Drew Parrish

P Chattanooga Lookouts

Age 29 LHP 5'11" / 200 lbs AA peak 0.3 · 2027

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	25	MIX2 levels	28	24	117	6.54	6.89	17.6%	13.4%	—	K 14.9% · BB 12.6% · FIP 7.38
2024	26	MIX2 levels	29	18	115	3.28	3.54	24.3%	4.9%	—	K 20.2% · BB 4.8% · FIP 4.66
2025	27	MIX2 levels	29	9	70	4.37	4.39	18.4%	9.4%	—	K 15.1% · BB 9.4% · FIP 4.93
2026	28	No MLB games played
2027PROJ	29	MLBCIN	1	1	1	5.03	5.03	16.0%	8.6%	0.0
2028PROJ31% MLB	30	MLBCIN	3	3	18	5.06	5.14	16.4%	8.9%	0.1
2029PROJ51% MLB	31	MLBCIN	4	4	24	5.16	5.28	16.5%	9.3%	0.0

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

Contract

No contract data on file.

Scouting grades · 20-80

Stuff45Control50Command45

CompsDanny Wirchansky (age 27) · Roy Merritt (age 30) · Edgar Osuna (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 112121vR 129

ERA5.03

FIP5.03

K%16.0%

BB%8.6%

K-BB%7.4%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 IP

Grades · Contract

Scouting Grades

STUF4545

CTRL5050

CMD4545

K†3040

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	23	MIX MLE	2 levels	22	18	99	392	118	28	8	82%	4.5	24.1%	7.9%	16.3%	2.6%	2.83	3.47	—
2021	23	MIX RAW	2 levels	22	18	99	392	118	28	8	82%	4.5	30.1%	7.1%	23.0%	2.0%	2.83	2.61	—
2022	24	MIX MLE	2 levels	27	25	129	545	99	58	20	93%	4.8	15.4%	11.3%	4.1%	4.3%	4.13	5.59	—
2022	24	MIX RAW	2 levels	27	25	129	545	99	58	20	93%	4.8	18.2%	10.6%	7.5%	3.7%	4.13	4.93	—
2023	25	MIX MLE	2 levels	28	24	117	544	96	73	32	86%	4.2	14.9%	12.6%	2.3%	7.2%	6.54	7.38	—
2023	25	MIX RAW	2 levels	28	24	117	544	96	73	32	86%	4.2	17.6%	13.4%	4.2%	5.9%	6.54	6.89	—
2024	26	MIX MLE	2 levels	29	18	115	465	113	23	16	62%	4.0	20.2%	4.8%	15.4%	4.9%	3.28	4.66	—
2024	26	MIX MLE	2 levels	29	18	115	465	113	23	16	62%	4.0	20.2%	4.8%	15.4%	4.9%	3.28	4.66	—
2024	26	MIX RAW	2 levels	29	18	115	465	113	23	16	62%	4.0	24.3%	4.9%	19.4%	3.4%	3.28	3.54	—
2025	27	MIX MLE	2 levels	29	9	70	310	57	29	9	31%	2.4	15.1%	9.4%	5.7%	3.5%	4.37	4.93	—
2025	27	MIX MLE	2 levels	29	9	70	310	57	29	9	31%	2.4	15.1%	9.4%	5.7%	3.5%	4.37	4.93	—
2025	27	MIX RAW	2 levels	29	9	70	310	57	29	9	31%	2.4	18.4%	9.4%	9.0%	2.9%	4.37	4.39	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	CIN	1	1	1	4	1	0	0	100%	1.0	16.0%	8.6%	7.4%	3.3%	5.03	5.03	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	CIN	9	9	56	236	39	21	8	100%	6.2	16.4%	8.9%	7.4%	3.5%	5.06	5.14	+0.2
2029	31	MLB MLE	CIN	8	8	48	201	33	19	7	100%	5.9	16.5%	9.3%	7.2%	3.7%	5.16	5.28	+0.1
2028	30	MLB CTX	CIN	3	3	18	76	12	7	3	100%	6.0	16.4%	8.9%	7.4%	3.5%	5.06	5.14	+0.1
2029	31	MLB CTX	CIN	4	4	24	101	17	9	4	100%	6.0	16.5%	9.3%	7.2%	3.7%	5.16	5.28	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		7	7	42	177	29	16	6	100%	6.0	16.4%	9.1%	7.3%	3.6%	5.12	4.84	+0.3
/ 200 IP	—	RAW		33	33	200	844	138	76	29	100%	6.0	16.4%	9.1%	7.3%	3.6%	5.12	4.84	+1.3
Career	—	MLE		135	94	530	2256	400	213	106	70%	3.9	17.7%	9.4%	8.3%	4.7%	4.26	5.37	+0.2
/ 200 IP	—	MLE		51	35	200	852	151	80	40	70%	3.9	17.7%	9.4%	8.3%	4.7%	4.26	5.37	+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.

2025 AAChattanooga Lookouts · 44 IPFIP 3.10 → 3.72 (+0.62)K% 22.5% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.46%	—	×0.810	18.19%
BB% (unintentional) /BF	8.02%	—	×1.100	8.82%
HR / BF /BF	1.60%	÷1.021	×1.200	1.88%

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 104).

Result: FIP 3.10 → 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).

2025 AAALouisville Bats · 26 IPFIP 6.19 → 6.78 (+0.59)K% 12.2% → 10.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.20%	—	×0.860	10.49%
BB% (unintentional) /BF	11.38%	—	×0.900	10.24%
HR / BF /BF	4.88%	÷0.901	×1.100	5.95%

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 80).

Result: FIP 6.19 → 6.78, 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 AAMississippi Braves · 108 IPFIP 3.55 → 4.66 (+1.11)K% 24.9% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.94%	—	×0.810	20.20%
BB% (unintentional) /BF	4.35%	—	×1.100	4.78%
HR / BF /BF	3.66%	÷0.906	×1.200	4.85%

Result: FIP 3.55 → 4.66, 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 AAAGwinnett Stripers · 7 IPFIP 3.70 → 3.69 (−0.01)K% 14.3% → 12.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.29%	—	×0.860	12.29%
BB% (unintentional) /BF	14.29%	—	×0.900	12.86%
HR / BF /BF	0.00%	÷0.968	×1.100	0.00%

Result: FIP 3.70 → 3.69, 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 AAAOmaha Storm Chasers · 84 IPFIP 6.93 → 7.49 (+0.57)K% 16.2% → 13.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.20%	—	×0.860	13.93%
BB% (unintentional) /BF	14.68%	—	×0.900	13.22%
HR / BF /BF	6.08%	÷0.942	×1.100	7.10%

Result: FIP 6.93 → 7.49, 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 AANorthwest Arkansas Naturals · 33 IPFIP 5.51 → 7.09 (+1.58)K% 21.5% → 17.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.48%	—	×0.810	17.40%
BB% (unintentional) /BF	10.07%	—	×1.100	11.07%
HR / BF /BF	5.37%	÷0.872	×1.200	7.39%

Result: FIP 5.51 → 7.09, 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 AAAOmaha Storm Chasers · 74 IPFIP 5.98 → 6.52 (+0.54)K% 15.5% → 13.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.45%	—	×0.880	13.60%
BB% (unintentional) /BF	13.33%	—	×1.050	14.00%
HR / BF /BF	4.55%	÷0.984	×1.100	5.08%

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 97).

Result: FIP 5.98 → 6.52, 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 AANorthwest Arkansas Naturals · 55 IPFIP 3.32 → 4.17 (+0.86)K% 22.3% → 18.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.33%	—	×0.810	18.08%
BB% (unintentional) /BF	6.51%	—	×1.100	7.16%
HR / BF /BF	2.33%	÷0.905	×1.200	3.08%

Result: FIP 3.32 → 4.17, 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
Drew Parrish (OGILVIE)	—	—	5.03	16.0%	8.6%	3.3%	—	5.20	16.4%	7.3%	104	+0.17	—	—	—
Danny Wirchansky L 2024 · 4.47 FIP	27	SP-	4.47	16.2%	7.4%	3.3%	.246	5.88	13.0%	0.2%	68	+1.41	4.47	179	81
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	77
Edgar Osuna L 2017 · 5.05 FIP	29	SP	5.05	10.6%	8.2%	3.3%	.345	5.09	10.0%	2.8%	83	+0.04	5.05	175	76
John Anderson L 2016 · 4.23 FIP	27	SP-	4.23	14.3%	8.7%	2.2%	.367	—	—	—	—	—	4.12	235	75
Carlos Teller L 2016 · 4.86 FIP	29	SP-	4.86	14.3%	10.7%	2.9%	.297	4.74	12.6%	1.1%	148	-0.12	3.75	333	75
Matt Lujan L 2017 · 4.69 FIP	28	SP-	4.69	14.3%	6.4%	3.6%	.348	—	—	—	—	—	4.06	227	74
Jack Snodgrass L 2016 · 5.01 FIP	28	SP-	5.01	15.7%	10.1%	3.6%	.305	—	—	—	—	—	4.66	118	73
Enrique Lechuga L 2015 · 4.70 FIP	29	SP-	4.70	10.0%	10.5%	2.0%	.354	3.78	10.5%	4.4%	59	-0.92	3.78	137	71
Darin Gorski L 2016 · 4.50 FIP	28	SP	4.50	15.0%	9.8%	2.6%	.299	—	—	—	—	—	4.50	206	70
Chris Michalak L 2001 · 4.92 FIP	30	SP-	4.92	11.0%	8.2%	3.1%	.291	4.71	7.0%	-4.3%	14	-0.21	4.71	186	70
Amilcar Gaxiola L 2019 · 4.61 FIP	28	SP-	4.61	11.8%	10.0%	2.3%	.316	—	—	—	—	—	4.58	321	69
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	69
Tommy Shirley L 2016 · 4.93 FIP	27	SP-	4.93	13.0%	8.8%	3.3%	.366	—	—	—	—	—	3.35	147	69
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	69
Kyle Hald L 2015 · 4.33 FIP	26	SP	4.33	12.1%	7.4%	2.4%	.313	—	—	—	—	—	4.33	124	68
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	68
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	68
Onelki Garcia L 2017 · 4.02 FIP	27	SP-	4.02	16.5%	9.3%	2.1%	.328	—	—	—	—	—	2.99	164	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	67
John Bale L 2003 · 4.12 FIP	29	SP	4.12	19.0%	5.1%	3.6%	.305	—	—	—	—	—	2.49	168	67

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	0.9	57	16.2%	8.9%	1.34	5.08
Carlos Almánzar ('05)	1.2	60	16.3%	7.9%	1.32	4.82
Jose Cabrera ('02)	1.4	68	16.2%	7.9%	1.39	4.95
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Steve Kealey ('68-'73, -1 WAR*)	1.1	54	18.5%*	7.2%*	1.32*	5.26*