Joe Musgrove

P El Paso Chihuahuas

Age 34 RHP 6'5" / 230 lbs AAA peak 1.3 · 2027

Overview

AAASP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	30	MIX3 levels	19	19	107	3.29	2.83	25.1%	4.8%	3.5	K 24.3% · BB 5.0% · FIP 3.02
2024	31	MIX2 levels	20	20	103	3.93	3.54	24.3%	5.4%	2.3	K 24.6% · BB 5.6% · FIP 3.56
2026	33	MIX2 levels	4	4	16	4.60	3.67	19.1%	4.4%	—	K 15.1% · BB 1.6% · FIP 4.14
2027PROJ	34	MLBSD	7	7	40	4.07	4.22	22.0%	6.9%	0.6
2028PROJ	35	MLBSD	13	13	79	4.25	4.33	23.0%	6.6%	1.0
2029PROJ	36	MLBSD	11	11	66	4.52	4.70	22.0%	7.2%	0.6

Last 3 seasons WAR 5.8 · Next 3 projected WAR 2.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2024

K%63

xwOBA vs39

FB Velo29

CompsJose Oyervides (age 34) · Manuel Flores (age 33) · Jarrett Grube (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 113105vR 97

ERA4.07

FIP4.22

K%22.0%

BB%6.9%

K-BB%15.1%

Proj IP88

Value2027 · WAR

Runs saved vs league avg · 88 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p2993.0

Whiff%

p6928.3%

p6324.6%

xwOBA vs

p390.324

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)
2015	22	MIX MLE	3 levels	19	14	101	392	99	8	9	74%	5.3	19.6%	2.3%	17.3%	2.7%	1.88	3.21	—
2015	22	MIX RAW	3 levels	19	14	101	392	99	8	9	74%	5.3	25.3%	2.0%	23.2%	2.3%	1.88	2.53	—
2016	23	MIX MLE	3 levels	27	24	147	595	142	26	18	89%	5.5	21.8%	4.5%	17.3%	3.1%	3.30	3.56	+3.3
2016	23	MIX RAW	3 levels	27	24	147	595	142	26	18	89%	5.5	23.9%	4.4%	19.5%	3.0%	3.30	3.29	+3.8
2017	24	MIX MLE	2 levels	39	16	116	484	105	29	18	41%	3.0	21.2%	5.8%	15.4%	4.0%	4.49	4.25	+0.4
2017	24	MIX RAW	2 levels	39	16	116	484	105	29	18	41%	3.0	21.7%	6.0%	15.7%	3.7%	4.49	4.05	+0.7
2018	25	MIX MLE	4 levels	23	23	133	558	117	22	13	100%	5.8	20.6%	4.1%	16.5%	2.7%	4.13	3.35	+3.4
2018	25	MIX RAW	4 levels	23	23	133	558	117	22	13	100%	5.8	21.0%	3.9%	17.0%	2.3%	4.13	3.11	+3.8
2019	26	MLB MLE	Pittsburgh Pirates	32	31	170	718	157	38	21	97%	5.3	21.9%	5.3%	16.6%	3.2%	4.44	3.66	+3.6
2019	26	MLB RAW	Pittsburgh Pirates	32	31	170	718	157	38	21	97%	5.3	21.9%	5.3%	16.6%	2.9%	4.44	3.53	+3.9
2020	27	MLB MLE	Pittsburgh Pirates	8	8	40	166	55	16	5	100%	5.0	33.1%	9.6%	23.5%	3.3%	3.86	3.31	+1.0
2020	27	MLB RAW	Pittsburgh Pirates	8	8	40	166	55	16	5	100%	5.0	33.1%	9.6%	23.5%	3.0%	3.86	3.18	+1.1
2021	28	MLB MLE	San Diego Padres	32	31	181	748	203	51	22	97%	5.7	27.1%	6.8%	20.3%	2.9%	3.18	3.25	+4.8
2021	28	MLB RAW	San Diego Padres	32	31	181	748	203	51	22	97%	5.7	27.1%	6.8%	20.3%	2.9%	3.18	3.28	+4.7
2022	29	MLB MLE	San Diego Padres	30	30	181	740	184	41	22	100%	6.0	24.9%	5.5%	19.3%	2.9%	2.93	3.29	+4.7
2022	29	MLB RAW	San Diego Padres	30	30	181	740	184	41	22	100%	6.0	24.9%	5.5%	19.3%	3.0%	2.93	3.33	+4.6
2023	30	MIX MLE	3 levels	19	19	107	442	111	21	10	100%	5.6	24.3%	5.0%	19.3%	2.4%	3.29	3.02	+3.2
2023	30	MIX RAW	3 levels	19	19	107	442	111	21	10	100%	5.6	25.1%	4.8%	20.4%	2.3%	3.29	2.83	+3.5
2024	31	MIX MLE	2 levels	20	20	103	424	103	23	14	100%	5.2	24.6%	5.6%	19.0%	3.3%	3.93	3.56	+2.3
2024	31	MIX MLE	2 levels	20	20	103	424	103	23	14	100%	5.2	24.6%	5.6%	19.0%	3.3%	3.93	3.56	+2.3
2024	31	MIX RAW	2 levels	20	20	103	424	103	23	14	100%	5.2	24.3%	5.4%	18.9%	3.3%	3.93	3.54	+2.3
2026	33	MIX MLE	2 levels	4	4	16	68	13	3	2	100%	3.9	15.1%	1.6%	13.5%	3.9%	4.60	4.14	—
2026	33	MIX MLE	2 levels	4	4	16	68	13	3	2	100%	3.9	15.1%	1.6%	13.5%	3.9%	4.60	4.14	—
2026	33	MIX RAW	2 levels	4	4	16	68	13	3	2	100%	3.9	19.1%	4.4%	14.7%	2.9%	4.60	3.67	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			206	180	1056	4385	1050	252	133	87%	5.1	23.9%	5.7%	18.2%	3.0%	3.73	3.46	+24.9
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	SD	7	7	40	169	37	12	5	100%	5.7	22.0%	6.9%	15.1%	3.1%	4.07	4.22	+0.6
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	SD	13	13	79	334	77	22	12	100%	6.1	23.0%	6.6%	16.4%	3.5%	4.20	4.28	+1.0
2029	36	MLB MLE	SD	11	11	66	277	61	20	11	100%	6.0	22.0%	7.2%	14.8%	3.9%	4.47	4.65	+0.6
2028	35	MLB CTX	SD	13	13	79	334	77	22	12	100%	6.1	23.0%	6.6%	16.4%	3.6%	4.25	4.33	+1.0
2029	36	MLB CTX	SD	11	11	66	279	61	20	11	100%	6.0	22.0%	7.2%	14.8%	3.9%	4.52	4.70	+0.6
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		230	204	1201	4997	1188	294	156	89%	5.2	23.8%	5.9%	17.9%	3.1%	3.81	3.55	+27.0
/ 200 IP	—	RAW		38	34	200	832	198	49	26	89%	5.2	23.8%	5.9%	17.9%	3.1%	3.81	3.55	+4.5
Career	—	MLE		253	220	1295	5335	1245	280	162	87%	5.1	23.3%	5.2%	18.1%	3.0%	3.54	3.46	+26.5
/ 200 IP	—	MLE		39	34	200	824	192	43	25	87%	5.1	23.3%	5.2%	18.1%	3.0%	3.54	3.46	+4.4

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.

2026 AAAEl Paso Chihuahuas · 13 IPFIP 3.77 → 4.14 (+0.38)K% 17.5% → 15.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.54%	—	×0.860	15.09%
BB% (unintentional) /BF	1.75%	—	×0.900	1.58%
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 3.77 → 4.14, 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 AAAEl Paso Chihuahuas · 4 IPFIP 1.37 → 1.64 (+0.26)K% 27.3% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.27%	—	×0.860	23.45%
BB% (unintentional) /BF	4.55%	—	×0.900	4.09%
HR / BF /BF	0.00%	÷1.052	×1.100	0.00%

Result: FIP 1.37 → 1.64, 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 ALake Elsinore Storm · 5 IPFIP -0.12 → 0.72 (+0.84)K% 38.1% → 28.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.10%	—	×0.740	28.19%
BB% (unintentional) /BF	0.00%	—	×1.180	0.00%
HR / BF /BF	0.00%	÷1.121	×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 124).

Result: FIP -0.12 → 0.72, 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).

2018 AAAIndianapolis Indians · 11 IPFIP 1.60 → 1.87 (+0.28)K% 24.4% → 21.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.44%	—	×0.880	21.51%
BB% (unintentional) /BF	4.44%	—	×1.050	4.67%
HR / BF /BF	0.00%	÷1.041	×1.100	0.00%

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 108).

Result: FIP 1.60 → 1.87, 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).

2017 AAAFresno Grizzlies · 7 IPFIP 1.56 → 1.94 (+0.38)K% 31.8% → 28.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.82%	—	×0.880	28.00%
BB% (unintentional) /BF	9.09%	—	×1.050	9.55%
HR / BF /BF	0.00%	÷0.963	×1.100	0.00%

Result: FIP 1.56 → 1.94, 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).

2016 AAAFresno Grizzlies · 59 IPFIP 3.30 → 3.67 (+0.37)K% 24.1% → 21.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.05%	—	×0.880	21.16%
BB% (unintentional) /BF	2.95%	—	×1.050	3.10%
HR / BF /BF	3.38%	÷1.040	×1.100	3.57%

Result: FIP 3.30 → 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).

2016 AACorpus Christi Hooks · 26 IPFIP 1.53 → 2.04 (+0.51)K% 29.4% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.41%	—	×0.810	23.82%
BB% (unintentional) /BF	2.94%	—	×1.100	3.24%
HR / BF /BF	0.98%	÷1.196	×1.200	0.98%

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 139).

Result: FIP 1.53 → 2.04, 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).

2015 AACorpus Christi Hooks · 45 IPFIP 4.14 → 4.79 (+0.64)K% 19.0% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.97%	—	×0.810	15.36%
BB% (unintentional) /BF	3.45%	—	×1.100	3.79%
HR / BF /BF	4.02%	÷1.059	×1.200	4.56%

Result: FIP 4.14 → 4.79, 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
Joe Musgrove (OGILVIE)	—	—	—	—	—	3.1%	—	4.45	22.6%	15.7%	145	+0.23	—	—	—
Jose Oyervides R 2016 · 3.09 FIP	34	SP	3.09	24.9%	8.2%	1.9%	.318	5.55	17.0%	7.8%	195	+2.46	3.01	407	78
Manuel Flores R 2019 · 4.32 FIP	33	SP	4.32	17.1%	7.4%	3.1%	.291	—	—	—	—	—	3.46	515	73
Jarrett Grube R 2016 · 4.74 FIP	34	SP-	4.74	18.9%	7.2%	4.2%	.280	4.41	15.8%	7.7%	134	-0.33	3.75	393	72
Josh Lowey R 2019 · 3.45 FIP	34	SP	3.45	22.4%	6.8%	2.5%	.303	—	—	—	—	—	2.22	426	69
Hiroki Kuroda R 2009 · 3.54 FIP	34	SP	3.54	17.9%	4.7%	2.5%	.270	3.43	19.1%	14.2%	618	-0.11	2.96	1,319	69
Jonathan Castellanos R 2016 · 3.40 FIP	34	SP	3.40	15.2%	7.4%	1.2%	.314	5.04	9.4%	0.3%	174	+1.64	3.40	394	68
Jorge Martinez R 2019 · 3.71 FIP	34	SP	3.71	16.3%	5.7%	2.3%	.348	—	—	—	—	—	3.53	214	66
Guillermo Moscoso R 2018 · 5.07 FIP	34	SP-	5.07	18.2%	8.4%	4.5%	.318	4.35	12.6%	5.9%	104	-0.72	3.56	486	66
Orlando Hernandez R 2004 · 3.77 FIP	34	SP	3.77	23.4%	10.0%	2.5%	.278	4.34	20.5%	11.7%	438	+0.57	3.35	1,315	66
Kenshin Kawakami R 2009 · 3.97 FIP	34	SP-	3.97	15.7%	7.6%	2.2%	.277	4.06	15.1%	9.5%	87	+0.09	3.97	244	65
Koji Uehara R 2009 · 3.52 FIP	34	SP	3.52	17.2%	3.9%	2.5%	.300	2.55	33.5%	30.6%	145	-0.97	1.28	481	65
Yoanner Negrin R 2017 · 3.15 FIP	33	SP	3.15	15.6%	6.0%	1.1%	.277	3.87	17.5%	9.4%	148	+0.72	3.15	485	64
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	59
Leo Medrano R 2016 · 4.34 FIP	33	SP	4.34	11.0%	7.3%	2.3%	.312	—	—	—	—	—	3.76	222	59
Logan Duran R 2016 · 3.77 FIP	34	SP	3.77	15.3%	8.9%	1.5%	.299	3.66	15.5%	6.6%	29	-0.11	3.42	187	59
Jason Simontacchi R 2007 · 4.96 FIP	33	SP	4.96	13.0%	5.9%	4.0%	.331	—	—	—	—	—	4.79	356	58
Matt Buschmann R 2016 · 4.84 FIP	32	SP	4.84	12.8%	8.4%	3.2%	.325	—	—	—	—	—	4.03	277	58
Albert Suárez R 2024 · 4.00 FIP	34	SP-	4.00	19.5%	6.8%	3.1%	.293	4.14	17.8%	10.6%	80	+0.14	3.58	616	58
Josh Lindblom R 2021 · 3.79 FIP	34	SP-	3.79	22.7%	6.9%	3.2%	.319	5.07	20.8%	12.0%	133	+1.28	1.83	480	57
Jonathan Albaladejo R 2017 · 3.21 FIP	34	SP	3.21	14.2%	3.3%	1.6%	.341	—	—	—	—	—	2.30	173	57

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	6.4	107	23.6%	6.1%	1.20	3.82
Collin McHugh ('23)	5.0	90	23.3%	6.7%	0.96	3.72
Ross Stripling ('24)	4.2	94	20.9%	5.6%	1.32	4.17
Kenta Maeda ('25)	4.9	123	25.8%	7.0%	1.30	4.20
Scott Bankhead ('86-'95, 10 WAR*)	4.5	100	21.2%*	7.3%*	1.36*	4.16*
Rick Aguilera ('85-'00, 22 WAR*)	6.5	81	24.3%*	6.1%*	1.18*	3.65*
Doug Bird ('73-'83, 10 WAR*)	6.1	110	20.3%*	5.8%*	1.41*	4.43*