Janson Junk

P Miami Marlins

Age 31 RHP 6'2" / 197 lbs MLB Svc 2.0 · Ctrl thru 2030 peak 1.2 · 2027

Overview

MLBSP40-MANPre-ArbFA 2031

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	28	MIX2 levels	30	9	68	4.87	4.29	20.5%	8.3%	0.2	K 18.3% · BB 7.4% · FIP 4.16
2025	29	MIX2 levels	31	25	160	3.70	2.73	19.5%	3.1%	5.4	K 18.4% · BB 3.0% · FIP 2.85
2026	30	MIX2 levels	28	27	129	4.18	4.00	17.3%	6.0%	2.1	K 17.0% · BB 6.3% · FIP 4.12
2027PROJ	31	MLBMIA	14	14	85	4.15	4.18	16.7%	4.8%	1.2
2028PROJ95% MLB	32	MLBMIA	11	11	65	4.24	4.35	15.9%	5.1%	0.7
2029PROJ95% MLB	33	MLBMIA	8	8	48	4.47	4.62	15.0%	5.6%	0.4

Last 3 seasons WAR 7.8 · Next 3 projected WAR 2.3Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2030Service2.262First FA2031

2027Pre-Arb$0.8M2028Arb-1$2M2029Arb-2$2M2030Arb-3$2M

Skills · percentileStatcast 2026

xwOBA vs47

FB Velo44

K%14

Form4.26 ERA (proj 4.15) · K 19.8% (proj 16.7%) · BB 6.6% (proj 4.8%) · last 60d · 25 IP through Oct 27

CompsCasey Lawrence (age 30) · Bruce Billings (age 29) · Jarrett Grube (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 111103vR 95

ERA4.15

FIP4.18

K%16.7%

BB%4.8%

K-BB%12.0%

Proj IP85

Value2027 · WAR

Runs saved vs league avg · 85 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit+$14M ctrl surplus

Statcast · Contract

Statcast Percentiles

FB Velo

p4494.1

Whiff%

p1015.9%

p1417.0%

xwOBA vs

p470.315

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

Status Pre-Arb

MLB Debut 2021

Service 2.262 yrs.days

Team Control Through 2030

First FA Year 2031

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Pre-Arb	$0.8M	+1.2	$10M	+$9M
2028	Arb-1	$2M	+0.7	$3M	+$1M
2029	Arb-2	$2M	+0.4	$1M	+$0.1M
2030	Arb-3	$2M	+0.1	$0.3M	+$0.0M (cut)
Totals		$4M		$14M	+$10M

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)
2017	21	ROK MLE	GCL Yankees East	11	0	13	61	10	6	0	0%	1.2	11.1%	12.3%	-1.1%	0.0%	0.71	3.72	—
2017	21	ROK RAW	GCL Yankees East	11	0	13	61	10	6	0	0%	1.2	16.4%	9.8%	6.6%	0.0%	0.71	2.94	—
2018	22	A MLE	Charleston RiverDogs	17	15	88	372	71	31	9	88%	5.2	14.1%	9.8%	4.3%	3.9%	3.77	5.28	—
2018	22	A RAW	Charleston RiverDogs	17	15	88	372	71	31	9	88%	5.2	19.1%	8.3%	10.8%	2.4%	3.77	3.87	—
2019	23	MIX MLE	3 levels	22	14	88	411	81	42	10	64%	4.0	15.6%	11.3%	4.2%	2.8%	5.54	4.74	—
2019	23	MIX RAW	3 levels	22	14	88	411	81	42	10	64%	4.0	19.7%	10.2%	9.5%	2.4%	5.54	4.17	—
2021	25	MIX MLE	2 levels	23	21	109	446	107	29	16	91%	4.8	19.9%	7.1%	12.8%	3.5%	2.96	4.23	+1.5
2021	25	MIX RAW	2 levels	23	21	109	446	107	29	16	91%	4.8	24.0%	6.5%	17.5%	3.6%	2.96	3.84	+2.0
2022	26	MIX MLE	2 levels	19	17	82	349	80	21	10	89%	4.3	19.5%	6.1%	13.4%	3.2%	4.83	4.01	+1.4
2022	26	MIX RAW	2 levels	19	17	82	349	80	21	10	89%	4.3	22.9%	6.0%	16.9%	2.9%	4.83	3.50	+1.9
2023	27	MIX MLE	2 levels	29	26	147	627	99	46	15	90%	5.1	13.6%	6.7%	6.9%	2.9%	4.21	4.37	+1.8
2023	27	MIX RAW	2 levels	29	26	147	627	99	46	15	90%	5.1	15.8%	7.3%	8.5%	2.4%	4.21	4.02	+2.4
2024	28	MIX MLE	2 levels	30	9	68	302	62	25	10	30%	2.3	18.3%	7.4%	10.8%	3.0%	4.87	4.16	+0.3
2024	28	MIX MLE	2 levels	30	9	68	302	62	25	10	30%	2.3	18.3%	7.4%	10.8%	3.0%	4.87	4.16	+0.3
2024	28	MIX RAW	2 levels	30	9	68	302	62	25	10	30%	2.3	20.5%	8.3%	12.3%	3.3%	4.87	4.29	+0.2
2025	29	MIX MLE	2 levels	31	25	160	642	125	20	10	81%	5.2	18.4%	3.0%	15.4%	1.7%	3.70	2.85	+5.1
2025	29	MIX MLE	2 levels	31	25	160	642	125	20	10	81%	5.2	18.4%	3.0%	15.4%	1.7%	3.70	2.85	+5.1
2025	29	MIX RAW	2 levels	31	25	160	642	125	20	10	81%	5.2	19.5%	3.1%	16.4%	1.6%	3.70	2.73	+5.4
2026	30	MIX MLE	2 levels	28	27	129	549	95	33	16	96%	4.6	17.0%	6.3%	10.7%	3.0%	4.18	4.12	+2.0
2026	30	MIX MLE	2 levels	28	27	129	549	95	33	16	96%	4.6	17.0%	6.3%	10.7%	3.0%	4.18	4.12	+2.0
2026	30	MIX RAW	2 levels	28	27	129	549	95	33	16	96%	4.6	17.3%	6.0%	11.3%	2.9%	4.18	4.00	+2.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			62	48	274	1159	200	57	33	77%	4.4	17.3%	4.9%	12.3%	2.8%	4.57	3.83	+5.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	MIA	14	14	85	359	60	17	10	100%	6.1	16.7%	4.8%	12.0%	2.7%	4.15	4.18	+1.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	MIA	11	11	68	289	46	15	9	100%	6.2	15.9%	5.1%	10.8%	3.0%	4.32	4.43	+0.8
2029	33	MLB MLE	MIA	8	8	50	213	32	12	7	100%	6.3	15.0%	5.6%	9.4%	3.3%	4.56	4.71	+0.4
2030	34	MLB MLE	MIA	6	6	34	145	20	9	5	100%	5.7	14.1%	6.1%	8.0%	3.6%	4.84	5.02	+0.1
2028	32	MLB CTX	MIA	11	11	65	274	44	14	8	100%	5.9	15.9%	5.1%	10.8%	2.8%	4.24	4.35	+0.7
2029	33	MLB CTX	MIA	8	8	48	203	31	11	6	100%	6.0	15.0%	5.6%	9.4%	3.1%	4.47	4.62	+0.4
2030	34	MLB CTX	MIA	5	5	31	131	19	8	4	100%	6.2	14.1%	6.1%	8.0%	3.4%	4.74	4.92	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		86	72	418	1767	293	90	52	84%	4.9	16.6%	5.1%	11.4%	2.9%	4.52	3.95	+7.2
/ 200 IP	—	RAW		41	34	200	846	140	43	25	84%	4.9	16.6%	5.1%	11.4%	2.9%	4.52	3.95	+3.5
Career	—	MLE		210	154	885	3759	632	262	107	73%	4.2	16.8%	7.0%	9.9%	2.9%	4.11	4.13	+6.4
/ 200 IP	—	MLE		47	35	200	849	143	59	24	73%	4.2	16.8%	7.0%	9.9%	2.9%	4.11	4.13	+3.0

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 AAAJacksonville Jumbo Shrimp · 6 IPFIP 3.26 → 3.75 (+0.48)K% 23.1% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.08%	—	×0.860	19.85%
BB% (unintentional) /BF	0.00%	—	×0.900	0.00%
HR / BF /BF	3.85%	÷1.000	×1.100	4.23%

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 3.26 → 3.75, 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 AAAJacksonville Jumbo Shrimp · 50 IPFIP 2.04 → 2.41 (+0.37)K% 24.6% → 21.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.62%	—	×0.860	21.17%
BB% (unintentional) /BF	3.59%	—	×0.900	3.23%
HR / BF /BF	1.03%	÷0.903	×1.100	1.25%

Result: FIP 2.04 → 2.41, 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 AAALas Vegas Aviators · 60 IPFIP 3.86 → 4.16 (+0.30)K% 21.3% → 18.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.26%	—	×0.860	18.28%
BB% (unintentional) /BF	8.27%	—	×0.900	7.44%
HR / BF /BF	2.76%	÷1.001	×1.100	3.03%

Result: FIP 3.86 → 4.16, 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 AAANashville Sounds · 140 IPFIP 4.00 → 4.37 (+0.37)K% 15.8% → 13.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.82%	—	×0.860	13.61%
BB% (unintentional) /BF	7.41%	—	×0.900	6.67%
HR / BF /BF	2.36%	÷0.905	×1.100	2.87%

Result: FIP 4.00 → 4.37, 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 AAASalt Lake Bees · 74 IPFIP 3.55 → 4.01 (+0.46)K% 22.1% → 19.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.12%	—	×0.880	19.46%
BB% (unintentional) /BF	5.77%	—	×1.050	6.06%
HR / BF /BF	2.88%	÷0.978	×1.100	3.25%

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 96).

Result: FIP 3.55 → 4.01, 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 AARocket City Trash Pandas · 93 IPFIP 3.44 → 3.88 (+0.44)K% 25.9% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.87%	—	×0.810	20.95%
BB% (unintentional) /BF	7.20%	—	×1.100	7.92%
HR / BF /BF	2.93%	÷1.249	×1.200	2.82%

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 150).

Result: FIP 3.44 → 3.88, 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).

2019 A+Tampa Tarpons · 81 IPFIP 3.81 → 4.74 (+0.93)K% 20.2% → 15.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.21%	—	×0.770	15.56%
BB% (unintentional) /BF	9.84%	—	×1.150	11.32%
HR / BF /BF	2.13%	÷0.960	×1.250	2.77%

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 92).

Result: FIP 3.81 → 4.74, 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).

2019 AATrenton Thunder · 5 IPFIP 7.32 → 8.45 (+1.13)K% 13.6% → 11.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.64%	—	×0.810	11.05%
BB% (unintentional) /BF	22.73%	—	×1.100	25.00%
HR / BF /BF	4.55%	÷0.960	×1.200	5.68%

Result: FIP 7.32 → 8.45, 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
Janson Junk (OGILVIE)	—	—	—	—	—	2.7%	—	4.65	15.2%	9.7%	153	+0.47	—	—	—
Casey Lawrence R 2018 · 3.77 FIP	30	SP-	3.77	18.1%	4.4%	3.0%	.305	4.08	20.0%	14.8%	86	+0.31	3.57	1,374	66
Bruce Billings R 2015 · 3.09 FIP	29	SP-	3.09	15.6%	5.6%	1.1%	.309	—	—	—	—	—	3.09	121	65
Jarrett Grube R 2015 · 3.75 FIP	33	SP	3.75	18.7%	4.2%	3.1%	.285	4.57	17.3%	9.6%	253	+0.82	3.75	393	63
Kenshin Kawakami R 2009 · 3.97 FIP	34	SP-	3.97	15.7%	7.6%	2.2%	.277	4.06	15.1%	9.5%	87	+0.09	3.97	244	62
Luke Hudson R 2006 · 3.81 FIP	29	SP-	3.81	14.5%	8.4%	1.6%	.307	—	—	—	—	—	3.81	235	62
Yohan Pino R 2015 · 4.13 FIP	31	SP-	4.13	17.8%	5.8%	3.3%	.312	5.33	15.2%	11.6%	35	+1.20	3.84	193	60
Scott Carroll R 2016 · 4.94 FIP	31	SP	4.94	10.5%	8.6%	3.0%	.289	5.71	14.4%	5.8%	22	+0.77	3.92	377	60
Leo Medrano R 2015 · 3.76 FIP	32	SP	3.76	14.2%	3.9%	2.5%	.354	4.34	11.0%	3.7%	113	+0.58	3.76	222	60
Jorge Campillo R 2008 · 3.93 FIP	29	SP-	3.93	16.3%	5.5%	2.8%	.283	—	—	—	—	—	3.93	172	60
Mike Wright Jr. R 2021 · 3.89 FIP	31	SP-	3.89	19.1%	8.8%	2.4%	.237	4.79	14.4%	1.1%	56	+0.90	3.76	725	59
Cory Riordan R 2016 · 4.24 FIP	30	SP	4.24	14.3%	5.0%	3.1%	.341	—	—	—	—	—	4.24	154	59
Mike Fiers R 2016 · 4.30 FIP	31	SP	4.30	18.5%	5.8%	3.7%	.308	4.96	19.2%	12.2%	510	+0.66	2.83	1,140	58
Chase Anderson R 2019 · 4.39 FIP	31	SP	4.39	20.9%	8.1%	3.7%	.259	5.39	19.2%	10.0%	218	+1.00	3.30	1,260	58
Juan Delgadillo R 2015 · 4.54 FIP	32	SP	4.54	15.5%	7.2%	3.3%	.316	4.47	10.9%	4.7%	39	-0.07	4.47	143	58
Brad Peacock R 2019 · 4.22 FIP	31	SP-	4.22	25.1%	8.1%	4.0%	.261	4.15	22.8%	12.5%	96	-0.07	2.97	748	58
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	57
Daniel McCutchen R 2015 · 4.30 FIP	32	SP-	4.30	13.9%	4.4%	3.3%	.268	4.74	10.8%	4.9%	155	+0.44	4.13	476	57
Tim Adleman R 2019 · 4.30 FIP	31	SP	4.30	22.8%	7.8%	3.9%	.266	4.71	18.5%	11.1%	90	+0.41	3.63	605	57
Kohei Arihara R 2022 · 4.58 FIP	29	SP-	4.58	16.4%	7.2%	3.5%	.333	—	—	—	—	—	4.58	135	57
Scott McGregor R 2015 · 4.37 FIP	28	SP-	4.37	11.8%	7.6%	2.4%	.293	—	—	—	—	—	4.37	107	57

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	2.6	85	16.6%	5.1%	1.14	4.48
Austin Pruitt ('24)	1.6	63	16.6%	5.6%	1.31	4.54
Mike Jeffcoat ('83-'94, 1 WAR*)	2.5	83	15.2%*	6.7%*	1.16*	4.65*
Tom Hausman ('75-'82, 1 WAR*)	2.2	74	14.3%*	6.5%*	1.22*	4.45*
Taylor Buchholz ('11)	1.6	78	17.7%	6.6%	1.19	4.28
Wally Whitehurst ('89-'96, 4 WAR*)	2.4	98	19.0%*	6.3%*	1.11*	4.50*
Robbie Erlin ('22)	1.7	68	19.2%	4.9%	1.13	4.87