Michael Grove

P Gwinnett Stripers

Age 30 RHP 6'3" / 200 lbs AAA peak 0.3 · 2027

Overview

AAARP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	26	MIX2 levels	23	14	82	5.57	3.73	26.8%	5.6%	1.6	K 25.9% · BB 5.6% · FIP 3.74
2024	27	MIX2 levels	49	2	62	4.48	3.39	25.1%	7.3%	0.9	K 25.0% · BB 7.4% · FIP 3.39
2026	29	MIX3 levels	28	5	44	3.92	3.24	28.3%	8.2%	0.7	K 24.2% · BB 9.1% · FIP 3.01
2027PROJ	30	MLBTB	58	0	61	4.08	4.04	24.0%	8.3%	0.4
2028PROJ95% MLB	31	MLBTB	46	0	48	4.19	4.27	23.3%	8.6%	0.2
2029PROJ95% MLB	32	MLBTB	38	0	40	4.39	4.52	22.5%	9.0%	0.0

Last 3 seasons WAR 3.2 · Next 3 projected WAR 0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2024

K%65

xwOBA vs64

FB Velo43

CompsJose Contreras (age 31) · Brian Sweeney (age 30) · Yoanner Negrin (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10597vR 89

ERA4.08

FIP4.04

K%24.0%

BB%8.3%

K-BB%15.8%

Proj IP61

Value2027 · WAR

Runs saved vs league avg · 61 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL5555

CMD5555

K†6060

Statcast Percentiles

FB Velo

p4394.0

Whiff%

p5826.6%

p6525.0%

xwOBA vs

p640.298

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)
2019	22	A+ MLE	Rancho Cucamonga Quakes	21	21	52	231	73	19	7	100%	2.5	24.3%	9.5%	14.9%	3.9%	6.10	4.39	—
2019	22	A+ RAW	Rancho Cucamonga Quakes	21	21	52	231	73	19	7	100%	2.5	31.6%	8.2%	23.4%	3.0%	6.10	3.14	—
2021	24	AA MLE	Tulsa Drillers	21	19	71	338	88	42	19	90%	3.4	21.1%	13.7%	7.4%	7.2%	7.86	7.01	—
2021	24	AA RAW	Tulsa Drillers	21	19	71	338	88	42	19	90%	3.4	26.0%	12.4%	13.6%	5.6%	7.86	5.87	—
2022	25	MIX MLE	3 levels	26	23	105	455	114	35	17	88%	4.1	22.3%	8.0%	14.3%	4.0%	4.02	4.40	+1.2
2022	25	MIX RAW	3 levels	26	23	105	455	114	35	17	88%	4.1	25.1%	7.7%	17.4%	3.7%	4.02	4.03	+1.7
2023	26	MIX MLE	2 levels	23	14	82	355	95	20	14	61%	3.6	25.9%	5.6%	20.3%	3.9%	5.57	3.74	+1.6
2023	26	MIX RAW	2 levels	23	14	82	355	95	20	14	61%	3.6	26.8%	5.6%	21.1%	3.9%	5.57	3.73	+1.6
2024	27	MIX MLE	2 levels	49	2	62	259	65	19	7	4%	1.3	25.0%	7.4%	17.6%	2.7%	4.48	3.39	+0.9
2024	27	MIX MLE	2 levels	49	2	62	259	65	19	7	4%	1.3	25.0%	7.4%	17.6%	2.7%	4.48	3.39	+0.9
2024	27	MIX RAW	2 levels	49	2	62	259	65	19	7	4%	1.3	25.1%	7.3%	17.8%	2.7%	4.48	3.39	+0.9
2026	29	MIX MLE	3 levels	28	5	44	184	52	15	5	18%	1.6	24.2%	9.1%	15.2%	1.5%	3.92	3.01	+0.8
2026	29	MIX MLE	3 levels	28	5	44	184	52	15	5	18%	1.6	24.2%	9.1%	15.2%	1.5%	3.92	3.01	+0.8
2026	29	MIX RAW	3 levels	28	5	44	184	52	15	5	18%	1.6	28.3%	8.2%	20.1%	2.7%	3.92	3.24	+0.7
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			67	20	156	679	157	44	27	30%	2.3	23.1%	6.5%	16.6%	4.0%	5.47	4.18	+0.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	TB	58	0	61	258	62	21	7	0%	1.1	24.0%	8.3%	15.8%	2.8%	4.08	4.04	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	TB	48	0	50	212	49	18	6	0%	1.0	23.3%	8.6%	14.6%	3.0%	4.19	4.27	+0.2
2029	32	MLB MLE	TB	40	0	42	177	40	16	6	0%	1.0	22.5%	9.0%	13.5%	3.3%	4.39	4.52	+0.0
2028	31	MLB CTX	TB	46	0	48	203	47	17	6	0%	1.0	23.3%	8.6%	14.6%	3.0%	4.19	4.27	+0.2
2029	32	MLB CTX	TB	38	0	40	169	38	15	6	0%	1.1	22.5%	9.0%	13.5%	3.3%	4.39	4.52	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		150	20	244	1048	242	77	39	13%	1.6	23.0%	7.3%	15.7%	3.7%	5.04	4.10	+1.3
/ 200 IP	—	RAW		123	16	200	860	199	63	32	13%	1.6	23.0%	7.3%	15.7%	3.7%	5.04	4.10	+1.1
Career	—	MLE		168	84	416	1822	430	160	75	50%	2.5	23.6%	8.8%	14.8%	4.1%	5.30	4.47	+3.4
/ 200 IP	—	MLE		81	40	200	875	207	77	36	50%	2.5	23.6%	8.8%	14.8%	4.1%	5.30	4.47	+2.7

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 AAAGwinnett Stripers · 35 IPFIP 2.73 → 3.01 (+0.28)K% 28.2% → 24.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.19%	—	×0.860	24.24%
BB% (unintentional) /BF	10.07%	—	×0.900	9.06%
HR / BF /BF	1.34%	÷1.000	×1.100	1.48%

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 2.73 → 3.01, 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 AAAOklahoma City Baseball Club · 11 IPFIP 3.10 → 3.60 (+0.50)K% 25.6% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.58%	—	×0.860	22.00%
BB% (unintentional) /BF	6.98%	—	×0.900	6.28%
HR / BF /BF	2.33%	÷0.896	×1.100	2.85%

Result: FIP 3.10 → 3.60, 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 AAAOklahoma City Dodgers · 13 IPFIP 1.91 → 2.57 (+0.66)K% 41.5% → 35.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.51%	—	×0.860	35.70%
BB% (unintentional) /BF	1.89%	—	×0.900	1.70%
HR / BF /BF	3.77%	÷1.006	×1.100	4.13%

Result: FIP 1.91 → 2.57, 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 AAAOklahoma City Dodgers · 60 IPFIP 4.04 → 4.59 (+0.55)K% 26.7% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.67%	—	×0.880	23.47%
BB% (unintentional) /BF	8.24%	—	×1.050	8.65%
HR / BF /BF	3.92%	÷0.997	×1.100	4.33%

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 99).

Result: FIP 4.04 → 4.59, 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 AATulsa Drillers · 16 IPFIP 2.09 → 2.88 (+0.79)K% 32.8% → 26.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.84%	—	×0.810	26.60%
BB% (unintentional) /BF	7.46%	—	×1.100	8.21%
HR / BF /BF	1.49%	÷0.993	×1.200	1.80%

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 99).

Result: FIP 2.09 → 2.88, 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 AATulsa Drillers · 71 IPFIP 5.56 → 7.01 (+1.45)K% 26.0% → 21.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.04%	—	×0.810	21.09%
BB% (unintentional) /BF	12.43%	—	×1.100	13.67%
HR / BF /BF	5.62%	÷0.935	×1.200	7.22%

Result: FIP 5.56 → 7.01, 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 A+Rancho Cucamonga Quakes · 52 IPFIP 3.14 → 4.39 (+1.25)K% 31.6% → 24.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.60%	—	×0.770	24.33%
BB% (unintentional) /BF	8.23%	—	×1.150	9.46%
HR / BF /BF	3.03%	÷0.969	×1.250	3.91%

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 94).

Result: FIP 3.14 → 4.39, 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).

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
Michael Grove (OGILVIE)	—	—	4.04	24.0%	8.3%	2.8%	—	4.38	22.9%	14.1%	92	+0.34	—	—	—
Jose Contreras R 2003 · 3.03 FIP	31	SP-	3.03	24.6%	9.9%	1.4%	.255	4.30	17.9%	9.5%	571	+1.27	2.43	1,279	65
Brian Sweeney R 2004 · 3.03 FIP	30	SW	3.03	15.9%	3.2%	1.6%	.380	4.26	9.7%	5.1%	56	+1.23	3.03	108	63
Yoanner Negrin R 2015 · 3.79 FIP	31	SW	3.79	15.1%	7.5%	1.9%	.256	3.29	15.0%	8.5%	270	-0.50	3.15	485	62
Ryan Jensen R 2005 · 4.35 FIP	29	SW	4.35	15.7%	5.2%	3.5%	.310	—	—	—	—	—	4.35	253	61
Junior Guerra R 2015 · 3.18 FIP	30	SW	3.18	26.8%	10.3%	1.9%	.269	4.15	20.8%	10.9%	390	+0.97	3.18	646	61
Tiago Da Silva R 2015 · 3.10 FIP	30	SW	3.10	19.6%	4.5%	2.0%	.278	2.38	21.4%	18.5%	98	-0.72	2.21	287	60
Mark Serrano R 2016 · 3.16 FIP	30	SU	3.16	17.7%	6.5%	1.3%	.290	4.36	21.1%	14.0%	88	+1.20	3.16	120	60
Edgar Alberto Garcia R 2017 · 4.01 FIP	29	SP-	4.01	17.3%	10.9%	1.8%	.305	—	—	—	—	—	4.01	272	59
Mike Burns R 2009 · 4.90 FIP	31	SP-	4.90	17.2%	6.6%	4.4%	.307	—	—	—	—	—	3.10	104	59
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	59
José De León R 2023 · 3.62 FIP	30	SW	3.62	21.0%	8.4%	2.2%	.301	5.66	21.1%	8.2%	75	+2.04	3.24	445	59
Ross Ohlendorf R 2013 · 4.01 FIP	30	SW	4.01	18.2%	5.3%	3.2%	.265	4.18	23.5%	14.4%	122	+0.17	3.30	617	58
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	58
Antonio Guzman R 2017 · 3.15 FIP	29	SW	3.15	19.7%	10.0%	0.8%	.249	4.96	19.3%	4.6%	44	+1.81	3.15	254	57
A.J. Morris R 2016 · 4.60 FIP	29	SW	4.60	16.9%	6.9%	3.7%	.345	—	—	—	—	—	3.02	123	57
Cody Satterwhite R 2017 · 4.22 FIP	30	SU	4.22	17.0%	7.1%	3.0%	.310	—	—	—	—	—	3.69	147	57
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	57
Britt Reames R 2002 · 3.76 FIP	28	SU	3.76	24.7%	10.4%	2.6%	.323	—	—	—	—	—	3.76	204	57
Mike Fyhrie R 2000 · 3.08 FIP	30	SU	3.08	19.5%	5.0%	1.8%	.309	3.87	13.7%	4.4%	69	+0.79	3.08	173	56
Josh A. Smith R 2018 · 2.91 FIP	30	SP-	2.91	21.7%	5.2%	1.8%	.337	4.28	19.5%	12.2%	157	+1.37	2.91	598	56

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	1.5	52	23.2%	7.6%	1.35	4.84
Chris Hatcher ('18)	1.3	53	22.9%	8.4%	1.32	4.65
Michael Tonkin ('25)	1.6	55	23.2%	8.1%	1.28	4.23
Adam Morgan ('21)	1.8	62	20.8%	7.2%	1.58	4.80
Tom Dukes ('67-'72, -2 WAR*)	1.1	43	22.7%*	8.7%*	1.16*	5.37*
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*