John Matthews

P Amarillo Sod Poodles

Age 29 RHP 6'1" / 190 lbs AA

Overview

AAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	24	MIX2 levels	33	1	78	4.37	3.79	21.6%	12.0%	—	K 16.5% · BB 13.0% · FIP 4.51
2023	25	MIX2 levels	34	1	48	7.55	4.23	21.3%	14.5%	—	K 16.0% · BB 16.8% · FIP 5.09
2024	26	AAARI	28	0	26	8.06	4.78	14.7%	10.9%	—	K 11.9% · BB 11.9% · FIP 4.85
2025	27	No MLB games played
2026	28	No MLB games played
2027PROJ	29	MLBARI	—	—	0	4.68	4.68	20.2%	10.1%	—
2028PROJ31% MLB	30	MLBARI	5	0	5	4.75	4.82	20.2%	10.3%	-0.0

Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsWirfin Obispo (age 30) · Jim Miller (age 30) · Diego Moreno (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 122114vR 106

ERA4.68

FIP4.68

K%20.2%

BB%10.1%

K-BB%10.2%

Proj IP15

Value2027 · WAR

Runs saved vs league avg · 15 IP

Grades · Contract

Scouting Grades

K†5050

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	21	ROK MLE	AZL Rangers	5	0	9	41	12	6	0	0%	1.8	29.3%	14.6%	14.6%	0.0%	5.00	2.48	—
2019	21	ROK RAW	AZL Rangers	5	0	9	41	12	6	0	0%	1.8	29.3%	14.6%	14.6%	0.0%	5.00	2.43	—
2021	23	A MLE	Down East Wood Ducks	24	11	68	319	80	28	9	46%	2.8	18.6%	10.4%	8.2%	3.7%	6.78	4.87	—
2021	23	A RAW	Down East Wood Ducks	24	11	68	319	80	28	9	46%	2.8	25.1%	8.8%	16.3%	2.8%	6.78	3.71	—
2022	24	MIX MLE	2 levels	33	1	78	334	72	40	6	3%	2.4	16.5%	13.0%	3.4%	2.1%	4.37	4.51	—
2022	24	MIX RAW	2 levels	33	1	78	334	72	40	6	3%	2.4	21.6%	12.0%	9.6%	1.8%	4.37	3.79	—
2023	25	MIX MLE	2 levels	34	1	48	235	50	34	4	3%	1.4	16.0%	16.8%	-0.8%	2.2%	7.55	5.09	—
2023	25	MIX RAW	2 levels	34	1	48	235	50	34	4	3%	1.4	21.3%	14.5%	6.8%	1.7%	7.55	4.23	—
2024	26	AA MLE	Amarillo Sod Poodles	28	0	26	129	19	14	3	0%	0.9	11.9%	11.9%	-0.0%	2.3%	8.06	4.85	—
2024	26	AA MLE	Amarillo Sod Poodles	28	0	26	129	19	14	3	0%	0.9	11.9%	11.9%	-0.0%	2.3%	8.06	4.85	—
2024	26	AA RAW	Amarillo Sod Poodles	28	0	26	129	19	14	3	0%	0.9	14.7%	10.9%	3.9%	2.3%	8.06	4.78	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	ARI	—	—	0	—	—	—	—	—	—	20.2%	10.1%	10.2%	3.0%	4.68	4.68	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	ARI	16	0	17	72	14	7	2	0%	1.1	20.2%	10.3%	9.9%	3.2%	4.75	4.82	-0.1
2028	30	MLB CTX	ARI	5	0	5	21	4	2	1	0%	1.0	20.2%	10.3%	9.9%	3.2%	4.75	4.82	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		5	0	5	22	5	2	1	0%	1.1	20.2%	10.3%	9.9%	3.2%	4.75	4.44	+0.0
/ 200 IP	—	RAW		190	0	200	844	188	75	38	0%	1.1	20.2%	10.3%	9.9%	3.2%	4.75	4.44	+0.2
Career	—	MLE		124	13	228	1058	179	137	27	10%	1.8	16.9%	13.0%	4.0%	2.5%	6.19	4.71	-0.1
/ 200 IP	—	MLE		109	11	200	927	157	120	24	10%	1.8	16.9%	13.0%	4.0%	2.5%	6.19	4.71	-0.6

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.

2024 AAAmarillo Sod Poodles · 26 IPFIP 4.51 → 4.85 (+0.34)K% 14.7% → 11.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.73%	—	×0.810	11.93%
BB% (unintentional) /BF	10.85%	—	×1.100	11.94%
HR / BF /BF	2.33%	÷1.229	×1.200	2.27%

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 146).

Result: FIP 4.51 → 4.85, 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 AAFrisco RoughRiders · 45 IPFIP 4.35 → 5.09 (+0.74)K% 19.7% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.73%	—	×0.810	15.98%
BB% (unintentional) /BF	15.25%	—	×1.100	16.77%
HR / BF /BF	1.79%	÷0.974	×1.200	2.21%

Result: FIP 4.35 → 5.09, 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 A+Hickory Crawdads · 75 IPFIP 3.76 → 4.51 (+0.75)K% 21.4% → 16.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.38%	—	×0.770	16.47%
BB% (unintentional) /BF	11.32%	—	×1.150	13.02%
HR / BF /BF	1.89%	÷1.123	×1.250	2.10%

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 125).

Result: FIP 3.76 → 4.51, 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 ADown East Wood Ducks · 68 IPFIP 3.64 → 4.87 (+1.22)K% 25.1% → 18.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.08%	—	×0.740	18.56%
BB% (unintentional) /BF	8.78%	—	×1.180	10.36%
HR / BF /BF	2.82%	÷0.996	×1.300	3.68%

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 99).

Result: FIP 3.64 → 4.87, 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).

2019 ROKAZL Rangers · 9 IPFIP 2.48 → 3.74 (+1.25)K% 29.3% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.27%	—	×0.680	19.90%
BB% (unintentional) /BF	14.63%	—	×1.250	18.29%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

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 100).

Result: FIP 2.48 → 3.74, 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
John Matthews (OGILVIE)	—	—	4.68	20.2%	10.1%	3.0%	—	4.82	20.2%	9.9%	17	+0.14	—	—	—
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	82
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	82
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	82
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	81
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	81
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	80
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	80
Thad Weber R 2013 · 5.18 FIP	28	SU	5.18	16.4%	13.1%	3.3%	.244	4.52	12.2%	6.0%	308	-0.66	4.40	378	79
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	78
Brandon Cunniff R 2017 · 4.79 FIP	28	SU	4.79	20.1%	11.6%	3.5%	.275	6.80	13.9%	-1.9%	30	+2.01	3.89	180	78
Carlos Fisher R 2011 · 4.33 FIP	28	SU	4.33	15.5%	9.1%	2.5%	.275	—	—	—	—	—	2.48	245	77
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	77
Coleman Huntley III R 2022 · 4.05 FIP	29	SU	4.05	24.4%	10.9%	3.0%	.311	2.38	20.9%	12.6%	25	-1.67	2.38	160	77
Gregory Infante R 2016 · 4.47 FIP	29	SU	4.47	19.0%	12.3%	2.6%	.333	3.43	22.5%	15.8%	120	-1.04	2.97	230	77
Joe Colón J R 2017 · 4.25 FIP	27	SU	4.25	20.4%	12.1%	2.4%	.315	—	—	—	—	—	3.27	113	76
Marc Magliaro R 2018 · 3.94 FIP	28	SU	3.94	19.6%	7.3%	2.9%	.307	—	—	—	—	—	3.94	125	76
Francisco Mendoza R 2016 · 3.81 FIP	28	SU	3.81	17.9%	7.7%	2.3%	.344	—	—	—	—	—	3.13	120	75
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	75
Jeremy Fikac R 2004 · 4.91 FIP	29	SU	4.91	19.6%	8.0%	4.5%	.276	—	—	—	—	—	3.10	136	75
Ronald Peña R 2021 · 4.49 FIP	29	SU	4.49	16.5%	10.4%	2.7%	.288	—	—	—	—	—	3.72	187	75