Zach Logue

P Oklahoma City Baseball Club

Age 31 LHP 6'0" / 165 lbs AAA peak 0.6 · 2027

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	26	MIX2 levels	31	27	136	7.56	6.51	15.7%	8.9%	-1.6	K 14.6% · BB 9.2% · FIP 6.43
2023	27	MIX2 levels	30	21	101	6.66	5.54	20.3%	9.8%	-0.2	K 17.4% · BB 9.4% · FIP 6.02
2024	28	MIX3 levels	27	13	99	2.90	3.21	23.5%	6.9%	1.6	K 19.7% · BB 6.4% · FIP 3.67
2025	29	No MLB games played
2026	30	No MLB games played
2027PROJ	31	MLBLAD	1	1	6	4.46	4.68	19.4%	8.1%	0.0
2028PROJ29% MLB	32	MLBLAD	3	3	17	4.71	4.90	19.1%	8.6%	0.1
2029PROJ44% MLB	33	MLBLAD	4	4	21	4.95	5.13	18.5%	9.1%	0.1

Last 3 seasons WAR -0.2 · Next 3 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsKwang Hyun Kim (age 32) · Tsuyoshi Wada (age 33) · Brandon Mann (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 106114vR 122

ERA4.46

FIP4.68

K%19.4%

BB%8.1%

K-BB%11.3%

Proj IP65

Value2027 · WAR

Runs saved vs league avg · 65 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)
2017	21	ROK MLE	Bluefield Blue Jays	3	2	5	16	5	0	0	67%	1.7	31.2%	0.0%	31.2%	0.0%	0.00	0.46	—
2017	21	ROK RAW	Bluefield Blue Jays	3	2	5	16	5	0	0	67%	1.7	31.2%	0.0%	31.2%	0.0%	0.00	1.10	—
2018	22	MIX MLE	2 levels	27	25	154	633	129	34	16	93%	5.7	15.5%	6.2%	9.3%	3.0%	3.15	4.21	—
2018	22	MIX RAW	2 levels	27	25	154	633	129	34	16	93%	5.7	20.4%	5.4%	15.0%	2.5%	3.15	3.44	—
2019	23	MIX MLE	2 levels	20	18	104	445	83	36	15	90%	5.2	15.1%	8.3%	6.8%	4.9%	4.14	5.58	—
2019	23	MIX RAW	2 levels	20	18	104	445	83	36	15	90%	5.2	18.7%	8.1%	10.6%	3.4%	4.14	4.41	—
2021	25	MIX MLE	2 levels	25	24	125	511	144	27	15	96%	5.0	24.1%	5.6%	18.5%	3.2%	3.67	3.55	—
2021	25	MIX RAW	2 levels	25	24	125	511	144	27	15	96%	5.0	28.2%	5.3%	22.9%	2.9%	3.67	3.00	—
2022	26	MIX MLE	2 levels	31	27	136	642	101	57	38	87%	4.4	14.6%	9.2%	5.5%	6.2%	7.56	6.43	-1.5
2022	26	MIX RAW	2 levels	31	27	136	642	101	57	38	87%	4.4	15.7%	8.9%	6.9%	5.9%	7.56	6.51	-1.6
2023	27	MIX MLE	2 levels	30	21	101	469	95	46	23	70%	3.4	17.4%	9.4%	8.0%	5.8%	6.66	6.02	-0.7
2023	27	MIX RAW	2 levels	30	21	101	469	95	46	23	70%	3.4	20.3%	9.8%	10.4%	4.9%	6.66	5.54	-0.2
2024	28	MIX MLE	3 levels	27	13	99	405	95	28	9	48%	3.7	19.7%	6.4%	13.3%	2.6%	2.90	3.67	+1.1
2024	28	MIX MLE	3 levels	27	13	99	405	95	28	9	48%	3.7	19.7%	6.4%	13.3%	2.6%	2.90	3.67	+1.1
2024	28	MIX RAW	3 levels	27	13	99	405	95	28	9	48%	3.7	23.5%	6.9%	16.5%	2.2%	2.90	3.21	+1.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			19	10	70	318	56	22	17	53%	3.7	17.6%	6.9%	10.7%	5.3%	7.20	5.60	-0.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	LAD	1	1	6	25	5	2	1	100%	6.0	19.4%	8.1%	11.3%	3.3%	4.46	4.68	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	LAD	9	9	57	240	46	21	8	100%	6.3	19.1%	8.6%	10.4%	3.5%	4.71	4.90	+0.3
2029	33	MLB MLE	LAD	8	8	48	201	37	18	8	100%	6.0	18.5%	9.1%	9.4%	3.8%	4.95	5.13	+0.1
2028	32	MLB CTX	LAD	3	3	17	72	14	6	3	100%	5.7	19.1%	8.6%	10.4%	3.5%	4.71	4.90	+0.1
2029	33	MLB CTX	LAD	4	4	21	89	16	8	3	100%	5.2	18.5%	9.1%	9.4%	3.8%	4.95	5.13	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		25	16	107	476	86	36	23	64%	4.3	18.0%	7.6%	10.4%	4.8%	6.38	5.17	+0.3
/ 200 IP	—	RAW		47	30	200	886	160	67	43	64%	4.3	18.0%	7.6%	10.4%	4.8%	6.38	5.17	+0.5
Career	—	MLE		163	130	725	3121	549	234	135	80%	4.4	17.6%	7.5%	10.1%	4.3%	4.64	4.94	+0.3
/ 200 IP	—	MLE		45	36	200	861	151	65	37	80%	4.4	17.6%	7.5%	10.1%	4.3%	4.64	4.94	+0.4

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.

2024 AAAOklahoma City Baseball Club · 94 IPFIP 3.22 → 3.67 (+0.44)K% 23.0% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.96%	—	×0.860	19.74%
BB% (unintentional) /BF	7.12%	—	×0.900	6.41%
HR / BF /BF	2.11%	÷0.896	×1.100	2.59%

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 79).

Result: FIP 3.22 → 3.67, 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 AAAToledo Mud Hens · 90 IPFIP 5.33 → 6.02 (+0.68)K% 20.2% → 17.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.24%	—	×0.860	17.40%
BB% (unintentional) /BF	10.48%	—	×0.900	9.43%
HR / BF /BF	4.76%	÷0.901	×1.100	5.81%

Result: FIP 5.33 → 6.02, 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 AAALas Vegas Aviators · 79 IPFIP 6.59 → 6.89 (+0.30)K% 15.3% → 13.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.32%	—	×0.880	13.49%
BB% (unintentional) /BF	9.61%	—	×1.050	10.09%
HR / BF /BF	6.49%	÷1.075	×1.100	6.64%

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 115).

Result: FIP 6.59 → 6.89, 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 AAABuffalo Bisons · 89 IPFIP 3.00 → 3.31 (+0.31)K% 25.2% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.20%	—	×0.880	22.18%
BB% (unintentional) /BF	5.42%	—	×1.050	5.69%
HR / BF /BF	2.44%	÷1.081	×1.100	2.48%

Result: FIP 3.00 → 3.31, 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 AANew Hampshire Fisher Cats · 36 IPFIP 3.01 → 4.19 (+1.18)K% 35.9% → 29.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.92%	—	×0.810	29.09%
BB% (unintentional) /BF	4.93%	—	×1.100	5.42%
HR / BF /BF	4.23%	÷0.973	×1.200	5.21%

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 95).

Result: FIP 3.01 → 4.19, 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 AANew Hampshire Fisher Cats · 101 IPFIP 4.42 → 5.58 (+1.16)K% 18.6% → 15.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.59%	—	×0.810	15.06%
BB% (unintentional) /BF	7.53%	—	×1.100	8.28%
HR / BF /BF	3.53%	÷0.860	×1.200	4.92%

Result: FIP 4.42 → 5.58, 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 AAABuffalo Bisons · 3 IPFIP 3.94 → 4.27 (+0.33)K% 20.0% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.880	17.60%
BB% (unintentional) /BF	20.00%	—	×1.050	21.00%
HR / BF /BF	0.00%	÷1.000	×1.100	0.00%

Result: FIP 3.94 → 4.27, 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 A+Dunedin Blue Jays · 100 IPFIP 3.13 → 3.72 (+0.59)K% 20.2% → 15.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.24%	—	×0.770	15.58%
BB% (unintentional) /BF	5.48%	—	×1.150	6.30%
HR / BF /BF	1.90%	÷1.147	×1.250	2.08%

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 129).

Result: FIP 3.13 → 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).

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
Zach Logue (OGILVIE)	—	—	—	—	—	3.3%	—	5.00	18.8%	9.9%	104	+0.32	—	—	—
Kwang Hyun Kim L 2020 · 3.76 FIP	32	SP	3.76	15.6%	6.5%	2.1%	.214	4.21	17.7%	9.5%	107	+0.45	3.76	146	77
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	76
Brandon Mann L 2016 · 4.72 FIP	32	SP	4.72	19.4%	7.9%	4.1%	.320	3.97	19.0%	7.6%	128	-0.75	3.59	190	70
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	70
John Bale L 2003 · 4.12 FIP	29	SP	4.12	19.0%	5.1%	3.6%	.305	—	—	—	—	—	2.49	168	68
Tomas Solis L 2015 · 4.20 FIP	32	SP	4.20	15.0%	6.2%	2.9%	.264	5.09	12.0%	3.7%	159	+0.89	4.20	327	67
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	67
Arturo Lopez L 2015 · 4.80 FIP	32	SP	4.80	13.7%	6.2%	3.8%	.301	4.80	10.9%	4.2%	217	+0.00	4.34	445	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
Santiago Gutierrez L 2017 · 3.95 FIP	31	SP-	3.95	15.0%	8.2%	2.0%	.366	6.54	17.1%	3.7%	46	+2.59	3.90	341	63
Alejandro Astorga L 2017 · 4.01 FIP	30	SP	4.01	14.4%	8.2%	2.0%	.306	—	—	—	—	—	3.72	311	62
Carlos Teller L 2017 · 4.63 FIP	30	SP	4.63	12.2%	9.6%	2.5%	.322	4.90	13.1%	-1.1%	60	+0.27	3.75	333	62
Everett Teaford L 2015 · 4.42 FIP	31	SP-	4.42	13.9%	7.6%	2.8%	.324	—	—	—	—	—	4.42	208	61
Sean Nolin L 2021 · 4.54 FIP	31	SP-	4.54	20.4%	8.9%	3.7%	.316	5.87	19.3%	12.9%	23	+1.33	3.79	309	61
Marco Tovar L 2019 · 4.78 FIP	30	SP	4.78	12.6%	5.6%	3.7%	.316	—	—	—	—	—	3.78	327	60
Irwin Delgado L 2019 · 4.73 FIP	30	SP	4.73	15.6%	9.5%	3.2%	.404	—	—	—	—	—	3.52	383	60
Roy Merritt L 2017 · 3.95 FIP	31	SP	3.95	16.2%	5.8%	2.7%	.339	—	—	—	—	—	3.93	129	60
Kelvin Marte L 2019 · 5.25 FIP	31	SP	5.25	12.0%	10.8%	3.3%	.340	—	—	—	—	—	3.44	360	60
Enrique Lechuga L 2017 · 3.78 FIP	31	SP	3.78	10.5%	6.1%	1.5%	.390	—	—	—	—	—	3.78	137	58
Daniel Rodriguez L 2016 · 4.46 FIP	31	SP	4.46	19.3%	11.1%	2.9%	.333	4.32	16.9%	8.2%	226	-0.14	2.89	391	57

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	1.2	60	18.6%	8.1%	1.57	5.42
Giovanni Carrara ('06)	2.4	59	16.3%	9.7%	1.41	4.69
JC Ramírez ('19)	1.4	72	16.4%	8.4%	1.44	4.71
Juan Gutierrez ('14)	1.4	57	19.4%	8.4%	1.04	4.49
Minnie Rojas ('66-'68, 1 WAR*)	1.3	87	17.1%*	6.5%*	1.35*	4.07*
Steve Shields ('85-'89, -3 WAR*)	1.1	55	17.0%*	9.0%*	1.61*	5.49*
Rich Hinton ('71-'79, -2 WAR*)	1.2	50	21.3%*	8.0%*	1.15*	5.41*