Adam Kloffenstein

P Scranton/Wilkes-Barre RailRiders

Age 26 RHP 6'5" / 245 lbs AAA peak 0.1 · 2027

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	MIX2 levels	18	17	90	4.68	4.72	19.3%	10.8%	0.7	K 16.7% · BB 9.8% · FIP 4.98
2025	24	MIX3 levels	21	18	91	5.66	5.22	24.8%	11.1%	—	K 20.5% · BB 10.5% · FIP 6.48
2026	25	AAAScranton/Wilk…	26	24	123	4.89	4.64	20.5%	12.6%	—	K 17.6% · BB 11.3% · FIP 4.83
2027PROJ	26	MLBNYY	2	2	15	5.42	5.42	18.5%	11.6%	-0.0
2028PROJ43% MLB	27	MLBNYY	8	8	50	5.33	5.34	18.8%	11.3%	0.0
2029PROJ63% MLB	28	MLBNYY	11	11	66	5.31	5.35	18.9%	11.2%	0.0

Last 3 seasons WAR 0.7 · Next 3 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.5 / P90 1.0, comp-based) · star 0% · didn't stick 94%

CompsM.D. Johnson (age 26) · Carlos Pimentel (age 26) · Chi Chi González (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 136128vR 120

ERA5.42

FIP5.42

K%18.5%

BB%11.6%

K-BB%6.9%

Proj IP148

Value2027 · WAR

Runs saved vs league avg · 148 IP

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)
2018	17	ROK MLE	GCL Blue Jays	2	2	2	9	4	2	0	100%	1.0	44.4%	22.2%	22.2%	0.0%	0.00	2.16	—
2018	17	ROK RAW	GCL Blue Jays	2	2	2	9	4	2	0	100%	1.0	44.4%	22.2%	22.2%	0.0%	0.00	2.10	—
2021	20	A+ MLE	Vancouver Canadians	23	23	101	466	107	61	10	100%	4.4	17.7%	15.1%	2.6%	3.0%	6.22	5.13	—
2021	20	A+ RAW	Vancouver Canadians	23	23	101	466	107	61	10	100%	4.4	23.0%	13.1%	9.9%	2.1%	6.22	4.08	—
2022	21	MIX MLE	2 levels	25	24	112	513	118	55	16	96%	4.5	18.4%	11.9%	6.5%	3.8%	5.54	5.12	—
2022	21	MIX RAW	2 levels	25	24	112	513	118	55	16	96%	4.5	23.0%	10.7%	12.3%	3.1%	5.54	4.32	—
2023	22	MIX MLE	2 levels	26	25	128	545	140	54	14	96%	4.9	21.1%	10.1%	11.0%	3.0%	3.16	4.26	—
2023	22	MIX RAW	2 levels	26	25	128	545	140	54	14	96%	4.9	25.7%	9.9%	15.8%	2.6%	3.16	3.60	—
2024	23	MIX MLE	2 levels	18	17	90	379	73	41	13	94%	5.0	16.7%	9.8%	6.9%	3.7%	4.68	4.98	+0.4
2024	23	MIX MLE	2 levels	18	17	90	379	73	41	13	94%	5.0	16.7%	9.8%	6.9%	3.7%	4.68	4.98	+0.4
2024	23	MIX RAW	2 levels	18	17	90	379	73	41	13	94%	5.0	19.3%	10.8%	8.4%	3.4%	4.68	4.72	+0.7
2025	24	MIX MLE	3 levels	21	18	91	415	103	46	20	86%	4.3	20.5%	10.5%	10.0%	6.9%	5.66	6.48	—
2025	24	MIX MLE	3 levels	21	18	91	415	103	46	20	86%	4.3	20.5%	10.5%	10.0%	6.9%	5.66	6.48	—
2025	24	MIX RAW	3 levels	21	18	91	415	103	46	20	86%	4.3	24.8%	11.1%	13.7%	4.8%	5.66	5.22	—
2026	25	AAA MLE	Scranton/Wilkes-Barre RailRiders	26	24	123	541	111	68	16	92%	4.7	17.6%	11.3%	6.3%	3.3%	4.89	4.83	—
2026	25	AAA MLE	Scranton/Wilkes-Barre RailRiders	26	24	123	541	111	68	16	92%	4.7	17.6%	11.3%	6.3%	3.3%	4.89	4.83	—
2026	25	AAA RAW	Scranton/Wilkes-Barre RailRiders	26	24	123	541	111	68	16	92%	4.7	20.5%	12.6%	7.9%	3.0%	4.89	4.64	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			1	0	1	3	0	0	0	0%	1.0	0.0%	0.0%	0.0%	0.0%	0.00	3.10	+0.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	NYY	2	2	15	63	12	7	2	100%	7.5	18.5%	11.6%	6.9%	3.7%	5.42	5.42	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	NYY	20	20	118	499	94	56	18	100%	5.9	18.8%	11.3%	7.5%	3.7%	5.33	5.34	+0.1
2029	28	MLB MLE	NYY	18	18	106	447	85	50	17	100%	5.9	18.9%	11.2%	7.8%	3.7%	5.31	5.35	+0.1
2030	29	MLB MLE	NYY	16	16	96	404	76	45	16	100%	6.0	18.8%	11.2%	7.6%	3.8%	5.35	5.42	-0.0
2031	30	MLB MLE	NYY	14	14	86	365	68	42	15	100%	6.2	18.6%	11.4%	7.2%	4.0%	5.47	5.57	-0.2
2028	27	MLB CTX	NYY	8	8	50	211	40	24	8	100%	6.2	18.8%	11.3%	7.5%	3.7%	5.33	5.34	+0.0
2029	28	MLB CTX	NYY	11	11	66	279	53	31	10	100%	6.0	18.9%	11.2%	7.8%	3.7%	5.31	5.35	+0.0
2030	29	MLB CTX	NYY	12	12	70	296	56	33	11	100%	5.8	18.8%	11.2%	7.6%	3.8%	5.35	5.42	-0.0
2031	30	MLB CTX	NYY	12	12	69	291	54	33	12	100%	5.8	18.6%	11.4%	7.2%	4.0%	5.47	5.57	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		44	43	256	1080	202	121	41	98%	5.8	18.7%	11.2%	7.5%	3.8%	5.35	5.04	+1.0
/ 200 IP	—	RAW		34	33	200	843	158	94	32	98%	5.9	18.7%	11.2%	7.5%	3.8%	5.35	5.04	+0.8
Career	—	MLE		141	133	648	2868	540	330	110	94%	4.6	18.8%	11.5%	7.3%	3.8%	4.93	5.07	-0.0
/ 200 IP	—	MLE		44	41	200	886	167	102	34	94%	4.6	18.8%	11.5%	7.3%	3.8%	4.93	5.07	-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 AAAScranton/Wilkes-Barre RailRiders · 123 IPFIP 4.58 → 4.83 (+0.25)K% 20.5% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.52%	—	×0.860	17.65%
BB% (unintentional) /BF	12.57%	—	×0.900	11.31%
HR / BF /BF	2.96%	÷1.000	×1.100	3.25%

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 4.58 → 4.83, 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 AAABuffalo Bisons · 82 IPFIP 5.47 → 6.48 (+1.01)K% 23.9% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.87%	—	×0.860	20.53%
BB% (unintentional) /BF	11.67%	—	×0.900	10.50%
HR / BF /BF	5.31%	÷0.847	×1.100	6.89%

Result: FIP 5.47 → 6.48, 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 ADunedin Blue Jays · 4 IPFIP 1.62 → 2.29 (+0.66)K% 25.0% → 18.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.740	18.50%
BB% (unintentional) /BF	5.00%	—	×1.180	5.90%
HR / BF /BF	0.00%	÷1.284	×1.300	0.00%

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 157).

Result: FIP 1.62 → 2.29, 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 AAAMemphis Redbirds · 89 IPFIP 4.74 → 4.98 (+0.24)K% 19.4% → 16.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.41%	—	×0.860	16.70%
BB% (unintentional) /BF	10.90%	—	×0.900	9.81%
HR / BF /BF	3.46%	÷1.020	×1.100	3.73%

Result: FIP 4.74 → 4.98, 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 AANew Hampshire Fisher Cats · 89 IPFIP 3.02 → 3.81 (+0.78)K% 27.6% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.63%	—	×0.810	22.38%
BB% (unintentional) /BF	8.68%	—	×1.100	9.55%
HR / BF /BF	2.11%	÷1.000	×1.200	2.53%

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 3.02 → 3.81, 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 AAAMemphis Redbirds · 39 IPFIP 4.92 → 5.31 (+0.39)K% 21.2% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.21%	—	×0.860	18.24%
BB% (unintentional) /BF	12.73%	—	×0.900	11.45%
HR / BF /BF	3.64%	÷0.955	×1.100	4.19%

Result: FIP 4.92 → 5.31, 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).

2022 AANew Hampshire Fisher Cats · 86 IPFIP 4.32 → 5.10 (+0.78)K% 22.2% → 18.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.17%	—	×0.810	17.95%
BB% (unintentional) /BF	11.34%	—	×1.100	12.47%
HR / BF /BF	3.02%	÷1.027	×1.200	3.53%

Result: FIP 4.32 → 5.10, 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+Vancouver Canadians · 26 IPFIP 3.90 → 5.16 (+1.26)K% 25.9% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.86%	—	×0.770	19.91%
BB% (unintentional) /BF	8.62%	—	×1.150	9.91%
HR / BF /BF	3.45%	÷0.952	×1.250	4.53%

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 3.90 → 5.16, 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).

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
Adam Kloffenstein (OGILVIE)	—	—	—	—	—	3.7%	—	5.37	18.9%	7.6%	320	-0.05	—	—	—
M.D. Johnson R 2023 · 5.64 FIP	26	SP	5.64	16.4%	12.7%	4.2%	.254	3.52	14.6%	4.7%	67	-2.12	3.52	395	80
Carlos Pimentel R 2016 · 4.30 FIP	26	SP	4.30	16.1%	9.7%	2.4%	.339	4.61	11.9%	-0.6%	13	+0.31	4.30	301	80
Chi Chi González R 2019 · 4.99 FIP	27	SP	4.99	16.7%	10.5%	3.6%	.302	4.55	15.3%	7.8%	225	-0.44	4.01	800	79
Chandler Champlain R 2024 · 4.72 FIP	25	SP	4.72	16.7%	8.1%	3.6%	.298	4.77	15.3%	8.7%	247	+0.05	4.56	628	79
Juan Carlos Sulbaran R 2016 · 4.65 FIP	26	SP	4.65	15.0%	8.9%	3.1%	.289	—	—	—	—	—	4.65	278	79
Riley Gowens R 2024 · 4.55 FIP	24	SP	4.55	22.6%	10.3%	3.7%	.279	4.37	21.3%	12.1%	173	-0.18	4.30	295	78
Nestor Molina R 2016 · 4.83 FIP	27	SP	4.83	15.0%	8.0%	3.6%	.304	3.61	17.0%	10.2%	289	-1.22	3.01	401	78
Nic Swanson R 2024 · 4.91 FIP	25	SP	4.91	19.3%	11.8%	3.5%	.286	5.43	19.9%	6.5%	132	+0.52	4.29	438	78
Asher Wojciechowski R 2015 · 4.30 FIP	26	SP	4.30	15.7%	8.5%	2.6%	.323	4.61	20.4%	12.2%	287	+0.31	3.15	678	78
Austin Love R 2022 · 4.34 FIP	23	SP	4.34	20.6%	10.6%	3.0%	.358	3.58	22.1%	9.7%	56	-0.76	3.58	240	78
Kyle Haynes R 2016 · 4.58 FIP	25	SP	4.58	15.7%	9.9%	2.8%	.324	—	—	—	—	—	4.08	240	77
Shao-Ching Chiang R 2019 · 4.72 FIP	25	SP	4.72	18.8%	10.0%	3.5%	.316	—	—	—	—	—	3.94	575	77
Nolan McLean R 2024 · 4.40 FIP	23	SP	4.40	20.0%	10.1%	3.1%	.292	3.26	25.6%	16.0%	341	-1.14	3.17	451	77
Brady Feigl R 2021 · 5.26 FIP	25	SP	5.26	19.4%	9.6%	4.7%	.296	—	—	—	—	—	3.93	257	77
Glenn Otto Jr. R 2022 · 4.73 FIP	26	SP	4.73	18.2%	10.6%	3.3%	.247	5.43	23.5%	9.1%	58	+0.70	2.56	369	77
Justin Armbruester R 2024 · 5.73 FIP	25	SP	5.73	20.2%	11.1%	5.3%	.289	1.49	27.5%	21.9%	15	-4.24	1.49	373	77
Nate Long R 2015 · 4.67 FIP	29	SP	4.67	14.8%	10.6%	2.7%	.285	—	—	—	—	—	4.67	151	76
Jared Mortensen R 2015 · 4.42 FIP	27	SP-	4.42	16.9%	7.8%	3.2%	.287	4.99	20.9%	2.1%	72	+0.57	4.42	200	76
Jarrod Cande R 2024 · 5.42 FIP	24	SP	5.42	16.7%	11.0%	4.3%	.256	5.72	11.7%	-3.6%	23	+0.30	4.31	315	75
Mike Vasil R 2024 · 5.03 FIP	24	SP	5.03	15.4%	7.7%	4.1%	.310	3.89	19.4%	8.3%	101	-1.14	3.63	429	75

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	2.8	111	18.7%	11.3%	1.46	5.37
Jeff Robinson ('87-'92, 0 WAR*)	3.5	118	18.3%*	10.9%*	1.38*	5.14*
Matt Beech ('98)	1.5	98	20.2%	10.0%	1.59	5.37
Kevin Foster ('01)	2.5	127	18.9%	10.0%	1.55	4.86
Armando Galarraga ('12)	2.7	108	14.6%	9.6%	1.56	4.78
Jack Armstrong ('88-'94, 2 WAR*)	3.9	131	19.2%*	9.2%*	1.59*	4.89*
Jesse Jefferson ('73-'81, -1 WAR*)	5.4	121	17.2%*	10.7%*	1.32*	5.13*