Noah Miller — OGILVIE

Noah MillerSS Oklahoma City Comets

Age 23 S/R 5'11" / 190 lbs AAA HR +15%K -3% Svc 0.0 · Ctrl thru 2033 peak 1.2 · 2030

wRC+†68

AVG/OBP/SLG.209 / .256 / .287

PA320

HR3

K%23

BB%6

MLB%10%

Scouting · now → future

HIT

40↗45

PWR

30→30

SPD

50↘46

FLD

60↗66

EYE

42↗50

trajectory · 10 yrs

0.6peak

2029

Contract

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

Status MiLB

MLB Debut 2028

Service 0 yrs (est)

Team Control Through 2033

First FA Year 2034

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2028
2027	MiLB	still in minors · estimated debut 2028
2028	Pre-Arb	$0.8M	+0.9	$4M	+$3M
2029	Arb-1	$0.8M	+1.1	$10M	+$9M
2030	Arb-2	$0.9M	+1.2	$11M	+$10M
2031	Arb-3	$2M	+1.1	$10M	+$8M
2032	Ext / FA-deal	$3M	+0.9	$4M	+$2M
2033	Ext / FA-deal	$3M	+0.6	$3M	-$0.0M
Totals		$10M		$42M	+$31M

Career Projections (MLE)

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2026 = actual YTD + projected ROS + total. 2027+ via Advanced Marcel + aging curve.

Year	Age	Lvl	Team	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
2021	18	ROK	FCL Twins	96	87	14	2	1	1	6	38	1	1	1	.161	.223	.241	.465	.080	.265	40	6	.209	18	-9	-0	+0	+1	+3	-0.5
2022	19	A	Fort Myers Mighty Mussels	469	403	68	11	3	2	56	157	6	23	7	.169	.280	.226	.505	.057	.266	33	12	.236	39	-32	+2	+0	+5	+13	-1.3
2023	20	A+	Cedar Rapids Kernels	526	477	87	15	4	5	43	140	1	12	3	.182	.251	.262	.513	.080	.244	27	8	.233	37	-38	+1	+0	+6	+15	-1.6
2024	21	A+	2 teams	590	542	113	16	0	5	38	123	4	7	3	.208	.265	.266	.531	.057	.258	21	6	.237	39	-40	+0	+0	+6	+17	-1.8
2025	22	AAA	3 teams	384	364	83	14	2	4	14	89	1	1	0	.228	.259	.310	.569	.082	.286	23	4	.249	49	-22	+0	+0	+4	+11	-0.7
▸ 2026 Season (actual · ROS · total)
2026	23	AAA	Oklahoma City Comets	104	91	22	3	1	2	12	21	0	0	0	.242	.330	.363	.693	.121	.290	20	12	.303	90	-1	+0	+0	+1	+3	0.3
ROS	23	MLB	LAD	216	198	43	7	1	3	15	49	1	2	0	.217	.276	.308	.584	.091	.272	23	7	.260	57	-10	+0	+2	+2	+6	0.1
TOT	23	MLB	LAD	320	289	65	10	2	5	27	70	1	2	0	.225	.293	.325	.619	.100	.278	22	8	.274	68	-12	+0	+2	+3	+9	0.4
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	24	MLB 19%	LAD	454	417	93	16	2	6	32	95	2	3	1	.223	.282	.314	.596	.091	.272	21	7	.269	64	-18	+0	+5	+5	+13	0.4
2028	25	MLB 27%	LAD	483	443	100	17	2	8	35	101	2	4	1	.226	.285	.327	.613	.102	.275	21	7	.278	71	-16	+0	+5	+5	+14	0.9
2029	26	MLB 36%	LAD	499	456	104	18	2	9	38	105	2	4	1	.228	.290	.336	.626	.107	.276	21	8	.283	75	-14	+0	+5	+5	+14	1.1
2030	27	MLB 44%	LAD	504	458	105	18	2	9	39	107	2	3	1	.229	.293	.336	.629	.107	.277	21	8	.284	76	-14	+0	+5	+5	+14	1.2
2031	28	MLB 47%	LAD	503	457	104	18	2	9	39	107	2	3	0	.228	.291	.335	.626	.107	.276	21	8	.283	75	-14	+1	+5	+5	+14	1.1
2032	29	MLB 50%	LAD	495	451	102	17	2	9	39	107	2	2	0	.226	.291	.333	.623	.106	.275	22	8	.281	73	-15	+0	+4	+5	+14	0.9
2033	30	MLB 61%	LAD	485	442	99	17	2	8	38	106	2	1	0	.224	.288	.326	.614	.102	.274	22	8	.278	71	-16	+0	+3	+5	+14	0.6
2034	31	MLB 71%	LAD	472	430	95	16	2	8	37	106	2	0	0	.221	.286	.323	.609	.102	.273	22	8	.274	68	-17	+0	+2	+5	+13	0.4
2035	32	MLB 82%	LAD	454	414	90	15	2	7	35	104	2	0	0	.217	.282	.314	.596	.097	.271	23	8	.270	65	-18	+0	+1	+5	+13	0.1
2036	33	MLB 92%	LAD	425	387	83	14	2	6	33	100	2	0	0	.214	.280	.307	.587	.093	.270	24	8	.265	61	-19	+0	+0	+5	+12	-0.2
2037	34	MLB	LAD	379	346	72	12	1	5	29	93	1	0	0	.208	.271	.292	.563	.084	.268	25	8	.258	56	-19	+0	-1	+4	+11	-0.5
▸ Career Totals (MLE all levels + projections)
Career	—			7434	6772	1455	243	32	104	566	1727	35	66	18	.215	.279	.306	.585	.091	.271	23	8	.264	60	-332	+6	+38	+80	+211	0.2
/ 162G	—			650	592	127	21	3	9	49	151	3	6	2	.215	.278	.306	.583	.091	.271	23	8	.264	60	-29	+0	+3	+7	+18	0.0

Historical Stats — Raw (Per Stint)

Actual MLB + MiLB stats as they happened, one row per stint at each level. Use this to see what really got recorded; the table above shows MLB-equivalent translations + projections.

Year	Age	Lvl	Team	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
2021	18	ROK	FCL Twins	96	84	20	3	1	2	9	26	1	1	1	.238	.319	.369	.688	.131	.316	27	9	.305	92	-1	-0	—	—	+3	0.2
2022	19	A	Fort Myers Mighty Mussels	469	383	81	12	4	2	76	110	6	23	7	.211	.351	.279	.630	.068	.287	23	16	.300	87	-7	+2	—	—	+13	0.9
2023	20	A+	Cedar Rapids Kernels	526	462	103	20	5	8	58	108	1	12	3	.223	.311	.340	.651	.117	.271	21	11	.295	84	-10	+1	—	—	+15	0.6
2024	21	AA	Tulsa Drillers	136	129	29	5	0	0	6	28	0	2	2	.225	.259	.264	.523	.039	.284	21	4	.238	40	-9	-0	—	—	+4	-0.6
2024	21	A+	Great Lakes Loons	454	395	99	14	0	6	49	66	4	5	1	.251	.339	.332	.670	.081	.284	15	11	.306	93	-4	+1	—	—	+13	1.0
2025	22	AAA	Oklahoma City Comets	242	227	54	12	0	4	11	44	0	1	0	.238	.273	.344	.617	.106	.273	18	5	.272	66	-9	+0	—	—	+7	-0.2
2025	22	AA	Tulsa Drillers	111	103	30	3	1	1	6	24	1	0	0	.291	.333	.369	.702	.078	.372	22	5	.316	100	+0	+0	—	—	+3	0.3
2025	22	ROK	ACL Dodgers	31	24	8	2	1	0	6	1	0	0	0	.333	.467	.500	.967	.167	.333	3	19	.416	176	+3	+0	—	—	+1	0.4

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
Noah Miller (OGILVIE)	23	40→45	30	50→46	50	.209/.256/.287	.078	.267	3	3	23%	6%	48	-1.0	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Fernando Flores 2015 · AAA	23	48	38→40	43→40	42	.232/.263/.311	.079	.275	6	5	18%	4%	56	-1.3	.245/.276/.334	.089	.290	7	5	18%	4%	67	-0.5	.254/.283/.345	.091	.301	7	2	18%	3%	71	-0.2
✕Jose Reyes 2007 · AAA	23	48	36→30	42→45	44	.227/.266/.287	.060	.270	4	6	18%	5%	50	-1.7	.220/.266/.309	.089	.273	8	8	22%	6%	57	-1.2	.196/.240/.290	.094	.240	11	6	23%	5%	42	-0.5
✕Rafael Marchán 2022 · MLB	23	43	35→45	43→40	46	.201/.255/.260	.059	.244	3	5	19%	6%	40	-2.4	.214/.279/.310	.096	.246	7	4	16%	6%	64	-0.8	.228/.306/.335	.107	.259	10	2	16%	8%	80	+0.1
✕Yonathan Mendoza 2017 · AA	23	51	36→30	47→45	48	.240/.293/.304	.063	.287	4	6	17%	6%	67	-0.5	.239/.288/.294	.055	.291	4	6	18%	6%	63	-0.9	.232/.283/.274	.042	.284	3	5	19%	7%	52	-1.0
✕Noe Becerra 2010 · AAA	23	44	39→30	43→40	48	.212/.275/.292	.079	.267	7	7	22%	8%	57	-1.2	.232/.282/.316	.084	.273	7	7	17%	6%	66	-0.6	.278/.325/.338	.060	.315	3	0	12%	6%	89	+0.3
✕Angelo Amendolare 2016 · AAA	23	47	37→30	45→50	51	.221/.294/.298	.076	.266	4	7	18%	8%	67	-0.5	.230/.303/.298	.068	.302	3	9	23%	8%	71	-0.3	.244/.324/.286	.042	.329	0	10	23%	9%	72	-0.1
✕Sergio Burruel 2014 · AAA	23	44	36→30	49→30	45	.208/.270/.272	.063	.280	3	7	25%	7%	50	-1.8	.236/.283/.307	.071	.308	6	5	24%	5%	63	-0.8	.244/.307/.320	.075	.298	8	1	19%	7%	75	+0.0
✕Rey Navarro 2013 · AAA	23	47→50	39→45	46→50	44	.224/.263/.312	.088	.256	7	9	16%	4%	56	-1.3	.237/.274/.349	.112	.265	11	7	15%	5%	71	-0.3	.240/.273/.357	.117	.264	12	5	14%	4%	70	-0.3
✕Angelo Mora 2016 · AA	23	48→52	38→45	43→45	41	.227/.267/.315	.088	.296	5	7	24%	5%	59	-1.1	.236/.273/.336	.100	.311	6	6	25%	5%	66	-0.6	.230/.264/.335	.104	.298	9	7	25%	4%	59	-0.7
✕Chuck Taylor 2017 · AA	23	48→54	37→40	44→50	47	.226/.291/.299	.073	.292	4	7	23%	8%	66	-0.6	.230/.291/.319	.089	.293	7	6	22%	7%	71	-0.3	.226/.289/.316	.090	.285	8	4	22%	7%	66	-0.5
✕Jose Coronado 2009 · AA	23	48→54	34→30	44→50	43	.223/.270/.275	.052	.293	2	7	24%	6%	50	-1.8	.230/.278/.294	.064	.297	3	8	22%	6%	58	-1.2	.223/.273/.285	.062	.289	3	6	23%	6%	51	-1.1
✕Riley Unroe 2019 · AAA	23	39→47	37→45	45→55	44	.190/.259/.261	.071	.276	5	12	32%	8%	43	-2.2	.213/.275/.314	.101	.294	9	11	29%	7%	63	-0.9	.221/.306/.342	.121	.297	13	26	28%	10%	80	+0.2
✕Rodrigo Aguirre 2008 · AAA	24	42	40→30	45	42	.208/.247/.297	.089	.256	7	10	22%	5%	46	-2.0	.248/.292/.358	.110	.280	9	6	15%	5%	81	+0.4	.267/.313/.345	.078	.298	4	2	11%	6%	82	+0.2
✕Manuel Bobadilla 2007 · AAA	23	42	40→45	47→45	46	.205/.256/.291	.086	.239	7	10	18%	6%	48	-1.9	.220/.287/.330	.110	.274	12	6	23%	8%	72	-0.2	.237/.309/.344	.107	.292	11	4	21%	8%	83	+0.3
✕Louis Ott 2008 · A	23	47→48	38→30	47→45	45	.222/.286/.300	.078	.296	6	8	26%	7%	64	-0.8	.228/.300/.296	.068	.325	4	7	28%	9%	69	-0.4	.228/.307/.282	.054	.331	3	6	29%	10%	65	-0.4
✕Chace Numata 2016 · A	23	47	37→40	48→40	45	.223/.272/.292	.069	.267	4	5	18%	5%	56	-1.3	.240/.290/.320	.080	.287	4	4	17%	6%	70	-0.3	.236/.285/.317	.081	.279	4	2	16%	6%	65	-0.3
✕David Urias 2008 · AAA	23	43	39→40	39→45	38	.213/.245/.297	.085	.267	7	7	23%	3%	45	-2.1	.234/.267/.310	.076	.284	4	9	18%	4%	57	-1.2	.286/.313/.364	.078	.333	6	6	15%	3%	87	+0.3
✕Christian Lopes 2016 · AA	23	45→51	37→45	43→50	46	.211/.269/.283	.072	.265	4	4	21%	7%	52	-1.6	.227/.289/.324	.097	.281	7	12	21%	7%	71	-0.3	.211/.296/.334	.123	.266	13	13	24%	9%	76	+0.0
✕Elih Marrero 2021 · A	24	44	38→40	49→55	45	.209/.266/.289	.080	.272	5	6	24%	7%	53	-1.5	.214/.285/.291	.077	.307	4	20	29%	9%	61	-1.0	.207/.287/.272	.066	.304	3	27	30%	10%	55	-0.5
✕Dante Bichette Jr. 2016 · AA	23	42→48	41→40	40	42	.207/.258/.301	.094	.275	8	2	27%	6%	53	-1.5	.226/.286/.323	.097	.293	9	4	24%	7%	69	-0.4	.239/.299/.331	.092	.299	8	3	22%	7%	74	-0.0

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)