Josh Rogers

P Albuquerque Isotopes

Age 33 LHP 6'3" / 211 lbs AAA

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	28	MIX4 levels	31	18	98	6.13	6.20	14.1%	8.9%	-0.9	K 12.2% · BB 9.5% · FIP 6.15
2023	29	AAACOL	30	13	104	8.02	6.94	13.1%	8.6%	—	K 11.3% · BB 7.8% · FIP 6.75
2024	30	MIX3 levels	26	17	95	6.42	5.79	12.8%	4.2%	-0.4	K 11.0% · BB 3.8% · FIP 5.62
2025	31	No MLB games played
2026	32	No MLB games played
2027PROJ	33	MLBCOL	3	3	16	4.65	4.80	17.8%	7.7%	0.1
2028PROJ6% MLB	34	MLBCOL	1	1	6	4.86	5.04	17.3%	8.2%	0.0
2029PROJMLE	35	MLBCOL	1	1	1	5.12	5.32	16.7%	8.8%	0.0

Last 3 seasons WAR -1.3 · Next 3 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2024

FB Velo10

K%10

xwOBA vs10

CompsKwang Hyun Kim (age 33) · Jorge Castillo (age 33) · Oscar Rivera (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 108116vR 124

ERA4.65

FIP4.80

K%17.8%

BB%7.7%

K-BB%10.0%

Proj IP165

Value2027 · WAR

Runs saved vs league avg · 165 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1089.5

Whiff%

p1012.7%

p106.0%

xwOBA vs

p100.406

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)
2015	21	A MLE	Charleston RiverDogs	2	0	6	29	6	3	0	0%	3.2	20.7%	10.3%	10.3%	0.0%	5.68	2.66	—
2015	21	A RAW	Charleston RiverDogs	2	0	6	29	6	3	0	0%	3.2	20.7%	10.3%	10.3%	0.0%	5.68	2.63	—
2016	22	MIX MLE	2 levels	24	24	136	549	115	22	6	100%	5.7	16.0%	4.6%	11.4%	1.6%	2.38	3.20	—
2016	22	MIX RAW	2 levels	24	24	136	549	115	22	6	100%	5.7	20.9%	4.0%	16.9%	1.1%	2.38	2.47	—
2017	23	MIX MLE	2 levels	15	15	92	369	80	16	8	100%	6.1	17.0%	4.9%	12.1%	2.8%	3.24	3.80	—
2017	23	MIX RAW	2 levels	15	15	92	369	80	16	8	100%	6.1	21.7%	4.3%	17.3%	2.2%	3.24	3.01	—
2018	24	MIX MLE	2 levels	27	27	151	647	107	40	18	100%	5.6	14.7%	6.5%	8.2%	3.1%	3.93	4.38	+1.8
2018	24	MIX RAW	2 levels	27	27	151	647	107	40	18	100%	5.6	16.5%	6.2%	10.4%	2.8%	3.93	4.03	+2.5
2019	25	MIX MLE	2 levels	16	11	69	323	38	16	25	69%	4.3	10.5%	5.1%	5.4%	8.9%	8.57	7.72	-1.7
2019	25	MIX RAW	2 levels	16	11	69	323	38	16	25	69%	4.3	11.8%	5.0%	6.8%	7.7%	8.57	7.38	-1.5
2021	27	MIX MLE	2 levels	24	21	126	543	85	38	21	88%	5.2	14.3%	7.2%	7.0%	4.2%	4.14	5.13	+0.4
2021	27	MIX RAW	2 levels	24	21	126	543	85	38	21	88%	5.2	15.7%	7.0%	8.7%	3.9%	4.14	4.82	+0.8
2022	28	MIX MLE	4 levels	31	18	98	440	62	39	24	58%	3.2	12.2%	9.5%	2.7%	5.2%	6.13	6.15	-0.8
2022	28	MIX RAW	4 levels	31	18	98	440	62	39	24	58%	3.2	14.1%	8.9%	5.2%	5.5%	6.13	6.20	-0.9
2023	29	AAA MLE	Albuquerque Isotopes	30	13	104	487	64	42	31	43%	3.5	11.3%	7.8%	3.5%	6.6%	8.02	6.75	—
2023	29	AAA RAW	Albuquerque Isotopes	30	13	104	487	64	42	31	43%	3.5	13.1%	8.6%	4.5%	6.4%	8.02	6.94	—
2024	30	MIX MLE	3 levels	26	17	95	431	55	18	24	65%	3.7	11.0%	3.8%	7.2%	5.4%	6.42	5.62	-0.2
2024	30	MIX MLE	3 levels	26	17	95	431	55	18	24	65%	3.7	11.0%	3.8%	7.2%	5.4%	6.42	5.62	-0.2
2024	30	MIX RAW	3 levels	26	17	95	431	55	18	24	65%	3.7	12.8%	4.2%	8.6%	5.6%	6.42	5.79	-0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			36	12	99	439	48	38	23	33%	2.8	10.9%	8.7%	2.3%	5.2%	5.55	6.30	-1.9
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	COL	3	3	16	68	12	5	2	100%	5.3	17.8%	7.7%	10.0%	3.3%	4.65	4.80	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	COL	19	19	117	494	85	41	18	100%	6.2	17.3%	8.2%	9.0%	3.6%	4.86	5.04	+0.5
2029	35	MLB MLE	COL	15	15	90	379	63	33	15	100%	6.0	16.7%	8.8%	7.9%	3.9%	5.12	5.32	+0.1
2028	34	MLB CTX	COL	1	1	6	25	4	2	1	100%	6.0	17.3%	8.2%	9.0%	3.6%	4.86	5.04	+0.0
2029	35	MLB CTX	COL	1	1	1	4	1	0	0	100%	1.0	16.7%	8.8%	7.9%	3.9%	5.12	5.32	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		37	13	106	470	53	41	24	35%	2.9	11.3%	8.6%	2.7%	5.1%	5.50	6.05	-1.8
/ 200 IP	—	RAW		70	25	200	884	100	77	45	36%	2.9	11.3%	8.6%	2.7%	5.1%	5.50	6.05	-3.4
Career	—	MLE		195	146	879	3818	519	240	169	75%	4.5	13.6%	6.3%	7.3%	4.4%	5.03	5.18	-0.4
/ 200 IP	—	MLE		44	33	200	869	118	55	38	75%	4.5	13.6%	6.3%	7.3%	4.4%	5.03	5.18	-0.3

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 AAAAlbuquerque Isotopes · 83 IPFIP 5.71 → 5.82 (+0.12)K% 13.6% → 11.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.56%	—	×0.860	11.66%
BB% (unintentional) /BF	4.26%	—	×0.900	3.83%
HR / BF /BF	5.85%	÷1.096	×1.100	5.87%

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 119).

Result: FIP 5.71 → 5.82, 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 AAAAlbuquerque Isotopes · 104 IPFIP 6.58 → 6.75 (+0.17)K% 13.1% → 11.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.14%	—	×0.860	11.30%
BB% (unintentional) /BF	8.62%	—	×0.900	7.76%
HR / BF /BF	6.37%	÷1.062	×1.100	6.60%

Result: FIP 6.58 → 6.75, 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).

2022 AAAJacksonville Jumbo Shrimp · 60 IPFIP 5.68 → 6.06 (+0.38)K% 14.6% → 12.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.61%	—	×0.880	12.85%
BB% (unintentional) /BF	8.99%	—	×1.050	9.44%
HR / BF /BF	4.87%	÷1.032	×1.100	5.19%

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 106).

Result: FIP 5.68 → 6.06, 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 AAHarrisburg Senators · 9 IPFIP 7.69 → 9.12 (+1.43)K% 15.2% → 12.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.22%	—	×0.810	12.33%
BB% (unintentional) /BF	8.70%	—	×1.100	9.57%
HR / BF /BF	8.70%	÷0.979	×1.200	10.65%

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 96).

Result: FIP 7.69 → 9.12, 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).

2021 AAARochester Red Wings · 90 IPFIP 4.48 → 4.95 (+0.47)K% 16.1% → 14.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.07%	—	×0.880	14.14%
BB% (unintentional) /BF	6.12%	—	×1.050	6.43%
HR / BF /BF	3.57%	÷0.968	×1.100	4.06%

Result: FIP 4.48 → 4.95, 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 AAANorfolk Tides · 55 IPFIP 6.39 → 7.47 (+1.08)K% 13.0% → 11.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.99%	—	×0.880	11.43%
BB% (unintentional) /BF	3.94%	—	×1.050	4.13%
HR / BF /BF	7.09%	÷0.889	×1.100	8.77%

Result: FIP 6.39 → 7.47, 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).

2018 AAANorfolk Tides · 140 IPFIP 3.89 → 4.31 (+0.42)K% 17.1% → 15.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.09%	—	×0.880	15.04%
BB% (unintentional) /BF	5.92%	—	×1.050	6.22%
HR / BF /BF	2.71%	÷0.964	×1.100	3.09%

Result: FIP 3.89 → 4.31, 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).

2017 A+Tampa Yankees · 53 IPFIP 2.31 → 3.11 (+0.80)K% 24.4% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.40%	—	×0.770	18.79%
BB% (unintentional) /BF	3.83%	—	×1.150	4.40%
HR / BF /BF	1.44%	÷0.949	×1.250	1.89%

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 90).

Result: FIP 2.31 → 3.11, 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 Rogers (OGILVIE)	—	—	—	—	—	3.3%	—	5.16	17.0%	8.6%	207	+0.36	—	—	—
Kwang Hyun Kim L 2021 · 4.21 FIP	33	SP-	4.21	17.7%	8.2%	2.9%	.266	—	—	—	—	—	3.76	146	68
Jorge Castillo L 2015 · 4.50 FIP	33	SP	4.50	16.8%	9.2%	3.0%	.292	4.95	12.4%	7.2%	186	+0.45	4.50	408	66
Oscar Rivera L 2015 · 3.68 FIP	34	SP	3.68	14.2%	6.9%	1.7%	.298	4.66	10.4%	3.0%	129	+0.98	3.68	237	63
Mauricio Lara L 2015 · 3.62 FIP	36	SP	3.62	13.9%	6.9%	1.5%	.310	3.69	12.1%	5.1%	220	+0.07	3.62	444	63
Tomas Solis L 2016 · 4.86 FIP	33	SP	4.86	12.4%	8.5%	3.1%	.273	5.95	10.1%	2.4%	117	+1.09	4.20	327	62
Arturo Lopez L 2016 · 5.26 FIP	33	SP	5.26	11.5%	7.9%	3.9%	.341	4.92	11.3%	5.2%	224	-0.34	4.34	445	62
Orlando Lara L 2017 · 4.39 FIP	32	SP	4.39	14.7%	6.5%	3.1%	.346	4.09	22.0%	14.2%	104	-0.30	3.85	426	62
Roy Merritt L 2017 · 3.95 FIP	31	SP	3.95	16.2%	5.8%	2.7%	.339	—	—	—	—	—	3.93	129	60
Everett Teaford L 2015 · 4.42 FIP	31	SP-	4.42	13.9%	7.6%	2.8%	.324	—	—	—	—	—	4.42	208	60
Tsuyoshi Wada L 2014 · 3.60 FIP	33	SP	3.60	19.7%	6.2%	2.5%	.290	3.66	16.8%	9.7%	119	+0.06	3.60	188	58
Daniel Rodriguez L 2017 · 3.87 FIP	32	SP	3.87	13.1%	9.7%	1.2%	.335	4.77	20.8%	13.0%	112	+0.90	2.89	391	56
Shota Imanaga L 2024 · 3.71 FIP	30	SP	3.71	25.1%	4.0%	4.0%	.262	4.76	22.8%	17.9%	319	+1.05	3.71	492	52
Pat Misch L 2015 · 3.94 FIP	33	SP-	3.94	11.6%	7.9%	1.5%	.257	—	—	—	—	—	3.50	265	47
Enrique Lechuga L 2017 · 3.78 FIP	31	SP	3.78	10.5%	6.1%	1.5%	.390	—	—	—	—	—	3.78	137	46
Matt Dermody L 2023 · 3.87 FIP	33	SP	3.87	20.7%	4.6%	3.5%	.336	—	—	—	—	—	2.38	348	42
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	40
Travis Blackley L 2016 · 3.85 FIP	33	SP	3.85	11.6%	10.7%	0.7%	.301	6.88	6.1%	-3.6%	27	+3.03	3.85	409	37
Austin Bibens-Dirkx R 2018 · 4.89 FIP	33	SP-	4.89	17.9%	7.6%	4.3%	.322	4.82	15.9%	9.5%	147	-0.07	3.97	567	37
Luke Westphal L 2022 · 4.35 FIP	33	SW	4.35	24.2%	13.4%	2.9%	.302	5.19	15.7%	-0.7%	26	+0.84	2.97	294	37
Cory Riordan R 2016 · 4.24 FIP	30	SP	4.24	14.3%	5.0%	3.1%	.341	—	—	—	—	—	4.24	154	36

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	2.4	94	16.0%	8.3%	1.52	4.98
Dave Williams ('07)	2.0	82	13.8%	9.3%	1.41	4.83
Masato Yoshii ('02)	3.8	151	13.9%	6.9%	1.33	4.62
Dick Pole ('73-'78, -1 WAR*)	2.7	88	15.8%*	8.8%*	1.47*	5.40*
Mike Brown ('82-'87, -2 WAR*)	1.3	85	14.3%*	8.8%*	1.41*	5.73*
Jo-Jo Reyes ('16)	1.7	84	14.0%	9.6%	1.44	6.06
Dick Lange ('72-'75, -3 WAR*)	1.4	92	16.6%*	9.6%*	1.42*	5.49*