Cody Miller

SS Rome Emperors

Age 23 R/R 5'11" / 189 lbs A+ Svc 0.0 · Ctrl thru 2036

Overview

A+PROSPECTMiLBFA 2037

OGV OFP35OGV rank#981ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2025	21	A+/AATL	118	.327/.385/.449	2	10	70	—	.255/.300/.364
2026	22	A+/AATL	569	.202/.338/.342	15	56	45	—	.155/.259/.261
2027PROJMLE	23	MLBATL	1	.206/.284/.323	0	0	73	0.0
2028PROJ30% MLB	24	MLBATL	129	.210/.288/.332	3	4	76	0.1
2029PROJ44% MLB	25	MLBATL	204	.212/.291/.337	5	6	78	0.2

Next 3 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2036Service0.0First FA2037

2027MiLB2028MiLB2029MiLB2030MiLB2031Pre-Arb$0.9M2032Pre-Arb$0.9M2033Pre-Arb$0.9M2034Arb-1$0.6M+2

Skills · percentileMiLB Statcast 2026 A+

Speed81

Z-Con%72

Whiff%55

Chase%54

ISO40

BB%40

Career WAR0.0 WAR median (P10 -0.0 / P90 0.0, comp-based) · star 2% · didn't stick 96%

CompsMario Lisson (age 23) · Cooper Bowman (age 22) · Tyler Goeddel (age 23)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†73

AVG/OBP/SLG.206 / .284 / .323

PA1

HR0

K%29

BB%8

BABIP277

ISO112

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$5M ctrl surplus

Contract

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

Status MiLB

MLB Debut 2031

Service 0 yrs (est)

Team Control Through 2036

First FA Year 2037

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2031
2028	MiLB	still in minors · estimated debut 2031
2029	MiLB	still in minors · estimated debut 2031
2030	MiLB	still in minors · estimated debut 2031
2031	Pre-Arb	$0.9M	+0.3	$0.9M	+$0.3M
2032	Pre-Arb	$0.9M	+0.2	$0.5M	+$0.0M
2033	Pre-Arb	$0.9M	+0.1	$0.3M	+$0.0M (cut)
2034	Arb-1	$0.6M	—	—	—
2035	Ext	beyond projection horizon · no WAR estimate
2036	Ext	beyond projection horizon · no WAR estimate
Totals		$2M		$2M	+$0.3M

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 these numbers are built

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2027 = full-season projection (no games played yet). 2028+ via Advanced Marcel + aging curve.

Year	Age	Lvl	Team	MLB%	PA	AB	H	2B	3B	HR	BB	SO	HBP	SB	CS	AVG	OBP	SLG	OPS	ISO	BABIP	K%	BB%	wOBA	wRC+	BAT	RUN	FLD	POS	REP	WAR
▸ Career — actual stats, one row per stint (as recorded, no adjustments)
2025	21	A+	Rome Emperors	—	70	64	19	3	1	1	5	22	1	6	1	297	357	422	779	125	439	31	7	349	48	—	—	—	—	—	—
2025	21	A	Augusta GreenJackets	—	48	43	16	2	0	1	3	10	1	4	2	372	426	488	914	116	455	21	6	401	103	—	—	—	—	—	—
2026	22	A+	Rome Emperors	—	354	295	59	12	1	8	37	102	15	31	6	200	320	329	649	129	267	29	10	296	37	—	—	—	—	—	—
2026	22	A	Augusta GreenJackets	—	215	170	35	4	1	7	35	57	8	25	7	206	366	365	731	159	259	27	16	337	57	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2025	21	A+ MLE	Rome Emperors	—	70	66	14	2	1	1	3	29	1	6	1	212	257	318	575	106	348	41	4	239	48	—	—	—	—	—	—
2025	21	A MLE	Augusta GreenJackets	—	48	44	14	2	0	1	2	14	1	4	2	318	362	432	794	114	404	29	4	321	103	—	—	—	—	—	—
2026	22	A+ MLE	Rome Emperors	—	354	310	48	9	1	7	22	133	15	31	6	155	245	258	503	103	221	38	6	223	37	—	—	—	—	—	—
2026	22	A MLE	Augusta GreenJackets	—	215	181	28	3	1	5	24	78	8	25	7	155	282	265	547	110	220	36	11	252	57	—	—	—	—	—	—
2025	21	A+ MLE	2 teams	—	118	110	27	3	1	2	5	43	2	10	3	245	291	345	636	100	379	36	4	272	70	—	—	—	—	—	—
2025	21	A+ RAW	2 teams	—	118	107	35	5	1	2	8	32	2	10	3	327	385	449	833	121	446	27	7	370	70	—	—	—	—	—	—
2026	22	A+ MLE	2 teams	—	569	491	76	12	2	12	46	211	23	56	13	155	259	261	520	106	232	37	8	234	44	—	—	—	—	—	—
2026	22	A+ RAW	2 teams	—	569	465	94	16	2	15	72	159	23	56	13	202	338	342	679	140	264	28	13	312	44	—	—	—	—	—	—
2025	21	A+ MLE	2 teams	—	118	110	27	3	1	2	5	43	2	10	3	245	291	345	636	100	371	36	4	272	70	—	—	—	—	—	—
2026	22	A+ MLE	2 teams	—	569	495	76	12	2	12	46	211	23	56	13	154	259	259	518	105	221	37	8	234	44	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2025	21	A+ MLE	2 teams	—	118	110	27	3	1	2	5	43	2	10	3	245	291	345	636	100	371	36	4	272	70	—	—	—	—	—	—
2026	22	A+ MLE	2 teams	—	569	495	76	12	2	12	46	211	23	56	13	154	259	259	518	105	221	37	8	234	44	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	23	MLB MLE	ATL	0%	559	499	102	19	2	11	42	162	13	18	4	206	284	323	607	117	277	29	8	276	73	-18	+2	+0	+6	+12	0.2
▸ 2027 — real world (MLB)
2027	23	MLB CTX	ATL	0%	1	1	0	0	0	0	0	0	0	0	0	206	284	323	607	117	277	0	0	276	73	-0	+0	+0	+0	+0	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	24	MLB MLE	ATL	30%	427	382	80	15	2	9	32	122	10	13	3	210	288	332	620	122	279	29	7	281	76	-12	+1	+0	+5	+9	0.3
2029	25	MLB MLE	ATL	44%	461	413	86	16	2	10	35	130	10	13	3	212	291	337	628	125	279	28	8	284	78	-12	+1	+0	+5	+10	0.5
2030	26	MLB MLE	ATL	51%	480	430	91	17	2	11	37	134	10	13	3	213	292	341	633	127	280	28	8	286	80	-12	+1	+0	+5	+10	0.5
2031	27	MLB MLE	ATL	52%	486	435	93	18	2	11	38	135	10	12	3	214	293	341	634	127	280	28	8	287	80	-11	+1	+0	+5	+11	0.6
2032	28	MLB MLE	ATL	53%	485	434	93	18	2	11	38	134	10	11	3	214	292	340	632	126	280	28	8	286	80	-12	+1	-1	+5	+11	0.4
2033	29	MLB MLE	ATL	53%	475	426	90	17	2	10	37	133	9	10	3	212	289	334	624	123	279	28	8	283	77	-13	+1	-1	+5	+10	0.2
2034	30	MLB MLE	ATL	52%	465	417	87	16	2	10	36	131	9	9	3	209	286	327	613	118	277	28	8	278	74	-14	+1	-2	+5	+10	-0.1
2028	24	MLB CTX	ATL	30%	129	115	25	5	1	3	10	37	3	4	1	210	288	332	620	122	279	29	8	281	76	-4	+0	+0	+1	+3	0.1
2029	25	MLB CTX	ATL	44%	204	182	39	7	1	5	16	57	4	6	1	212	291	337	628	125	279	28	8	284	78	-5	+1	+0	+2	+4	0.2
2030	26	MLB CTX	ATL	51%	244	218	47	9	1	6	19	68	5	6	2	213	292	341	633	127	280	28	8	286	80	-6	+0	+0	+3	+5	0.2
2031	27	MLB CTX	ATL	52%	255	228	49	9	1	6	20	71	5	6	2	214	293	341	634	127	280	28	8	287	80	-6	+0	+0	+3	+6	0.3
2032	28	MLB CTX	ATL	53%	259	232	49	9	1	6	20	72	5	6	2	214	292	340	632	126	280	28	8	286	80	-6	+0	-0	+3	+6	0.2
2033	29	MLB CTX	ATL	53%	250	223	47	9	1	5	20	70	5	5	1	212	289	334	624	123	279	28	8	283	77	-7	+1	-1	+3	+5	0.1
2034	30	MLB CTX	ATL	52%	242	216	46	9	1	5	19	68	5	5	1	209	286	327	613	118	277	28	8	278	74	-7	+1	-1	+3	+5	-0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1583	1414	302	57	7	36	124	443	32	38	10	214	292	340	632	127	282	28	8	284	73	-41	+4	-2	+17	+34	1.2
/ 162G	—	A+C		—	650	581	124	23	3	15	51	182	13	16	4	213	291	341	632	127	282	28	8	284	73	-17	+1	-1	+7	+14	0.5
Career	—	MLE		—	4176	3725	761	139	18	90	320	1234	98	154	39	204	285	324	608	119	277	30	8	276	73	-92	+8	-4	+37	+76	2.5
/ 162G	—	MLE		—	650	580	119	22	3	14	50	192	15	24	6	205	285	326	611	121	278	30	8	276	73	-17	+2	-1	+7	+14	0.5

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+Rome Emperors · 354 PAwOBA .294 → .223 (−71)K% 28.8% → 37.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.81%	÷1.000	×1.310	—	—	37.75%
BB% (unintentional) /PA	10.45%	÷1.000	×0.600	—	×1.012	6.35%
HBP% /PA	4.24%	—	×0.770	—	×1.012	3.30%
Singles /BIP	19.69%	÷1.000	×0.870	×0.969	×1.012	16.80%
Doubles /BIP	6.22%	÷1.000	×0.780	×0.969	×1.012	4.76%
Triples /BIP	0.52%	÷1.000	×0.850	×0.969	×1.012	0.43%
Home runs /BIP	4.15%	÷1.000	×0.880	—	×1.012	3.69%

Factors used: league row South Atlantic League. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 22 vs a level average of 22.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.969.

Result: wOBA .294 → .223; ISO .129 → .105; BABIP .267 → .221. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2026 AAugusta GreenJackets · 215 PAwOBA .332 → .252 (−81)K% 26.5% → 36.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.51%	÷1.000	×1.360	—	—	36.06%
BB% (unintentional) /PA	16.28%	÷1.000	×0.690	—	—	11.23%
HBP% /PA	3.72%	—	×0.780	—	—	2.90%
Singles /BIP	20.35%	÷1.000	×0.920	×0.950	—	17.79%
Doubles /BIP	3.54%	÷1.000	×0.830	×0.950	—	2.79%
Triples /BIP	0.88%	÷1.000	×0.910	×0.950	—	0.77%
Home runs /BIP	6.19%	÷1.000	×0.800	—	—	4.96%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 22 vs a level average of 22.0 → +0.0% on BB/HBP/hit rates (0.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .332 → .252; ISO .159 → .121; BABIP .259 → .220. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2025 A+Rome Emperors · 70 PAwOBA .340 → .239 (−101)K% 31.4% → 41.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	31.43%	÷0.983	×1.310	—	—	41.88%
BB% (unintentional) /PA	7.14%	÷1.020	×0.600	—	×1.027	4.32%
HBP% /PA	1.43%	—	×0.770	—	×1.027	1.13%
Singles /BIP	33.33%	÷1.098	×0.870	—	×1.027	27.12%
Doubles /BIP	7.14%	÷1.173	×0.780	—	×1.027	4.88%
Triples /BIP	2.38%	÷1.075	×0.850	—	×1.027	1.93%
Home runs /BIP	2.38%	÷0.819	×0.880	—	×1.027	2.63%

Factors used: league row South Atlantic League. Park (home-season share, regressed): HR 64, 1B 120, 2B 135, 3B 115, K 97, BB 104 — applied at half strength. Age: age 21 vs a level average of 22.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average).

Result: wOBA .340 → .239; ISO .125 → .096; BABIP .439 → .348. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2025 AAugusta GreenJackets · 48 PAwOBA .398 → .321 (−77)K% 20.8% → 28.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.83%	÷0.984	×1.360	—	—	28.80%
BB% (unintentional) /PA	6.25%	÷0.985	×0.690	—	×1.015	4.44%
HBP% /PA	2.08%	—	×0.780	—	×1.015	1.65%
Singles /BIP	39.39%	÷1.030	×0.920	—	×1.015	35.72%
Doubles /BIP	6.06%	÷0.977	×0.830	—	×1.015	5.23%
Triples /BIP	0.00%	÷1.037	×0.910	—	×1.015	0.00%
Home runs /BIP	3.03%	÷1.281	×0.800	—	×1.015	1.92%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 156, 1B 106, 2B 95, 3B 107, K 97, BB 97 — applied at half strength. Age: age 21 vs a level average of 22.0 → +1.5% on BB/HBP/hit rates (1.0 yr younger than average).

Result: wOBA .398 → .321; ISO .116 → .080; BABIP .455 → .404. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Danny Espinosalast yr '17 career totals — 8 seasons, 3,267 PA	4.9	3,267	98	64	221	297	378	+16	+36	11.0	11.4
/162	664	20	13	+3.2	+7.3	2.2	pk7: 12
#2Alex Gonzalez'94-'06 * career totals — 12 seasons, 5,528 PA	8.3	5,528	137	97	232*	290*	379*	+55	+6	8.3	10.0
/162	664	16	12	+6.6	+0.8	1.0	pk7: 12
#3Dylan Moorelast yr '25 career totals — 7 seasons, 1,922 PA	2.9	1,922	63	118	206	310	383	+4	+8	6.6	6.6
/162	664	22	41	+1.3	+2.7	2.3	pk7: 7
#4Carlos Sanchez'14-'22 * career totals — 6 seasons, 2,503 PA	3.8	2,503	32	30	248*	305*	353*	+8	+0	2.1	2.6
/162	664	8	8	+2.0	+0.0	0.6	pk7: 3
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 3 projected seasons	2.4	1,583	35	38	213	288	338	+17	+0	2.4	2.4
/162	664	15	16	+7.1	+0.0	1.0	pk7: 2
#5Frank Duffy'70-'79 * career totals — 7 seasons, 2,924 PA	4.4	2,924	26	49	234*	283*	348*	+30	-2	0.9	2.1
/162	664	6	11	+6.7	-0.5	0.2	pk7: 3
#6Enzo Hernandez'71-'78 * career totals — 6 seasons, 2,612 PA	3.9	2,612	2	129	222*	281*	294*	+28	+4	1.6	1.9
/162	664	1	33	+7.0	+1.0	0.4	pk7: 2

Career Path Comps

What happened to players with a similar stat profile at this age · Y-axis: wRC+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

		Scouting				At Match Age									Next 3 Yrs									Peak 3 Yrs
Comp	Age	HIT	PWR	SPD	EYE	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR
Cody Miller (OGILVIE)	23	—	—	—	—	204/282/320	116	277	4	7	29%	7%	73	-0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Mario Lisson 2007 · A	23	45→49	44→50	55	47	220/297/341	122	293	11	22	27%	8%	82	+0.0	215/267/326	111	279	11	19	26%	5%	67	-1.1	222/292/345	123	288	15	8	27%	7%	80	-0.1
✕Cooper Bowman 2022 · A	22	44	45	56→60	41	214/289/346	132	303	12	19	32%	7%	81	-0.1	204/281/321	117	287	12	34	31%	8%	72	-0.7	210/283/330	120	279	11	40	27%	8%	72	-0.5
✕Tyler Goeddel 2016 · AA	23	49→52	43→45	56→55	43	236/290/355	119	308	9	19	26%	6%	82	-0.0	220/282/323	103	282	8	14	24%	7%	72	-0.7	204/271/293	89	262	6	12	23%	7%	59	-0.9
✕Juan Mora 2022 · A	22	44	42→45	55	47	215/295/325	110	284	9	14	26%	8%	78	-0.3	222/280/325	103	297	9	9	27%	6%	72	-0.7	218/275/319	102	286	9	8	26%	5%	67	-0.5
✕Clay Fuller 2010 · A	23	43→46	42→45	56→55	46	208/288/316	108	299	9	20	31%	9%	73	-0.6	213/273/328	115	291	12	16	30%	7%	70	-0.8	210/264/327	117	279	14	16	29%	5%	63	-0.8
✕Corey Toups 2016 · A	23	49→50	41→45	56→50	46	234/295/343	109	305	7	17	25%	7%	81	-0.1	217/279/332	115	309	9	16	31%	7%	73	-0.6	206/271/319	113	301	10	16	33%	7%	64	-0.9
✕Michael Guldberg 2022 · A	23	45	44→45	55	44	222/290/341	119	280	12	16	24%	7%	80	-0.2	214/272/298	84	283	6	12	25%	6%	62	-1.4	205/259/264	60	274	3	10	25%	6%	47	-0.7
✕Dru Baker 2023 · A	23	49→57	44→40	58→60	45	236/301/356	120	326	11	24	30%	8%	86	+0.3	240/293/333	93	336	8	32	29%	6%	78	-0.3	239/291/316	77	338	6	36	29%	5%	70	-0.7
✕Tsung-Che Cheng 2024 · AA	23	47→48	44→45	57→55	46	230/292/354	124	295	9	20	25%	8%	82	+0.0	211/279/311	100	292	9	17	29%	8%	68	-1.0	200/274/289	89	282	8	17	30%	9%	59	-1.2
✕Tim Tawa 2022 · A	23	45	47→55	58→50	45	221/289/359	138	303	14	18	30%	8%	83	+0.1	213/278/339	126	273	14	11	26%	8%	74	-0.5	223/286/391	168	267	21	13	25%	7%	88	+0.3
✕Peyton Wilson 2023 · A	23	44→52	46→45	57→55	41	218/283/349	132	301	14	20	31%	7%	78	-0.3	221/289/335	114	292	10	18	26%	8%	78	-0.3	215/288/326	111	284	9	19	26%	8%	72	-0.6
✕Lolo Sanchez 2022 · A	23	44→45	45	53→55	48	220/295/343	124	262	13	23	21%	8%	82	+0.0	208/283/298	90	252	9	13	20%	8%	68	-1.0	193/271/258	65	233	6	9	19%	8%	51	-0.9
✕Jared Serna 2024 · A	22	45→48	45	53→50	45	226/284/352	126	276	13	18	23%	7%	79	-0.2	214/271/321	107	261	11	15	22%	6%	68	-1.0	202/265/300	97	245	10	16	21%	6%	58	-1.4
✕Christopher Bostick 2016 · AA	23	45→55	44→45	55	39	223/269/343	121	289	11	18	27%	5%	72	-0.7	237/286/343	106	313	7	11	25%	5%	78	-0.3	245/298/359	114	318	9	7	25%	6%	83	+0.0
✕Hunter Jones 2015 · A	23	42→52	45→40	55	40	211/270/335	124	290	13	16	31%	6%	70	-0.8	205/262/291	86	278	7	19	27%	6%	57	-1.8	226/281/321	94	290	6	16	23%	5%	69	-0.8
✕Jared Oliva 2019 · A	23	46→49	42→45	55→65	42	221/288/333	112	305	9	24	29%	7%	77	-0.3	224/283/322	98	311	7	25	28%	6%	72	-0.7	221/286/346	125	277	12	55	24%	6%	75	-0.3
✕Justin Dean 2021 · A	24	47	42→45	58→65	44	221/291/328	107	313	8	23	30%	8%	76	-0.4	202/279/300	98	317	8	27	36%	8%	67	-1.1	212/289/296	84	320	7	47	33%	9%	66	-0.8
✕Trey Sweeney 2023 · AA	23	38→45	48→50	57→55	45	200/273/344	144	263	16	19	30%	8%	74	-0.5	218/289/354	136	286	15	17	28%	8%	82	+0.0	219/291/353	133	286	15	17	27%	8%	81	-0.1
✕Chase d'Arnaud 2010 · A	23	49→50	42→45	55→60	49	236/311/356	119	289	8	19	20%	8%	91	+0.6	229/288/337	108	289	6	27	22%	6%	77	-0.3	225/286/341	117	286	11	26	24%	7%	77	-0.2
✕Chad Hinshaw 2015 · A	24	44→42	47→45	56→55	39	217/292/359	142	298	14	23	31%	6%	85	+0.2	211/284/312	101	305	8	24	31%	7%	71	-0.8	197/271/276	80	293	6	25	32%	7%	55	-1.0

Cody Miller

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps