Justin Sterner

P Athletics

Age 30 RHP 6'1" / 215 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	27	MIX2 levels	36	1	51	3.20	3.38	30.5%	8.1%	0.7	K 27.0% · BB 8.0% · FIP 3.92
2025	28	MIX2 levels	62	1	68	3.44	4.04	25.3%	7.5%	0.4	K 26.3% · BB 7.1% · FIP 3.90
2026	29	MLBOAK	46	0	43	6.12	5.42	21.7%	6.5%	-0.4
2027PROJ	30	MLBOAK	24	0	25	4.27	4.43	24.8%	6.4%	0.0
2028PROJ92% MLB	31	MLBOAK	37	0	39	4.50	4.66	24.1%	6.8%	-0.0
2029PROJ93% MLB	32	MLBOAK	31	0	33	4.75	4.91	23.3%	7.1%	-0.1

Last 3 seasons WAR 0.7 · Next 3 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs71

K%47

FB Velo36

CompsKiko Calero (age 30) · Ryan Tepera (age 30) · Neil Wagner (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 108100vR 92

ERA4.27

FIP4.43

K%24.8%

BB%6.4%

K-BB%18.4%

Proj IP27

Value2027 · WAR

Runs saved vs league avg · 27 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL5050

CMD6060

K†6060

Statcast Percentiles

FB Velo

p3693.5

Whiff%

p7929.9%

p4721.7%

xwOBA vs

p710.292

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)
2021	24	MIX MLE	3 levels	32	0	57	240	78	21	7	0%	1.8	23.9%	9.4%	14.5%	4.7%	3.45	4.83	—
2021	24	MIX RAW	3 levels	32	0	57	240	78	21	7	0%	1.8	32.5%	8.8%	23.8%	2.9%	3.45	3.07	—
2022	25	MIX MLE	2 levels	38	0	48	211	65	22	7	0%	1.3	26.5%	9.6%	16.9%	4.3%	3.94	4.46	—
2022	25	MIX RAW	2 levels	38	0	48	211	65	22	7	0%	1.3	30.8%	10.4%	20.4%	3.3%	3.94	3.66	—
2023	26	MIX MLE	2 levels	34	0	55	233	71	21	13	0%	1.6	25.6%	8.3%	17.3%	5.7%	5.27	5.14	—
2023	26	MIX RAW	2 levels	34	0	55	233	71	21	13	0%	1.6	30.5%	9.0%	21.5%	5.6%	5.27	4.75	—
2024	27	MIX MLE	2 levels	36	1	51	210	64	17	7	3%	1.4	27.0%	8.0%	19.0%	3.8%	3.20	3.92	+0.4
2024	27	MIX MLE	2 levels	36	1	51	210	64	17	7	3%	1.4	27.0%	8.0%	19.0%	3.8%	3.20	3.92	+0.4
2024	27	MIX RAW	2 levels	36	1	51	210	64	17	7	3%	1.4	30.5%	8.1%	22.4%	3.3%	3.20	3.38	+0.7
2025	28	MIX MLE	2 levels	62	1	68	281	71	21	11	2%	1.1	26.3%	7.1%	19.2%	3.9%	3.44	3.90	+0.5
2025	28	MIX MLE	2 levels	62	1	68	281	71	21	11	2%	1.1	26.3%	7.1%	19.2%	3.9%	3.44	3.90	+0.5
2025	28	MIX RAW	2 levels	62	1	68	281	71	21	11	2%	1.1	25.3%	7.5%	17.8%	3.9%	3.44	4.04	+0.4
2026	29	MLB MLE	Athletics	46	0	43	184	40	12	11	0%	0.9	21.7%	6.5%	15.2%	6.1%	6.12	5.46	-0.5
2026	29	MLB MLE	Athletics	46	0	43	184	40	12	11	0%	0.9	21.7%	6.5%	15.2%	6.1%	6.12	5.46	-0.5
2026	29	MLB RAW	Athletics	46	0	43	184	40	12	11	0%	0.9	21.7%	6.5%	15.2%	6.0%	6.12	5.42	-0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			107	1	112	469	114	31	21	1%	1.0	24.3%	6.6%	17.7%	4.5%	4.27	4.34	+0.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	OAK	24	0	25	106	26	7	4	0%	1.0	24.8%	6.4%	18.4%	4.1%	4.27	4.43	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	OAK	41	0	43	180	43	12	8	0%	1.0	24.1%	6.8%	17.3%	4.3%	4.50	4.66	-0.1
2029	32	MLB MLE	OAK	34	0	35	149	35	11	7	0%	1.0	23.3%	7.1%	16.1%	4.5%	4.75	4.91	-0.1
2028	31	MLB CTX	OAK	37	0	39	165	40	11	7	0%	1.1	24.1%	6.8%	17.3%	4.3%	4.50	4.66	-0.0
2029	32	MLB CTX	OAK	31	0	33	139	32	10	6	0%	1.1	23.3%	7.1%	16.1%	4.5%	4.75	4.91	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		176	1	184	775	187	52	34	1%	1.0	24.1%	6.7%	17.3%	4.4%	4.41	4.36	+0.4
/ 200 IP	—	RAW		191	1	200	842	203	56	37	1%	1.0	24.1%	6.7%	17.3%	4.4%	4.41	4.36	+0.4
Career	—	MLE		248	2	321	1359	344	111	64	1%	1.3	25.3%	8.2%	17.1%	4.7%	4.15	4.58	+0.1
/ 200 IP	—	MLE		154	1	200	846	214	69	40	1%	1.3	25.3%	8.2%	17.1%	4.7%	4.15	4.58	+0.1

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.

2024 AAADurham Bulls · 47 IPFIP 3.59 → 3.92 (+0.33)K% 31.4% → 27.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.41%	—	×0.860	27.02%
BB% (unintentional) /BF	8.90%	—	×0.900	8.01%
HR / BF /BF	3.66%	÷1.061	×1.100	3.80%

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 112).

Result: FIP 3.59 → 3.92, 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 AAADurham Bulls · 36 IPFIP 4.78 → 4.86 (+0.08)K% 26.1% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.09%	—	×0.860	22.43%
BB% (unintentional) /BF	11.80%	—	×0.900	10.62%
HR / BF /BF	4.35%	÷1.137	×1.100	4.21%

Result: FIP 4.78 → 4.86, 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 AAMontgomery Biscuits · 19 IPFIP 4.62 → 5.78 (+1.16)K% 40.3% → 32.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.28%	—	×0.810	32.63%
BB% (unintentional) /BF	2.78%	—	×1.100	3.06%
HR / BF /BF	8.33%	÷1.087	×1.200	9.20%

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 117).

Result: FIP 4.62 → 5.78, 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).

2022 AAMontgomery Biscuits · 41 IPFIP 3.37 → 4.46 (+1.09)K% 32.7% → 26.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.75%	—	×0.810	26.53%
BB% (unintentional) /BF	8.77%	—	×1.100	9.65%
HR / BF /BF	3.51%	÷0.970	×1.200	4.34%

Result: FIP 3.37 → 4.46, 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 AAADurham Bulls · 7 IPFIP 4.79 → 5.22 (+0.43)K% 22.5% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.50%	—	×0.880	19.80%
BB% (unintentional) /BF	17.50%	—	×1.050	18.38%
HR / BF /BF	2.50%	÷1.034	×1.100	2.66%

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 107).

Result: FIP 4.79 → 5.22, 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 AAMontgomery Biscuits · 28 IPFIP 3.44 → 4.51 (+1.08)K% 28.3% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.32%	—	×0.810	22.94%
BB% (unintentional) /BF	6.19%	—	×1.100	6.81%
HR / BF /BF	3.54%	÷0.938	×1.200	4.53%

Result: FIP 3.44 → 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 A+Bowling Green Hot Rods · 16 IPFIP 3.85 → 5.28 (+1.44)K% 32.9% → 25.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.91%	—	×0.770	25.34%
BB% (unintentional) /BF	11.39%	—	×1.150	13.10%
HR / BF /BF	3.80%	÷0.978	×1.250	4.85%

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 96).

Result: FIP 3.85 → 5.28, 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 AJupiter Hammerheads · 13 IPFIP 0.90 → 2.05 (+1.15)K% 41.7% → 30.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.67%	—	×0.740	30.83%
BB% (unintentional) /BF	10.42%	—	×1.180	12.29%
HR / BF /BF	0.00%	÷0.891	×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 0.90 → 2.05, 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
Justin Sterner (OGILVIE)	—	—	4.43	24.8%	6.4%	4.1%	—	4.77	23.7%	16.8%	78	+0.34	—	—	—
Kiko Calero R 2005 · 3.51 FIP	30	SU	3.51	22.7%	7.0%	2.6%	.252	3.23	23.3%	13.9%	99	-0.28	2.27	298	79
Ryan Tepera R 2018 · 3.90 FIP	30	SU	3.90	25.9%	8.7%	3.4%	.282	3.20	28.4%	19.9%	104	-0.70	2.35	445	77
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	77
Manny Acosta R 2011 · 3.75 FIP	30	SU	3.75	22.5%	7.4%	2.9%	.321	4.49	21.3%	10.2%	47	+0.74	3.08	350	76
Adrian Ramirez R 2019 · 4.29 FIP	31	SU	4.29	21.7%	6.3%	4.0%	.327	—	—	—	—	—	3.04	137	76
Rob Wooten R 2015 · 4.86 FIP	30	SU	4.86	19.3%	5.5%	4.9%	.299	3.87	17.7%	14.4%	111	-0.99	2.48	253	75
Jeff Zimmerman R 2001 · 3.58 FIP	28	SU	3.58	26.4%	5.5%	3.7%	.216	—	—	—	—	—	3.58	229	74
Shane Greene R 2019 · 3.50 FIP	30	SU	3.50	25.4%	6.3%	3.2%	.232	4.26	20.5%	9.9%	86	+0.76	2.86	563	74
Kazuhiro Sasaki R 2000 · 3.93 FIP	32	SU	3.93	29.4%	9.8%	3.8%	.212	2.88	24.9%	19.3%	161	-1.05	2.76	223	73
Kaleb Fleck R 2018 · 3.47 FIP	29	SU	3.47	24.6%	5.9%	3.1%	.346	—	—	—	—	—	2.68	177	73
Jhan Mariñez R 2018 · 4.09 FIP	29	SU	4.09	21.2%	7.9%	3.2%	.331	—	—	—	—	—	3.16	253	73
Cory Wade R 2012 · 4.15 FIP	29	SU	4.15	22.2%	4.1%	4.4%	.322	—	—	—	—	—	3.48	178	72
Tyler Sturdevant R 2016 · 3.44 FIP	30	SU	3.44	23.8%	6.5%	2.8%	.323	4.48	13.5%	6.8%	60	+1.04	3.44	149	72
Fernando Rodriguez Jr. R 2015 · 3.34 FIP	31	SU	3.34	26.5%	9.6%	2.3%	.241	3.89	23.3%	13.2%	105	+0.55	3.34	335	72
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	72
Scott Atchison R 2007 · 4.55 FIP	31	SU	4.55	19.1%	7.6%	3.8%	.297	4.59	16.2%	9.5%	60	+0.04	2.52	340	72
Andrew Robinson R 2017 · 4.32 FIP	29	SU	4.32	23.4%	8.8%	3.8%	.245	—	—	—	—	—	3.19	160	72
Gerardo Sanchez R 2019 · 3.58 FIP	30	SU	3.58	20.5%	5.4%	2.8%	.300	—	—	—	—	—	2.65	137	71
Alex Wimmers R 2017 · 3.61 FIP	28	SU	3.61	23.2%	5.8%	3.2%	.235	—	—	—	—	—	3.61	230	71
Jose Valverde R 2008 · 3.31 FIP	30	SU	3.31	27.4%	5.6%	3.3%	.269	3.47	24.1%	13.7%	189	+0.16	2.21	752	71

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	1.1	44	24.2%	7.1%	1.70	4.39
Erik Swanson ('25)	1.3	53	25.7%	6.8%	1.66	4.20
Mike Mayers ('23)	1.3	53	23.0%	8.3%	1.61	5.21
Chris Hatcher ('18)	1.3	53	22.9%	8.4%	1.32	4.65
Pete Ladd ('79-'86, 0 WAR*)	1.4	72	24.6%*	7.8%*	1.53*	4.42*
Julio Navarro ('62-'70, 1 WAR*)	1.1	53	21.7%*	7.8%*	1.55*	4.13*
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*