Evan Phillips

P Los Angeles Dodgers

Age 32 RHP 6'2" / 215 lbs MLB peak 0.7 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MIX2 levels	63	0	56	3.51	2.99	28.3%	6.9%	1.0	K 27.6% · BB 7.0% · FIP 3.04
2025	30	MIX2 levels	13	1	11	3.18	1.25	31.2%	6.2%	0.5	K 31.2% · BB 6.2% · FIP 1.25
2026	31	MIX2 levels	43	0	36	3.00	3.38	30.5%	5.3%	0.5	K 31.1% · BB 2.8% · FIP 3.31
2027PROJ	32	MLBLAD	59	0	62	3.50	3.34	30.0%	4.3%	0.9
2028PROJ95% MLB	33	MLBLAD	51	0	54	3.57	3.62	29.1%	4.8%	0.6
2029PROJ90% MLB	34	MLBLAD	43	0	45	3.78	3.93	28.2%	5.3%	0.3

Last 3 seasons WAR 2.0 · Next 3 projected WAR 1.9Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%90

FB Velo84

xwOBA vs42

Form2.33 ERA (proj 3.50) · K 31.2% (proj 30.0%) · BB 6.5% (proj 4.3%) · last 90d · 19 IP through Oct 27

CompsAkinori Otsuka (age 32) · Chris Martin (age 32) · C.C. Lee (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9789vR 80

ERA3.50

FIP3.34

K%30.0%

BB%4.3%

K-BB%25.7%

Proj IP62

Value2027 · WAR

Runs saved vs league avg · 62 IP

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL5555

CMD6060

K†7070

Statcast Percentiles

FB Velo

p8496.9

Whiff%

p5926.7%

p9031.1%

xwOBA vs

p420.321

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	20	MIX MLE	2 levels	18	0	30	118	37	12	2	0%	1.6	21.4%	13.7%	7.8%	1.7%	2.73	3.96	—
2015	20	MIX RAW	2 levels	18	0	30	118	37	12	2	0%	1.6	31.4%	10.2%	21.2%	1.7%	2.73	2.70	—
2016	21	MIX MLE	2 levels	43	0	63	262	62	23	2	0%	1.5	18.9%	9.8%	9.1%	0.8%	3.02	3.21	—
2016	21	MIX RAW	2 levels	43	0	63	262	62	23	2	0%	1.5	23.7%	8.8%	14.9%	0.8%	3.02	2.64	—
2017	22	MIX MLE	2 levels	40	1	51	234	53	32	6	2%	1.3	19.2%	14.6%	4.6%	3.3%	6.14	5.11	—
2017	22	MIX RAW	2 levels	40	1	51	234	53	32	6	2%	1.3	22.6%	13.7%	9.0%	2.6%	6.14	4.42	—
2018	23	MIX MLE	2 levels	48	1	63	261	80	25	7	2%	1.3	27.3%	9.9%	17.5%	2.6%	4.29	3.47	+0.8
2018	23	MIX RAW	2 levels	48	1	63	261	80	25	7	2%	1.3	30.7%	9.6%	21.1%	2.7%	4.29	3.20	+1.0
2019	24	MIX MLE	2 levels	52	0	68	311	84	37	4	0%	1.3	25.3%	12.2%	13.1%	1.4%	4.92	3.26	+1.0
2019	24	MIX RAW	2 levels	52	0	68	311	84	37	4	0%	1.3	27.0%	11.9%	15.1%	1.3%	4.92	3.03	+1.2
2020	25	MLB MLE	Baltimore Orioles	14	0	14	69	20	10	1	0%	1.0	29.0%	14.5%	14.5%	1.3%	5.02	3.21	+0.2
2020	25	MLB RAW	Baltimore Orioles	14	0	14	69	20	10	1	0%	1.0	29.0%	14.5%	14.5%	1.4%	5.02	3.31	+0.2
2021	26	MIX MLE	2 levels	28	1	42	178	49	17	6	4%	1.5	25.0%	9.9%	15.1%	3.5%	4.32	4.15	+0.2
2021	26	MIX RAW	2 levels	28	1	42	178	49	17	6	4%	1.5	27.5%	9.6%	18.0%	3.4%	4.32	3.84	+0.3
2022	27	MLB MLE	Los Angeles Dodgers	64	0	63	233	77	14	2	0%	1.0	33.0%	6.0%	27.0%	0.8%	1.14	1.52	+2.3
2022	27	MLB RAW	Los Angeles Dodgers	64	0	63	233	77	14	2	0%	1.0	33.0%	6.0%	27.0%	0.9%	1.14	1.73	+2.1
2023	28	MLB MLE	Los Angeles Dodgers	62	0	61	234	66	11	6	0%	1.0	28.2%	4.7%	23.5%	2.5%	2.05	2.66	+1.4
2023	28	MLB RAW	Los Angeles Dodgers	62	0	61	234	66	11	6	0%	1.0	28.2%	4.7%	23.5%	2.6%	2.05	2.76	+1.3
2024	29	MIX MLE	2 levels	63	0	56	233	66	16	6	0%	0.9	27.6%	7.0%	20.6%	2.5%	3.51	3.04	+1.0
2024	29	MIX MLE	2 levels	63	0	56	233	66	16	6	0%	0.9	27.6%	7.0%	20.6%	2.5%	3.51	3.04	+1.0
2024	29	MIX RAW	2 levels	63	0	56	233	66	16	6	0%	0.9	28.3%	6.9%	21.5%	2.6%	3.51	2.99	+1.0
2025	30	MIX MLE	2 levels	13	1	11	48	15	3	0	8%	0.9	31.2%	6.2%	25.0%	0.0%	3.18	1.25	+0.5
2025	30	MIX MLE	2 levels	13	1	11	48	15	3	0	8%	0.9	31.2%	6.2%	25.0%	0.0%	3.18	1.25	+0.5
2025	30	MIX RAW	2 levels	13	1	11	48	15	3	0	8%	0.9	31.2%	6.2%	25.0%	0.0%	3.18	1.25	+0.5
2026	31	MIX MLE	2 levels	43	0	36	151	46	8	6	0%	0.8	31.1%	2.8%	28.3%	4.5%	3.00	3.31	+0.5
2026	31	MIX MLE	2 levels	43	0	36	151	46	8	6	0%	0.8	31.1%	2.8%	28.3%	4.5%	3.00	3.31	+0.5
2026	31	MIX RAW	2 levels	43	0	36	151	46	8	6	0%	0.8	30.5%	5.3%	25.2%	4.0%	3.00	3.38	+0.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			281	1	278	1149	324	90	28	0%	1.0	28.2%	7.8%	20.4%	2.4%	3.37	3.05	+5.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	LAD	59	0	62	262	79	11	9	0%	1.1	30.0%	4.3%	25.7%	3.4%	3.50	3.34	+0.9
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	LAD	54	0	57	241	70	12	9	0%	1.1	29.1%	4.8%	24.3%	3.6%	3.57	3.62	+0.6
2029	34	MLB MLE	LAD	47	0	49	208	59	11	8	0%	1.0	28.2%	5.3%	22.9%	3.9%	3.78	3.93	+0.4
2028	33	MLB CTX	LAD	51	0	54	228	66	11	8	0%	1.1	29.1%	4.8%	24.3%	3.6%	3.57	3.62	+0.6
2029	34	MLB CTX	LAD	43	0	45	190	54	10	7	0%	1.0	28.2%	5.3%	22.9%	3.9%	3.78	3.93	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		375	1	377	1566	444	111	44	0%	1.0	28.3%	7.1%	21.3%	2.8%	3.45	3.14	+6.3
/ 200 IP	—	RAW		199	1	200	831	236	59	23	0%	1.0	28.3%	7.1%	21.3%	2.8%	3.45	3.14	+3.4
Career	—	MLE		488	4	558	2332	604	216	50	1%	1.1	25.9%	9.3%	16.6%	2.2%	3.55	3.27	+6.0
/ 200 IP	—	MLE		175	1	200	835	216	77	18	1%	1.1	25.9%	9.3%	16.6%	2.2%	3.55	3.27	+3.1

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 AAAOklahoma City Comets · 10 IPFIP 3.29 → 3.61 (+0.32)K% 28.9% → 24.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.89%	—	×0.860	24.84%
BB% (unintentional) /BF	11.11%	—	×0.900	10.00%
HR / BF /BF	2.22%	÷1.000	×1.100	2.44%

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 3.29 → 3.61, 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 AAAOklahoma City Comets · 6 IPFIP 0.66 → 1.02 (+0.36)K% 34.6% → 29.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.62%	—	×0.860	29.77%
BB% (unintentional) /BF	3.85%	—	×0.900	3.46%
HR / BF /BF	0.00%	÷0.956	×1.100	0.00%

Result: FIP 0.66 → 1.02, 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 AAADurham Bulls · 28 IPFIP 4.09 → 4.56 (+0.48)K% 31.7% → 27.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.67%	—	×0.880	27.87%
BB% (unintentional) /BF	10.83%	—	×1.050	11.38%
HR / BF /BF	4.17%	÷1.059	×1.100	4.33%

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 112).

Result: FIP 4.09 → 4.56, 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 AAANorfolk Tides · 40 IPFIP 2.83 → 3.30 (+0.48)K% 25.7% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.73%	—	×0.880	22.64%
BB% (unintentional) /BF	9.94%	—	×1.050	10.44%
HR / BF /BF	1.17%	÷0.889	×1.100	1.45%

Result: FIP 2.83 → 3.30, 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 AAANorfolk Tides · 51 IPFIP 1.57 → 2.06 (+0.48)K% 35.6% → 31.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.64%	—	×0.880	31.37%
BB% (unintentional) /BF	7.43%	—	×1.050	7.80%
HR / BF /BF	0.99%	÷0.964	×1.100	1.13%

Result: FIP 1.57 → 2.06, 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 AAAGwinnett Braves · 30 IPFIP 3.73 → 4.09 (+0.36)K% 20.7% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.71%	—	×0.880	18.23%
BB% (unintentional) /BF	15.71%	—	×1.050	16.50%
HR / BF /BF	0.71%	÷0.972	×1.100	0.81%

Result: FIP 3.73 → 4.09, 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).

2017 AAMississippi Braves · 21 IPFIP 5.21 → 6.63 (+1.41)K% 25.5% → 20.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.53%	—	×0.810	20.68%
BB% (unintentional) /BF	10.64%	—	×1.100	11.70%
HR / BF /BF	5.32%	÷0.925	×1.200	6.90%

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 85).

Result: FIP 5.21 → 6.63, 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 AAMississippi Braves · 34 IPFIP 2.76 → 3.43 (+0.67)K% 28.5% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.48%	—	×0.810	23.07%
BB% (unintentional) /BF	10.60%	—	×1.100	11.66%
HR / BF /BF	1.32%	÷1.084	×1.200	1.47%

Result: FIP 2.76 → 3.43, 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
Evan Phillips (OGILVIE)	—	—	3.34	30.0%	4.3%	3.4%	—	3.76	28.7%	23.7%	106	+0.42	—	—	—
Akinori Otsuka R 2004 · 2.61 FIP	32	SU	2.61	27.9%	6.4%	1.9%	.251	2.78	20.3%	13.4%	155	+0.17	2.39	232	71
Chris Martin R 2018 · 3.04 FIP	32	SU	3.04	20.9%	1.7%	2.7%	.311	2.92	25.7%	23.1%	117	-0.12	1.76	431	68
C.C. Lee R 2018 · 3.03 FIP	31	SU	3.03	34.7%	9.1%	3.1%	.275	—	—	—	—	—	2.59	149	67
Gregory Infante R 2018 · 4.07 FIP	31	SU	4.07	22.0%	4.6%	4.1%	.291	—	—	—	—	—	2.97	230	67
Will Harris R 2017 · 3.35 FIP	32	SU	3.35	29.4%	4.0%	4.1%	.270	2.87	27.1%	20.6%	134	-0.48	2.17	414	64
Blake Parker R 2017 · 2.52 FIP	32	SU	2.52	33.9%	6.3%	2.7%	.228	4.20	26.6%	18.8%	144	+1.68	2.52	406	63
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	63
Justin Miller R 2010 · 3.42 FIP	32	SU	3.42	29.1%	5.8%	3.7%	.286	—	—	—	—	—	2.63	373	63
Danny Patterson R 2003 · 2.35 FIP	32	SU	2.35	26.0%	5.5%	1.4%	.286	5.10	13.4%	5.6%	42	+2.75	2.35	373	63
Sergio Santos R 2015 · 4.17 FIP	32	SU	4.17	24.7%	8.2%	3.9%	.283	—	—	—	—	—	1.36	178	63
Chris Hatcher R 2017 · 4.31 FIP	32	SU	4.31	24.5%	7.4%	4.3%	.291	5.32	18.0%	8.4%	36	+1.01	2.51	246	63
Frank Herrmann R 2016 · 4.42 FIP	32	SU	4.42	21.5%	4.8%	4.6%	.271	—	—	—	—	—	2.92	219	62
Jay Jackson R 2019 · 2.80 FIP	31	SU	2.80	32.4%	9.1%	2.3%	.272	3.59	29.4%	19.9%	41	+0.79	2.36	261	62
Spencer Patton R 2021 · 3.04 FIP	33	SU	3.04	27.9%	8.7%	2.2%	.305	4.97	21.2%	10.4%	88	+1.93	2.79	239	62
Ben Heller R 2024 · 3.76 FIP	32	SU	3.76	31.0%	7.9%	4.2%	.299	—	—	—	—	—	2.49	246	61
Dale Thayer R 2013 · 3.62 FIP	32	SU	3.62	23.7%	7.4%	2.9%	.287	3.85	20.6%	15.0%	103	+0.23	2.75	239	61
Mark Serrano R 2017 · 3.56 FIP	31	SU	3.56	21.9%	6.4%	2.7%	.240	5.25	20.2%	12.3%	42	+1.69	3.16	120	61
George Kontos R 2017 · 3.71 FIP	32	SU	3.71	25.2%	6.5%	3.5%	.287	4.41	14.7%	8.6%	97	+0.70	2.56	421	61
Tony Pena Jr. R 2015 · 2.80 FIP	34	SU	2.80	18.8%	2.7%	1.7%	.294	3.02	18.7%	14.4%	82	+0.22	2.80	128	60
Jesus Pirela R 2019 · 3.24 FIP	30	SU	3.24	22.5%	5.3%	2.5%	.277	—	—	—	—	—	3.24	161	60

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	2.2	56	28.6%	7.1%	1.12	3.46
Giovanny Gallegos ('24)	1.7	56	29.6%	6.6%	1.18	3.49
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*
Héctor Rondón ('20)	2.2	54	24.2%	7.4%	1.03	3.49
Josh Fields ('18)	1.4	46	27.5%	8.0%	0.98	3.71
Joe Sambito ('76-'87, 8 WAR*)	3.1	70	26.8%*	7.5%*	1.06*	3.65*
Joe Hoerner ('63-'77, 8 WAR*)	2.8	51	23.2%*	7.9%*	1.21*	3.52*