Josh Knoth

P Wisconsin Timber Rattlers

Age 21 RHP 6'1" / 190 lbs A+ Svc 0.0 · Ctrl thru 2033 peak 0.9 · 2030

Overview

A+PROSPECTMiLBFA 2034

OGV OFP40OGV rank#226ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	18	ACarolina Mudc…	21	21	84	4.48	3.33	26.6%	11.1%	—	K 19.7% · BB 13.1% · FIP 4.35
2026	20	MIX3 levels	22	20	88	4.11	3.80	23.8%	9.6%	—	K 18.0% · BB 10.4% · FIP 4.89
2027PROJ	21	MLBMIL	—	—	0	4.90	4.90	19.9%	10.7%	—
2028PROJ49% MLB	22	MLBMIL	7	7	35	4.78	4.69	21.6%	9.8%	0.3
2029PROJ73% MLB	23	MLBMIL	10	10	51	4.58	4.48	22.6%	9.1%	0.6

Next 3 projected WAR 0.9Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2033Service0.0First FA2034

2027MiLB2028Pre-Arb$0.8M2029Pre-Arb$0.8M2030Pre-Arb$0.8M2031Arb-1$2M2032Arb-2$3M2033Arb-3$4M

Career WAR0.0 WAR median (P10 -0.5 / P90 12, comp-based) · star 2% · didn't stick 81%

CompsJosé López (age 21) · Chih-Jung Liu (age 22) · Tanner Burns (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 126118vR 110

ERA4.90

FIP4.90

K%19.9%

BB%10.7%

K-BB%9.2%

Proj IP57

Value2027 · WAR

Runs saved vs league avg · 57 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$21M ctrl surplus

Contract

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status MiLB

MLB Debut 2028

Service 0 yrs (est)

Team Control Through 2033

First FA Year 2034

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2028
2028	Pre-Arb	$0.8M	+0.3	$1M	+$0.4M
2029	Pre-Arb	$0.8M	+0.6	$2M	+$1M
2030	Pre-Arb	$0.8M	+0.8	$3M	+$2M
2031	Arb-1	$2M	+0.8	$2M	+$1M
2032	Arb-2	$3M	+0.8	$2M	+$0.2M
2033	Arb-3	$4M	+0.8	$2M	+$0.0M (cut)
Totals		$8M		$12M	+$5M

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	18	A MLE	Carolina Mudcats	21	21	84	361	96	40	7	100%	4.0	19.7%	13.1%	6.6%	2.3%	4.48	4.35	—
2024	18	A MLE	Carolina Mudcats	21	21	84	361	96	40	7	100%	4.0	19.7%	13.1%	6.6%	2.3%	4.48	4.35	—
2024	18	A RAW	Carolina Mudcats	21	21	84	361	96	40	7	100%	4.0	26.6%	11.1%	15.5%	1.9%	4.48	3.33	—
2026	20	MIX MLE	3 levels	22	20	88	366	87	35	10	91%	4.0	18.0%	10.4%	7.6%	3.6%	4.11	4.89	—
2026	20	MIX MLE	3 levels	22	20	88	366	87	35	10	91%	4.0	18.0%	10.4%	7.6%	3.6%	4.11	4.89	—
2026	20	MIX RAW	3 levels	22	20	88	366	87	35	10	91%	4.0	23.8%	9.6%	14.2%	2.7%	4.11	3.80	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	21	MLB	MIL	—	—	0	—	—	—	—	—	—	19.9%	10.7%	9.2%	3.2%	4.90	4.90	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	22	MLB MLE	MIL	14	14	70	296	64	29	9	100%	5.0	21.6%	9.8%	11.8%	3.1%	4.69	4.60	+0.7
2029	23	MLB MLE	MIL	13	13	70	296	67	27	9	100%	5.4	22.6%	9.1%	13.5%	3.1%	4.50	4.40	+0.8
2030	24	MLB MLE	MIL	13	13	70	296	68	26	9	100%	5.4	23.1%	8.7%	14.4%	3.0%	4.37	4.29	+0.9
2031	25	MLB MLE	MIL	11	11	66	278	65	24	8	100%	6.0	23.5%	8.5%	14.9%	3.0%	4.28	4.23	+0.9
2032	26	MLB MLE	MIL	11	11	66	280	66	24	8	100%	6.0	23.7%	8.5%	15.2%	3.0%	4.23	4.20	+0.9
2033	27	MLB MLE	MIL	11	11	65	273	65	23	8	100%	5.9	23.6%	8.6%	15.1%	3.1%	4.24	4.24	+0.9
2034	28	MLB MLE	MIL	10	10	62	260	61	23	8	100%	6.2	23.5%	8.7%	14.8%	3.2%	4.29	4.33	+0.8
2035	29	MLB MLE	MIL	10	10	57	241	56	22	8	100%	5.7	23.3%	8.9%	14.4%	3.3%	4.39	4.46	+0.6
2036	30	MLB MLE	MIL	9	9	57	240	60	20	8	100%	6.3	24.9%	8.4%	16.5%	3.5%	4.38	4.37	+0.7
2037	31	MLB MLE	MIL	8	8	50	212	52	19	8	100%	6.3	24.5%	8.8%	15.7%	3.7%	4.49	4.57	+0.5
2038	32	MLB MLE	MIL	7	7	44	185	44	17	7	100%	6.2	24.1%	9.2%	14.9%	4.0%	4.67	4.79	+0.3
2028	22	MLB CTX	MIL	7	7	35	148	32	14	5	100%	5.0	21.6%	9.8%	11.8%	3.3%	4.78	4.69	+0.3
2029	23	MLB CTX	MIL	10	10	51	215	49	20	7	100%	5.1	22.6%	9.1%	13.5%	3.2%	4.58	4.48	+0.6
2030	24	MLB CTX	MIL	10	10	58	245	57	21	8	100%	5.8	23.1%	8.7%	14.4%	3.2%	4.45	4.37	+0.8
2031	25	MLB CTX	MIL	10	10	58	245	57	21	8	100%	5.8	23.5%	8.5%	14.9%	3.2%	4.36	4.31	+0.8
2032	26	MLB CTX	MIL	10	10	60	253	60	21	8	100%	6.0	23.7%	8.5%	15.2%	3.2%	4.31	4.28	+0.8
2033	27	MLB CTX	MIL	10	10	60	253	60	22	8	100%	6.0	23.6%	8.6%	15.1%	3.2%	4.32	4.32	+0.8
2034	28	MLB CTX	MIL	10	10	58	245	58	21	8	100%	5.8	23.5%	8.7%	14.8%	3.3%	4.38	4.42	+0.7
2035	29	MLB CTX	MIL	9	9	54	228	53	20	8	100%	6.0	23.3%	8.9%	14.4%	3.5%	4.48	4.55	+0.6
2036	30	MLB CTX	MIL	9	9	54	228	57	19	8	100%	6.0	24.9%	8.4%	16.5%	3.7%	4.48	4.47	+0.7
2037	31	MLB CTX	MIL	8	8	48	203	50	18	8	100%	6.0	24.5%	8.8%	15.7%	3.9%	4.59	4.67	+0.5
2038	32	MLB CTX	MIL	7	7	42	177	43	16	7	100%	6.0	24.1%	9.2%	14.9%	4.2%	4.78	4.90	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		99	99	578	2440	574	214	83	100%	5.8	23.5%	8.8%	14.8%	3.4%	4.48	4.09	+9.0
/ 200 IP	—	RAW		34	34	200	844	199	74	29	100%	5.8	23.5%	8.8%	14.8%	3.4%	4.48	4.09	+3.1
Career	—	MLE		43	41	172	727	137	85	22	95%	4.0	18.9%	11.7%	7.1%	3.0%	4.29	4.62	+8.0
/ 200 IP	—	MLE		50	48	200	845	159	99	25	95%	4.0	18.9%	11.7%	7.1%	3.0%	4.29	4.62	+2.4

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.

2026 A+Wisconsin Timber Rattlers · 69 IPFIP 3.64 → 4.59 (+0.95)K% 22.9% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.92%	—	×0.770	17.65%
BB% (unintentional) /BF	9.03%	—	×1.150	10.38%
HR / BF /BF	2.43%	÷1.000	×1.250	3.04%

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 3.64 → 4.59, 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 AABiloxi Shuckers · 13 IPFIP 5.37 → 6.53 (+1.16)K% 25.0% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.810	20.25%
BB% (unintentional) /BF	9.62%	—	×1.100	10.58%
HR / BF /BF	5.77%	÷1.000	×1.200	6.92%

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 100).

Result: FIP 5.37 → 6.53, 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).

2026 ROKACL Brewers · 6 IPFIP 2.45 → 3.77 (+1.32)K% 30.8% → 20.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.77%	—	×0.680	20.92%
BB% (unintentional) /BF	15.38%	—	×1.250	19.23%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. 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 2.45 → 3.77, 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 ACarolina Mudcats · 84 IPFIP 3.32 → 4.35 (+1.03)K% 26.6% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.59%	—	×0.740	19.68%
BB% (unintentional) /BF	11.08%	—	×1.180	13.07%
HR / BF /BF	1.94%	÷1.101	×1.300	2.29%

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 120).

Result: FIP 3.32 → 4.35, 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
Josh Knoth (OGILVIE)	—	—	—	—	—	3.2%	—	4.43	22.4%	13.2%	211	-0.47	—	—	—
José López R 2015 · 4.04 FIP	21	SP	4.04	19.1%	9.9%	2.3%	.329	3.77	17.9%	9.9%	436	-0.27	3.12	543	91
Chih-Jung Liu R 2021 · 4.41 FIP	22	SP	4.41	18.8%	10.5%	2.9%	.331	6.08	21.6%	9.0%	233	+1.67	4.41	283	91
Tanner Burns R 2021 · 4.34 FIP	22	SP	4.34	22.2%	10.6%	3.2%	.292	5.31	19.4%	6.5%	244	+0.97	4.34	382	89
Christian Roa R 2021 · 4.94 FIP	22	SP	4.94	19.6%	12.4%	3.5%	.321	4.90	22.5%	6.9%	260	-0.04	4.14	414	89
John Klein R 2023 · 4.47 FIP	21	SP	4.47	17.4%	11.4%	2.5%	.287	4.18	19.6%	9.9%	293	-0.29	3.19	346	87
Jared Karros R 2023 · 4.77 FIP	22	SP	4.77	19.0%	8.9%	3.9%	.290	5.26	17.8%	8.3%	120	+0.49	3.36	191	87
CJ Van Eyk R 2021 · 4.79 FIP	22	SP	4.79	21.8%	12.7%	3.5%	.302	4.64	15.2%	5.3%	127	-0.15	4.18	457	87
Will Sanders R 2024 · 4.95 FIP	22	SP	4.95	19.3%	11.8%	3.6%	.297	4.11	20.1%	12.5%	173	-0.84	3.92	266	86
Juan Nuñez R 2022 · 4.49 FIP	21	SP	4.49	19.6%	13.2%	2.5%	.300	4.42	22.8%	8.3%	148	-0.07	2.88	245	86
Logan Gragg R 2019 · 4.14 FIP	20	SP	4.14	17.4%	9.5%	2.4%	.343	5.20	15.2%	8.2%	202	+1.06	4.14	412	85
Chad Patrick R 2022 · 3.86 FIP	23	SP	3.86	20.3%	9.9%	2.2%	.315	4.19	22.1%	14.2%	422	+0.33	3.69	570	85
Curtis Taylor R 2017 · 3.95 FIP	22	SP	3.95	19.3%	9.9%	2.2%	.305	3.40	23.5%	13.7%	96	-0.55	2.58	408	85
Frank German R 2019 · 5.01 FIP	21	SP	5.01	19.5%	12.4%	3.6%	.308	4.56	18.9%	9.4%	123	-0.45	3.10	218	84
Ryan Jensen R 2021 · 4.86 FIP	23	SP	4.86	21.4%	10.8%	4.0%	.236	4.48	22.0%	5.1%	180	-0.38	3.92	311	84
Marcelo Perez R 2023 · 3.84 FIP	23	SP	3.84	18.0%	8.6%	2.1%	.288	4.99	14.7%	7.3%	238	+1.15	3.84	306	84
Trevor Harrison R 2024 · 4.03 FIP	18	SP	4.03	21.0%	10.6%	2.5%	.331	4.94	19.7%	7.0%	205	+0.91	3.79	277	84
Ryan Harvey R 2023 · 5.20 FIP	22	SP	5.20	16.7%	13.1%	3.4%	.294	4.50	17.0%	5.9%	87	-0.70	4.08	133	83
Cody Laweryson R 2021 · 4.06 FIP	23	SP	4.06	21.7%	8.4%	3.1%	.329	3.48	21.4%	12.8%	178	-0.58	2.48	298	83
TJ Shook R 2021 · 4.90 FIP	23	SP	4.90	21.7%	13.8%	3.4%	.311	4.98	20.7%	10.3%	296	+0.08	3.35	452	83
Rick Van Den Hurk R 2007 · 4.88 FIP	22	SP	4.88	21.6%	11.3%	4.0%	.331	4.31	21.2%	12.5%	90	-0.57	3.27	172	83

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	3.7	61	23.1%	9.0%	1.25	4.44
David Hernandez ('19)	3.2	65	23.9%	9.1%	1.22	4.12
Russ Springer ('10)	4.3	66	20.9%	9.4%	1.27	4.52
Stan Belinda ('00)	3.4	61	21.3%	9.9%	1.13	4.12
Xavier Hernandez ('89-'98, 3 WAR*)	3.4	67	23.9%*	9.1%*	1.12*	4.20*
Mark Guthrie ('89-'03, 8 WAR*)	4.9	65	22.8%*	8.5%*	1.07*	4.01*
Tom Niedenfuer ('81-'90, 8 WAR*)	3.3	65	23.1%*	8.1%*	1.19*	3.80*