Ethan Dorchies

P Wisconsin Timber Rattlers

Age 20 RHP 6'5" / 215 lbs A+ Svc 0.0 · Ctrl thru 2034 peak 1.1 · 2031

Overview

A+PROSPECTMiLBFA 2035

OGV OFP45OGV rank#120ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	18	MIX2 levels	19	11	82	2.74	2.84	26.7%	10.5%	—	K 19.2% · BB 12.6% · FIP 3.78
2026	19	A+MIL	25	25	113	5.26	4.34	19.6%	9.5%	—	K 15.1% · BB 10.9% · FIP 5.21
2027PROJ	20	MLBMIL	1	1	1	5.23	5.23	16.7%	11.5%	0.0
2028PROJ49% MLB	21	MLBMIL	13	13	66	5.08	5.00	18.6%	10.6%	0.4
2029PROJ73% MLB	22	MLBMIL	19	19	97	4.83	4.70	20.4%	9.8%	0.9

Next 3 projected WAR 1.2Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2034Service0.0First FA2035

2027MiLB2028MiLB2029Pre-Arb$0.8M2030Pre-Arb$0.8M2031Pre-Arb$0.9M2032Arb-1$3M2033Arb-2$5M2034Arb-3$7M

Career WAR0.0 WAR median (P10 -0.2 / P90 15, comp-based) · star 2% · didn't stick 81%

CompsAdam Hill (age 22) · Trevor Clifton (age 20) · Josh Grosz (age 21)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 133124vR 116

ERA5.23

FIP5.23

K%16.7%

BB%11.5%

K-BB%5.2%

Proj IP133

Value2027 · WAR

Runs saved vs league avg · 133 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$47M ctrl surplus

Contract

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

Status MiLB

MLB Debut 2029

Service 0 yrs (est)

Team Control Through 2034

First FA Year 2035

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2029
2028	MiLB	still in minors · estimated debut 2029
2029	Pre-Arb	$0.8M	+0.9	$3M	+$2M
2030	Pre-Arb	$0.8M	+1.3	$8M	+$8M
2031	Pre-Arb	$0.9M	+1.5	$9M	+$8M
2032	Arb-1	$3M	+1.3	$7M	+$5M
2033	Arb-2	$5M	+1.3	$7M	+$4M
2034	Arb-3	$7M	+1.3	$6M	+$3M
Totals		$17M		$40M	+$31M

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)
2025	18	MIX MLE	2 levels	19	11	82	333	89	35	4	58%	4.3	19.2%	12.6%	6.6%	1.3%	2.74	3.78	—
2025	18	MIX MLE	2 levels	19	11	82	333	89	35	4	58%	4.3	19.2%	12.6%	6.6%	1.3%	2.74	3.78	—
2025	18	MIX RAW	2 levels	19	11	82	333	89	35	4	58%	4.3	26.7%	10.5%	16.2%	1.2%	2.74	2.84	—
2026	19	A+ MLE	Wisconsin Timber Rattlers	25	25	113	515	101	49	15	100%	4.5	15.1%	10.9%	4.2%	3.6%	5.26	5.21	—
2026	19	A+ MLE	Wisconsin Timber Rattlers	25	25	113	515	101	49	15	100%	4.5	15.1%	10.9%	4.2%	3.6%	5.26	5.21	—
2026	19	A+ RAW	Wisconsin Timber Rattlers	25	25	113	515	101	49	15	100%	4.5	19.6%	9.5%	10.1%	2.9%	5.26	4.34	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	20	MLB	MIL	1	1	1	4	1	0	0	100%	1.0	16.7%	11.5%	5.2%	3.1%	5.23	5.23	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	21	MLB MLE	MIL	26	26	133	562	104	59	17	100%	5.1	18.6%	10.6%	8.0%	3.0%	5.00	4.92	+0.7
2029	22	MLB MLE	MIL	26	26	133	562	115	55	17	100%	5.1	20.4%	9.8%	10.7%	3.0%	4.75	4.62	+1.2
2030	23	MLB MLE	MIL	25	25	133	562	121	52	16	100%	5.3	21.6%	9.3%	12.3%	2.9%	4.56	4.44	+1.5
2031	24	MLB MLE	MIL	24	24	133	562	125	51	16	100%	5.5	22.3%	9.0%	13.3%	2.9%	4.42	4.33	+1.7
2032	25	MLB MLE	MIL	18	18	104	438	99	39	13	100%	5.8	22.7%	8.9%	13.8%	2.9%	4.33	4.27	+1.4
2033	26	MLB MLE	MIL	17	17	104	439	101	39	13	100%	6.1	22.9%	8.8%	14.1%	2.9%	4.28	4.25	+1.4
2034	27	MLB MLE	MIL	17	17	102	429	98	38	13	100%	6.0	22.9%	8.9%	14.0%	2.9%	4.29	4.29	+1.3
2035	28	MLB MLE	MIL	16	16	97	409	93	37	12	100%	6.1	22.8%	9.1%	13.7%	3.0%	4.34	4.37	+1.2
2036	29	MLB MLE	MIL	15	15	90	381	86	35	12	100%	6.0	22.5%	9.3%	13.2%	3.2%	4.44	4.50	+0.9
2037	30	MLB MLE	MIL	14	14	82	347	77	33	12	100%	5.9	22.2%	9.6%	12.6%	3.4%	4.59	4.68	+0.7
2038	31	MLB MLE	MIL	12	12	74	312	68	31	11	100%	6.2	21.8%	10.0%	11.8%	3.6%	4.77	4.88	+0.4
2039	32	MLB MLE	MIL	11	11	66	279	60	29	11	100%	6.0	21.3%	10.3%	11.0%	3.9%	4.97	5.11	+0.2
2028	21	MLB CTX	MIL	13	13	66	279	52	29	9	100%	5.1	18.6%	10.6%	8.0%	3.2%	5.08	5.00	+0.4
2029	22	MLB CTX	MIL	19	19	97	410	84	40	13	100%	5.1	20.4%	9.8%	10.7%	3.1%	4.83	4.70	+0.9
2030	23	MLB CTX	MIL	21	21	112	473	102	44	15	100%	5.3	21.6%	9.3%	12.3%	3.1%	4.64	4.52	+1.3
2031	24	MLB CTX	MIL	21	21	119	502	112	45	15	100%	5.7	22.3%	9.0%	13.3%	3.0%	4.50	4.41	+1.5
2032	25	MLB CTX	MIL	16	16	95	401	91	36	12	100%	5.9	22.7%	8.9%	13.8%	3.0%	4.41	4.35	+1.3
2033	26	MLB CTX	MIL	16	16	97	410	94	36	12	100%	6.1	22.9%	8.8%	14.1%	3.0%	4.36	4.33	+1.3
2034	27	MLB CTX	MIL	16	16	97	410	94	37	13	100%	6.1	22.9%	8.9%	14.0%	3.1%	4.37	4.37	+1.3
2035	28	MLB CTX	MIL	15	15	92	388	88	35	12	100%	6.1	22.8%	9.1%	13.7%	3.2%	4.42	4.45	+1.1
2036	29	MLB CTX	MIL	14	14	86	363	82	34	12	100%	6.1	22.5%	9.3%	13.2%	3.3%	4.53	4.59	+0.9
2037	30	MLB CTX	MIL	13	13	78	329	73	32	12	100%	6.0	22.2%	9.6%	12.6%	3.6%	4.68	4.77	+0.6
2038	31	MLB CTX	MIL	12	12	70	296	64	29	11	100%	5.8	21.8%	10.0%	11.8%	3.8%	4.87	4.98	+0.4
2039	32	MLB CTX	MIL	10	10	63	266	57	28	11	100%	6.3	21.3%	10.3%	11.0%	4.1%	5.08	5.22	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		187	187	1071	4523	992	424	147	100%	5.7	21.9%	9.4%	12.6%	3.2%	4.61	4.22	+14.9
/ 200 IP	—	RAW		35	35	200	844	185	79	27	100%	5.7	21.9%	9.4%	12.6%	3.2%	4.61	4.22	+2.8
Career	—	MLE		44	36	195	848	142	98	23	82%	4.4	16.7%	11.6%	5.1%	2.7%	4.20	4.65	+12.6
/ 200 IP	—	MLE		45	37	200	870	145	101	24	82%	4.4	16.7%	11.6%	5.1%	2.7%	4.20	4.65	+2.0

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 A+Wisconsin Timber Rattlers · 113 IPFIP 4.25 → 5.21 (+0.96)K% 19.6% → 15.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.61%	—	×0.770	15.10%
BB% (unintentional) /BF	9.51%	—	×1.150	10.94%
HR / BF /BF	2.91%	÷1.000	×1.250	3.64%

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 100).

Result: FIP 4.25 → 5.21, 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 ACarolina Mudcats · 55 IPFIP 3.45 → 4.34 (+0.89)K% 25.0% → 18.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.740	18.50%
BB% (unintentional) /BF	11.84%	—	×1.180	13.97%
HR / BF /BF	1.75%	÷1.214	×1.300	1.88%

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 143).

Result: FIP 3.45 → 4.34, 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 ROKACL Brewers · 27 IPFIP 1.49 → 2.56 (+1.06)K% 30.5% → 20.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.48%	—	×0.680	20.72%
BB% (unintentional) /BF	7.62%	—	×1.250	9.52%
HR / BF /BF	0.00%	÷0.971	×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 94).

Result: FIP 1.49 → 2.56, 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).

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
Ethan Dorchies (OGILVIE)	—	—	—	—	—	3.1%	—	4.66	20.2%	10.3%	399	-0.57	—	—	—
Adam Hill R 2019 · 5.00 FIP	22	SP	5.00	15.6%	12.6%	3.0%	.297	6.06	19.6%	8.9%	91	+1.06	5.00	213	89
Trevor Clifton R 2015 · 4.25 FIP	20	SP	4.25	16.5%	12.0%	1.9%	.276	3.82	17.3%	7.1%	345	-0.43	3.03	588	86
Josh Grosz R 2024 · 4.83 FIP	21	SP	4.83	19.2%	11.7%	3.4%	.271	5.07	21.5%	8.5%	183	+0.24	4.75	301	86
Josh Bostick R 2024 · 4.65 FIP	22	SP	4.65	19.3%	11.2%	3.2%	.304	5.40	21.7%	12.6%	119	+0.75	4.65	226	85
Barrett Kent R 2024 · 5.40 FIP	19	SP	5.40	18.0%	14.0%	3.7%	.313	4.52	13.6%	-2.1%	27	-0.88	4.52	140	85
Jamison Hill R 2022 · 4.83 FIP	23	SP	4.83	18.4%	11.6%	3.3%	.280	5.02	16.1%	3.0%	202	+0.19	4.72	326	84
Chris McElvain R 2023 · 4.76 FIP	22	SP	4.76	15.8%	11.6%	2.8%	.275	5.24	15.8%	4.7%	198	+0.48	4.07	294	84
Alex Royalty R 2019 · 4.33 FIP	22	SP	4.33	14.9%	11.6%	1.8%	.302	4.50	17.7%	8.6%	40	+0.17	4.33	151	84
Nick Pivetta R 2015 · 4.83 FIP	22	SP	4.83	14.6%	11.6%	2.7%	.288	3.74	23.5%	15.3%	478	-1.09	2.06	1,597	83
Adrian Houser R 2015 · 4.38 FIP	22	SP-	4.38	16.6%	8.8%	2.9%	.298	3.90	15.5%	7.4%	163	-0.48	3.45	1,221	83
Ty Cummings R 2024 · 4.34 FIP	22	SP	4.34	19.0%	10.5%	2.8%	.329	5.36	14.4%	6.0%	178	+1.02	4.34	295	83
Brad Penny R 2000 · 4.51 FIP	22	SP	4.51	15.1%	10.6%	2.5%	.282	3.78	17.4%	10.9%	531	-0.73	3.28	2,060	83
Jordan Jackson R 2022 · 4.15 FIP	23	SP	4.15	16.8%	9.7%	2.2%	.323	5.51	13.1%	1.7%	74	+1.36	4.15	193	83
David Palladino R 2015 · 4.93 FIP	22	SP-	4.93	14.4%	11.8%	2.8%	.310	—	—	—	—	—	4.93	122	83
Jake Peppers R 2024 · 5.02 FIP	22	SP	5.02	15.3%	12.2%	3.0%	.293	5.15	14.8%	-1.3%	89	+0.13	4.83	186	82
Jose Almonte R 2016 · 4.11 FIP	20	SP	4.11	17.0%	9.1%	2.4%	.293	4.01	20.3%	8.0%	139	-0.10	4.01	279	82
Garrett Cave R 2018 · 4.99 FIP	22	SP	4.99	16.4%	14.9%	2.5%	.301	4.97	17.8%	-8.8%	40	-0.02	4.97	156	82
Victor Alcántara R 2015 · 4.40 FIP	22	SP	4.40	15.7%	10.9%	2.3%	.337	4.10	16.3%	5.6%	267	-0.30	3.50	464	82
Aaron Davenport R 2022 · 4.81 FIP	22	SP	4.81	20.0%	13.2%	3.2%	.280	4.94	16.9%	5.6%	391	+0.13	4.04	498	82
Micah Ottenbreit R 2024 · 4.33 FIP	21	SP	4.33	17.9%	11.8%	2.3%	.305	3.42	17.7%	8.4%	47	-0.91	3.04	141	82

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	6.9	106	21.2%	9.6%	1.19	4.62
Bud Norris ('18)	6.1	122	21.7%	9.1%	1.15	4.45
Mike Bielecki ('84-'97, 9 WAR*)	6.2	95	18.4%*	9.1%*	1.15*	4.47*
Jorge De La Rosa ('18)	7.6	109	19.1%	10.3%	1.05	4.58
Derek Holland ('21)	7.3	113	19.7%	8.4%	1.35	4.62
Diego Segui ('62-'77, 10 WAR*)	9.0	121	22.2%*	9.9%*	1.19*	4.40*
John Curtis ('70-'84, 6 WAR*)	8.2	117	16.9%*	9.3%*	1.20*	4.63*