Erik Miller

P Boston Red Sox

Age 29 LHP 6'5" / 269 lbs MLB peak 0.5 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MLBSF	73	10	67	3.88	3.56	30.6%	13.4%	0.8
2025	27	MIX2 levels	40	0	33	1.91	3.10	18.6%	12.4%	0.6	K 17.2% · BB 12.5% · FIP 3.23
2026	28	MIX3 levels	59	3	53	2.87	2.69	32.8%	13.2%	1.2	K 32.6% · BB 13.7% · FIP 2.82
2027PROJ	29	MLBBOS	48	0	50	3.72	3.86	30.8%	14.1%	0.4
2028PROJ95% MLB	30	MLBBOS	38	0	40	3.93	4.07	30.1%	14.4%	0.2
2029PROJ95% MLB	31	MLBBOS	30	0	32	4.15	4.30	29.3%	14.8%	0.1

Last 3 seasons WAR 2.5 · 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

K%90

xwOBA vs88

FB Velo82

Form3.15 ERA (proj 3.72) · K 33.0% (proj 30.8%) · BB 13.2% (proj 14.1%) ▲ last 90d · 20 IP through Oct 27

CompsScott Sauerbeck (age 29) · Armando Almanza (age 29) · Jake Diekman (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 8189vR 97

ERA3.72

FIP3.86

K%30.8%

BB%14.1%

K-BB%16.7%

Proj IP50

Value2027 · WAR

Runs saved vs league avg · 50 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL2525

CMD4545

K†7070

Statcast Percentiles

FB Velo

p8296.8

Whiff%

p9035.0%

p9032.6%

xwOBA vs

p880.275

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	MIX MLE	2 levels	5	3	16	68	23	8	0	60%	3.2	22.9%	12.9%	10.0%	0.0%	2.25	2.80	—
2019	21	MIX RAW	2 levels	5	3	16	68	23	8	0	60%	3.2	33.8%	11.8%	22.1%	0.0%	2.25	1.73	—
2021	23	MIX MLE	3 levels	5	5	13	58	16	11	0	100%	2.5	27.6%	19.0%	8.6%	0.0%	1.42	3.17	—
2021	23	MIX RAW	3 levels	5	5	13	58	16	11	0	100%	2.5	27.6%	19.0%	8.6%	0.0%	1.42	3.18	—
2022	24	MIX MLE	2 levels	32	7	48	211	62	31	4	22%	1.5	24.4%	15.8%	8.6%	2.0%	3.54	4.15	—
2022	24	MIX RAW	2 levels	32	7	48	211	62	31	4	22%	1.5	29.4%	14.7%	14.7%	1.9%	3.54	3.53	—
2023	25	MIX MLE	2 levels	54	0	62	258	88	44	2	0%	1.2	28.3%	16.2%	12.1%	0.9%	2.45	3.28	—
2023	25	MIX RAW	2 levels	54	0	62	258	88	44	2	0%	1.2	34.1%	17.1%	17.1%	0.8%	2.45	2.81	—
2024	26	MLB MLE	San Francisco Giants	73	10	67	284	87	38	7	14%	0.9	30.6%	13.4%	17.3%	2.7%	3.88	3.67	+0.7
2024	26	MLB MLE	San Francisco Giants	73	10	67	284	87	38	7	14%	0.9	30.6%	13.4%	17.3%	2.7%	3.88	3.67	+0.7
2024	26	MLB RAW	San Francisco Giants	73	10	67	284	87	38	7	14%	0.9	30.6%	13.4%	17.3%	2.5%	3.88	3.56	+0.8
2025	27	MIX MLE	2 levels	40	0	33	145	27	18	0	0%	0.8	17.2%	12.5%	4.7%	0.0%	1.91	3.23	+0.5
2025	27	MIX MLE	2 levels	40	0	33	145	27	18	0	0%	0.8	17.2%	12.5%	4.7%	0.0%	1.91	3.23	+0.5
2025	27	MIX RAW	2 levels	40	0	33	145	27	18	0	0%	0.8	18.6%	12.4%	6.2%	0.0%	1.91	3.10	+0.6
2026	28	MIX MLE	3 levels	59	3	53	235	77	31	3	5%	0.9	32.6%	13.7%	18.9%	1.4%	2.87	2.82	+1.1
2026	28	MIX MLE	3 levels	59	3	53	235	77	31	3	5%	0.9	32.6%	13.7%	18.9%	1.4%	2.87	2.82	+1.1
2026	28	MIX RAW	3 levels	59	3	53	235	77	31	3	5%	0.9	32.8%	13.2%	19.6%	1.3%	2.87	2.69	+1.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			166	11	149	639	183	85	10	7%	0.9	28.6%	13.3%	15.3%	1.6%	3.09	3.23	+2.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	BOS	48	0	50	211	65	30	5	0%	1.0	30.8%	14.1%	16.7%	2.2%	3.72	3.86	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	BOS	40	0	42	177	53	26	4	0%	1.0	30.1%	14.4%	15.7%	2.4%	3.93	4.07	+0.2
2029	31	MLB MLE	BOS	32	0	33	140	41	21	4	0%	1.0	29.3%	14.8%	14.5%	2.6%	4.15	4.30	+0.1
2028	30	MLB CTX	BOS	38	0	40	169	51	24	4	0%	1.1	30.1%	14.4%	15.7%	2.4%	3.93	4.07	+0.2
2029	31	MLB CTX	BOS	30	0	32	135	40	20	3	0%	1.1	29.3%	14.8%	14.5%	2.6%	4.15	4.30	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		234	11	220	940	273	129	17	5%	0.9	29.0%	13.7%	15.3%	1.9%	3.39	3.41	+3.0
/ 200 IP	—	RAW		213	10	200	855	248	117	15	5%	0.9	29.0%	13.7%	15.3%	1.9%	3.39	3.41	+2.7
Career	—	MLE		268	28	293	1259	345	183	17	10%	1.1	27.4%	14.6%	12.8%	1.4%	2.92	3.39	+2.7
/ 200 IP	—	MLE		183	19	200	859	235	125	12	10%	1.1	27.4%	14.6%	12.8%	1.4%	2.92	3.39	+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.

2023 AAASacramento River Cats · 52 IPFIP 3.10 → 3.28 (+0.18)K% 32.9% → 28.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.88%	—	×0.860	28.28%
BB% (unintentional) /BF	18.02%	—	×0.900	16.22%
HR / BF /BF	0.90%	÷1.057	×1.100	0.94%

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 111).

Result: FIP 3.10 → 3.28, 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).

2023 AARichmond Flying Squirrels · 10 IPFIP 0.99 → 1.80 (+0.81)K% 41.7% → 33.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.67%	—	×0.810	33.75%
BB% (unintentional) /BF	11.11%	—	×1.100	12.22%
HR / BF /BF	0.00%	÷0.906	×1.200	0.00%

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 81).

Result: FIP 0.99 → 1.80, 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 AAReading Fightin Phils · 36 IPFIP 2.03 → 2.66 (+0.63)K% 30.1% → 24.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.14%	—	×0.810	24.41%
BB% (unintentional) /BF	11.64%	—	×1.100	12.81%
HR / BF /BF	0.00%	÷1.051	×1.200	0.00%

Result: FIP 2.03 → 2.66, 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 AAALehigh Valley IronPigs · 12 IPFIP 6.87 → 7.48 (+0.62)K% 27.7% → 24.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.69%	—	×0.880	24.37%
BB% (unintentional) /BF	21.54%	—	×1.050	22.62%
HR / BF /BF	6.15%	÷1.039	×1.100	6.52%

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 108).

Result: FIP 6.87 → 7.48, 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).

2021 AClearwater Threshers · 6 IPFIP 2.32 → 3.55 (+1.24)K% 37.0% → 27.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.04%	—	×0.740	27.41%
BB% (unintentional) /BF	18.52%	—	×1.180	21.85%
HR / BF /BF	0.00%	÷0.993	×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 99).

Result: FIP 2.32 → 3.55, 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 ALakewood BlueClaws · 13 IPFIP 1.87 → 2.80 (+0.93)K% 30.9% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.91%	—	×0.740	22.87%
BB% (unintentional) /BF	10.91%	—	×1.180	12.87%
HR / BF /BF	0.00%	÷0.809	×1.300	0.00%

Result: FIP 1.87 → 2.80, 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
Erik Miller (OGILVIE)	—	—	3.86	30.8%	14.1%	2.2%	—	4.17	29.8%	15.2%	75	+0.31	—	—	—
Scott Sauerbeck L 2001 · 3.04 FIP	29	SU	3.04	28.1%	12.1%	1.4%	.348	3.64	23.6%	11.9%	119	+0.60	2.79	386	70
Armando Almanza L 2002 · 4.34 FIP	29	SU	4.34	30.0%	11.6%	4.2%	.272	5.01	21.8%	12.0%	62	+0.67	2.90	211	67
Jake Diekman L 2016 · 3.23 FIP	29	SU	3.23	26.7%	11.3%	1.7%	.241	3.09	28.6%	15.8%	115	-0.14	2.27	592	67
Zach Phillips L 2016 · 3.01 FIP	29	SU	3.01	27.4%	11.9%	1.3%	.370	3.20	19.2%	10.6%	86	+0.19	2.33	202	66
Justin Wilson L 2017 · 3.26 FIP	29	SU	3.26	32.3%	13.7%	2.1%	.271	3.40	27.8%	15.9%	113	+0.14	2.49	554	65
Edward Paredes L 2016 · 3.47 FIP	29	SU	3.47	24.1%	13.0%	1.4%	.225	3.55	23.7%	14.0%	86	+0.08	2.36	130	64
Yuki Matsui L 2024 · 3.63 FIP	28	SU	3.63	26.8%	8.9%	3.0%	.242	4.25	23.9%	12.6%	140	+0.62	3.63	203	63
Zac Rosscup L 2017 · 2.85 FIP	29	SU	2.85	29.5%	7.8%	2.3%	.275	4.42	26.4%	5.9%	35	+1.57	2.56	173	63
Kyle Regnault L 2018 · 3.82 FIP	29	SU	3.82	27.6%	9.7%	3.3%	.367	—	—	—	—	—	2.88	204	62
Clay Rapada L 2011 · 4.34 FIP	30	SU	4.34	26.1%	10.1%	3.9%	.268	3.00	24.5%	14.2%	38	-1.34	3.00	120	62
Sammy Solís L 2018 · 4.39 FIP	29	SU	4.39	24.9%	9.6%	4.0%	.330	4.05	26.2%	17.3%	23	-0.34	2.51	190	61
Brian Fuentes L 2005 · 2.92 FIP	29	SU	2.92	28.3%	9.3%	1.9%	.273	3.08	26.9%	18.5%	189	+0.16	2.08	602	60
Nick Hagadone L 2015 · 3.65 FIP	29	SU	3.65	22.6%	8.9%	2.4%	.329	3.74	22.6%	13.3%	33	+0.09	2.97	141	60
Doug Creek L 2000 · 4.57 FIP	31	SU	4.57	27.5%	13.6%	3.8%	.267	4.75	21.9%	7.8%	132	+0.18	4.48	277	60
Damaso Marte L 2004 · 4.27 FIP	29	SU	4.27	22.4%	9.9%	3.3%	.236	3.28	25.9%	15.1%	149	-0.99	2.41	495	60
Mike Dunn L 2014 · 2.82 FIP	29	SU	2.82	27.3%	8.6%	1.7%	.281	3.92	25.3%	14.8%	147	+1.10	2.82	432	60
Hunter Cervenka L 2019 · 3.11 FIP	29	SU	3.11	26.6%	13.1%	1.1%	.283	—	—	—	—	—	3.08	194	59
Josh Smoker L 2018 · 3.66 FIP	29	SU	3.66	22.1%	8.4%	2.5%	.318	6.58	14.2%	3.4%	14	+2.92	2.71	230	59
George Sherrill L 2006 · 2.74 FIP	29	SU	2.74	24.1%	13.2%	0.0%	.275	3.20	25.0%	16.1%	168	+0.46	2.74	323	59
Raul Valdes L 2010 · 4.02 FIP	32	SU	4.02	21.4%	9.9%	2.7%	.301	3.14	27.4%	22.5%	78	-0.88	2.29	160	58

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	29.3%	14.4%	0.74	3.46
John Rocker ('03)	1.3	51	29.4%	14.5%	0.81	3.42
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*
Mark Littell ('73-'82, 7 WAR*)	2.7	66	30.7%*	13.4%*	0.74*	3.75*
Tippy Martinez ('74-'88, 9 WAR*)	4.2	76	27.7%*	12.0%*	0.77*	3.82*