Austin Adams

P Worcester Red Sox

Age 36 RHP 6'3" / 220 lbs AAA peak 0.2 · 2027

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	32	MIX2 levels	36	0	30	4.50	2.13	31.1%	10.4%	0.9	K 29.0% · BB 9.9% · FIP 2.34
2024	33	MLBOakland Athle…	56	0	41	3.92	3.32	27.7%	11.0%	0.6
2025	34	AAABOS	24	1	24	9.13	4.54	26.6%	16.4%	—	K 22.8% · BB 14.8% · FIP 4.48
2026	35	No MLB games played
2027PROJ	36	MLBBOS	6	0	6	4.20	4.26	25.9%	11.1%	0.0
2028PROJMLE	37	MLBBOS	—	—	0	4.48	4.66	24.8%	11.8%	—
2029PROJMLE	38	MLBBOS	—	—	0	4.85	5.10	23.6%	12.5%	—

Last 3 seasons WAR 1.5 · Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2024

K%80

xwOBA vs49

FB Velo34

CompsKeiichi Yabu (age 36) · Joe Nelson (age 34) · Hirokazu Sawamura (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 111103vR 95

ERA4.20

FIP4.26

K%25.9%

BB%11.1%

K-BB%14.8%

Proj IP55

Value2027 · WAR

Runs saved vs league avg · 55 IP

Grades · Statcast · Contract

Scouting Grades

STUF7070

CTRL3535

CMD5050

K†6060

Statcast Percentiles

FB Velo

p3493.4

Whiff%

p9035.3%

p8027.7%

xwOBA vs

p490.313

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	24	MIX MLE	3 levels	38	0	55	238	71	47	0	0%	1.4	25.6%	19.3%	6.3%	0.0%	3.27	3.39	—
2015	24	MIX RAW	3 levels	38	0	55	238	71	47	0	0%	1.4	29.8%	19.7%	10.1%	0.0%	3.27	3.08	—
2016	25	MIX MLE	2 levels	34	0	44	184	63	24	2	0%	1.3	28.4%	15.2%	13.2%	1.4%	3.05	3.40	—
2016	25	MIX RAW	2 levels	34	0	44	184	63	24	2	0%	1.3	34.2%	13.0%	21.2%	1.1%	3.05	2.47	—
2017	26	MIX MLE	2 levels	50	0	64	294	101	42	2	0%	1.3	30.2%	13.5%	16.7%	0.8%	2.25	2.72	+1.4
2017	26	MIX RAW	2 levels	50	0	64	294	101	42	2	0%	1.3	34.4%	14.3%	20.1%	0.7%	2.25	2.32	+1.7
2018	27	MIX MLE	2 levels	43	0	47	218	78	22	1	0%	1.1	32.5%	9.5%	23.1%	0.4%	3.42	1.79	+1.6
2018	27	MIX RAW	2 levels	43	0	47	218	78	22	1	0%	1.1	35.8%	10.1%	25.7%	0.5%	3.42	1.47	+1.8
2019	28	MIX MLE	3 levels	44	2	48	192	85	21	4	5%	1.1	41.7%	10.4%	31.3%	2.2%	3.17	2.12	+1.4
2019	28	MIX RAW	3 levels	44	2	48	192	85	21	4	5%	1.1	44.3%	10.9%	33.3%	2.1%	3.17	1.96	+1.5
2020	29	MLB MLE	San Diego Padres	3	0	4	17	7	2	1	0%	1.3	41.2%	11.8%	29.4%	5.9%	4.50	4.34	+0.0
2020	29	MLB RAW	San Diego Padres	3	0	4	17	7	2	1	0%	1.3	41.2%	11.8%	29.4%	5.9%	4.50	4.35	+0.0
2021	30	MLB MLE	San Diego Padres	65	0	53	241	76	33	1	0%	0.8	31.5%	13.7%	17.8%	0.4%	4.10	2.39	+1.4
2021	30	MLB RAW	San Diego Padres	65	0	53	241	76	33	1	0%	0.8	31.5%	13.7%	17.8%	0.4%	4.10	2.34	+1.4
2022	31	MLB MLE	San Diego Padres	2	0	2	9	2	3	0	0%	1.2	22.2%	33.3%	-11.1%	0.0%	0.00	5.45	-0.0
2022	31	MLB RAW	San Diego Padres	2	0	2	9	2	3	0	0%	1.2	22.2%	33.3%	-11.1%	0.0%	0.00	5.24	-0.0
2023	32	MIX MLE	2 levels	36	0	30	135	42	14	1	0%	0.8	29.0%	9.9%	19.1%	0.8%	4.50	2.34	+0.8
2023	32	MIX RAW	2 levels	36	0	30	135	42	14	1	0%	0.8	31.1%	10.4%	20.7%	0.7%	4.50	2.13	+0.9
2024	33	MLB MLE	Oakland Athletics	56	0	41	191	53	21	4	0%	0.7	27.7%	11.0%	16.8%	2.3%	3.92	3.41	+0.6
2024	33	MLB MLE	Oakland Athletics	56	0	41	191	53	21	4	0%	0.7	27.7%	11.0%	16.8%	2.3%	3.92	3.41	+0.6
2024	33	MLB RAW	Oakland Athletics	56	0	41	191	53	21	4	0%	0.7	27.7%	11.0%	16.8%	2.1%	3.92	3.32	+0.6
2025	34	AAA MLE	Worcester Red Sox	24	1	24	128	34	21	3	4%	1.0	22.8%	14.8%	8.1%	2.6%	9.13	4.48	—
2025	34	AAA MLE	Worcester Red Sox	24	1	24	128	34	21	3	4%	1.0	22.8%	14.8%	8.1%	2.6%	9.13	4.48	—
2025	34	AAA RAW	Worcester Red Sox	24	1	24	128	34	21	3	4%	1.0	26.6%	16.4%	10.2%	2.3%	9.13	4.54	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			188	2	156	705	223	94	11	1%	0.8	31.6%	13.3%	18.3%	1.6%	4.10	2.97	+2.9
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	BOS	6	0	6	25	7	3	1	0%	1.0	25.9%	11.1%	14.8%	2.8%	4.20	4.26	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	BOS	37	0	39	164	41	19	5	0%	1.0	24.8%	11.8%	13.0%	3.3%	4.48	4.66	-0.0
2029	38	MLB MLE	BOS	26	0	28	117	28	15	4	0%	1.1	23.6%	12.5%	11.2%	3.7%	4.85	5.10	-0.2
2028	37	MLB CTX	BOS	—	—	0	—	—	—	—	—	—	24.8%	11.8%	13.0%	3.3%	4.48	4.66	—
2029	38	MLB CTX	BOS	—	—	0	—	—	—	—	—	—	23.6%	12.5%	11.2%	3.7%	4.85	5.10	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		188	2	156	707	223	94	11	1%	0.8	31.6%	13.3%	18.3%	1.6%	4.11	2.98	+2.9
/ 200 IP	—	RAW		241	3	200	906	286	120	14	1%	0.8	31.6%	13.3%	18.3%	1.6%	4.11	2.98	+3.7
Career	—	MLE		395	3	413	1847	560	245	21	1%	1.0	30.3%	13.3%	17.0%	1.1%	3.68	2.85	+2.7
/ 200 IP	—	MLE		191	1	200	894	271	119	10	1%	1.0	30.3%	13.3%	17.0%	1.1%	3.68	2.85	+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.

2025 AAAWorcester Red Sox · 24 IPFIP 4.22 → 4.48 (+0.26)K% 26.6% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.56%	—	×0.860	22.84%
BB% (unintentional) /BF	16.41%	—	×0.900	14.77%
HR / BF /BF	2.34%	÷0.984	×1.100	2.62%

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 97).

Result: FIP 4.22 → 4.48, 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 AAAReno Aces · 13 IPFIP 1.38 → 1.68 (+0.30)K% 37.0% → 31.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.04%	—	×0.860	31.85%
BB% (unintentional) /BF	11.11%	—	×0.900	10.00%
HR / BF /BF	0.00%	÷1.012	×1.100	0.00%

Result: FIP 1.38 → 1.68, 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).

2019 AAATacoma Rainiers · 14 IPFIP -0.42 → 0.12 (+0.54)K% 50.0% → 44.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	50.00%	—	×0.880	44.00%
BB% (unintentional) /BF	5.56%	—	×1.050	5.83%
HR / BF /BF	0.00%	÷1.049	×1.100	0.00%

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 110).

Result: FIP -0.42 → 0.12, 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 AAASyracuse Chiefs · 46 IPFIP 1.38 → 1.79 (+0.41)K% 37.0% → 32.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.97%	—	×0.880	32.53%
BB% (unintentional) /BF	9.00%	—	×1.050	9.45%
HR / BF /BF	0.47%	÷1.205	×1.100	0.43%

Result: FIP 1.38 → 1.79, 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).

2017 AAASyracuse Chiefs · 59 IPFIP 2.24 → 2.72 (+0.48)K% 34.3% → 30.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.34%	—	×0.880	30.22%
BB% (unintentional) /BF	12.83%	—	×1.050	13.47%
HR / BF /BF	0.75%	÷0.980	×1.100	0.85%

Result: FIP 2.24 → 2.72, 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 AAArkansas Travelers · 41 IPFIP 2.52 → 3.40 (+0.88)K% 35.1% → 28.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.06%	—	×0.810	28.40%
BB% (unintentional) /BF	13.79%	—	×1.100	15.17%
HR / BF /BF	1.15%	÷0.972	×1.200	1.42%

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 94).

Result: FIP 2.52 → 3.40, 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).

2015 AAArkansas Travelers · 37 IPFIP 2.96 → 3.72 (+0.76)K% 31.4% → 25.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.41%	—	×0.810	25.44%
BB% (unintentional) /BF	19.87%	—	×1.100	21.86%
HR / BF /BF	0.00%	÷1.022	×1.200	0.00%

Result: FIP 2.96 → 3.72, 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).

2015 A+Inland Empire 66ers · 15 IPFIP 1.67 → 2.54 (+0.87)K% 33.9% → 26.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.87%	—	×0.770	26.08%
BB% (unintentional) /BF	11.29%	—	×1.150	12.98%
HR / BF /BF	0.00%	÷0.896	×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 79).

Result: FIP 1.67 → 2.54, 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
Austin Adams (OGILVIE)	—	—	4.26	25.9%	11.1%	2.8%	—	4.84	24.3%	12.3%	66	+0.58	—	—	—
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	71
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	70
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	69
Juan Sandoval R 2017 · 3.42 FIP	36	SU	3.42	16.7%	7.2%	1.5%	.298	5.41	15.9%	8.7%	57	+1.99	3.24	225	69
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	66
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	66
Kazuhiro Sasaki R 2003 · 3.30 FIP	35	SU	3.30	19.3%	8.7%	1.3%	.274	—	—	—	—	—	2.76	223	65
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	65
Peter Moylan R 2015 · 3.11 FIP	36	SU	3.11	18.4%	8.2%	0.9%	.259	3.84	18.2%	9.1%	145	+0.73	2.54	431	64
Jim Miller R 2016 · 5.43 FIP	34	SU	5.43	20.4%	14.1%	4.1%	.347	—	—	—	—	—	3.95	140	63
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	63
Daniel Bard R 2021 · 3.62 FIP	36	SU	3.62	26.3%	11.5%	2.3%	.337	3.64	24.6%	10.3%	110	+0.02	2.56	456	62
Salvador Valdez R 2019 · 4.30 FIP	36	SW	4.30	17.1%	8.2%	2.9%	.405	—	—	—	—	—	3.60	326	59
Matt Bush R 2022 · 3.73 FIP	36	SU	3.73	30.3%	6.6%	4.3%	.224	3.79	26.2%	17.5%	36	+0.06	2.87	249	59
Jay Jackson R 2024 · 5.31 FIP	36	SU	5.31	25.4%	7.9%	6.1%	.304	—	—	—	—	—	2.36	261	58
Francisco Del Rosario R 2017 · 4.15 FIP	36	SU	4.15	16.4%	10.0%	2.1%	.267	6.35	11.9%	-0.6%	77	+2.20	3.93	194	57
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	56
Jesus Adrian Castillo R 2019 · 5.13 FIP	35	SU	5.13	13.1%	7.8%	3.9%	.319	—	—	—	—	—	2.23	173	55
Erubiel Gonzalez R 2015 · 3.43 FIP	36	SU	3.43	12.4%	6.0%	1.1%	.328	3.26	14.8%	10.4%	69	-0.17	2.99	119	54
Yoshihisa Hirano R 2020 · 5.02 FIP	36	SU	5.02	17.5%	12.7%	3.3%	.381	—	—	—	—	—	3.45	132	51

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	46	28.8%	12.9%	0.87	4.25
Rex Brothers ('21)	1.6	54	27.6%	13.5%	0.98	4.08
Matt Mantei ('05)	1.6	54	28.0%	14.1%	0.84	4.07
Kyle Barraclough ('23)	1.4	56	28.2%	13.9%	0.99	3.86
Rod Scurry ('80-'88, 5 WAR*)	2.3	58	29.6%*	13.6%*	0.91*	3.67*
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*
Mike Stanton ('75-'85, 0 WAR*)	1.9	64	27.8%*	10.8%*	0.80*	4.82*