Logan Allen

P Columbus Clippers

Age 28 LHP 6'0" / 190 lbs AAA peak 0.6 · 2027

Overview

AAARP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	30	28	146	5.61	5.70	19.7%	9.9%	-0.5	K 18.7% · BB 9.6% · FIP 5.68
2025	26	MLBCLE	30	29	157	4.25	4.20	18.0%	9.0%	2.2
2026	27	MIX2 levels	28	23	120	4.89	3.98	25.5%	8.2%	2.0	K 22.4% · BB 7.5% · FIP 4.27
2027PROJ	28	MLBCLE	14	14	87	4.76	4.83	19.0%	8.3%	0.6
2028PROJ	29	MLBCLE	10	10	62	4.90	4.99	18.4%	8.6%	0.3
2029PROJ	30	MLBCLE	10	10	57	4.92	4.93	19.7%	8.1%	0.3

Last 3 seasons WAR 3.7 · Next 3 projected WAR 1.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs47

K%34

FB Velo10

CompsEric Stults (age 28) · John Lamb (age 28) · Roenis Elías (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 109117vR 125

ERA4.76

FIP4.83

K%19.0%

BB%8.3%

K-BB%10.7%

Proj IP87

Value2027 · WAR

Runs saved vs league avg · 87 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1091.0

Whiff%

p1019.7%

p3419.8%

xwOBA vs

p470.315

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)
2021	22	MIX MLE	2 levels	21	19	111	431	143	26	12	90%	5.3	26.3%	6.8%	19.5%	3.5%	2.26	3.67	—
2021	22	MIX RAW	2 levels	21	19	111	431	143	26	12	90%	5.3	33.2%	6.0%	27.1%	2.8%	2.26	2.63	—
2022	23	MIX MLE	2 levels	27	27	133	562	177	51	17	100%	4.9	26.4%	9.7%	16.7%	3.5%	4.75	4.00	—
2022	23	MIX RAW	2 levels	27	27	133	562	177	51	17	100%	4.9	31.5%	9.1%	22.4%	3.0%	4.75	3.25	—
2023	24	MIX MLE	2 levels	29	29	146	623	145	57	17	100%	5.0	22.7%	9.0%	13.7%	2.7%	3.71	3.83	+2.7
2023	24	MIX RAW	2 levels	29	29	146	623	145	57	17	100%	5.0	23.3%	9.1%	14.1%	2.7%	3.71	3.80	+2.8
2024	25	MIX MLE	2 levels	30	28	146	644	127	64	34	93%	4.9	18.7%	9.6%	9.1%	5.4%	5.61	5.68	-0.4
2024	25	MIX MLE	2 levels	30	28	146	644	127	64	34	93%	4.9	18.7%	9.6%	9.1%	5.4%	5.61	5.68	-0.4
2024	25	MIX RAW	2 levels	30	28	146	644	127	64	34	93%	4.9	19.7%	9.9%	9.8%	5.3%	5.61	5.70	-0.5
2025	26	MLB MLE	Cleveland Guardians	30	29	157	676	122	61	18	97%	5.2	18.0%	9.0%	9.0%	2.7%	4.25	4.18	+2.2
2025	26	MLB MLE	Cleveland Guardians	30	29	157	676	122	61	18	97%	5.2	18.0%	9.0%	9.0%	2.7%	4.25	4.18	+2.2
2025	26	MLB RAW	Cleveland Guardians	30	29	157	676	122	61	18	97%	5.2	18.0%	9.0%	9.0%	2.7%	4.25	4.20	+2.2
2026	27	MIX MLE	2 levels	28	23	120	537	137	44	19	82%	4.3	22.4%	7.5%	14.9%	3.8%	4.89	4.27	+1.6
2026	27	MIX MLE	2 levels	28	23	120	537	137	44	19	82%	4.3	22.4%	7.5%	14.9%	3.8%	4.89	4.27	+1.6
2026	27	MIX RAW	2 levels	28	23	120	537	137	44	19	82%	4.3	25.5%	8.2%	17.3%	3.5%	4.89	3.98	+2.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			81	75	396	1726	336	156	59	93%	4.9	19.5%	9.0%	10.4%	3.4%	4.55	4.52	+4.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	CLE	14	14	87	367	70	31	13	100%	6.2	19.0%	8.3%	10.7%	3.5%	4.76	4.83	+0.6
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	CLE	10	10	62	260	48	22	9	100%	6.2	18.4%	8.6%	9.8%	3.6%	4.90	4.99	+0.3
2029	30	MLB MLE	CLE	10	10	57	242	48	20	9	100%	5.7	19.7%	8.1%	11.6%	3.8%	4.92	4.93	+0.3
2030	31	MLB MLE	CLE	7	7	44	187	36	16	8	100%	6.3	19.0%	8.4%	10.5%	4.0%	5.06	5.16	+0.1
2028	29	MLB CTX	CLE	10	10	62	262	48	22	9	100%	6.2	18.4%	8.6%	9.8%	3.6%	4.90	4.99	+0.3
2029	30	MLB CTX	CLE	10	10	57	241	47	19	9	100%	5.7	19.7%	8.1%	11.6%	3.8%	4.92	4.93	+0.3
2030	31	MLB CTX	CLE	7	7	44	186	35	16	7	100%	6.3	19.0%	8.4%	10.5%	4.0%	5.06	5.16	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		108	102	559	2416	467	214	85	94%	5.2	19.3%	8.8%	10.5%	3.5%	4.66	4.52	+5.7
/ 200 IP	—	RAW		39	37	200	864	167	77	30	94%	5.2	19.3%	8.8%	10.5%	3.5%	4.66	4.52	+2.0
Career	—	MLE		165	155	812	3473	765	303	125	94%	4.9	22.0%	8.7%	13.3%	3.6%	4.30	4.32	+4.7
/ 200 IP	—	MLE		41	38	200	855	189	75	31	94%	4.9	22.0%	8.7%	13.3%	3.6%	4.30	4.32	+1.7

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 AAAColumbus Clippers · 103 IPFIP 3.84 → 4.24 (+0.40)K% 26.5% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.54%	—	×0.860	22.82%
BB% (unintentional) /BF	8.33%	—	×0.900	7.50%
HR / BF /BF	3.51%	÷1.000	×1.100	3.86%

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 3.84 → 4.24, 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 AAAColumbus Clippers · 49 IPFIP 5.67 → 5.92 (+0.25)K% 22.6% → 19.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.64%	—	×0.860	19.47%
BB% (unintentional) /BF	10.85%	—	×0.900	9.76%
HR / BF /BF	5.66%	÷1.060	×1.100	5.87%

Result: FIP 5.67 → 5.92, 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 AAAColumbus Clippers · 20 IPFIP 2.51 → 2.77 (+0.26)K% 30.2% → 26.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.23%	—	×0.860	26.00%
BB% (unintentional) /BF	10.47%	—	×0.900	9.42%
HR / BF /BF	1.16%	÷1.037	×1.100	1.23%

Result: FIP 2.51 → 2.77, 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).

2022 AAAkron RubberDucks · 73 IPFIP 2.74 → 3.72 (+0.98)K% 35.6% → 28.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.62%	—	×0.810	28.85%
BB% (unintentional) /BF	7.53%	—	×1.100	8.29%
HR / BF /BF	3.08%	÷1.014	×1.200	3.65%

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 103).

Result: FIP 2.74 → 3.72, 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 AAAColumbus Clippers · 60 IPFIP 3.80 → 4.31 (+0.50)K% 27.0% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.04%	—	×0.880	23.79%
BB% (unintentional) /BF	10.74%	—	×1.050	11.28%
HR / BF /BF	2.96%	÷1.001	×1.100	3.26%

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 100).

Result: FIP 3.80 → 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).

2021 AAAkron RubberDucks · 60 IPFIP 3.17 → 4.51 (+1.33)K% 32.9% → 26.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.90%	—	×0.810	26.65%
BB% (unintentional) /BF	5.63%	—	×1.100	6.19%
HR / BF /BF	3.90%	÷0.893	×1.200	5.24%

Result: FIP 3.17 → 4.51, 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+Lake County Captains · 51 IPFIP 1.92 → 2.71 (+0.79)K% 33.5% → 25.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.50%	—	×0.770	25.80%
BB% (unintentional) /BF	6.50%	—	×1.150	7.47%
HR / BF /BF	1.50%	÷1.222	×1.250	1.53%

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 144).

Result: FIP 1.92 → 2.71, 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
Logan Allen (OGILVIE)	—	—	—	—	—	3.5%	—	5.02	19.0%	10.7%	163	+0.19	—	—	—
Eric Stults L 2008 · 4.39 FIP	28	SP	4.39	18.0%	6.6%	3.6%	.267	4.42	14.5%	4.7%	62	+0.03	3.50	773	70
John Lamb L 2018 · 4.64 FIP	28	SP	4.64	22.5%	7.2%	4.6%	.319	—	—	—	—	—	3.38	390	65
Roenis Elías L 2017 · 5.83 FIP	28	SP	5.83	14.1%	6.1%	5.7%	.301	3.73	19.2%	11.0%	142	-2.10	3.15	728	63
Greg Smith L 2010 · 5.33 FIP	26	SP	5.33	17.0%	12.1%	3.9%	.339	—	—	—	—	—	3.37	349	63
Brandon Claussen L 2006 · 4.89 FIP	27	SP	4.89	16.2%	7.7%	4.0%	.312	—	—	—	—	—	4.41	310	62
Mike Minor L 2016 · 5.63 FIP	28	SP	5.63	19.2%	11.8%	4.8%	.330	3.76	23.2%	16.4%	443	-1.87	2.43	1,460	60
Marlon Arias L 2015 · 4.32 FIP	30	SP	4.32	16.8%	12.2%	2.0%	.330	3.73	17.2%	9.5%	22	-0.59	3.73	154	59
Jack Snodgrass L 2016 · 5.01 FIP	28	SP-	5.01	15.7%	10.1%	3.6%	.305	—	—	—	—	—	4.66	118	59
Eric DuBose L 2004 · 5.50 FIP	28	SP	5.50	14.2%	13.0%	3.5%	.274	5.45	12.6%	-1.5%	29	-0.05	3.92	178	59
Matt Tracy L 2017 · 4.82 FIP	28	SP-	4.82	16.1%	9.4%	3.5%	.325	3.24	13.9%	3.5%	49	-1.58	3.24	298	58
Roy Merritt L 2016 · 3.93 FIP	30	SP-	3.93	13.3%	5.9%	2.2%	.293	3.95	16.2%	10.4%	116	+0.02	3.93	129	57
Misael Siverio L 2017 · 4.32 FIP	28	SP	4.32	17.3%	9.1%	2.8%	.299	—	—	—	—	—	3.89	185	57
Marco Tovar L 2017 · 5.04 FIP	28	SP-	5.04	16.1%	11.3%	3.4%	.317	4.78	12.6%	7.0%	82	-0.26	3.78	327	56
Pedro Hernandez L 2016 · 4.09 FIP	27	SP	4.09	13.1%	8.9%	1.8%	.270	—	—	—	—	—	4.09	124	56
Brad Mills L 2014 · 5.61 FIP	29	SP-	5.61	18.8%	10.9%	5.0%	.364	5.00	14.5%	4.0%	182	-0.61	4.22	243	56
Sean Manaea L 2020 · 3.75 FIP	28	SP	3.75	20.3%	3.6%	3.5%	.309	3.89	24.8%	18.0%	455	+0.14	3.28	1,511	56
Matt Lujan L 2017 · 4.69 FIP	28	SP-	4.69	14.3%	6.4%	3.6%	.348	—	—	—	—	—	4.06	227	55
Darin Gorski L 2016 · 4.50 FIP	28	SP	4.50	15.0%	9.8%	2.6%	.299	—	—	—	—	—	4.50	206	55
Carlos Hernandez L 2015 · 5.42 FIP	28	SP	5.42	11.0%	5.0%	4.8%	.320	3.30	14.0%	10.2%	228	-2.12	2.83	331	55
Alejandro Soto L 2015 · 4.41 FIP	29	SP	4.41	12.8%	7.0%	2.7%	.367	4.07	14.6%	9.1%	128	-0.34	3.96	280	54

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	3.2	92	19.3%	8.8%	1.36	4.68
Ross Ohlendorf ('16)	2.9	84	17.2%	8.6%	1.38	4.82
Mark Grant ('84-'93, 0 WAR*)	3.2	91	18.0%*	8.5%*	1.41*	4.84*
Rich Folkers ('70-'77, -0 WAR*)	2.1	85	19.1%*	8.8%*	1.35*	4.91*
Jerry Garvin ('77-'82, 4 WAR*)	3.0	101	19.3%*	8.4%*	1.44*	4.52*
Brian Matusz ('16)	2.6	76	19.8%	8.7%	1.34	4.92
Daniel Norris ('23)	2.9	73	21.5%	8.9%	1.39	4.73