Braylon Payne — OGILVIE

Braylon PayneOF Wisconsin Timber Rattlers

Age 19 L/L 6'2" / 186 lbs A+ BB +10%HR +7% Svc 0.0 · Ctrl thru 2035 peak 2.6 · 2033

wRC+†91

AVG/OBP/SLG.197 / .273 / .327

PA320

HR8

SB16

K%35

BB%9

MLB%0%

Scouting · now → future

HIT

20↗32

PWR

30↗50

SPD

70→70

FLD

45↗53

EYE

57↘55

trajectory · 10 yrs

2.6peak

2033

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	+2.0	$18M	+$17M
2031	Arb-3	$0.9M	+2.3	$21M	+$20M
2032	Ext / FA-deal	$0.9M	+2.5	$24M	+$23M
2033	Ext / FA-deal	$5M	+2.6	$26M	+$20M
2034	Ext / FA-deal	$9M	+2.6	$26M	+$18M
2035	Ext / FA-deal	$12M	+2.5	$26M	+$14M
Totals		$29M		$141M	+$112M

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
2024	17	A	Carolina Mudcats	19	17	6	1	1	0	2	4	0	4	1	.353	.421	.529	.950	.176	.462	21	11	.391	157	+1	+0	+0	-0	+1	0.2
2025	18	A	Carolina Mudcats	342	307	57	7	2	5	33	142	0	31	10	.186	.265	.270	.535	.085	.321	42	10	.246	46	-21	+2	+0	-2	+10	-1.1
▸ 2026 Season (actual · ROS · total)
2026	19	A+	Wisconsin Timber Rattlers	52	44	12	1	0	3	7	18	1	6	2	.273	.385	.500	.885	.227	.391	35	13	.402	166	+4	+0	+0	-0	+1	0.6
ROS	19	MLB	MIL	268	239	50	8	1	8	25	93	2	10	3	.209	.289	.351	.641	.142	.298	35	9	.286	77	-7	+1	-0	-2	+8	-0.0
TOT	19	MLB	MIL	320	283	62	9	1	11	32	111	3	16	5	.219	.305	.375	.680	.155	.315	35	10	.305	91	-3	+1	-0	-2	+9	0.5
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	20	MLB 11%	MIL	403	357	78	12	2	12	39	131	4	15	4	.218	.302	.364	.667	.146	.302	33	10	.298	86	-6	+1	-0	-2	+11	0.4
2028	21	MLB 28%	MIL	489	431	95	15	2	15	50	151	5	18	5	.220	.309	.369	.678	.148	.303	31	10	.310	95	-3	+2	-0	-3	+14	1.0
2029	22	MLB 48%	MIL	548	479	110	18	3	18	58	164	6	19	5	.230	.320	.392	.713	.163	.303	30	11	.319	102	+1	+2	-0	-3	+16	1.5
2030	23	MLB 66%	MIL	588	513	119	19	3	21	64	172	6	20	5	.232	.324	.404	.728	.172	.303	29	11	.325	107	+4	+2	-0	-4	+17	2.0
2031	24	MLB 82%	MIL	614	533	125	20	3	22	69	177	7	20	5	.235	.330	.407	.737	.173	.303	29	11	.329	110	+7	+2	-0	-4	+17	2.3
2032	25	MLB	MIL	629	545	129	21	3	23	72	181	7	20	5	.237	.333	.413	.746	.176	.304	29	11	.332	112	+9	+2	-0	-4	+18	2.5
2033	26	MLB	MIL	635	550	130	21	3	24	73	182	7	20	5	.236	.333	.416	.750	.180	.304	29	11	.334	113	+10	+2	-0	-4	+18	2.6
2034	27	MLB	MIL	634	548	130	21	3	24	74	183	7	19	5	.237	.335	.418	.753	.181	.304	29	12	.334	113	+10	+2	-0	-4	+18	2.6
2035	28	MLB	MIL	629	543	127	20	3	23	74	182	7	19	4	.234	.333	.409	.742	.175	.304	29	12	.332	113	+9	+2	-1	-4	+18	2.5
2036	29	MLB	MIL	619	534	125	20	3	23	73	181	7	18	4	.234	.334	.412	.746	.178	.303	29	12	.330	111	+8	+2	-2	-4	+18	2.2
2037	30	MLB	MIL	608	525	121	19	3	22	72	180	6	17	4	.230	.330	.404	.734	.173	.302	30	12	.327	109	+6	+2	-2	-4	+17	1.9
2038	31	MLB	MIL	594	513	117	18	3	21	70	178	6	16	3	.228	.328	.398	.725	.170	.300	30	12	.323	106	+4	+2	-3	-4	+17	1.6
2039	32	MLB	MIL	575	496	111	17	2	20	68	176	6	15	2	.224	.325	.387	.712	.163	.299	31	12	.319	102	+1	+2	-4	-3	+16	1.3
2040	33	MLB	MIL	546	472	103	16	2	18	64	170	5	14	2	.218	.318	.375	.693	.157	.297	31	12	.313	98	-1	+2	-4	-3	+15	0.9
2041	34	MLB	MIL	498	432	93	14	2	16	58	160	5	13	1	.215	.315	.368	.683	.153	.295	32	12	.306	93	-4	+2	-5	-3	+14	0.4
2042	35	MLB	MIL	442	384	80	12	2	13	51	146	4	12	1	.208	.308	.352	.659	.143	.293	33	12	.299	87	-7	+2	-6	-3	+13	-0.1
2043	36	MLB	MIL	381	331	67	10	1	11	44	130	3	10	0	.202	.302	.338	.640	.136	.290	34	12	.290	80	-9	+2	-6	-2	+11	-0.5
▸ Career Totals (MLE all levels + projections)
Career	—			10061	8749	1973	309	47	339	1133	3083	100	330	74	.226	.321	.388	.709	.162	.304	31	11	.317	101	+12	+36	-36	-60	+285	24.2
/ 162G	—			650	565	128	20	3	22	73	199	6	21	5	.227	.321	.389	.710	.163	.305	31	11	.317	101	+1	+2	-2	-4	+18	1.5

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
2024	17	A	Carolina Mudcats	19	16	7	1	1	0	3	3	0	4	1	.438	.526	.625	1.151	.188	.538	16	16	.501	241	+3	+0	—	—	+1	0.4
2025	18	A	Carolina Mudcats	342	288	69	9	4	8	52	103	0	31	10	.240	.356	.382	.738	.142	.341	30	15	.334	114	+5	+2	—	—	+10	1.8

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
Braylon Payne (OGILVIE)	19	20→32	30→50	70	55	.197/.273/.327	.130	.287	8	9	35%	9%	67	-0.3	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Carlos Jimenez 2022 · A	19	39→41	42→50	53→55	44	.191/.270/.293	.102	.283	10	11	34%	8%	56	-1.3	.199/.283/.318	.119	.317	11	15	37%	9%	69	-0.4	.216/.296/.349	.133	.314	15	19	33%	9%	78	+0.1
●Corbin Carroll 2021 · A	20	46→54	40→60	57→60	46	.216/.286/.313	.097	.312	6	16	31%	9%	67	-0.5	.247/.323/.431	.184	.329	19	26	29%	9%	114	+2.7	.245/.332/.462	.217	.278	24	37	21%	10%	121	+3.5
✕Akil Baddoo 2019 · A	20	42→51	43→55	56→55	48	.206/.282/.325	.120	.283	9	13	29%	9%	69	-0.4	.212/.283/.340	.128	.306	11	16	32%	9%	73	-0.1	.232/.314/.375	.143	.300	15	24	26%	11%	91	+0.8
✕Taylor Trammell 2018 · A	20	46	41→55	56→55	44	.219/.278/.321	.102	.303	8	21	29%	7%	66	-0.6	.206/.279/.299	.093	.299	8	19	31%	9%	61	-1.0	.205/.299/.385	.179	.274	22	23	32%	11%	90	+0.6
●Trent Grisham 2016 · A	19	49→48	38→60	55	48	.229/.299/.313	.084	.311	4	18	26%	8%	72	-0.2	.199/.282/.286	.087	.299	6	16	32%	10%	59	-1.1	.238/.325/.431	.194	.282	22	14	23%	10%	110	+1.9
✕Dalton Pompey 2012 · A	19	40→50	41→45	56→55	44	.195/.266/.289	.094	.272	9	17	30%	8%	53	-1.5	.217/.283/.315	.098	.299	7	21	28%	8%	66	-0.6	.253/.315/.362	.109	.325	7	28	23%	8%	88	+0.8
✕Franchy Cordero 2014 · A	19	46→53	38→55	57→50	39	.211/.266/.297	.086	.326	5	13	35%	7%	53	-1.5	.209/.251/.287	.078	.321	5	13	35%	5%	44	-2.1	.230/.301/.392	.162	.321	18	12	32%	8%	92	+0.8
●Esteury Ruiz 2019 · A	20	44→54	43→50	58→70	37	.212/.260/.329	.117	.307	9	25	33%	5%	60	-1.0	.203/.254/.314	.111	.301	11	30	34%	5%	54	-1.4	.264/.338/.396	.132	.327	13	74	22%	6%	108	+1.6
✕Forrest Wall 2015 · A	19	47→56	41→45	56→70	47	.226/.290/.328	.102	.300	7	17	26%	8%	72	-0.2	.218/.270/.316	.098	.284	7	16	24%	6%	60	-1.0	.260/.332/.371	.111	.354	9	50	27%	9%	98	+1.0
●Michael Saunders 2007 · A	20	45→52	39→55	54→55	43	.210/.273/.299	.088	.305	6	15	31%	8%	58	-1.2	.234/.295/.362	.128	.331	12	16	31%	7%	84	+0.6	.251/.327/.433	.182	.309	19	17	24%	10%	112	+1.9
✕Jarred Kelenic 2019 · A	20	45→55	43→60	57→50	42	.218/.278/.332	.114	.297	9	12	29%	7%	69	-0.4	.225/.282/.404	.179	.286	22	13	29%	7%	90	+1.0	.222/.292/.404	.182	.285	20	15	29%	8%	91	+1.0
✕Jasson Domínguez 2023 · AA	20	43→53	46→50	56→60	43	.209/.282/.339	.129	.315	13	19	36%	8%	73	-0.1	.236/.308/.376	.140	.328	16	27	30%	9%	93	+1.3	.249/.323/.390	.141	.333	16	33	28%	10%	99	+1.2
✕Jose Escobar 2023 · A	18	45→47	44→50	57→50	40	.222/.271/.344	.122	.287	10	14	26%	5%	69	-0.4	.224/.289/.328	.104	.294	9	12	26%	6%	72	-0.2	.212/.286/.306	.093	.292	9	9	28%	7%	63	-0.5
✕Johan Mieses 2015 · A	20	43→32	41→55	59→50	42	.208/.262/.314	.106	.276	8	21	27%	6%	57	-1.2	.196/.243/.346	.150	.273	17	9	34%	5%	59	-1.1	.194/.269/.375	.181	.237	26	7	31%	7%	74	-0.0
✕Carlos Jorge 2023 · A	19	45→46	46→45	63→55	45	.218/.297/.358	.140	.309	12	29	32%	9%	84	+0.6	.206/.276/.324	.118	.298	11	25	32%	8%	66	-0.6	.199/.268/.305	.106	.282	9	28	31%	7%	55	-1.0
●Bo Naylor 2019 · A	19	44→43	39→55	52→50	46	.211/.278/.300	.089	.298	6	9	30%	8%	60	-1.0	.194/.251/.313	.119	.273	11	7	31%	7%	53	-1.5	.216/.308/.399	.183	.269	22	12	28%	11%	97	+1.2
✕Jett Williams 2023 · A	19	45	41→55	55	43	.216/.285/.315	.099	.290	7	13	27%	7%	68	-0.5	.204/.313/.323	.119	.295	10	23	31%	12%	83	+0.6	.202/.308/.336	.135	.284	11	26	30%	12%	81	+0.3
●Colby Rasmus 2006 · A	19	44→54	44→60	53→50	34	.205/.255/.325	.119	.341	10	11	41%	6%	57	-1.2	.223/.285/.376	.153	.280	17	15	26%	7%	84	+0.6	.237/.305/.454	.217	.309	28	3	32%	8%	109	+1.8
●Riley Greene 2021 · A	20	44→54	44→60	53→50	39	.215/.271/.330	.115	.305	11	9	32%	6%	66	-0.6	.252/.315/.404	.152	.357	15	10	31%	8%	103	+1.9	.263/.332/.466	.203	.338	25	5	28%	9%	124	+3.1
✕Cole Roederer 2019 · A	19	42→33	43→45	53→50	41	.207/.262/.318	.111	.296	11	14	33%	7%	59	-1.1	.191/.261/.291	.100	.280	9	12	33%	8%	52	-1.6	.187/.255/.306	.119	.269	14	12	34%	7%	52	-1.0

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)