Matt Gage

P San Francisco Giants

Age 34 LHP 6'4" / 261 lbs MLB ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	31	AAANYM	40	0	42	4.10	3.48	28.3%	12.2%	—	K 24.4% · BB 11.0% · FIP 3.70
2025	32	MIX2 levels	61	3	69	2.23	2.46	21.1%	5.7%	1.7	K 19.5% · BB 5.6% · FIP 2.62
2026	33	MIX3 levels	38	4	32	6.25	5.78	17.0%	12.9%	-0.5	K 17.5% · BB 13.5% · FIP 6.16
2027PROJ	34	MLBSF	71	0	75	4.57	4.82	18.7%	10.1%	-0.2
2028PROJ79% MLB	35	MLBSF	51	0	54	4.86	5.10	18.0%	10.4%	-0.3
2029PROJ70% MLB	36	MLBSF	21	0	22	5.16	5.40	17.3%	10.8%	-0.2

Last 3 seasons WAR 1.3 · Next 3 projected WAR -0.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo18

K%18

xwOBA vs16

CompsJames Jones (age 34) · Alejandro Soto (age 33) · Luke Westphal (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 108117vR 125

ERA4.57

FIP4.82

K%18.7%

BB%10.1%

K-BB%8.5%

Proj IP90

Value2027 · WAR

Runs saved vs league avg · 90 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1892.2

Whiff%

p4424.4%

p1817.5%

xwOBA vs

p160.352

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	2 levels	24	22	116	480	101	22	5	92%	4.8	16.0%	5.3%	10.7%	1.4%	4.27	3.20	—
2015	22	MIX RAW	2 levels	24	22	116	480	101	22	5	92%	4.8	21.0%	4.6%	16.5%	1.0%	4.27	2.49	—
2016	23	AA MLE	Richmond Flying Squirrels	23	23	136	564	106	34	2	100%	5.9	15.2%	6.6%	8.6%	0.4%	3.38	2.89	—
2016	23	AA RAW	Richmond Flying Squirrels	23	23	136	564	106	34	2	100%	5.9	18.8%	6.0%	12.8%	0.4%	3.38	2.48	—
2017	24	MIX MLE	2 levels	26	25	145	638	95	39	8	96%	5.6	12.5%	6.6%	5.9%	1.7%	4.21	3.80	—
2017	24	MIX RAW	2 levels	26	25	145	638	95	39	8	96%	5.6	14.9%	6.1%	8.8%	1.3%	4.21	3.31	—
2018	25	MIX MLE	2 levels	20	19	103	472	80	25	7	95%	5.2	14.4%	5.6%	8.8%	1.7%	5.16	3.51	—
2018	25	MIX RAW	2 levels	20	19	103	472	80	25	7	95%	5.2	16.9%	5.3%	11.7%	1.5%	5.16	3.16	—
2019	26	AAA MLE	Diablos Rojos del Mexico	25	24	118	523	106	39	14	96%	4.7	17.8%	7.8%	10.0%	2.6%	5.57	4.03	—
2019	26	AAA RAW	Diablos Rojos del Mexico	25	24	118	523	106	39	14	96%	4.7	20.3%	7.5%	12.8%	2.7%	5.57	3.84	—
2021	28	MIX MLE	2 levels	43	0	46	198	58	13	8	0%	1.1	25.1%	6.9%	18.2%	4.5%	4.14	4.34	—
2021	28	MIX RAW	2 levels	43	0	46	198	58	13	8	0%	1.1	29.3%	6.6%	22.7%	4.0%	4.14	3.69	—
2022	29	MIX MLE	2 levels	52	0	55	218	58	20	2	0%	1.1	24.1%	9.5%	14.6%	1.0%	2.11	2.82	+1.1
2022	29	MIX RAW	2 levels	52	0	55	218	58	20	2	0%	1.1	26.6%	9.2%	17.4%	0.9%	2.11	2.56	+1.3
2023	30	MIX MLE	2 levels	39	0	44	194	47	23	6	0%	1.1	20.1%	10.8%	9.3%	3.7%	4.30	4.79	-0.1
2023	30	MIX RAW	2 levels	39	0	44	194	47	23	6	0%	1.1	24.2%	11.9%	12.4%	3.1%	4.30	4.30	+0.1
2024	31	AAA MLE	Syracuse Mets	40	0	42	180	51	22	4	0%	1.0	24.4%	11.0%	13.4%	2.3%	4.10	3.70	—
2024	31	AAA MLE	Syracuse Mets	40	0	42	180	51	22	4	0%	1.0	24.4%	11.0%	13.4%	2.3%	4.10	3.70	—
2024	31	AAA RAW	Syracuse Mets	40	0	42	180	51	22	4	0%	1.0	28.3%	12.2%	16.1%	2.2%	4.10	3.48	—
2025	32	MIX MLE	2 levels	61	3	69	279	59	16	2	5%	1.1	19.5%	5.6%	14.0%	0.8%	2.23	2.62	+1.6
2025	32	MIX MLE	2 levels	61	3	69	279	59	16	2	5%	1.1	19.5%	5.6%	14.0%	0.8%	2.23	2.62	+1.6
2025	32	MIX RAW	2 levels	61	3	69	279	59	16	2	5%	1.1	21.1%	5.7%	15.4%	0.7%	2.23	2.46	+1.7
2026	33	MIX MLE	3 levels	38	4	32	147	25	19	6	11%	0.8	17.5%	13.5%	4.0%	5.1%	6.25	6.16	-0.6
2026	33	MIX MLE	3 levels	38	4	32	147	25	19	6	11%	0.8	17.5%	13.5%	4.0%	5.1%	6.25	6.16	-0.6
2026	33	MIX RAW	3 levels	38	4	32	147	25	19	6	11%	0.8	17.0%	12.9%	4.1%	4.1%	6.25	5.78	-0.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			83	2	78	340	69	36	8	2%	0.9	20.3%	10.6%	9.7%	2.4%	3.69	4.05	+0.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	SF	71	0	75	317	59	32	9	0%	1.1	18.7%	10.1%	8.5%	3.0%	4.57	4.82	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	SF	65	0	68	287	52	30	10	0%	1.0	18.0%	10.4%	7.6%	3.3%	4.86	5.10	-0.4
2029	36	MLB MLE	SF	30	0	32	135	23	15	5	0%	1.1	17.3%	10.8%	6.5%	3.7%	5.16	5.40	-0.3
2028	35	MLB CTX	SF	51	0	54	228	41	24	8	0%	1.1	18.0%	10.4%	7.6%	3.3%	4.86	5.10	-0.3
2029	36	MLB CTX	SF	21	0	22	93	16	10	3	0%	1.0	17.3%	10.8%	6.5%	3.7%	5.16	5.40	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		156	2	154	662	126	70	19	1%	1.0	19.1%	10.6%	8.5%	2.9%	4.31	4.40	+0.3
/ 200 IP	—	RAW		202	3	200	858	163	91	25	1%	1.0	19.1%	10.6%	8.5%	2.9%	4.31	4.40	+0.3
Career	—	MLE		391	120	905	3893	669	283	74	31%	2.3	17.2%	7.3%	9.9%	1.9%	4.17	3.61	-0.3
/ 200 IP	—	MLE		86	27	200	860	148	62	16	31%	2.3	17.2%	7.3%	9.9%	1.9%	4.17	3.61	-0.3

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 AAASacramento River Cats · 38 IPFIP 2.42 → 2.77 (+0.36)K% 22.5% → 19.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.54%	—	×0.860	19.38%
BB% (unintentional) /BF	3.52%	—	×0.900	3.17%
HR / BF /BF	1.41%	÷0.938	×1.100	1.65%

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 88).

Result: FIP 2.42 → 2.77, 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 AAASyracuse Mets · 42 IPFIP 3.48 → 3.70 (+0.23)K% 28.3% → 24.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.33%	—	×0.860	24.37%
BB% (unintentional) /BF	12.22%	—	×0.900	11.00%
HR / BF /BF	2.22%	÷1.059	×1.100	2.31%

Result: FIP 3.48 → 3.70, 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 AAASugar Land Space Cowboys · 37 IPFIP 4.29 → 4.79 (+0.50)K% 23.4% → 20.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.35%	—	×0.860	20.08%
BB% (unintentional) /BF	11.98%	—	×0.900	10.78%
HR / BF /BF	2.99%	÷0.896	×1.100	3.67%

Result: FIP 4.29 → 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).

2022 AAABuffalo Bisons · 42 IPFIP 2.25 → 2.63 (+0.39)K% 27.4% → 24.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.38%	—	×0.880	24.10%
BB% (unintentional) /BF	8.93%	—	×1.050	9.38%
HR / BF /BF	0.60%	÷0.951	×1.100	0.69%

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 90).

Result: FIP 2.25 → 2.63, 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 AAAReno Aces · 32 IPFIP 4.44 → 5.15 (+0.71)K% 27.0% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.03%	—	×0.880	23.78%
BB% (unintentional) /BF	8.11%	—	×1.050	8.51%
HR / BF /BF	4.73%	÷0.958	×1.100	5.43%

Result: FIP 4.44 → 5.15, 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 AAAmarillo Sod Poodles · 13 IPFIP 1.41 → 1.95 (+0.54)K% 36.0% → 29.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.00%	—	×0.810	29.16%
BB% (unintentional) /BF	2.00%	—	×1.100	2.20%
HR / BF /BF	2.00%	÷1.271	×1.200	1.89%

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 154).

Result: FIP 1.41 → 1.95, 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 AAADiablos Rojos del Mexico · 118 IPFIP 3.80 → 4.03 (+0.23)K% 20.3% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.27%	—	×0.880	17.84%
BB% (unintentional) /BF	7.46%	—	×1.050	7.83%
HR / BF /BF	2.68%	÷1.116	×1.100	2.64%

Result: FIP 3.80 → 4.03, 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 AAALas Vegas 51s · 63 IPFIP 3.28 → 3.55 (+0.27)K% 16.0% → 14.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.00%	—	×0.880	14.08%
BB% (unintentional) /BF	6.33%	—	×1.050	6.65%
HR / BF /BF	1.33%	÷1.009	×1.100	1.45%

Result: FIP 3.28 → 3.55, 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 Gage (OGILVIE)	—	—	—	—	—	3.0%	—	5.20	17.8%	7.2%	100	+0.38	—	—	—
James Jones L 2023 · 4.67 FIP	34	SU	4.67	13.7%	11.5%	2.3%	.246	—	—	—	—	—	3.58	127	72
Alejandro Soto L 2019 · 4.03 FIP	33	SW	4.03	17.1%	6.9%	2.7%	.376	—	—	—	—	—	3.96	280	69
Luke Westphal L 2022 · 4.35 FIP	33	SW	4.35	24.2%	13.4%	2.9%	.302	5.19	15.7%	-0.7%	26	+0.84	2.97	294	64
Juan Pablo Perez L 2013 · 3.68 FIP	34	SU	3.68	25.2%	11.5%	2.3%	.250	3.68	26.5%	11.2%	51	-0.00	1.75	104	63
Clay Rapada L 2015 · 3.84 FIP	34	SU	3.84	14.3%	8.0%	1.7%	.299	—	—	—	—	—	3.00	120	63
Tom Martin L 2004 · 4.74 FIP	34	SU	4.74	14.7%	7.8%	3.4%	.278	3.96	14.7%	7.1%	86	-0.78	3.40	303	63
Heriberto Ruelas L 2016 · 3.75 FIP	34	SU	3.75	15.0%	8.9%	1.4%	.310	3.42	17.2%	10.5%	49	-0.33	2.95	117	62
Hideki Okajima L 2010 · 4.27 FIP	34	SU	4.27	15.5%	7.0%	2.9%	.333	—	—	—	—	—	3.05	238	61
Dan Runzler L 2019 · 4.84 FIP	34	SU	4.84	16.0%	13.0%	2.6%	.284	—	—	—	—	—	2.84	187	61
Ryan Buchter L 2021 · 5.24 FIP	34	SU	5.24	22.9%	13.2%	4.4%	.267	—	—	—	—	—	2.37	296	60
Tim Byrdak L 2008 · 5.18 FIP	34	SU	5.18	19.8%	11.4%	4.2%	.229	4.30	22.4%	10.5%	138	-0.88	2.85	320	59
Pedro Borbón L 2002 · 4.57 FIP	34	SU	4.57	21.6%	7.3%	4.3%	.277	—	—	—	—	—	2.26	264	59
Doug Creek L 2003 · 5.00 FIP	34	SU	5.00	15.9%	13.0%	2.9%	.255	6.28	17.8%	10.9%	22	+1.28	4.48	277	54
Carlos Pulido L 2004 · 4.41 FIP	32	SU	4.41	16.4%	5.5%	3.6%	.341	—	—	—	—	—	2.91	111	54
Jamie Walker L 2005 · 3.81 FIP	34	SU	3.81	14.4%	4.8%	2.4%	.270	4.46	16.3%	12.2%	147	+0.65	3.48	442	54
Joey Eischen L 2004 · 3.63 FIP	34	SU	3.63	21.2%	7.5%	2.5%	.255	3.37	19.0%	9.1%	51	-0.26	2.13	294	53
Edwin Escobar L 2024 · 5.12 FIP	32	SU	5.12	19.6%	14.0%	3.5%	.275	—	—	—	—	—	4.28	218	53
Vic Darensbourg L 2005 · 4.11 FIP	34	SU	4.11	9.4%	5.2%	2.1%	.275	—	—	—	—	—	2.94	287	53
Scott Rice L 2015 · 3.67 FIP	33	SU	3.67	22.9%	17.2%	0.6%	.266	—	—	—	—	—	3.10	104	51
Stephen Randolph L 2007 · 5.97 FIP	33	SU	5.97	28.2%	19.2%	5.1%	.450	—	—	—	—	—	4.83	155	44

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	1.4	55	18.8%	10.6%	1.15	4.46
Josias Manzanillo ('04)	1.7	57	20.0%	10.2%	1.21	4.71
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Bill Pleis ('61-'66, -0 WAR*)	1.4	56	19.7%*	9.8%*	1.15*	4.53*
Bill Scherrer ('82-'88, 1 WAR*)	1.6	62	20.7%*	10.2%*	1.19*	4.44*
John Johnstone ('00)	1.4	56	19.4%	9.5%	1.23	4.01
Bill Risley ('98)	1.1	55	21.9%	10.9%	1.26	3.98