Kenten Egbert

P South Bend Cubs

Age 26 RHP 6'3" / 205 lbs A+ peak 0.3 · 2028

Overview

A+PROSPECT

ETA2029MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	ACHC	23	16	98	3.04	3.02	26.5%	8.1%	—	K 19.6% · BB 9.6% · FIP 4.26
2025	24	A+CHC	25	17	101	4.26	3.55	13.8%	5.8%	—	K 10.6% · BB 6.6% · FIP 4.04
2026	25	MIX2 levels	20	2	32	7.31	5.04	14.7%	9.2%	—	K 11.6% · BB 9.5% · FIP 5.28
2027PROJ	26	MLBCHC	—	—	0	5.48	5.48	10.0%	9.3%	—
2028PROJ37% MLB	27	MLBCHC	23	0	24	5.38	5.39	11.2%	9.2%	-0.2
2029PROJ59% MLB	28	MLBCHC	31	0	33	5.35	5.39	11.9%	9.2%	-0.3

Next 3 projected WAR -0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff25Control55Command35

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 98%

CompsAlfonso Sanchez (age 27) · Dennis O'Grady (age 26) · Mike Connolly (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 137129vR 121

ERA5.48

FIP5.48

K%10.0%

BB%9.3%

K-BB%0.7%

Proj IP60

Value2027 · WAR

Runs saved vs league avg · 60 IP

Grades · Contract

Scouting Grades

STUF2525

CTRL5555

CMD3535

K†3030

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)
2024	23	A MLE	Myrtle Beach Pelicans	23	16	98	393	104	32	8	70%	4.2	19.6%	9.6%	10.0%	2.9%	3.04	4.26	—
2024	23	A MLE	Myrtle Beach Pelicans	23	16	98	393	104	32	8	70%	4.2	19.6%	9.6%	10.0%	2.9%	3.04	4.26	—
2024	23	A RAW	Myrtle Beach Pelicans	23	16	98	393	104	32	8	70%	4.2	26.5%	8.1%	18.3%	2.0%	3.04	3.02	—
2025	24	A+ MLE	South Bend Cubs	25	17	101	434	60	25	7	68%	4.1	10.6%	6.6%	4.0%	1.8%	4.26	4.04	—
2025	24	A+ MLE	South Bend Cubs	25	17	101	434	60	25	7	68%	4.1	10.6%	6.6%	4.0%	1.8%	4.26	4.04	—
2025	24	A+ RAW	South Bend Cubs	25	17	101	434	60	25	7	68%	4.1	13.8%	5.8%	8.1%	1.6%	4.26	3.55	—
2026	25	MIX MLE	2 levels	20	2	32	163	24	15	5	10%	1.6	11.6%	9.5%	2.0%	3.6%	7.31	5.28	—
2026	25	MIX MLE	2 levels	20	2	32	163	24	15	5	10%	1.6	11.6%	9.5%	2.0%	3.6%	7.31	5.28	—
2026	25	MIX RAW	2 levels	20	2	32	163	24	15	5	10%	1.6	14.7%	9.2%	5.5%	3.1%	7.31	5.04	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	CHC	—	—	0	—	—	—	—	—	—	10.0%	9.3%	0.7%	3.0%	5.48	5.48	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	CHC	63	0	67	281	31	26	9	0%	1.1	11.2%	9.2%	2.0%	3.1%	5.38	5.39	-0.6
2029	28	MLB MLE	CHC	54	0	57	239	28	22	8	0%	1.1	11.9%	9.2%	2.7%	3.2%	5.35	5.39	-0.5
2030	29	MLB MLE	CHC	49	0	51	216	26	20	7	0%	1.0	12.2%	9.4%	2.8%	3.3%	5.40	5.46	-0.5
2031	30	MLB MLE	CHC	47	0	50	209	29	18	7	0%	1.1	14.1%	8.8%	5.2%	3.5%	5.35	5.34	-0.4
2032	31	MLB MLE	CHC	42	0	44	186	25	17	7	0%	1.1	13.7%	9.2%	4.5%	3.7%	5.47	5.54	-0.5
2028	27	MLB CTX	CHC	23	0	24	101	11	9	3	0%	1.0	11.2%	9.2%	2.0%	3.1%	5.38	5.39	-0.2
2029	28	MLB CTX	CHC	31	0	33	139	17	13	4	0%	1.1	11.9%	9.2%	2.7%	3.2%	5.35	5.39	-0.3
2030	29	MLB CTX	CHC	34	0	36	152	18	14	5	0%	1.1	12.2%	9.4%	2.8%	3.3%	5.40	5.46	-0.4
2031	30	MLB CTX	CHC	37	0	39	165	23	15	6	0%	1.1	14.1%	8.8%	5.2%	3.5%	5.35	5.34	-0.3
2032	31	MLB CTX	CHC	35	0	37	156	21	14	6	0%	1.1	13.7%	9.2%	4.5%	3.7%	5.47	5.54	-0.4
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		161	0	169	715	91	65	24	0%	1.1	12.7%	9.1%	3.6%	3.4%	5.39	5.05	-1.0
/ 200 IP	—	RAW		190	0	200	844	108	77	28	0%	1.0	12.7%	9.1%	3.6%	3.4%	5.39	5.05	-1.2
Career	—	MLE		68	35	231	990	142	82	25	51%	3.4	14.3%	8.3%	6.1%	2.5%	4.17	4.33	-0.1
/ 200 IP	—	MLE		59	30	200	857	123	71	22	51%	3.4	14.3%	8.3%	6.1%	2.5%	4.17	4.33	-0.0

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 A+South Bend Cubs · 24 IPFIP 3.48 → 4.20 (+0.73)K% 17.9% → 13.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.86%	—	×0.770	13.75%
BB% (unintentional) /BF	7.14%	—	×1.150	8.21%
HR / BF /BF	1.79%	÷1.000	×1.250	2.23%

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 3.48 → 4.20, 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 AAAIowa Cubs · 8 IPFIP 7.41 → 7.65 (+0.24)K% 7.8% → 6.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	7.84%	—	×0.860	6.75%
BB% (unintentional) /BF	13.73%	—	×0.900	12.35%
HR / BF /BF	5.88%	÷1.000	×1.100	6.47%

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 7.41 → 7.65, 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+South Bend Cubs · 101 IPFIP 3.55 → 4.04 (+0.49)K% 13.8% → 10.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.82%	—	×0.770	10.65%
BB% (unintentional) /BF	5.76%	—	×1.150	6.62%
HR / BF /BF	1.61%	÷1.106	×1.250	1.82%

Result: FIP 3.55 → 4.04, 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 AMyrtle Beach Pelicans · 98 IPFIP 3.01 → 4.26 (+1.25)K% 26.5% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.46%	—	×0.740	19.58%
BB% (unintentional) /BF	8.14%	—	×1.180	9.61%
HR / BF /BF	2.04%	÷0.908	×1.300	2.91%

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 82).

Result: FIP 3.01 → 4.26, 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
Kenten Egbert (OGILVIE)	—	—	5.48	10.0%	9.3%	3.0%	—	5.41	11.7%	2.4%	174	-0.07	—	—	—
Alfonso Sanchez R 2015 · 4.96 FIP	27	SP-	4.96	12.5%	9.1%	3.2%	.346	4.85	14.0%	5.3%	138	-0.11	4.51	224	85
Dennis O'Grady R 2015 · 4.95 FIP	26	SW	4.95	13.5%	11.0%	2.9%	.339	—	—	—	—	—	3.62	157	84
Mike Connolly R 2018 · 5.13 FIP	26	SW	5.13	13.2%	9.4%	3.5%	.321	—	—	—	—	—	3.94	328	81
Josh Roeder R 2019 · 4.71 FIP	26	SW	4.71	15.1%	8.7%	3.3%	.264	—	—	—	—	—	4.71	175	79
Bryce Morrow R 2015 · 4.31 FIP	27	SP-	4.31	12.8%	7.9%	2.4%	.316	5.44	10.1%	-0.2%	50	+1.13	4.31	125	79
Nolan Sanburn R 2017 · 4.55 FIP	26	SW	4.55	15.0%	10.4%	2.5%	.310	—	—	—	—	—	3.82	169	78
Tyler Yates R 2004 · 4.47 FIP	26	SW	4.47	15.4%	9.6%	2.6%	.333	3.64	22.5%	13.5%	116	-0.83	3.23	248	78
Cooper Adams R 2024 · 5.42 FIP	24	SW	5.42	13.0%	12.2%	3.4%	.275	4.32	21.7%	10.4%	141	-1.10	3.05	221	78
Jake McCasland R 2018 · 4.34 FIP	26	SW	4.34	12.8%	9.5%	2.0%	.313	—	—	—	—	—	3.07	367	77
Wilton Lopez R 2009 · 5.62 FIP	26	SW	5.62	9.3%	8.2%	4.1%	.368	2.79	19.5%	16.6%	204	-2.83	2.51	299	76
Victor Santos R 2003 · 5.99 FIP	26	SP-	5.99	12.8%	12.8%	4.3%	.293	4.38	15.4%	7.7%	411	-1.61	4.09	602	76
Adam Panayotovich R 2017 · 5.45 FIP	25	SP-	5.45	9.6%	9.0%	3.7%	.375	—	—	—	—	—	3.50	121	76
Dakota Hawkins R 2024 · 4.31 FIP	24	SW	4.31	16.3%	8.9%	2.7%	.277	4.32	19.4%	10.4%	102	+0.01	3.50	186	76
Luis Niebla R 2017 · 5.12 FIP	26	SP-	5.12	11.6%	13.2%	2.4%	.336	—	—	—	—	—	3.37	156	76
Jared Fernandez R 2001 · 4.66 FIP	29	SW	4.66	8.8%	10.5%	1.8%	.267	3.95	14.0%	5.6%	89	-0.71	3.57	101	75
Colby Morris R 2022 · 5.76 FIP	25	SW	5.76	16.2%	11.8%	4.6%	.268	—	—	—	—	—	4.11	105	75
Donovan Hand R 2013 · 4.72 FIP	27	SW	4.72	12.9%	7.0%	3.3%	.279	4.30	11.1%	6.8%	97	-0.42	4.30	305	75
Drasen Johnson R 2016 · 4.70 FIP	24	SW	4.70	9.6%	5.7%	3.1%	.325	—	—	—	—	—	4.70	110	75
Cullen Kafka R 2023 · 4.95 FIP	24	SW	4.95	14.2%	12.1%	2.8%	.330	—	—	—	—	—	3.64	148	75
Colin Bates R 2015 · 4.57 FIP	27	SP-	4.57	10.5%	6.5%	2.8%	.301	—	—	—	—	—	4.57	111	75

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	1.6	55	12.0%	9.2%	1.27	5.40
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Mike Lincoln ('10)	1.9	54	14.1%	8.9%	1.32	5.33
Matt Whiteside ('05)	2.0	58	14.5%	8.8%	1.15	5.23
Chuck Hartenstein ('66-'77, -1 WAR*)	1.5	59	13.7%*	7.2%*	1.50*	5.28*
Greg Booker ('83-'90, -1 WAR*)	1.3	53	13.3%*	10.2%*	1.07*	4.51*
Russ Swan ('89-'94, -2 WAR*)	1.3	89	12.3%*	9.9%*	1.13*	5.09*