Corey Knebel

P Salt Lake Bees

Age 35 RHP 6'3" / 225 lbs AAA peak 0.2 · 2027

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2021	29	MIX2 levels	33	5	31	2.30	2.17	33.1%	7.3%	0.9	K 29.7% · BB 7.9% · FIP 2.64
2022	30	MLBPHI	46	0	45	3.43	4.11	21.1%	12.9%	0.2
2024	32	MIX3 levels	18	1	15	11.74	5.64	21.7%	14.5%	—	K 21.9% · BB 11.5% · FIP 5.18
2025	33	No MLB games played
2026	34	No MLB games played
2027PROJ	35	MLBLAA	5	0	5	4.29	4.31	24.1%	9.6%	0.0
2028PROJMLE	36	MLBLAA	—	—	0	4.53	4.68	23.1%	10.2%	—
2029PROJMLE	37	MLBLAA	—	—	0	4.86	5.08	22.0%	10.8%	—

Last 3 seasons WAR 1.1 · Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2022

FB Velo65

xwOBA vs57

K%43

CompsYoshihisa Hirano (age 35) · Hirokazu Sawamura (age 34) · Neil Wagner (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 110102vR 94

ERA4.29

FIP4.31

K%24.1%

BB%9.6%

K-BB%14.6%

Proj IP52

Value2027 · WAR

Runs saved vs league avg · 52 IP

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL3535

CMD4545

K†6060

Statcast Percentiles

FB Velo

p6595.6

Whiff%

p6527.6%

p4321.2%

xwOBA vs

p570.305

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)
2014	22	MLB MLE	Detroit Tigers	8	0	9	39	11	3	0	0%	1.1	28.2%	7.7%	20.5%	0.0%	6.23	1.69	+0.3
2014	22	MLB RAW	Detroit Tigers	8	0	9	39	11	3	0	0%	1.1	28.2%	7.7%	20.5%	0.0%	6.23	1.60	+0.3
2015	23	MIX MLE	2 levels	64	0	66	274	80	22	9	0%	1.0	28.2%	8.1%	20.1%	3.2%	3.56	3.52	+0.8
2015	23	MIX RAW	2 levels	64	0	66	274	80	22	9	0%	1.0	29.2%	8.0%	21.2%	3.3%	3.56	3.45	+0.9
2016	24	MIX MLE	3 levels	48	3	49	203	58	17	3	6%	1.0	26.2%	9.0%	17.2%	2.0%	3.47	3.10	+0.9
2016	24	MIX RAW	3 levels	48	3	49	203	58	17	3	6%	1.0	28.6%	8.4%	20.2%	1.5%	3.47	2.57	+1.2
2017	25	MLB MLE	Milwaukee Brewers	76	0	76	309	126	35	6	0%	1.0	40.8%	11.3%	29.4%	1.8%	1.78	2.11	+2.2
2017	25	MLB RAW	Milwaukee Brewers	76	0	76	309	126	35	6	0%	1.0	40.8%	11.3%	29.4%	1.9%	1.78	2.19	+2.2
2018	26	MIX MLE	3 levels	61	0	59	238	93	24	7	0%	1.0	39.5%	9.9%	29.6%	3.0%	3.36	2.66	+1.3
2018	26	MIX RAW	3 levels	61	0	59	238	93	24	7	0%	1.0	39.1%	10.1%	29.0%	2.9%	3.36	2.71	+1.3
2020	28	MLB MLE	Milwaukee Brewers	15	0	13	62	15	8	4	0%	0.9	24.2%	12.9%	11.3%	6.1%	6.07	6.06	-0.2
2020	28	MLB RAW	Milwaukee Brewers	15	0	13	62	15	8	4	0%	0.9	24.2%	12.9%	11.3%	6.5%	6.07	6.55	-0.3
2021	29	MIX MLE	2 levels	33	5	31	124	41	9	2	15%	0.9	29.7%	7.9%	21.8%	1.9%	2.30	2.64	+0.7
2021	29	MIX RAW	2 levels	33	5	31	124	41	9	2	15%	0.9	33.1%	7.3%	25.8%	1.6%	2.30	2.17	+0.9
2022	30	MLB MLE	Philadelphia Phillies	46	0	45	194	41	25	4	0%	1.0	21.1%	12.9%	8.2%	1.9%	3.43	4.00	+0.3
2022	30	MLB RAW	Philadelphia Phillies	46	0	45	194	41	25	4	0%	1.0	21.1%	12.9%	8.2%	2.1%	3.43	4.11	+0.2
2024	32	MIX MLE	3 levels	18	1	15	83	18	12	3	6%	0.9	21.9%	11.5%	10.4%	4.5%	11.74	5.18	—
2024	32	MIX MLE	3 levels	18	1	15	83	18	12	3	6%	0.9	21.9%	11.5%	10.4%	4.5%	11.74	5.18	—
2024	32	MIX RAW	3 levels	18	1	15	83	18	12	3	6%	0.9	21.7%	14.5%	7.2%	3.6%	11.74	5.64	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			312	4	307	1282	407	130	34	1%	1.0	31.7%	10.1%	21.6%	2.7%	3.26	3.16	+5.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	35	MLB	LAA	5	0	5	21	5	2	1	0%	1.0	24.1%	9.6%	14.6%	3.0%	4.29	4.31	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	36	MLB MLE	LAA	36	0	38	159	37	16	5	0%	1.0	23.1%	10.2%	13.0%	3.4%	4.53	4.68	-0.1
2029	37	MLB MLE	LAA	26	0	28	116	26	13	4	0%	1.1	22.0%	10.8%	11.2%	3.8%	4.86	5.08	-0.2
2028	36	MLB CTX	LAA	—	—	0	—	—	—	—	—	—	23.1%	10.2%	13.0%	3.4%	4.53	4.68	—
2029	37	MLB CTX	LAA	—	—	0	—	—	—	—	—	—	22.0%	10.8%	11.2%	3.8%	4.86	5.08	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		312	4	307	1284	407	130	34	1%	1.0	31.7%	10.1%	21.6%	2.7%	3.26	3.16	+5.1
/ 200 IP	—	RAW		203	3	200	836	265	85	22	1%	1.0	31.7%	10.1%	21.6%	2.7%	3.26	3.16	+3.3
Career	—	MLE		369	9	363	1526	472	154	39	2%	1.0	31.0%	10.1%	20.9%	2.6%	3.52	3.18	+4.8
/ 200 IP	—	MLE		203	5	200	840	260	85	22	2%	1.0	31.0%	10.1%	20.9%	2.6%	3.52	3.18	+2.6

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.

2024 AAASalt Lake Bees · 10 IPFIP 4.56 → 5.18 (+0.62)K% 25.5% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.45%	—	×0.860	21.89%
BB% (unintentional) /BF	12.73%	—	×0.900	11.45%
HR / BF /BF	3.64%	÷0.886	×1.100	4.51%

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 77).

Result: FIP 4.56 → 5.18, 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 AAAOklahoma City Dodgers · 6 IPFIP -0.39 → 0.12 (+0.51)K% 47.8% → 42.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	47.83%	—	×0.880	42.09%
BB% (unintentional) /BF	4.35%	—	×1.050	4.57%
HR / BF /BF	0.00%	÷1.016	×1.100	0.00%

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 103).

Result: FIP -0.39 → 0.12, 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 AAAColorado Springs Sky Sox · 14 IPFIP 1.36 → 1.71 (+0.35)K% 30.4% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.43%	—	×0.880	26.78%
BB% (unintentional) /BF	6.52%	—	×1.050	6.85%
HR / BF /BF	0.00%	÷0.973	×1.100	0.00%

Result: FIP 1.36 → 1.71, 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 AAAColorado Springs Sky Sox · 15 IPFIP 2.26 → 2.86 (+0.61)K% 33.8% → 29.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.85%	—	×0.880	29.78%
BB% (unintentional) /BF	9.23%	—	×1.050	9.69%
HR / BF /BF	1.54%	÷0.886	×1.100	1.91%

Result: FIP 2.26 → 2.86, 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
Corey Knebel (OGILVIE)	—	—	4.31	24.1%	9.6%	3.0%	—	4.85	22.7%	12.2%	65	+0.54	—	—	—
Yoshihisa Hirano R 2019 · 3.72 FIP	35	SU	3.72	26.2%	8.6%	3.2%	.303	5.02	17.5%	4.8%	12	+1.30	3.45	132	76
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	74
Neil Wagner R 2017 · 3.11 FIP	33	SU	3.11	20.7%	8.6%	1.2%	.257	—	—	—	—	—	3.11	135	68
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	67
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	65
Brendan Donnelly R 2006 · 4.21 FIP	35	SU	4.21	19.1%	9.0%	2.9%	.260	3.19	18.6%	10.1%	60	-1.02	2.23	385	65
Toby Borland R 2004 · 4.28 FIP	35	SU	4.28	20.9%	8.1%	3.5%	.259	—	—	—	—	—	2.92	248	64
Jean Machi R 2017 · 4.12 FIP	35	SU	4.12	18.6%	6.6%	3.2%	.285	—	—	—	—	—	2.16	306	64
Juan Sandoval R 2016 · 3.24 FIP	35	SU	3.24	18.2%	10.2%	0.7%	.288	4.40	16.3%	9.1%	116	+1.16	3.24	225	64
Leo Rosales R 2015 · 3.99 FIP	34	SU	3.99	18.1%	10.8%	1.9%	.261	4.24	7.8%	-0.4%	22	+0.25	3.85	130	63
Hector Navarro R 2015 · 4.35 FIP	35	SU	4.35	15.0%	5.4%	3.3%	.281	3.00	15.2%	9.0%	81	-1.35	2.30	126	62
Brian Schlitter R 2021 · 4.70 FIP	35	SU	4.70	14.9%	9.1%	3.1%	.318	—	—	—	—	—	3.27	300	60
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	60
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	59
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	58
Fernando Rodriguez Jr. R 2019 · 5.11 FIP	35	SW	5.11	25.0%	11.2%	4.9%	.312	—	—	—	—	—	3.34	335	58
Kazuhiro Sasaki R 2003 · 3.30 FIP	35	SU	3.30	19.3%	8.7%	1.3%	.274	—	—	—	—	—	2.76	223	57
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	57
Rodolfo Aguirre R 2019 · 4.50 FIP	34	SU	4.50	21.3%	5.1%	4.7%	.244	—	—	—	—	—	3.39	212	57
Chris Nichting R 2001 · 4.11 FIP	35	SU	4.11	21.2%	3.7%	4.2%	.351	4.67	16.6%	13.3%	36	+0.56	4.11	103	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	2.1	47	29.4%	10.8%	1.10	3.60
Mychal Givens ('23)	2.3	58	28.2%	10.0%	1.05	3.47
Mike Gonzalez ('03-'13, 7 WAR*)	2.2	49	29.1%*	10.7%*	0.94*	3.18*
Cody Allen ('19)	2.3	58	30.5%	9.9%	1.07	3.14
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*
Al Hrabosky ('70-'82, 10 WAR*)	3.6	72	26.7%*	10.1%*	0.98*	3.50*