Jeff Belge

P Tennessee Smokies

Age 29 LHP 6'5" / 225 lbs AA

Overview

AAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	25	AATB	41	52	3.48	2.54	32.3%	13.5%	—	K 26.2% · BB 14.9% · FIP 3.30
2024	26	AATennessee Smo…	38	48	3.40	3.33	24.0%	11.2%	—	K 19.4% · BB 12.3% · FIP 4.20
2027PROJ	29	MLBCHC	1	1	4.58	4.58	21.9%	10.5%	-0.0
2028PROJ31% MLB	30	MLBCHC	7	7	4.66	4.73	21.7%	10.7%	-0.0

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

Contract

No contract data on file.

CompsRaul Valdes (age 32) · Colton Johnson (age 26) · Nick Hagadone (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 104112vR 120

ERA4.58

FIP4.58

K%21.9%

BB%10.5%

K-BB%11.4%

Proj IP28

Value2027 · WAR

Runs saved vs league avg · 28 IP

Grades · Contract

Scouting Grades

K†5050

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)
2019	21	MIX MLE	2 levels	6	0	6	26	5	6	0	0%	1.1	19.2%	23.1%	-3.8%	0.0%	2.84	4.40	—
2019	21	MIX RAW	2 levels	6	0	6	26	5	6	0	0%	1.1	19.2%	23.1%	-3.8%	0.0%	2.84	4.36	—
2021	23	A+ MLE	Great Lakes Loons	31	0	43	202	63	33	4	0%	1.4	24.0%	18.8%	5.2%	2.7%	5.61	4.91	—
2021	23	A+ RAW	Great Lakes Loons	31	0	43	202	63	33	4	0%	1.4	31.2%	16.3%	14.9%	2.0%	5.61	3.68	—
2022	24	A+ MLE	Great Lakes Loons	29	1	32	136	50	17	2	3%	1.1	28.3%	14.4%	13.9%	1.8%	3.66	3.53	—
2022	24	A+ RAW	Great Lakes Loons	29	1	32	136	50	17	2	3%	1.1	36.8%	12.5%	24.3%	1.5%	3.66	2.38	—
2023	25	AA MLE	Montgomery Biscuits	41	0	52	229	74	31	2	0%	1.3	26.2%	14.9%	11.3%	1.0%	3.48	3.30	—
2023	25	AA RAW	Montgomery Biscuits	41	0	52	229	74	31	2	0%	1.3	32.3%	13.5%	18.8%	0.9%	3.48	2.54	—
2024	26	AA MLE	Tennessee Smokies	38	0	48	196	47	22	3	0%	1.3	19.4%	12.3%	7.1%	2.2%	3.40	4.20	—
2024	26	AA MLE	Tennessee Smokies	38	0	48	196	47	22	3	0%	1.3	19.4%	12.3%	7.1%	2.2%	3.40	4.20	—
2024	26	AA RAW	Tennessee Smokies	38	0	48	196	47	22	3	0%	1.3	24.0%	11.2%	12.8%	1.5%	3.40	3.33	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	CHC	1	0	1	4	1	0	0	0%	1.0	21.9%	10.5%	11.4%	3.0%	4.58	4.58	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	CHC	21	0	22	95	21	10	3	0%	1.1	21.7%	10.7%	11.1%	3.2%	4.66	4.73	-0.0
2028	30	MLB CTX	CHC	7	0	7	30	6	3	1	0%	1.0	21.7%	10.7%	11.1%	3.2%	4.66	4.73	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		7	0	7	30	6	3	1	0%	1.0	21.7%	10.7%	11.1%	3.2%	4.66	4.35	+0.0
/ 200 IP	—	RAW		190	0	200	844	171	86	29	0%	1.1	21.7%	10.7%	11.1%	3.2%	4.66	4.35	+0.5
Career	—	MLE		145	1	181	789	190	122	14	1%	1.2	24.1%	15.4%	8.6%	1.8%	3.98	4.01	-0.0
/ 200 IP	—	MLE		160	1	200	872	210	135	16	1%	1.2	24.1%	15.4%	8.6%	1.8%	3.98	4.01	-0.4

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.

2024 AATennessee Smokies · 48 IPFIP 3.34 → 4.20 (+0.87)K% 24.0% → 19.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.98%	—	×0.810	19.42%
BB% (unintentional) /BF	11.22%	—	×1.100	12.35%
HR / BF /BF	1.53%	÷0.854	×1.200	2.15%

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 71).

Result: FIP 3.34 → 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).

2023 AAMontgomery Biscuits · 52 IPFIP 2.57 → 3.30 (+0.74)K% 32.3% → 26.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.31%	—	×0.810	26.17%
BB% (unintentional) /BF	13.54%	—	×1.100	14.89%
HR / BF /BF	0.87%	÷1.087	×1.200	0.96%

Result: FIP 2.57 → 3.30, 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 A+Great Lakes Loons · 32 IPFIP 2.39 → 3.53 (+1.14)K% 36.8% → 28.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.76%	—	×0.770	28.31%
BB% (unintentional) /BF	12.50%	—	×1.150	14.37%
HR / BF /BF	1.47%	÷1.013	×1.250	1.82%

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 103).

Result: FIP 2.39 → 3.53, 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).

2021 A+Great Lakes Loons · 43 IPFIP 3.62 → 4.91 (+1.29)K% 31.2% → 24.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.19%	—	×0.770	24.01%
BB% (unintentional) /BF	16.34%	—	×1.150	18.79%
HR / BF /BF	1.98%	÷0.930	×1.250	2.66%

Result: FIP 3.62 → 4.91, 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).

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
Jeff Belge (OGILVIE)	—	—	4.58	21.9%	10.5%	3.0%	—	4.73	21.7%	11.1%	22	+0.15	—	—	—
Raul Valdes L 2010 · 4.02 FIP	32	SU	4.02	21.4%	9.9%	2.7%	.301	3.14	27.4%	22.5%	78	-0.88	2.29	160	87
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	82
Nick Hagadone L 2015 · 3.65 FIP	29	SU	3.65	22.6%	8.9%	2.4%	.329	3.74	22.6%	13.3%	33	+0.09	2.97	141	81
Edward Paredes L 2016 · 3.47 FIP	29	SU	3.47	24.1%	13.0%	1.4%	.225	3.55	23.7%	14.0%	86	+0.08	2.36	130	81
Jeff Ibarra L 2017 · 3.64 FIP	29	SU	3.64	18.1%	7.0%	2.1%	.342	2.85	20.6%	17.2%	29	-0.79	2.85	101	80
Clay Rapada L 2011 · 4.34 FIP	30	SU	4.34	26.1%	10.1%	3.9%	.268	3.00	24.5%	14.2%	38	-1.34	3.00	120	80
Andrew Barbosa L 2017 · 4.67 FIP	29	SU	4.67	20.2%	9.6%	3.8%	.301	—	—	—	—	—	2.70	175	80
Jose Meraz L 2017 · 4.34 FIP	29	SU	4.34	16.4%	10.3%	2.4%	.282	3.80	10.5%	-2.0%	30	-0.54	3.78	110	80
Josh Smoker L 2018 · 3.66 FIP	29	SU	3.66	22.1%	8.4%	2.5%	.318	6.58	14.2%	3.4%	14	+2.92	2.71	230	80
Arturo Barradas L 2017 · 3.42 FIP	29	SU	3.42	18.1%	7.0%	1.8%	.288	3.24	16.1%	9.5%	34	-0.18	3.24	163	79
Ryan Verdugo L 2015 · 3.61 FIP	28	SU	3.61	19.8%	10.8%	1.5%	.281	3.36	22.7%	17.3%	82	-0.25	3.36	153	79
Matt Thornton L 2006 · 3.43 FIP	29	SU	3.43	21.6%	7.5%	2.2%	.263	2.61	27.2%	20.5%	196	-0.82	1.71	663	79
Darin Downs L 2014 · 3.78 FIP	29	SU	3.78	18.2%	11.5%	1.4%	.255	4.06	12.9%	8.7%	16	+0.28	2.83	107	78
Sammy Solís L 2018 · 4.39 FIP	29	SU	4.39	24.9%	9.6%	4.0%	.330	4.05	26.2%	17.3%	23	-0.34	2.51	190	78
Colt Hynes L 2013 · 4.76 FIP	28	SU	4.76	15.5%	8.3%	3.5%	.361	3.49	19.3%	12.8%	96	-1.27	3.42	169	77
Keith Hessler L 2018 · 4.96 FIP	29	SU	4.96	19.8%	13.3%	3.4%	.348	—	—	—	—	—	3.31	228	77
Juan Pablo Perez L 2007 · 5.32 FIP	28	SU	5.32	17.5%	14.0%	3.5%	.324	—	—	—	—	—	1.75	104	77
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	76
Mike Zagurski L 2012 · 4.48 FIP	29	SU	4.48	20.9%	11.7%	3.0%	.305	—	—	—	—	—	2.94	120	75
Yuki Matsui L 2024 · 3.63 FIP	28	SU	3.63	26.8%	8.9%	3.0%	.242	4.25	23.9%	12.6%	140	+0.62	3.63	203	74

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	0.3	25	21.8%	10.6%	1.18	4.62
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Manny Acosta ('12)	1.2	41	20.5%	10.9%	1.09	3.99
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*