Griff McGarry

P Oklahoma City Comets

Age 28 RHP 6'2" / 190 lbs AAA

Overview

AAAPROSPECT

ETA2029MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	30	0	32	4.55	4.99	28.0%	23.3%	—	K 23.4% · BB 21.4% · FIP 5.08
2025	26	MIX3 levels	21	21	84	3.44	2.67	35.1%	13.9%	—	K 27.4% · BB 16.3% · FIP 3.68
2026	27	MIX2 levels	38	0	34	7.15	5.45	27.0%	28.1%	—	K 23.7% · BB 25.9% · FIP 5.10
2027PROJ	28	MLBLAD	6	0	6	5.12	5.12	26.4%	20.0%	-0.0
2028PROJ37% MLB	29	MLBLAD	15	0	16	5.12	5.17	25.9%	19.1%	-0.1
2029PROJ55% MLB	30	MLBLAD	18	0	19	5.20	5.29	25.3%	18.7%	-0.2

Next 3 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.1 / P90 0.2, comp-based) · star 0% · didn't stick 97%

CompsJeff Ames (age 28) · Jared Mortensen (age 28) · Jose De La Torre (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 130122vR 114

ERA5.12

FIP5.12

K%26.4%

BB%20.0%

K-BB%6.4%

Proj IP59

Value2027 · WAR

Runs saved vs league avg · 59 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)
2021	22	MIX MLE	2 levels	8	4	24	100	43	14	0	50%	3.0	29.9%	14.9%	15.0%	0.0%	2.96	2.46	—
2021	22	MIX RAW	2 levels	8	4	24	100	43	14	0	50%	3.0	43.0%	14.0%	29.0%	0.0%	2.96	1.29	—
2022	23	MIX MLE	3 levels	27	19	87	364	130	53	9	70%	3.2	29.0%	15.2%	13.8%	3.0%	3.71	4.20	—
2022	23	MIX RAW	3 levels	27	19	87	364	130	53	9	70%	3.2	35.7%	14.6%	21.2%	2.5%	3.71	3.28	—
2023	24	MIX MLE	3 levels	17	17	60	270	81	50	5	100%	3.5	25.9%	17.1%	8.8%	2.0%	6.00	4.17	—
2023	24	MIX RAW	3 levels	17	17	60	270	81	50	5	100%	3.5	30.0%	18.5%	11.5%	1.9%	6.00	3.98	—
2024	25	MIX MLE	2 levels	30	0	32	150	42	35	3	0%	1.1	23.4%	21.4%	2.0%	2.3%	4.55	5.08	—
2024	25	MIX MLE	2 levels	30	0	32	150	42	35	3	0%	1.1	23.4%	21.4%	2.0%	2.3%	4.55	5.08	—
2024	25	MIX RAW	2 levels	30	0	32	150	42	35	3	0%	1.1	28.0%	23.3%	4.7%	2.0%	4.55	4.99	—
2025	26	MIX MLE	3 levels	21	21	84	353	124	49	5	100%	4.0	27.4%	16.3%	11.2%	1.5%	3.44	3.68	—
2025	26	MIX MLE	3 levels	21	21	84	353	124	49	5	100%	4.0	27.4%	16.3%	11.2%	1.5%	3.44	3.68	—
2025	26	MIX RAW	3 levels	21	21	84	353	124	49	5	100%	4.0	35.1%	13.9%	21.2%	1.4%	3.44	2.67	—
2026	27	MIX MLE	2 levels	38	0	34	178	48	50	2	0%	0.9	23.7%	25.9%	-2.2%	1.3%	7.15	5.10	—
2026	27	MIX MLE	2 levels	38	0	34	178	48	50	2	0%	0.9	23.7%	25.9%	-2.2%	1.3%	7.15	5.10	—
2026	27	MIX RAW	2 levels	38	0	34	178	48	50	2	0%	0.9	27.0%	28.1%	-1.1%	1.1%	7.15	5.45	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	LAD	6	0	6	25	7	5	1	0%	1.0	26.4%	20.0%	6.4%	2.4%	5.12	5.12	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	LAD	41	0	43	182	47	35	5	0%	1.1	25.9%	19.1%	6.7%	2.6%	5.12	5.17	-0.3
2029	30	MLB MLE	LAD	34	0	35	149	38	28	4	0%	1.0	25.3%	18.7%	6.6%	2.9%	5.20	5.29	-0.3
2028	29	MLB CTX	LAD	15	0	16	68	17	13	2	0%	1.1	25.9%	19.1%	6.7%	2.6%	5.12	5.17	-0.1
2029	30	MLB CTX	LAD	18	0	19	80	20	15	2	0%	1.1	25.3%	18.7%	6.6%	2.9%	5.20	5.29	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		34	0	35	149	38	28	4	0%	1.0	25.6%	18.9%	6.7%	2.8%	5.16	4.86	-0.1
/ 200 IP	—	RAW		190	0	200	844	215	159	23	0%	1.1	25.6%	18.9%	6.7%	2.8%	5.16	4.86	-0.7
Career	—	MLE		141	61	321	1415	380	252	27	43%	2.3	26.8%	17.8%	9.0%	1.9%	4.46	4.15	-0.6
/ 200 IP	—	MLE		88	38	200	882	237	157	17	43%	2.3	26.8%	17.8%	9.0%	1.9%	4.46	4.15	-1.6

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 AAAOklahoma City Comets · 32 IPFIP 5.07 → 5.10 (+0.03)K% 27.5% → 23.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.54%	—	×0.860	23.69%
BB% (unintentional) /BF	28.74%	—	×0.900	25.87%
HR / BF /BF	1.20%	÷1.000	×1.100	1.32%

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 5.07 → 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).

2025 AAReading Fightin Phils · 72 IPFIP 2.84 → 3.68 (+0.85)K% 33.9% → 27.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.88%	—	×0.810	27.44%
BB% (unintentional) /BF	14.80%	—	×1.100	16.28%
HR / BF /BF	1.32%	÷1.036	×1.200	1.52%

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 107).

Result: FIP 2.84 → 3.68, 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 AClearwater Threshers · 7 IPFIP 0.29 → 1.39 (+1.10)K% 43.3% → 32.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	43.33%	—	×0.740	32.07%
BB% (unintentional) /BF	6.67%	—	×1.180	7.87%
HR / BF /BF	0.00%	÷1.083	×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 117).

Result: FIP 0.29 → 1.39, 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 AAALehigh Valley IronPigs · 31 IPFIP 4.94 → 5.08 (+0.15)K% 27.2% → 23.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.21%	—	×0.860	23.40%
BB% (unintentional) /BF	23.81%	—	×0.900	21.43%
HR / BF /BF	2.04%	÷0.989	×1.100	2.27%

Result: FIP 4.94 → 5.08, 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 AAReading Fightin Phils · 55 IPFIP 3.32 → 4.17 (+0.85)K% 32.0% → 25.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.03%	—	×0.810	25.95%
BB% (unintentional) /BF	15.58%	—	×1.100	17.14%
HR / BF /BF	1.73%	÷1.050	×1.200	1.98%

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).

2023 AAALehigh Valley IronPigs · 4 IPFIP 6.96 → 6.62 (−0.34)K% 14.3% → 12.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.29%	—	×0.860	12.29%
BB% (unintentional) /BF	40.00%	—	×0.900	36.00%
HR / BF /BF	0.00%	÷1.028	×1.100	0.00%

Result: FIP 6.96 → 6.62, 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+Jersey Shore BlueClaws · 47 IPFIP 2.80 → 4.56 (+1.76)K% 42.1% → 32.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	42.05%	—	×0.770	32.38%
BB% (unintentional) /BF	12.31%	—	×1.150	14.15%
HR / BF /BF	3.08%	÷0.881	×1.250	4.37%

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 76).

Result: FIP 2.80 → 4.56, 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 AAReading Fightin Phils · 33 IPFIP 2.94 → 3.67 (+0.73)K% 29.5% → 23.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.55%	—	×0.810	23.93%
BB% (unintentional) /BF	15.15%	—	×1.100	16.67%
HR / BF /BF	0.76%	÷1.051	×1.200	0.87%

Result: FIP 2.94 → 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).

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
Griff McGarry (OGILVIE)	—	—	—	—	—	2.4%	—	5.22	25.6%	6.7%	78	+0.10	—	—	—
Jeff Ames R 2019 · 4.45 FIP	28	SU	4.45	25.6%	16.8%	2.5%	.351	—	—	—	—	—	3.85	272	69
Jared Mortensen R 2016 · 4.99 FIP	28	SU	4.99	20.9%	18.8%	2.3%	.250	—	—	—	—	—	4.42	200	67
Jose De La Torre R 2013 · 5.22 FIP	27	SU	5.22	28.3%	18.9%	3.9%	.308	3.87	17.6%	6.6%	110	-1.35	2.64	141	67
Tyler Davis R 2024 · 6.02 FIP	25	SU	6.02	21.0%	18.8%	4.2%	.317	3.78	21.9%	10.2%	111	-2.24	3.20	137	65
José A. Váldez R 2018 · 4.02 FIP	28	SU	4.02	23.1%	16.2%	1.5%	.325	4.21	16.8%	6.2%	103	+0.19	4.02	328	65
Peyton Gray R 2021 · 4.27 FIP	26	SU	4.27	29.2%	14.1%	3.4%	.307	—	—	—	—	—	3.62	160	65
Emmanuel Chapman R 2024 · 4.08 FIP	25	SW	4.08	19.7%	10.6%	2.4%	.256	4.52	17.8%	1.3%	117	+0.44	3.81	198	64
Spencer Bivens R 2022 · 4.86 FIP	28	SU	4.86	19.8%	13.5%	3.1%	.265	3.85	18.1%	10.3%	272	-1.01	3.52	391	64
Dario Beltre R 2019 · 4.24 FIP	26	SU	4.24	21.4%	17.0%	1.4%	.331	—	—	—	—	—	2.71	110	64
Chris Perry R 2016 · 4.24 FIP	26	SU	4.24	21.3%	19.3%	0.9%	.254	—	—	—	—	—	3.55	113	64
Caleb Simpson R 2019 · 4.02 FIP	27	SU	4.02	24.7%	17.3%	1.5%	.189	4.23	22.4%	9.7%	54	+0.21	3.57	197	63
Zack Jones R 2018 · 5.00 FIP	27	SU	5.00	27.7%	24.1%	2.2%	.167	—	—	—	—	—	2.57	109	63
Garrett Hill R 2024 · 4.86 FIP	28	SU	4.86	20.7%	16.6%	2.6%	.307	4.58	15.4%	-3.2%	42	-0.28	3.02	539	63
Travis Hissong R 2017 · 4.17 FIP	26	SU	4.17	20.3%	13.5%	2.0%	.308	—	—	—	—	—	3.01	122	62
Dustin Antolin R 2017 · 4.35 FIP	27	SW	4.35	16.2%	14.4%	1.4%	.368	—	—	—	—	—	2.95	159	62
David Lebron R 2021 · 5.56 FIP	27	SU	5.56	26.7%	14.7%	5.2%	.278	—	—	—	—	—	4.28	144	62
Jefry Rodriguez R 2021 · 5.03 FIP	28	SW	5.03	19.4%	13.5%	3.4%	.287	4.58	19.8%	6.8%	64	-0.45	3.30	578	62
Zac Leigh R 2024 · 4.21 FIP	26	SU	4.21	21.8%	15.4%	1.8%	.367	4.74	19.4%	2.7%	87	+0.53	3.70	201	61
Adam Quintana R 2019 · 4.17 FIP	27	SW	4.17	18.6%	11.7%	2.1%	.297	—	—	—	—	—	1.72	201	61
Brian Glowicki R 2022 · 5.39 FIP	27	SU	5.39	18.2%	15.9%	3.3%	.229	—	—	—	—	—	2.31	189	61

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	0.7	46	26.0%	19.4%	1.01	5.14
Brian Bruney ('12)	1.3	43	21.2%	15.8%	0.94	4.68
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*
Derrick Turnbow ('08)	1.3	64	23.4%	14.8%	0.87	4.30
Armando Almanza ('05)	1.1	54	24.4%	14.3%	1.43	4.82
Ken Wright ('70-'74, -0 WAR*)	1.2	79	23.8%*	16.1%*	0.70*	5.24*
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*