DJ Herz

P Rochester Red Wings

Age 26 LHP 6'2" / 197 lbs AAA Svc 2.0 · Ctrl thru 2030 peak 0.9 · 2027

Overview

AAASP40-MANPre-ArbFA 2031

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	22	AAWSH	22	22	94	3.43	2.78	32.4%	13.9%	—	K 26.2% · BB 15.3% · FIP 3.54
2024	23	MIX2 levels	29	29	128	4.08	3.77	27.3%	12.4%	2.5	K 26.2% · BB 11.8% · FIP 3.82
2026	25	MIX5 levels	12	12	33	4.68	4.60	26.1%	7.2%	0.3	K 19.1% · BB 6.7% · FIP 6.80
2027PROJ	26	MLBWSH	13	13	78	4.26	4.50	24.3%	9.5%	0.8
2028PROJ90% MLB	27	MLBWSH	13	13	76	4.40	4.51	24.1%	9.4%	0.8
2029PROJ92% MLB	28	MLBWSH	12	12	74	4.50	4.58	23.8%	9.4%	0.7

Last 3 seasons WAR 2.8 · Next 3 projected WAR 2.3Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2030Service2.605First FA2031

2027Pre-Arb$0.8M2028Arb-1$3M2029Arb-2$4M2030Arb-3$5M

Skills · percentileStatcast 2024

K%80

xwOBA vs77

FB Velo36

CompsBrad Mills (age 26) · Hunter Barco (age 23) · Hung-Chih Kuo (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 92100vR 108

ERA4.26

FIP4.50

K%24.3%

BB%9.5%

K-BB%14.8%

Proj IP89

Value2027 · WAR

Runs saved vs league avg · 89 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$10M ctrl surplus

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL4545

CMD5555

K†6060

Statcast Percentiles

FB Velo

p3693.5

Whiff%

p7629.3%

p8027.7%

xwOBA vs

p770.286

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status Pre-Arb

MLB Debut 2024

Service 2.605 yrs.days

Team Control Through 2030

First FA Year 2031

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Pre-Arb	$0.8M	+0.8	$3M	+$2M
2028	Arb-1	$3M	+0.8	$3M	+$0.6M
2029	Arb-2	$4M	+0.7	$2M	+$0.0M (cut)
2030	Arb-3	$5M	+0.5	$2M	+$0.0M (cut)
Totals		$3M		$10M	+$3M

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	18	ROK MLE	AZL Cubs 2	6	6	10	50	8	8	0	100%	1.7	10.9%	20.0%	-9.1%	0.0%	2.61	4.71	—
2019	18	ROK RAW	AZL Cubs 2	6	6	10	50	8	8	0	100%	1.7	16.0%	16.0%	0.0%	0.0%	2.61	3.87	—
2021	20	MIX MLE	2 levels	20	20	82	324	131	44	7	100%	4.1	30.2%	16.0%	14.2%	2.9%	3.31	4.16	—
2021	20	MIX RAW	2 levels	20	20	82	324	131	44	7	100%	4.1	40.4%	13.6%	26.9%	2.2%	3.31	2.62	—
2022	21	MIX MLE	2 levels	26	26	95	418	141	70	8	100%	3.7	26.4%	18.9%	7.5%	2.4%	4.25	4.57	—
2022	21	MIX RAW	2 levels	26	26	95	418	141	70	8	100%	3.7	33.7%	16.7%	17.0%	1.9%	4.25	3.44	—
2023	22	AA MLE	Harrisburg Senators	22	22	94	411	133	57	5	100%	4.3	26.2%	15.3%	11.0%	1.3%	3.43	3.54	—
2023	22	AA RAW	Harrisburg Senators	22	22	94	411	133	57	5	100%	4.3	32.4%	13.9%	18.5%	1.2%	3.43	2.78	—
2024	23	MIX MLE	2 levels	29	29	128	550	150	68	14	100%	4.4	26.2%	11.8%	14.4%	2.6%	4.08	3.82	+2.4
2024	23	MIX MLE	2 levels	29	29	128	550	150	68	14	100%	4.4	26.2%	11.8%	14.4%	2.6%	4.08	3.82	+2.4
2024	23	MIX RAW	2 levels	29	29	128	550	150	68	14	100%	4.4	27.3%	12.4%	14.9%	2.5%	4.08	3.77	+2.5
2026	25	MIX MLE	5 levels	12	12	33	138	36	10	7	100%	2.7	19.1%	6.7%	12.4%	8.1%	4.68	6.80	-0.5
2026	25	MIX MLE	5 levels	12	12	33	138	36	10	7	100%	2.7	19.1%	6.7%	12.4%	8.1%	4.68	6.80	-0.5
2026	25	MIX RAW	5 levels	12	12	33	138	36	10	7	100%	2.7	26.1%	7.2%	18.8%	5.1%	4.68	4.60	+0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			21	21	96	417	112	39	14	100%	4.6	26.9%	9.4%	17.5%	3.4%	4.61	3.88	+1.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	WSH	13	13	78	329	80	31	11	100%	6.0	24.3%	9.5%	14.8%	3.4%	4.26	4.50	+0.8
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	WSH	14	14	84	355	85	33	12	100%	6.0	24.1%	9.4%	14.6%	3.4%	4.40	4.51	+0.9
2029	28	MLB MLE	WSH	13	13	80	337	80	32	12	100%	6.1	23.8%	9.4%	14.3%	3.5%	4.50	4.58	+0.8
2030	29	MLB MLE	WSH	12	12	73	309	71	30	11	100%	6.1	23.1%	9.6%	13.5%	3.6%	4.63	4.72	+0.6
2031	30	MLB MLE	WSH	11	11	65	276	62	27	10	100%	5.9	22.4%	9.8%	12.6%	3.8%	4.80	4.92	+0.4
2028	27	MLB CTX	WSH	13	13	76	321	77	30	11	100%	5.8	24.1%	9.4%	14.6%	3.4%	4.40	4.51	+0.8
2029	28	MLB CTX	WSH	12	12	74	312	74	29	11	100%	6.2	23.8%	9.4%	14.3%	3.5%	4.50	4.58	+0.7
2030	29	MLB CTX	WSH	11	11	68	287	66	27	10	100%	6.2	23.1%	9.6%	13.5%	3.6%	4.63	4.72	+0.5
2031	30	MLB CTX	WSH	10	10	61	258	58	25	10	100%	6.1	22.4%	9.8%	12.6%	3.8%	4.80	4.92	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		67	67	375	1595	387	151	56	100%	5.6	24.3%	9.5%	14.8%	3.5%	4.58	4.18	+5.4
/ 200 IP	—	RAW		36	36	200	851	207	81	30	100%	5.6	24.3%	9.5%	14.8%	3.5%	4.58	4.18	+2.9
Career	—	MLE		115	115	442	1891	491	277	50	100%	3.8	26.0%	14.7%	11.3%	2.7%	3.85	4.22	+4.3
/ 200 IP	—	MLE		52	52	200	855	222	125	23	100%	3.8	26.0%	14.7%	11.3%	2.7%	3.85	4.22	+2.2

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 AAARochester Red Wings · 13 IPFIP 6.23 → 6.80 (+0.58)K% 22.2% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.22%	—	×0.860	19.11%
BB% (unintentional) /BF	7.41%	—	×0.900	6.67%
HR / BF /BF	7.41%	÷1.000	×1.100	8.15%

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 6.23 → 6.80, 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).

2024 AAARochester Red Wings · 39 IPFIP 4.28 → 4.46 (+0.18)K% 26.2% → 22.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.19%	—	×0.860	22.52%
BB% (unintentional) /BF	19.05%	—	×0.900	17.14%
HR / BF /BF	1.79%	÷0.986	×1.100	1.99%

Result: FIP 4.28 → 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).

2023 AAHarrisburg Senators · 94 IPFIP 2.79 → 3.54 (+0.75)K% 32.4% → 26.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.36%	—	×0.810	26.21%
BB% (unintentional) /BF	13.87%	—	×1.100	15.26%
HR / BF /BF	1.22%	÷1.115	×1.200	1.31%

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 123).

Result: FIP 2.79 → 3.54, 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).

2022 A+South Bend Cubs · 64 IPFIP 2.32 → 3.54 (+1.22)K% 38.1% → 29.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.08%	—	×0.770	29.32%
BB% (unintentional) /BF	14.23%	—	×1.150	16.37%
HR / BF /BF	1.15%	÷0.938	×1.250	1.54%

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 88).

Result: FIP 2.32 → 3.54, 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).

2022 AATennessee Smokies · 32 IPFIP 5.24 → 6.26 (+1.02)K% 26.6% → 21.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.58%	—	×0.810	21.53%
BB% (unintentional) /BF	20.89%	—	×1.100	22.97%
HR / BF /BF	3.16%	÷1.010	×1.200	3.76%

Result: FIP 5.24 → 6.26, 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 AMyrtle Beach Pelicans · 66 IPFIP 2.81 → 4.45 (+1.64)K% 40.4% → 29.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.38%	—	×0.740	29.88%
BB% (unintentional) /BF	14.62%	—	×1.180	17.25%
HR / BF /BF	2.31%	÷0.977	×1.300	3.07%

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 95).

Result: FIP 2.81 → 4.45, 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+South Bend Cubs · 16 IPFIP 1.71 → 2.98 (+1.26)K% 40.6% → 31.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.62%	—	×0.770	31.28%
BB% (unintentional) /BF	9.38%	—	×1.150	10.78%
HR / BF /BF	1.56%	÷0.928	×1.250	2.10%

Result: FIP 1.71 → 2.98, 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 ROKAZL Cubs 2 · 10 IPFIP 3.78 → 4.71 (+0.94)K% 16.0% → 10.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.00%	—	×0.680	10.88%
BB% (unintentional) /BF	16.00%	—	×1.250	20.00%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

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 100).

Result: FIP 3.78 → 4.71, 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
DJ Herz (OGILVIE)	—	—	4.50	24.3%	9.5%	3.4%	—	4.60	23.7%	14.2%	237	+0.10	—	—	—
Brad Mills L 2011 · 5.37 FIP	26	SP-	5.37	19.8%	12.1%	4.4%	.328	5.61	18.8%	7.9%	21	+0.24	4.22	243	73
Hunter Barco L 2024 · 3.61 FIP	23	SP	3.61	23.4%	10.0%	2.2%	.275	3.72	21.1%	10.0%	195	+0.11	3.29	257	68
Hung-Chih Kuo L 2007 · 3.91 FIP	26	SP-	3.91	19.3%	10.0%	2.1%	.333	2.04	29.8%	22.7%	170	-1.87	1.63	287	65
Tommy Shirley L 2015 · 3.35 FIP	26	SP-	3.35	19.6%	7.0%	1.9%	.252	4.93	13.0%	4.2%	106	+1.58	3.35	147	64
Jordan Montgomery L 2018 · 4.07 FIP	25	SP	4.07	19.8%	10.3%	2.4%	.282	3.49	24.5%	17.4%	201	-0.58	3.11	1,189	64
Jake Dahlberg L 2021 · 4.33 FIP	27	SP	4.33	22.5%	5.0%	4.6%	.397	5.36	17.9%	10.2%	100	+1.03	3.11	226	63
David Purcey L 2008 · 4.39 FIP	26	SP	4.39	20.1%	10.0%	3.1%	.301	4.39	17.9%	5.0%	116	-0.00	3.60	206	63
James Paxton L 2015 · 4.22 FIP	26	SP	4.22	18.9%	9.4%	2.8%	.288	2.95	27.7%	21.7%	468	-1.27	2.46	1,022	63
Jordan Wicks L 2024 · 5.12 FIP	24	SP	5.12	20.8%	9.0%	4.8%	.306	4.12	18.4%	10.9%	184	-1.00	2.92	472	62
Michael Plassmeyer L 2023 · 4.41 FIP	26	SP	4.41	21.3%	9.0%	3.6%	.319	4.54	20.1%	13.8%	216	+0.13	3.42	653	62
Hayden Mullins L 2024 · 4.39 FIP	23	SP-	4.39	23.4%	12.4%	3.1%	.288	3.69	25.5%	11.8%	194	-0.70	3.54	283	62
T.J. Sikkema L 2024 · 3.57 FIP	26	SP-	3.57	18.5%	6.0%	2.3%	.282	4.10	16.1%	7.2%	87	+0.53	3.57	300	61
Taylor Varnell L 2021 · 4.48 FIP	26	SP	4.48	20.1%	10.3%	3.2%	.278	—	—	—	—	—	2.89	248	61
Aríel Miranda L 2015 · 3.46 FIP	26	SP	3.46	18.3%	10.2%	1.1%	.280	5.12	19.2%	10.2%	364	+1.66	3.46	431	60
Brent Headrick L 2024 · 4.12 FIP	26	SP-	4.12	26.7%	7.3%	4.3%	.262	2.73	28.8%	21.4%	125	-1.39	2.36	414	59
Hayden Wynja L 2024 · 4.79 FIP	25	SP-	4.79	18.0%	10.5%	3.4%	.274	—	—	—	—	—	4.74	154	59
Jonathan Dziedzic L 2017 · 5.29 FIP	26	SP	5.29	17.3%	8.2%	4.8%	.280	4.68	13.5%	4.4%	198	-0.61	3.88	522	59
Rodney Boone L 2024 · 4.56 FIP	24	SP-	4.56	18.1%	9.8%	3.2%	.221	3.64	18.5%	10.8%	78	-0.92	3.64	311	59
Christian MacLeod L 2024 · 4.77 FIP	24	SP	4.77	21.5%	13.6%	3.2%	.269	4.50	18.0%	3.0%	128	-0.27	3.88	280	58
Shawn Morimando L 2019 · 5.17 FIP	26	SP	5.17	21.0%	10.9%	4.5%	.330	5.47	19.4%	10.8%	100	+0.30	3.98	685	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	2.4	81	24.2%	9.5%	1.35	4.52
Rich DeLucia ('90-'99, 1 WAR*)	3.1	78	23.2%*	10.5%*	1.55*	4.65*
Dave Tobik ('78-'85, 4 WAR*)	2.0	66	24.5%*	9.3%*	1.33*	3.87*
Keith Atherton ('83-'89, 2 WAR*)	2.8	81	19.9%*	8.7%*	1.39*	4.24*
Adam Conley ('21)	2.2	87	19.8%	9.4%	1.16	4.71
Félix Peña ('21)	1.3	65	23.9%	8.5%	1.35	4.66
Juan Nicasio ('20)	3.6	80	21.3%	8.3%	1.04	4.71