Jack Dreyer

P Los Angeles Dodgers

Age 28 LHP 6'2" / 205 lbs MLB peak 0.6 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	46	0	57	2.20	2.12	31.7%	5.3%	—	K 26.8% · BB 5.0% · FIP 2.66
2025	26	MLBLAD	67	5	76	2.95	2.59	24.1%	6.2%	1.8
2026	27	MLBLAD	67	3	65	3.20	3.13	28.0%	7.3%	1.1
2027PROJ	28	MLBLAD	58	0	61	3.43	3.58	25.2%	6.6%	0.7
2028PROJ95% MLB	29	MLBLAD	47	0	49	3.62	3.74	24.7%	6.9%	0.5
2029PROJ95% MLB	30	MLBLAD	38	0	40	3.82	3.95	24.0%	7.1%	0.3

Last 3 seasons WAR 2.9 · Next 3 projected WAR 1.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%81

xwOBA vs73

FB Velo43

Form3.27 ERA (proj 3.43) · K 26.4% (proj 25.2%) · BB 12.1% (proj 6.6%) ▼ last 90d · 22 IP through Oct 27

CompsJustin Wilson (age 28) · Darin Downs (age 28) · Hideki Okajima (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 8189vR 97

ERA3.43

FIP3.58

K%25.2%

BB%6.6%

K-BB%18.6%

Proj IP62

Value2027 · WAR

Runs saved vs league avg · 62 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL5050

CMD5555

K†6060

Statcast Percentiles

FB Velo

p4394.0

Whiff%

p6728.0%

p8128.0%

xwOBA vs

p730.290

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)
2022	23	ROK MLE	ACL Dodgers	12	0	12	47	13	3	2	0%	1.0	27.7%	6.4%	21.3%	4.3%	1.50	3.91	—
2022	23	ROK RAW	ACL Dodgers	12	0	12	47	13	3	2	0%	1.0	27.7%	6.4%	21.3%	4.3%	1.50	3.85	—
2023	24	A+ MLE	Great Lakes Loons	42	0	55	227	79	36	1	0%	1.3	26.8%	18.2%	8.6%	0.6%	2.30	3.46	—
2023	24	A+ RAW	Great Lakes Loons	42	0	55	227	79	36	1	0%	1.3	34.8%	15.9%	18.9%	0.4%	2.30	2.42	—
2024	25	MIX MLE	2 levels	46	0	57	227	72	12	4	0%	1.2	26.8%	5.0%	21.8%	2.2%	2.20	2.66	—
2024	25	MIX MLE	2 levels	46	0	57	227	72	12	4	0%	1.2	26.8%	5.0%	21.8%	2.2%	2.20	2.66	—
2024	25	MIX RAW	2 levels	46	0	57	227	72	12	4	0%	1.2	31.7%	5.3%	26.4%	1.8%	2.20	2.12	—
2025	26	MLB MLE	Los Angeles Dodgers	67	5	76	307	74	19	4	7%	1.1	24.1%	6.2%	17.9%	1.2%	2.95	2.53	+1.8
2025	26	MLB MLE	Los Angeles Dodgers	67	5	76	307	74	19	4	7%	1.1	24.1%	6.2%	17.9%	1.2%	2.95	2.53	+1.8
2025	26	MLB RAW	Los Angeles Dodgers	67	5	76	307	74	19	4	7%	1.1	24.1%	6.2%	17.9%	1.3%	2.95	2.59	+1.8
2026	27	MLB MLE	Los Angeles Dodgers	67	3	65	261	73	19	7	4%	1.0	28.0%	7.3%	20.7%	2.6%	3.20	3.07	+1.1
2026	27	MLB MLE	Los Angeles Dodgers	67	3	65	261	73	19	7	4%	1.0	28.0%	7.3%	20.7%	2.6%	3.20	3.07	+1.1
2026	27	MLB RAW	Los Angeles Dodgers	67	3	65	261	73	19	7	4%	1.0	28.0%	7.3%	20.7%	2.7%	3.20	3.13	+1.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			134	8	141	568	147	38	11	6%	1.1	25.9%	6.7%	19.2%	1.9%	3.06	2.84	+2.9
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	LAD	58	0	61	258	65	17	7	0%	1.1	25.2%	6.6%	18.6%	2.5%	3.43	3.58	+0.7
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	LAD	49	0	51	217	54	15	6	0%	1.0	24.7%	6.9%	17.8%	2.7%	3.62	3.74	+0.5
2029	30	MLB MLE	LAD	40	0	42	179	43	13	5	0%	1.1	24.0%	7.1%	16.8%	2.9%	3.82	3.95	+0.3
2028	29	MLB CTX	LAD	47	0	49	207	51	14	6	0%	1.0	24.7%	6.9%	17.8%	2.7%	3.62	3.74	+0.5
2029	30	MLB CTX	LAD	38	0	40	169	40	12	5	0%	1.1	24.0%	7.1%	16.8%	2.9%	3.82	3.95	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		219	8	230	944	238	64	21	4%	1.1	25.3%	6.8%	18.5%	2.3%	3.31	3.07	+4.0
/ 200 IP	—	RAW		190	7	200	821	207	56	18	4%	1.1	25.3%	6.8%	18.5%	2.3%	3.31	3.07	+3.5
Career	—	MLE		234	8	265	1069	282	94	19	3%	1.1	26.4%	8.8%	17.6%	1.8%	2.65	2.95	+3.7
/ 200 IP	—	MLE		177	6	200	807	213	71	14	3%	1.1	26.4%	8.8%	17.6%	1.8%	2.65	2.95	+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.

2024 AAAOklahoma City Baseball Club · 43 IPFIP 2.49 → 3.07 (+0.57)K% 29.9% → 25.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.89%	—	×0.860	25.70%
BB% (unintentional) /BF	5.17%	—	×0.900	4.66%
HR / BF /BF	2.30%	÷0.896	×1.100	2.82%

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 79).

Result: FIP 2.49 → 3.07, 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 AATulsa Drillers · 15 IPFIP 0.63 → 1.31 (+0.68)K% 37.7% → 30.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.74%	—	×0.810	30.57%
BB% (unintentional) /BF	5.66%	—	×1.100	6.23%
HR / BF /BF	0.00%	÷1.063	×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 113).

Result: FIP 0.63 → 1.31, 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 A+Great Lakes Loons · 55 IPFIP 2.41 → 3.46 (+1.05)K% 34.8% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.80%	—	×0.770	26.80%
BB% (unintentional) /BF	15.86%	—	×1.150	18.24%
HR / BF /BF	0.44%	÷0.951	×1.250	0.58%

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 90).

Result: FIP 2.41 → 3.46, 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 ROKACL Dodgers · 12 IPFIP 3.91 → 6.11 (+2.20)K% 27.7% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.66%	—	×0.680	18.81%
BB% (unintentional) /BF	6.38%	—	×1.250	7.98%
HR / BF /BF	4.26%	÷0.912	×1.400	6.54%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 82).

Result: FIP 3.91 → 6.11, 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
Jack Dreyer (OGILVIE)	—	—	3.58	25.2%	6.6%	2.5%	—	3.83	24.3%	17.4%	94	+0.25	—	—	—
Justin Wilson L 2016 · 3.04 FIP	28	SU	3.04	25.9%	6.0%	2.5%	.333	3.45	29.7%	16.8%	152	+0.41	2.49	554	83
Darin Downs L 2013 · 3.30 FIP	28	SU	3.30	24.5%	6.0%	2.8%	.317	3.87	16.5%	7.3%	51	+0.57	2.83	107	79
Hideki Okajima L 2007 · 3.05 FIP	31	SU	3.05	23.2%	5.5%	2.2%	.234	3.87	20.2%	12.6%	169	+0.82	3.05	238	78
Adam Liberatore L 2015 · 3.64 FIP	28	SU	3.64	21.1%	7.3%	2.5%	.267	3.17	23.3%	15.2%	73	-0.47	2.38	124	78
Daniel Stumpf L 2019 · 3.56 FIP	28	SU	3.56	25.2%	8.8%	2.7%	.314	—	—	—	—	—	1.84	238	77
Hunter Cervenka L 2018 · 3.08 FIP	28	SU	3.08	24.6%	6.6%	2.2%	.268	3.11	26.6%	13.5%	55	+0.03	3.08	194	77
Ryan O'Rourke L 2016 · 3.05 FIP	28	SU	3.05	23.4%	6.7%	1.9%	.284	4.08	22.1%	7.8%	56	+1.03	3.05	145	76
Wesley Wright L 2013 · 3.73 FIP	28	SU	3.73	23.7%	7.3%	3.1%	.307	3.54	15.8%	6.9%	104	-0.19	3.03	375	76
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	75
Tony Sipp L 2011 · 4.43 FIP	28	SU	4.43	22.7%	8.4%	4.0%	.215	3.89	26.0%	16.7%	143	-0.54	2.22	504	75
Josh Edgin L 2014 · 2.62 FIP	27	SU	2.62	26.9%	5.8%	1.9%	.250	3.84	19.0%	7.4%	70	+1.22	2.62	195	75
Mike Dunn L 2013 · 3.05 FIP	28	SU	3.05	25.5%	8.5%	1.9%	.265	3.39	25.9%	16.8%	153	+0.34	2.82	432	75
Mike Holtz L 2001 · 3.66 FIP	28	SU	3.66	22.8%	6.6%	3.0%	.310	5.33	14.6%	-0.6%	35	+1.67	2.61	238	75
Ryan Sherriff L 2017 · 2.96 FIP	27	SU	2.96	20.7%	5.7%	1.6%	.257	—	—	—	—	—	2.96	245	74
Brian Fuentes L 2004 · 3.27 FIP	28	SU	3.27	23.9%	6.5%	2.5%	.304	3.33	25.8%	17.0%	201	+0.06	2.08	602	74
Damaso Marte L 2003 · 2.41 FIP	28	SU	2.41	27.7%	8.9%	1.0%	.240	3.88	23.9%	13.1%	177	+1.47	2.41	495	74
Kevin Chapman L 2016 · 3.35 FIP	28	SU	3.35	23.2%	9.5%	1.8%	.348	4.08	19.2%	8.0%	39	+0.73	3.01	194	74
Jose Mijares L 2013 · 2.78 FIP	28	SU	2.78	22.9%	6.8%	1.4%	.393	—	—	—	—	—	2.78	249	74
Josh Smoker L 2017 · 4.20 FIP	28	SU	4.20	25.5%	9.4%	3.8%	.329	4.35	20.2%	11.3%	59	+0.15	2.71	230	73
David Purcey L 2010 · 3.60 FIP	28	SU	3.60	22.4%	9.8%	2.1%	.245	4.29	16.7%	2.7%	59	+0.69	3.60	206	73

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	1.5	59	25.2%	7.5%	0.90	3.34
Todd Worrell ('97)	1.7	55	23.4%	7.5%	0.95	3.58
Pedro Báez ('22)	1.8	60	25.3%	8.3%	0.99	3.08
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
Carlos Diaz ('82-'86, 2 WAR*)	1.3	52	25.1%*	8.7%*	0.91*	3.84*
Joe Sambito ('76-'87, 8 WAR*)	3.1	70	26.8%*	7.5%*	1.06*	3.65*