Tayden Hall — OGILVIE

Tayden HallC Wisconsin Timber Rattlers

Age 23 L/R 6'2" / 215 lbs A+ BB +10%HR +7% Svc 0.0 · Ctrl thru 2035 peak 1.4 · 2030

wRC+†71

AVG/OBP/SLG.196 / .296 / .279

PA320

HR3

SB5

K%26

BB%11

MLB%0%

Scouting · now → future

HIT

25→25

PWR

30→30

SPD

45→45

EYE

62↘60

trajectory · 10 yrs

1.4peak

2030

Contract

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

Status MiLB

MLB Debut 2030

Service 0 yrs (est)

Team Control Through 2035

First FA Year 2036

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2030
2027	MiLB	still in minors · estimated debut 2030
2028	MiLB	still in minors · estimated debut 2030
2029	MiLB	still in minors · estimated debut 2030
2030	Arb-2	$0.9M	+1.4	$13M	+$12M
2031	Arb-3	$0.9M	+1.3	$12M	+$11M
2032	Ext / FA-deal	$0.9M	+1.2	$11M	+$11M
2033	Ext / FA-deal	$2M	+0.9	$4M	+$3M
2034	Ext / FA-deal	$2M	+0.7	$4M	+$2M
2035	Ext / FA-deal	$1M	+0.4	$2M	+$0.6M
Totals		$8M		$46M	+$38M

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
2022	19	ROK	2 teams	80	71	16	4	1	0	7	22	1	0	0	.225	.304	.310	.614	.085	.320	28	9	.274	68	-3	+0	+0	+1	+2	0.1
2023	20	A	3 teams	409	350	80	12	0	0	48	105	5	8	4	.229	.330	.263	.593	.034	.319	26	12	.276	69	-14	+0	+0	+7	+12	0.5
2024	21	A+	2 teams	404	350	78	13	3	2	40	88	7	5	2	.223	.315	.294	.609	.071	.285	22	10	.276	69	-14	+0	+0	+7	+11	0.5
2025	22	A+	Wisconsin Timber Rattlers	336	279	34	7	3	3	49	105	5	8	1	.122	.264	.201	.465	.079	.178	31	15	.220	27	-28	+1	+0	+6	+10	-1.1
▸ 2026 Season (actual · ROS · total)
2026	23	A+	Wisconsin Timber Rattlers	22	18	6	2	0	1	2	8	2	1	0	.333	.455	.611	1.066	.278	.556	36	9	.381	150	+1	+0	+0	+0	+1	0.3
ROS	23	MLB	MIL	298	258	51	9	2	3	34	78	4	4	1	.198	.301	.283	.584	.085	.268	26	11	.270	65	-12	+0	+0	+5	+8	0.2
TOT	23	MLB	MIL	320	276	57	11	2	4	36	86	6	5	1	.207	.311	.304	.616	.098	.283	27	11	.278	71	-11	+1	+0	+6	+9	0.5
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	24	MLB 10%	MIL	365	317	65	12	2	5	41	94	4	5	1	.205	.304	.303	.607	.098	.272	26	11	.283	75	-10	+1	+0	+7	+10	0.7
2028	25	MLB 25%	MIL	416	361	77	14	3	7	47	105	5	6	2	.213	.312	.327	.639	.114	.274	25	11	.291	81	-9	+0	+0	+7	+12	1.1
2029	26	MLB 43%	MIL	448	389	83	15	3	8	51	112	5	7	2	.213	.312	.329	.641	.116	.276	25	11	.295	84	-8	+1	+0	+8	+13	1.3
2030	27	MLB 58%	MIL	461	400	87	16	3	9	52	116	6	7	2	.217	.317	.340	.657	.123	.277	25	11	.296	84	-8	+1	+0	+8	+13	1.4
2031	28	MLB 68%	MIL	466	404	87	16	3	9	53	118	6	7	1	.215	.315	.337	.652	.121	.276	25	11	.295	84	-9	+1	-1	+8	+13	1.3
2032	29	MLB 77%	MIL	461	400	84	15	3	8	53	118	5	6	1	.210	.310	.323	.633	.113	.275	26	11	.292	82	-9	+1	-1	+8	+13	1.2
2033	30	MLB 84%	MIL	454	394	82	15	2	8	52	118	5	5	1	.208	.308	.317	.625	.109	.274	26	11	.289	80	-10	+1	-2	+8	+13	0.9
2034	31	MLB 91%	MIL	430	373	76	14	2	7	49	113	5	4	0	.204	.304	.308	.613	.105	.272	26	11	.286	77	-11	+1	-3	+8	+12	0.7
2035	32	MLB	MIL	400	347	69	12	2	6	46	108	4	3	0	.199	.300	.297	.597	.098	.271	27	12	.281	73	-12	+1	-4	+7	+11	0.4
2036	33	MLB	MIL	361	313	62	11	2	5	41	99	4	2	0	.198	.299	.294	.593	.096	.269	27	11	.276	69	-13	+0	-4	+6	+10	0.0
2037	34	MLB	MIL	311	270	52	9	2	4	35	88	3	2	0	.193	.292	.285	.577	.093	.267	28	11	.270	65	-12	+0	-5	+6	+9	-0.3
2038	35	MLB	MIL	255	221	41	7	1	3	29	75	3	2	0	.186	.289	.267	.556	.081	.265	29	11	.263	59	-12	+0	-6	+5	+7	-0.5
▸ Career Totals (MLE all levels + projections)
Career	—			6355	5497	1124	201	37	87	727	1662	77	81	18	.204	.306	.302	.608	.098	.274	26	11	.280	73	-195	+9	-25	+113	+180	8.4
/ 162G	—			650	562	116	21	4	9	74	170	8	8	2	.206	.307	.306	.613	.100	.276	26	11	.280	73	-20	+1	-3	+12	+18	0.8

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
2022	19	A+	Wisconsin Timber Rattlers	36	30	7	2	1	0	4	8	1	0	0	.233	.343	.367	.710	.133	.304	22	11	.315	99	-0	+0	—	—	+1	0.1
2022	19	ROK	ACL Brewers Blue	44	38	14	4	0	0	6	8	0	0	0	.368	.455	.474	.928	.105	.467	18	14	.418	178	+4	+0	—	—	+1	0.5
2023	20	A	Carolina Mudcats	217	173	46	8	0	0	40	41	2	3	3	.266	.409	.312	.721	.046	.343	19	18	.341	119	+5	-1	—	—	+6	1.0
2023	20	ROK	ACL Brewers	36	24	8	1	0	0	9	4	1	3	0	.333	.529	.375	.904	.042	.364	11	25	.406	169	+3	+1	—	—	+1	0.5
2023	20	INTL	Brisbane Bandits	156	135	40	9	0	5	17	20	2	2	1	.296	.383	.474	.857	.178	.312	13	11	.377	147	+8	+0	—	—	+4	1.3
2024	21	A+	Wisconsin Timber Rattlers	304	249	55	9	1	2	42	51	7	5	2	.221	.349	.289	.638	.068	.262	17	14	.298	86	-5	+0	—	—	+9	0.4
2024	21	A	Carolina Mudcats	100	82	31	6	3	0	17	16	0	0	0	.378	.485	.524	1.009	.146	.463	16	17	.443	197	+11	+0	—	—	+3	1.4
2025	22	A+	Wisconsin Timber Rattlers	336	261	41	9	3	4	67	79	5	8	1	.157	.339	.261	.600	.103	.204	24	20	.291	81	-7	+1	—	—	+10	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
Tayden Hall (OGILVIE)	23	25	30	45	60	.196/.296/.279	.084	.268	3	4	26%	11%	65	-0.4	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Taylor Krick 2011 · A	23	43	39→30	48→40	49	.206/.285/.289	.084	.266	7	7	24%	9%	62	-0.9	.224/.308/.287	.063	.307	4	5	26%	8%	71	-0.3	.233/.323/.283	.051	.326	2	2	26%	8%	73	-0.0
✕Michael Papierski 2019 · A	23	38→41	40	48→40	55	.186/.291/.272	.085	.244	8	6	25%	12%	61	-1.0	.189/.280/.274	.085	.266	8	4	29%	10%	56	-1.3	.198/.288/.298	.100	.256	11	0	25%	10%	63	-0.5
✕Nolan Fontana 2014 · A	23	43	40	52→50	58	.204/.316/.298	.095	.286	7	14	28%	14%	78	+0.2	.203/.301/.290	.087	.301	4	9	30%	12%	69	-0.4	.184/.288/.306	.123	.253	10	12	29%	12%	68	-0.2
✕Anthony Seigler 2023 · A	24	40→39	43→45	46→55	54	.196/.296/.310	.114	.268	9	11	28%	12%	72	-0.2	.198/.295/.313	.115	.254	11	19	24%	12%	72	-0.2	.200/.299/.321	.122	.247	12	27	23%	12%	74	-0.1
✕David Martin 2023 · A	22	45	39→30	49→30	42	.213/.285/.304	.091	.300	6	7	29%	6%	66	-0.6	.223/.305/.293	.070	.278	5	4	20%	9%	71	-0.3	.243/.334/.302	.059	.291	5	1	16%	10%	83	+0.3
✕Andy Paz 2016 · A	23	39	37→40	48→45	43	.187/.248/.258	.071	.267	5	5	31%	8%	37	-2.6	.224/.274/.290	.066	.298	4	7	24%	7%	55	-1.4	.235/.280/.283	.048	.303	3	7	22%	6%	52	-0.5
✕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
✕J.C. Escarra 2018 · A	23	40→46	38→45	44→45	49	.189/.278/.274	.086	.251	5	4	25%	9%	56	-1.3	.196/.263/.290	.094	.247	9	4	23%	7%	53	-1.5	.214/.291/.335	.121	.256	11	6	20%	8%	74	-0.0
✕Casey Turgeon 2016 · A	23	45	37→40	49→45	53	.213/.298/.290	.077	.264	4	9	20%	9%	67	-0.5	.208/.294/.301	.093	.265	7	7	22%	10%	69	-0.4	.197/.289/.295	.098	.250	9	5	23%	10%	63	-0.4
✕Greg Cullen 2021 · A	24	44→42	41→40	42→40	48	.215/.292/.315	.100	.268	8	3	22%	8%	72	-0.2	.229/.319/.338	.109	.306	11	4	26%	10%	89	+0.9	.232/.336/.332	.100	.317	11	4	27%	12%	91	+0.4
✕Jose Jimenez 2010 · A	23	41	42→40	48→30	51	.202/.282/.307	.104	.267	9	5	27%	10%	65	-0.7	.210/.274/.307	.097	.265	9	3	23%	8%	61	-1.0	.208/.267/.294	.087	.258	9	1	22%	7%	52	-0.9
✕Tim Arakawa 2016 · A	23	47→41	40→30	43→50	51	.224/.301/.316	.093	.289	6	6	24%	10%	75	-0.0	.207/.275/.278	.071	.281	5	11	26%	8%	53	-1.5	.196/.264/.253	.057	.269	5	13	27%	8%	41	-1.6
✕Anthony Vilar 2023 · A	24	45→40	39→40	46→50	48	.209/.286/.299	.090	.300	6	6	30%	10%	64	-0.8	.195/.286/.295	.100	.306	9	8	35%	11%	64	-0.8	.182/.276/.278	.096	.280	10	10	35%	11%	53	-0.9
✕Miguel Arrendell 2011 · A	23	43	37→30	50	50	.203/.284/.276	.073	.270	5	13	25%	10%	57	-1.2	.218/.274/.311	.093	.275	8	8	22%	7%	62	-0.9	.235/.287/.333	.098	.272	9	2	16%	6%	69	-0.1
✕Pratt Maynard 2013 · A	23	44	38→45	47→45	45	.212/.267/.289	.077	.270	6	7	23%	7%	53	-1.5	.222/.286/.327	.105	.279	8	5	22%	8%	71	-0.3	.224/.295/.345	.121	.277	10	2	22%	9%	76	+0.0
✕Jake Thomas 2016 · A	23	44	39→30	49→50	47	.211/.289/.295	.084	.283	7	8	26%	8%	65	-0.7	.207/.290/.274	.067	.301	3	8	29%	10%	59	-1.1	.202/.298/.259	.057	.302	1	8	29%	11%	56	-0.6
✕Sean McCraw 2009 · A	23	44	39→30	47→30	47	.210/.286/.289	.079	.290	7	4	28%	9%	62	-0.9	.199/.272/.271	.072	.278	4	4	27%	9%	51	-1.7	.180/.257/.251	.070	.249	4	1	27%	9%	36	-0.9
✕Jordan Pearce 2019 · A	23	40→36	40	46→40	49	.196/.267/.279	.083	.255	8	4	25%	9%	51	-1.7	.193/.278/.274	.081	.261	7	5	26%	9%	55	-1.4	.170/.273/.234	.064	.232	6	3	27%	10%	41	-1.4
✕Alexander Campos 2022 · A	22	43	42→40	46→45	48	.209/.289/.317	.108	.281	9	6	28%	9%	70	-0.3	.221/.304/.311	.090	.312	8	6	29%	9%	75	-0.0	.236/.329/.308	.072	.330	7	6	28%	11%	83	+0.2
✕Taylor Grzelakowski 2018 · A	24	43	40→45	50→30	42	.211/.263/.307	.096	.286	8	8	28%	6%	56	-1.3	.215/.275/.312	.097	.328	7	3	34%	7%	62	-0.9	.204/.270/.296	.092	.311	6	1	34%	8%	54	-0.8

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)