	68
Heriberto Ruelas L 2015 · 2.95 FIP	33	SU	2.95	19.1%	7.3%	1.0%	.352	3.57	16.2%	8.5%	89	+0.62	2.95	117	67
Adam Liberatore L 2018 · 4.28 FIP	31	SU	4.28	18.6%	9.1%	2.9%	.354	—	—	—	—	—	2.38	124	67
Kelly Wunsch L 2005 · 3.82 FIP	33	SU	3.82	21.0%	11.4%	1.9%	.261	—	—	—	—	—	3.36	175	67
Juan Pablo Perez L 2013 · 3.68 FIP	34	SU	3.68	25.2%	11.5%	2.3%	.250	3.68	26.5%	11.2%	51	-0.00	1.75	104	66
Zach Phillips L 2019 · 3.67 FIP	32	SU	3.67	19.1%	8.5%	2.0%	.355	—	—	—	—	—	2.33	202	66
Ryan Sherriff L 2023 · 3.78 FIP	33	SU	3.78	21.9%	11.0%	2.1%	.297	—	—	—	—	—	2.96	245	65
Doug Creek L 2002 · 4.99 FIP	33	SU	4.99	21.4%	12.6%	3.8%	.288	5.79	17.1%	7.9%	36	+0.80	4.48	277	63
Anthony Gose L 2024 · 3.78 FIP	33	SU	3.78	26.4%	11.3%	2.7%	.279	5.07	21.5%	10.1%	97	+1.29	3.78	233	63
Alejandro Soto L 2019 · 4.03 FIP	33	SW	4.03	17.1%	6.9%	2.7%	.376	—	—	—	—	—	3.96	280	62
Joey Eischen L 2003 · 4.00 FIP	33	SU	4.00	18.1%	5.4%	3.2%	.309	3.44	19.6%	10.3%	69	-0.56	2.13	294	62
Brandon Mann L 2017 · 4.24 FIP	33	SU	4.24	19.8%	11.3%	2.5%	.286	3.59	17.8%	6.4%	52	-0.65	3.59	190	62
Tim Byrdak L 2007 · 3.25 FIP	33	SU	3.25	24.6%	11.1%	1.5%	.280	4.96	20.1%	7.6%	155	+1.71	2.85	320	61
Colt Hynes L 2017 · 3.75 FIP	32	SW	3.75	14.1%	4.6%	2.3%	.306	—	—	—	—	—	3.42	169	61
Pedro Borbón L 2001 · 3.90 FIP	33	SU	3.90	20.7%	4.1%	3.7%	.258	4.57	21.6%	14.3%	50	+0.67	2.26	264	61
Francisley Bueno L 2014 · 3.61 FIP	33	SU	3.61	14.1%	3.5%	2.3%	.289	3.94	13.6%	6.9%	138	+0.33	2.43	188	61
Marlon Arias L 2017 · 3.73 FIP	32	SU	3.73	17.2%	7.7%	2.0%	.443	4.83	19.8%	8.6%	74	+1.10	3.73	154	61

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	1.5	43	21.4%	8.5%	0.89	3.76
David Carpenter ('19)	1.1	43	23.5%	8.4%	0.92	3.69
Scott Oberg ('19)	1.3	51	21.5%	9.3%	0.91	3.85
Blaine Hardy ('21)	1.5	48	18.5%	8.3%	0.99	3.78
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*
Mark Dewey ('90-'96, 3 WAR*)	1.2	42	18.7%*	9.6%*	0.80*	3.89*
Mike Perez ('90-'97, 3 WAR*)	1.7	58	18.5%*	8.2%*	0.88*	3.86*