Matt Pushard

P Jacksonville Jumbo Shrimp

Age 29 RHP 6'4" / 250 lbs AAA peak 0.2 · 2027

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MIX2 levels	41	0	55	2.28	3.03	29.8%	7.9%	—	K 24.1% · BB 8.9% · FIP 3.87
2025	27	AAAMIA	49	1	62	3.61	2.49	28.5%	9.0%	—	K 24.5% · BB 8.1% · FIP 2.84
2026	28	MIX2 levels	45	1	60	3.45	3.50	22.2%	9.6%	0.8	K 19.5% · BB 8.3% · FIP 3.81
2027PROJ	29	MLBSTL	45	0	47	4.31	4.31	21.0%	9.2%	0.1
2028PROJ76% MLB	30	MLBSTL	39	0	41	4.42	4.49	20.8%	9.5%	0.0
2029PROJ82% MLB	31	MLBSTL	35	0	37	4.57	4.68	20.6%	9.8%	-0.1

Last 3 seasons WAR 0.8 · Next 3 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.2 / P90 0.3, comp-based) · star 0% · didn't stick 96%

CompsNeil Wagner (age 29) · Joe Nelson (age 31) · Tyler Sturdevant (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 115107vR 99

ERA4.31

FIP4.31

K%21.0%

BB%9.2%

K-BB%11.8%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 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)
2022	24	ROK MLE	FCL Marlins	5	0	4	25	6	8	1	0%	0.7	24.0%	32.0%	-8.0%	4.0%	14.73	7.32	—
2022	24	ROK RAW	FCL Marlins	5	0	4	25	6	8	1	0%	0.7	24.0%	32.0%	-8.0%	4.0%	14.73	9.92	—
2023	25	MIX MLE	3 levels	39	0	53	213	52	17	2	0%	1.4	18.7%	9.0%	9.7%	1.0%	2.91	3.23	—
2023	25	MIX RAW	3 levels	39	0	53	213	52	17	2	0%	1.4	24.4%	8.0%	16.4%	0.9%	2.91	2.59	—
2024	26	MIX MLE	2 levels	41	0	55	228	68	18	6	0%	1.3	24.1%	8.9%	15.2%	3.0%	2.28	3.87	—
2024	26	MIX MLE	2 levels	41	0	55	228	68	18	6	0%	1.3	24.1%	8.9%	15.2%	3.0%	2.28	3.87	—
2024	26	MIX RAW	2 levels	41	0	55	228	68	18	6	0%	1.3	29.8%	7.9%	21.9%	2.6%	2.28	3.03	—
2025	27	AAA MLE	Jacksonville Jumbo Shrimp	49	1	62	256	73	23	3	2%	1.3	24.5%	8.1%	16.4%	1.4%	3.61	2.84	—
2025	27	AAA MLE	Jacksonville Jumbo Shrimp	49	1	62	256	73	23	3	2%	1.3	24.5%	8.1%	16.4%	1.4%	3.61	2.84	—
2025	27	AAA RAW	Jacksonville Jumbo Shrimp	49	1	62	256	73	23	3	2%	1.3	28.5%	9.0%	19.5%	1.2%	3.61	2.49	—
2026	28	MIX MLE	2 levels	45	1	60	261	58	25	5	2%	1.3	19.5%	8.3%	11.3%	2.4%	3.45	3.81	+0.5
2026	28	MIX MLE	2 levels	45	1	60	261	58	25	5	2%	1.3	19.5%	8.3%	11.3%	2.4%	3.45	3.81	+0.5
2026	28	MIX RAW	2 levels	45	1	60	261	58	25	5	2%	1.3	22.2%	9.6%	12.6%	1.9%	3.45	3.50	+0.8
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			6	0	7	32	6	4	0	0%	1.2	18.8%	12.5%	6.2%	0.0%	5.14	3.10	+0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	STL	45	0	47	198	42	18	5	0%	1.0	21.0%	9.2%	11.8%	2.6%	4.31	4.31	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	STL	51	0	53	225	47	21	6	0%	1.0	20.8%	9.5%	11.3%	2.9%	4.42	4.49	+0.0
2029	31	MLB MLE	STL	42	0	44	188	39	18	6	0%	1.1	20.6%	9.8%	10.8%	3.1%	4.57	4.68	-0.1
2028	30	MLB CTX	STL	39	0	41	173	36	16	5	0%	1.1	20.8%	9.5%	11.3%	2.9%	4.42	4.49	+0.0
2029	31	MLB CTX	STL	35	0	37	156	32	15	5	0%	1.1	20.6%	9.8%	10.8%	3.1%	4.57	4.68	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		80	0	84	358	74	36	10	0%	1.1	20.6%	9.9%	10.7%	2.7%	4.55	4.10	+0.4
/ 200 IP	—	RAW		189	0	200	850	176	85	24	0%	1.1	20.6%	9.9%	10.7%	2.7%	4.55	4.10	+1.1
Career	—	MLE		179	2	234	983	215	90	20	1%	1.3	21.8%	9.1%	12.7%	2.0%	3.27	3.54	+0.1
/ 200 IP	—	MLE		153	2	200	840	183	77	17	1%	1.3	21.8%	9.1%	12.7%	2.0%	3.27	3.54	+0.2

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 AAAJacksonville Jumbo Shrimp · 53 IPFIP 3.54 → 3.81 (+0.27)K% 22.7% → 19.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.71%	—	×0.860	19.53%
BB% (unintentional) /BF	9.17%	—	×0.900	8.25%
HR / BF /BF	2.18%	÷1.000	×1.100	2.40%

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 3.54 → 3.81, 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 AAAJacksonville Jumbo Shrimp · 62 IPFIP 2.47 → 2.84 (+0.36)K% 28.5% → 24.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.52%	—	×0.860	24.52%
BB% (unintentional) /BF	8.98%	—	×0.900	8.09%
HR / BF /BF	1.17%	÷0.903	×1.100	1.43%

Result: FIP 2.47 → 2.84, 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 AAPensacola Blue Wahoos · 53 IPFIP 3.10 → 3.87 (+0.77)K% 29.7% → 24.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.73%	—	×0.810	24.08%
BB% (unintentional) /BF	8.11%	—	×1.100	8.92%
HR / BF /BF	2.70%	÷1.064	×1.200	3.05%

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 113).

Result: FIP 3.10 → 3.87, 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).

2023 AAPensacola Blue Wahoos · 29 IPFIP 3.90 → 4.41 (+0.51)K% 17.4% → 14.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.36%	—	×0.810	14.06%
BB% (unintentional) /BF	10.74%	—	×1.100	11.82%
HR / BF /BF	1.65%	÷1.091	×1.200	1.82%

Result: FIP 3.90 → 4.41, 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 A+Beloit Sky Carp · 22 IPFIP 0.92 → 1.64 (+0.72)K% 32.6% → 25.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.58%	—	×0.770	25.09%
BB% (unintentional) /BF	4.49%	—	×1.150	5.17%
HR / BF /BF	0.00%	÷0.817	×1.250	0.00%

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 63).

Result: FIP 0.92 → 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).

2022 ROKFCL Marlins · 4 IPFIP 7.32 → 10.39 (+3.07)K% 24.0% → 16.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.00%	—	×0.680	16.32%
BB% (unintentional) /BF	32.00%	—	×1.250	40.00%
HR / BF /BF	4.00%	÷0.852	×1.400	6.57%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 70).

Result: FIP 7.32 → 10.39, 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
Matt Pushard (OGILVIE)	—	—	—	—	—	2.6%	—	4.58	20.8%	11.1%	98	+0.27	—	—	—
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	86
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	84
Tyler Sturdevant R 2015 · 4.37 FIP	29	SU	4.37	21.3%	8.5%	3.6%	.241	3.97	18.5%	11.9%	118	-0.40	3.44	149	83
Gerardo Sanchez R 2017 · 3.47 FIP	28	SU	3.47	21.6%	8.4%	2.1%	.355	3.58	20.5%	15.1%	56	+0.11	2.65	137	82
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	81
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	81
Brian Sanches R 2008 · 4.74 FIP	29	SU	4.74	18.5%	9.3%	3.7%	.378	4.01	20.5%	10.8%	182	-0.73	3.39	229	81
Diego Moreno R 2016 · 3.75 FIP	29	SU	3.75	21.0%	8.2%	2.5%	.347	3.13	17.8%	11.9%	54	-0.62	2.29	187	80
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	80
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	80
Tyler Walker R 2005 · 4.19 FIP	29	SU	4.19	19.4%	7.5%	3.2%	.303	3.61	19.7%	11.3%	93	-0.58	2.38	289	78
Kevin Gryboski R 2003 · 3.67 FIP	29	SU	3.67	16.8%	8.9%	1.6%	.295	3.92	9.4%	0.2%	82	+0.25	3.67	178	78
Marc Magliaro R 2018 · 3.94 FIP	28	SU	3.94	19.6%	7.3%	2.9%	.307	—	—	—	—	—	3.94	125	78
Justin Miller R 2016 · 3.74 FIP	29	SU	3.74	20.8%	9.7%	2.1%	.353	4.72	22.5%	16.5%	127	+0.98	2.63	292	78
Marcos Mateo R 2011 · 3.40 FIP	27	SU	3.40	25.5%	10.2%	2.1%	.361	—	—	—	—	—	3.12	104	78
Chuck King R 2024 · 3.17 FIP	26	SU	3.17	19.4%	9.9%	0.8%	.308	4.25	15.8%	8.7%	256	+1.08	3.17	294	77
Greg Burke R 2013 · 3.70 FIP	30	SU	3.70	17.9%	8.3%	1.9%	.357	3.61	22.1%	14.8%	62	-0.09	3.61	139	77
Michael Dimock R 2018 · 3.37 FIP	28	SU	3.37	23.5%	10.7%	1.6%	.346	—	—	—	—	—	3.08	166	77
Cody Hall R 2017 · 4.03 FIP	29	SU	4.03	26.8%	10.0%	3.5%	.299	3.92	25.9%	8.4%	19	-0.11	3.51	134	77
Carlos Fisher R 2011 · 4.33 FIP	28	SU	4.33	15.5%	9.1%	2.5%	.275	—	—	—	—	—	2.48	245	77

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	58	20.7%	9.6%	1.04	4.44
Kevin Quackenbush ('21)	1.0	52	21.0%	9.2%	1.04	4.41
Juan Gutierrez ('14)	1.4	57	19.4%	8.4%	1.04	4.49
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*
Gary Wayne ('89-'94, 2 WAR*)	1.2	62	19.9%*	9.4%*	1.05*	3.88*
John Johnstone ('00)	1.4	56	19.4%	9.5%	1.23	4.01
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*