Matt Waldron

P Washington Nationals

Age 30 RHP 6'2" / 185 lbs MLB peak 0.3 · 2027 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MIX2 levels	31	30	166	4.87	3.95	21.2%	6.1%	2.9	K 20.8% · BB 6.0% · FIP 3.93
2025	28	MIX4 levels	22	22	95	6.54	4.16	20.5%	8.4%	1.4	K 17.8% · BB 6.4% · FIP 4.25
2026	29	MIX2 levels	25	12	70	4.52	3.75	18.8%	5.8%	0.7	K 17.7% · BB 5.6% · FIP 3.83
2027PROJ	30	MLBWSH	4	4	23	4.49	4.51	16.6%	5.9%	0.2
2028PROJ95% MLB	31	MLBWSH	7	7	43	4.64	4.74	15.9%	6.2%	0.3
2029PROJ95% MLB	32	MLBWSH	6	6	36	4.85	5.00	15.1%	6.6%	0.2

Last 3 seasons WAR 4.9 · Next 3 projected WAR 0.7Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs72

FB Velo15

K%14

CompsDavid Hale (age 30) · Zack Segovia (age 32) · Travis Smith (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 109101vR 93

ERA4.49

FIP4.51

K%16.6%

BB%5.9%

K-BB%10.7%

Proj IP23

Value2027 · WAR

Runs saved vs league avg · 23 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1592.0

Whiff%

p1017.8%

p1417.0%

xwOBA vs

p720.291

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	22	ROK MLE	AZL Indians Red	4	0	10	34	17	0	1	0%	2.5	50.0%	0.0%	50.0%	2.9%	0.90	0.49	—
2019	22	ROK RAW	AZL Indians Red	4	0	10	34	17	0	1	0%	2.5	50.0%	0.0%	50.0%	2.9%	0.90	1.00	—
2021	24	MIX MLE	2 levels	20	20	104	445	103	35	8	100%	5.2	18.1%	8.9%	9.2%	2.2%	4.25	3.91	—
2021	24	MIX RAW	2 levels	20	20	104	445	103	35	8	100%	5.2	23.1%	7.9%	15.3%	1.8%	4.25	3.13	—
2022	25	MIX MLE	2 levels	25	25	114	512	96	38	14	100%	4.5	16.0%	7.9%	8.1%	2.8%	6.26	4.29	—
2022	25	MIX RAW	2 levels	25	25	114	512	96	38	14	100%	4.5	18.8%	7.4%	11.3%	2.7%	6.26	4.01	—
2023	26	MIX MLE	2 levels	28	24	134	589	130	42	27	86%	4.8	19.7%	6.6%	13.1%	4.7%	6.40	4.85	+0.9
2023	26	MIX RAW	2 levels	28	24	134	589	130	42	27	86%	4.8	22.1%	7.1%	14.9%	4.6%	6.40	4.72	+1.0
2024	27	MIX MLE	2 levels	31	30	166	709	150	43	24	97%	5.4	20.8%	6.0%	14.8%	3.3%	4.87	3.93	+2.9
2024	27	MIX MLE	2 levels	31	30	166	709	150	43	24	97%	5.4	20.8%	6.0%	14.8%	3.3%	4.87	3.93	+2.9
2024	27	MIX RAW	2 levels	31	30	166	709	150	43	24	97%	5.4	21.2%	6.1%	15.1%	3.4%	4.87	3.95	+2.9
2025	28	MIX MLE	4 levels	22	22	95	430	88	36	13	100%	4.3	17.8%	6.4%	11.4%	3.4%	6.54	4.25	+1.3
2025	28	MIX MLE	4 levels	22	22	95	430	88	36	13	100%	4.3	17.8%	6.4%	11.4%	3.4%	6.54	4.25	+1.3
2025	28	MIX RAW	4 levels	22	22	95	430	88	36	13	100%	4.3	20.5%	8.4%	12.1%	3.0%	6.54	4.16	+1.4
2026	29	MIX MLE	2 levels	25	12	70	293	55	17	8	48%	2.8	17.7%	5.6%	12.1%	2.8%	4.52	3.83	+0.6
2026	29	MIX MLE	2 levels	25	12	70	293	55	17	8	48%	2.8	17.7%	5.6%	12.1%	2.8%	4.52	3.83	+0.6
2026	29	MIX RAW	2 levels	25	12	70	293	55	17	8	48%	2.8	18.8%	5.8%	13.0%	2.7%	4.52	3.75	+0.7
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			53	37	235	1017	200	69	38	70%	4.4	19.7%	6.8%	12.9%	3.7%	5.16	4.38	+2.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	WSH	4	4	23	97	16	6	3	100%	5.8	16.6%	5.9%	10.7%	3.1%	4.49	4.51	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	WSH	8	8	46	193	31	12	6	100%	5.7	15.9%	6.2%	9.7%	3.3%	4.64	4.74	+0.3
2029	32	MLB MLE	WSH	6	6	37	158	24	10	6	100%	6.2	15.1%	6.6%	8.5%	3.6%	4.85	5.00	+0.2
2028	31	MLB CTX	WSH	7	7	43	182	29	11	6	100%	6.1	15.9%	6.2%	9.7%	3.3%	4.64	4.74	+0.3
2029	32	MLB CTX	WSH	6	6	36	152	23	10	5	100%	6.0	15.1%	6.6%	8.5%	3.6%	4.85	5.00	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		66	50	314	1350	252	90	49	76%	4.8	18.6%	6.7%	12.0%	3.7%	5.06	4.38	+3.8
/ 200 IP	—	RAW		42	32	200	859	160	57	31	76%	4.8	18.6%	6.7%	12.0%	3.7%	5.06	4.38	+2.4
Career	—	MLE		155	133	692	3012	571	205	99	86%	4.5	19.0%	6.8%	12.2%	3.3%	5.44	4.16	+3.3
/ 200 IP	—	MLE		45	38	200	871	165	59	29	86%	4.5	19.0%	6.8%	12.2%	3.3%	5.44	4.16	+2.1

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 · 27 IPFIP 2.55 → 2.79 (+0.24)K% 22.2% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.22%	—	×0.860	19.11%
BB% (unintentional) /BF	6.06%	—	×0.900	5.45%
HR / BF /BF	1.01%	÷1.000	×1.100	1.11%

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 2.55 → 2.79, 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).

2025 AAAEl Paso Chihuahuas · 82 IPFIP 3.89 → 4.25 (+0.35)K% 20.7% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.65%	—	×0.860	17.76%
BB% (unintentional) /BF	7.07%	—	×0.900	6.36%
HR / BF /BF	2.99%	÷0.981	×1.100	3.35%

Result: FIP 3.89 → 4.25, 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 AASan Antonio Missions · 6 IPFIP 4.56 → 5.52 (+0.96)K% 20.7% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.69%	—	×0.810	16.76%
BB% (unintentional) /BF	10.34%	—	×1.100	11.38%
HR / BF /BF	3.45%	÷0.950	×1.200	4.36%

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 90).

Result: FIP 4.56 → 5.52, 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 AAAEl Paso Chihuahuas · 20 IPFIP 3.80 → 4.04 (+0.23)K% 20.2% → 17.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.24%	—	×0.860	17.40%
BB% (unintentional) /BF	3.57%	—	×0.900	3.21%
HR / BF /BF	3.57%	÷1.078	×1.100	3.65%

Result: FIP 3.80 → 4.04, 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).

2023 AAAEl Paso Chihuahuas · 92 IPFIP 4.38 → 4.68 (+0.30)K% 23.8% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.80%	—	×0.860	20.47%
BB% (unintentional) /BF	7.21%	—	×0.900	6.49%
HR / BF /BF	4.33%	÷1.052	×1.100	4.52%

Result: FIP 4.38 → 4.68, 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 AAAEl Paso Chihuahuas · 69 IPFIP 4.70 → 4.87 (+0.17)K% 17.3% → 15.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.31%	—	×0.880	15.24%
BB% (unintentional) /BF	8.66%	—	×1.050	9.09%
HR / BF /BF	3.58%	÷1.138	×1.100	3.46%

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 128).

Result: FIP 4.70 → 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).

2022 AASan Antonio Missions · 44 IPFIP 2.55 → 3.20 (+0.64)K% 21.5% → 17.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.47%	—	×0.810	17.39%
BB% (unintentional) /BF	5.08%	—	×1.100	5.59%
HR / BF /BF	1.13%	÷0.870	×1.200	1.56%

Result: FIP 2.55 → 3.20, 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 A+Fort Wayne TinCaps · 72 IPFIP 2.97 → 3.76 (+0.78)K% 23.9% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.92%	—	×0.770	18.42%
BB% (unintentional) /BF	6.31%	—	×1.150	7.26%
HR / BF /BF	1.99%	÷1.057	×1.250	2.36%

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 111).

Result: FIP 2.97 → 3.76, 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 Waldron (OGILVIE)	—	—	—	—	—	3.1%	—	4.86	15.5%	9.1%	83	+0.35	—	—	—
David Hale R 2018 · 4.22 FIP	30	SP-	4.22	15.4%	7.5%	2.7%	.299	3.65	17.1%	11.3%	114	-0.57	3.30	581	68
Zack Segovia R 2015 · 4.78 FIP	32	SP	4.78	15.0%	8.3%	3.4%	.314	3.33	20.2%	14.3%	39	-1.45	3.33	144	67
Travis Smith R 2002 · 5.28 FIP	29	SP	5.28	13.1%	8.2%	4.1%	.324	5.71	15.0%	9.0%	51	+0.43	3.67	105	64
Yohan Pino R 2014 · 3.84 FIP	30	SP	3.84	19.4%	5.4%	3.1%	.312	4.45	17.1%	11.9%	133	+0.61	3.84	193	63
Austin Bibens-Dirkx R 2015 · 3.97 FIP	30	SP	3.97	17.4%	7.1%	2.6%	.315	4.94	15.9%	8.7%	305	+0.97	3.97	567	63
Kohei Arihara R 2022 · 4.58 FIP	29	SP-	4.58	16.4%	7.2%	3.5%	.333	—	—	—	—	—	4.58	135	63
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	62
Michael Mariot R 2019 · 5.01 FIP	30	SP	5.01	19.8%	11.1%	4.0%	.333	5.03	15.8%	7.4%	182	+0.02	2.40	701	61
Tyler Herron R 2017 · 4.02 FIP	30	SP	4.02	16.4%	8.7%	2.2%	.377	—	—	—	—	—	4.02	117	60
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	59
Danny Gutierrez R 2017 · 4.11 FIP	30	SP	4.11	15.1%	6.1%	2.8%	.362	—	—	—	—	—	3.34	239	59
Jorge Martinez R 2016 · 3.53 FIP	31	SP-	3.53	12.9%	5.3%	1.6%	.266	3.71	16.5%	11.5%	154	+0.18	3.53	214	59
Juan Omar Espinoza R 2015 · 4.81 FIP	31	SP-	4.81	8.9%	6.6%	3.0%	.346	4.84	8.4%	-0.8%	52	+0.03	4.81	104	59
Andrew Triggs R 2018 · 4.68 FIP	29	SP	4.68	23.6%	9.9%	4.2%	.263	—	—	—	—	—	1.66	242	59
Chi Chi González R 2022 · 4.30 FIP	30	SP-	4.30	17.6%	8.0%	3.0%	.315	5.33	11.2%	5.6%	122	+1.03	4.01	800	58
Juan Delgadillo R 2015 · 4.54 FIP	32	SP	4.54	15.5%	7.2%	3.3%	.316	4.47	10.9%	4.7%	39	-0.07	4.47	143	58
Joe Roa R 2002 · 4.60 FIP	30	SP-	4.60	11.7%	3.7%	3.7%	.278	4.47	15.5%	9.3%	121	-0.13	4.28	258	58
Brian Tollberg R 2002 · 4.98 FIP	29	SP	4.98	11.5%	5.9%	3.8%	.339	—	—	—	—	—	4.02	297	58
Luke Hudson R 2006 · 3.81 FIP	29	SP-	3.81	14.5%	8.4%	1.6%	.307	—	—	—	—	—	3.81	235	57
Robert Ellis R 2001 · 4.84 FIP	30	SP	4.84	9.9%	7.7%	2.9%	.287	8.08	9.0%	-2.2%	18	+3.24	4.84	110	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	1.7	57	18.4%	6.6%	1.40	5.01
Steve Kealey ('68-'73, -1 WAR*)	1.1	54	18.5%*	7.2%*	1.32*	5.26*
Brad Lincoln ('14)	1.1	56	17.4%	7.9%	1.30	4.74
Paul Reuschel ('75-'79, 1 WAR*)	2.0	79	16.8%*	7.6%*	1.29*	4.76*
Adam Morgan ('21)	1.8	62	20.8%	7.2%	1.58	4.80
Matt Wisler ('22)	2.5	63	20.1%	7.6%	1.40	4.59
Ron Taylor ('62-'72, 3 WAR*)	4.0	80	17.8%*	6.8%*	1.26*	4.74*