Phil Maton

P Chicago Cubs

Age 34 RHP 6'2" / 206 lbs MLB peak 0.1 · 2027 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	31	MLBNYM	71	64	3.66	3.73	22.6%	8.7%	0.6
2025	32	MLBTEX	63	61	2.79	2.12	32.7%	8.5%	1.8
2026	33	MIX2 levels	33	30	5.64	4.45	24.7%	11.0%	0.0	K 22.8% · BB 11.8% · FIP 4.76
2027PROJ	34	MLBCHC	27	28	3.97	4.16	24.8%	9.9%	0.1
2028PROJ	35	MLBCHC	28	29	4.29	4.50	23.8%	10.4%	0.0

Last 3 seasons WAR 2.5 · Next 2 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%53

FB Velo10

xwOBA vs10

CompsBlake Parker (age 34) · Yoshihisa Hirano (age 34) · Pat Venditte (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 112104vR 96

ERA3.97

FIP4.16

K%24.8%

BB%9.9%

K-BB%14.9%

Proj IP28

Value2027 · WAR

Runs saved vs league avg · 28 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL4545

CMD5555

K†6060

Statcast Percentiles

FB Velo

p1090.2

Whiff%

p5325.7%

p5322.8%

xwOBA vs

p100.389

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)
2016	23	MIX MLE	3 levels	38	0	52	201	78	11	3	0%	1.4	27.9%	5.8%	22.2%	1.5%	1.74	2.30	—
2016	23	MIX RAW	3 levels	38	0	52	201	78	11	3	0%	1.4	38.8%	5.5%	33.3%	1.5%	1.74	1.47	—
2017	24	MIX MLE	2 levels	69	0	68	284	77	22	11	0%	1.0	25.8%	7.9%	17.9%	3.8%	3.69	4.00	+0.4
2017	24	MIX RAW	2 levels	69	0	68	284	77	22	11	0%	1.0	27.1%	7.7%	19.4%	3.9%	3.69	3.90	+0.5
2018	25	MIX MLE	4 levels	57	0	60	270	74	25	4	0%	1.1	25.7%	10.3%	15.4%	1.4%	3.88	2.98	+1.1
2018	25	MIX RAW	4 levels	57	0	60	270	74	25	4	0%	1.1	27.4%	9.3%	18.1%	1.5%	3.88	2.75	+1.3
2019	26	MIX MLE	2 levels	52	0	66	280	80	21	10	0%	1.3	26.6%	7.7%	18.9%	3.7%	4.64	3.86	+0.5
2019	26	MIX RAW	2 levels	52	0	66	280	80	21	10	0%	1.3	28.6%	7.5%	21.1%	3.6%	4.64	3.60	+0.7
2020	27	MLB MLE	Cleveland Indians	23	0	22	96	32	5	1	0%	0.9	33.3%	5.2%	28.1%	1.0%	4.57	1.52	+0.8
2020	27	MLB RAW	Cleveland Indians	23	0	22	96	32	5	1	0%	0.9	33.3%	5.2%	28.1%	1.0%	4.57	1.44	+0.8
2021	28	MLB MLE	Houston Astros	65	1	67	297	85	32	6	2%	1.0	28.6%	10.8%	17.8%	2.1%	4.72	3.19	+1.1
2021	28	MLB RAW	Houston Astros	65	1	67	297	85	32	6	2%	1.0	28.6%	10.8%	17.8%	2.0%	4.72	3.16	+1.1
2022	29	MLB MLE	Houston Astros	67	0	66	281	73	22	10	0%	1.0	26.0%	7.8%	18.1%	3.7%	3.84	3.91	+0.5
2022	29	MLB RAW	Houston Astros	67	0	66	281	73	22	10	0%	1.0	26.0%	7.8%	18.1%	3.6%	3.84	3.86	+0.5
2023	30	MIX MLE	2 levels	69	0	67	278	77	23	6	0%	1.0	27.0%	8.4%	18.6%	2.3%	2.96	3.12	+1.1
2023	30	MIX RAW	2 levels	69	0	67	278	77	23	6	0%	1.0	27.7%	8.3%	19.4%	2.2%	2.96	3.00	+1.2
2024	31	MLB MLE	New York Mets	71	0	64	265	60	23	7	0%	0.9	22.6%	8.7%	14.0%	2.6%	3.66	3.74	+0.6
2024	31	MLB MLE	New York Mets	71	0	64	265	60	23	7	0%	0.9	22.6%	8.7%	14.0%	2.6%	3.66	3.74	+0.6
2024	31	MLB RAW	New York Mets	71	0	64	265	60	23	7	0%	0.9	22.6%	8.7%	14.0%	2.6%	3.66	3.73	+0.6
2025	32	MLB MLE	Texas Rangers	63	0	61	248	81	21	3	0%	1.0	32.7%	8.5%	24.2%	1.1%	2.79	2.03	+1.9
2025	32	MLB MLE	Texas Rangers	63	0	61	248	81	21	3	0%	1.0	32.7%	8.5%	24.2%	1.1%	2.79	2.03	+1.9
2025	32	MLB RAW	Texas Rangers	63	0	61	248	81	21	3	0%	1.0	32.7%	8.5%	24.2%	1.2%	2.79	2.12	+1.8
2026	33	MIX MLE	2 levels	33	0	30	146	36	16	5	0%	0.9	22.8%	11.8%	11.0%	3.8%	5.64	4.76	-0.1
2026	33	MIX MLE	2 levels	33	0	30	146	36	16	5	0%	0.9	22.8%	11.8%	11.0%	3.8%	5.64	4.76	-0.1
2026	33	MIX RAW	2 levels	33	0	30	146	36	16	5	0%	0.9	24.7%	11.0%	13.7%	3.4%	5.64	4.45	+0.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			509	1	500	2154	570	190	58	0%	1.0	26.5%	8.8%	17.6%	2.7%	4.10	3.47	+6.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	CHC	27	0	28	118	29	12	3	0%	1.0	24.8%	9.9%	14.9%	2.8%	3.97	4.16	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	CHC	28	0	29	122	29	13	4	0%	1.0	23.8%	10.4%	13.4%	3.1%	4.29	4.50	+0.0
2028	35	MLB CTX	CHC	28	0	29	122	29	13	4	0%	1.0	23.8%	10.4%	13.4%	3.1%	4.29	4.50	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		537	1	529	2276	599	203	62	0%	1.0	26.3%	8.9%	17.4%	2.7%	4.11	3.50	+6.6
/ 200 IP	—	RAW		203	0	200	861	226	77	23	0%	1.0	26.3%	8.9%	17.4%	2.7%	4.11	3.50	+2.5
Career	—	MLE		607	1	623	2646	713	227	67	0%	1.0	26.9%	8.6%	18.4%	2.5%	3.73	3.30	+6.4
/ 200 IP	—	MLE		195	0	200	849	229	73	21	0%	1.0	26.9%	8.6%	18.4%	2.5%	3.73	3.30	+2.4

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.

2019 AAAColumbus Clippers · 29 IPFIP 2.09 → 2.71 (+0.62)K% 40.2% → 35.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.17%	—	×0.880	35.35%
BB% (unintentional) /BF	7.69%	—	×1.050	8.08%
HR / BF /BF	2.56%	÷0.985	×1.100	2.86%

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 97).

Result: FIP 2.09 → 2.71, 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 AAAEl Paso Chihuahuas · 6 IPFIP 0.44 → 0.84 (+0.40)K% 37.0% → 32.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.04%	—	×0.880	32.59%
BB% (unintentional) /BF	3.70%	—	×1.050	3.89%
HR / BF /BF	0.00%	÷1.045	×1.100	0.00%

Result: FIP 0.44 → 0.84, 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).

2018 AASan Antonio Missions · 6 IPFIP 3.47 → 5.10 (+1.63)K% 30.4% → 24.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.43%	—	×0.810	24.65%
BB% (unintentional) /BF	4.35%	—	×1.100	4.78%
HR / BF /BF	4.35%	÷0.824	×1.200	6.33%

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 65).

Result: FIP 3.47 → 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).

2017 AAAEl Paso Chihuahuas · 25 IPFIP 2.09 → 2.44 (+0.36)K% 29.8% → 26.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.81%	—	×0.880	26.23%
BB% (unintentional) /BF	7.69%	—	×1.050	8.08%
HR / BF /BF	0.96%	÷1.087	×1.100	0.97%

Result: FIP 2.09 → 2.44, 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 A+Lake Elsinore Storm · 33 IPFIP 1.63 → 2.78 (+1.15)K% 37.3% → 28.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.30%	—	×0.770	28.72%
BB% (unintentional) /BF	6.35%	—	×1.150	7.30%
HR / BF /BF	1.59%	÷0.925	×1.250	2.15%

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 85).

Result: FIP 1.63 → 2.78, 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 AFort Wayne TinCaps · 13 IPFIP 0.36 → 1.18 (+0.81)K% 35.2% → 26.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.19%	—	×0.740	26.04%
BB% (unintentional) /BF	1.85%	—	×1.180	2.19%
HR / BF /BF	0.00%	÷0.888	×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 78).

Result: FIP 0.36 → 1.18, 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 AAAEl Paso Chihuahuas · 6 IPFIP 2.09 → 2.60 (+0.50)K% 57.1% → 50.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	57.14%	—	×0.880	50.29%
BB% (unintentional) /BF	9.52%	—	×1.050	10.00%
HR / BF /BF	4.76%	÷1.160	×1.100	4.52%

Result: FIP 2.09 → 2.60, 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).

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
Phil Maton (OGILVIE)	—	—	4.16	24.8%	9.9%	2.8%	—	4.50	23.8%	13.4%	29	+0.34	—	—	—
Blake Parker R 2019 · 4.65 FIP	34	SU	4.65	25.5%	8.6%	4.8%	.258	4.26	24.9%	15.4%	87	-0.39	2.52	406	75
Yoshihisa Hirano R 2018 · 3.45 FIP	34	SU	3.45	22.5%	7.3%	2.4%	.242	3.97	24.6%	15.2%	65	+0.52	3.45	132	74
Pat Venditte S 2019 · 3.53 FIP	34	SU	3.53	27.2%	9.3%	2.8%	.236	—	—	—	—	—	2.21	317	66
Rafael Martín R 2017 · 3.40 FIP	33	SU	3.40	20.4%	5.1%	2.5%	.305	4.71	22.5%	16.5%	47	+1.31	2.94	227	64
Jean Machi R 2016 · 4.36 FIP	34	SU	4.36	18.3%	6.6%	3.6%	.282	4.12	18.6%	12.0%	67	-0.24	2.16	306	64
Preston Guilmet R 2021 · 4.17 FIP	34	SU	4.17	28.6%	6.6%	4.8%	.246	—	—	—	—	—	2.31	288	61
Zack Segovia R 2016 · 3.33 FIP	33	SU	3.33	20.2%	5.9%	2.2%	.312	4.55	17.6%	4.0%	57	+1.22	3.33	144	61
Neil Wagner R 2017 · 3.11 FIP	33	SU	3.11	20.7%	8.6%	1.2%	.257	—	—	—	—	—	3.11	135	60
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	59
Scott McGough R 2024 · 4.56 FIP	34	SU	4.56	18.6%	12.2%	2.7%	.289	3.82	20.3%	13.1%	57	-0.74	3.55	429	59
Brendan Donnelly R 2005 · 4.02 FIP	34	SU	4.02	19.6%	5.9%	3.3%	.264	4.02	17.6%	8.5%	98	-0.00	2.23	385	59
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	59
Junior Guerra R 2019 · 4.13 FIP	34	SU	4.13	22.4%	9.9%	3.0%	.212	4.12	20.0%	5.9%	89	-0.01	3.18	646	58
Josh Lueke R 2019 · 4.11 FIP	34	SU	4.11	20.4%	6.4%	3.5%	.311	—	—	—	—	—	2.29	191	58
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	57
Leo Rosales R 2015 · 3.99 FIP	34	SU	3.99	18.1%	10.8%	1.9%	.261	4.24	7.8%	-0.4%	22	+0.25	3.85	130	57
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	57
Dale Thayer R 2015 · 4.34 FIP	34	SU	4.34	15.8%	7.0%	3.1%	.274	—	—	—	—	—	2.75	239	57
Dustin Molleken R 2017 · 3.38 FIP	32	SU	3.38	24.3%	12.4%	1.4%	.311	—	—	—	—	—	3.38	129	57
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	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	2.8	47	26.2%	9.3%	1.05	4.11
Will Smith ('24)	3.3	59	27.4%	8.7%	1.16	3.85
Trevor May ('23)	2.3	50	26.8%	8.5%	1.20	4.24
Jason Grilli ('17)	3.4	53	23.4%	9.8%	1.00	4.22
Rob Murphy ('85-'95, 6 WAR*)	3.1	69	25.2%*	9.2%*	1.07*	3.94*
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Paul Assenmacher ('86-'99, 12 WAR*)	4.3	61	27.8%*	8.3%*	0.98*	3.61*