Korbyn Dickerson

Korbyn DickersonCF Inland Empire 66ers

Age 22 R/R 6'1" / 205 lbs A K +7%HR -5% Svc 0.0 · Ctrl thru 2034

2026 ROS PROJECTION482 act + 9 ros · stats below = ROS only

showingROS

wRC+†81

AVG/OBP/SLG.125 / .222 / .125

PA9

HR0

K%33

BB%11

BABIP291

ISO138

MLB%0%

Value2026 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$17M ctrl surplus

Tools · ContractCON 39 / POW 51

Toolsscout grade

CONTACT39

scouting grade only

POWER51

scouting grade only

EYE47

scouting grade only

SPEED58

scouting grade only

DEFENSE52

scouting grade only

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
2026	MiLB	still in minors · estimated debut 2029
2027	MiLB	still in minors · estimated debut 2029
2028	MiLB	still in minors · estimated debut 2029
2029	Pre-Arb	$0.8M	+0.6	$2M	+$1M
2030	Pre-Arb	$0.9M	+0.7	$2M	+$1M
2031	Pre-Arb	$0.9M	+0.7	$2M	+$1M
2032	Arb-1	$3M	+0.6	$2M	+$0.0M (cut)
2033	Arb-2	$5M	+0.5	$1M	+$0.0M (cut)
2034	Arb-3	$5M	+0.4	$0.9M	+$0.0M (cut)
Totals		$3M		$9M	+$4M

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. 2026 = actual YTD + projected ROS + total. 2027+ 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
▸ Model inputs — neutral MLE (past 3 seasons + 2026 so far)
YTD	22	A MLE	SEA	—	482	429	89	13	1	12	42	166	10	35	6	207	293	326	619	119	306	34	9	278	74	-15	+5	+0	+2	+10	0.2
▸ 2026 season
YTD	22	A RAW	SEA	—	349	294	81	13	2	9	46	87	8	21	4	276	388	425	813	150	362	25	13	367	74	—	—	—	—	—	—
YTD	22	A+ RAW	SEA	—	133	115	31	5	0	6	16	35	2	14	2	270	368	470	838	200	338	26	12	373	74	—	—	—	—	—	—
ROS	22	A MLE	SEA	0%	9	8	1	0	0	0	1	3	0	0	0	125	222	125	347		294	33	11	288	81	-0	+0	-0	+0	+0	0.0
TOT	22	A MLE	SEA	—	491	437	90	13	1	12	43	169	10	35	6	206	292	323	614	117	304	34	9	278	74	-15	+5	-0	+2	+11	0.2
▸ Career projection (2027+) — MLB context, MLB playing time (PA × MLB%)
2027	23	MLB MLE	SEA	34%	521	464	103	17	2	15	45	156	7	16	3	222	300	364	665	142	296	30	9	298	87	-8	+2	-1	+2	+11	0.7
2028	24	MLB MLE	SEA	46%	562	500	112	19	2	16	49	164	8	16	3	224	303	366	669	142	296	29	9	303	91	-6	+2	-1	+2	+12	1.0
2029	25	MLB MLE	SEA	52%	607	540	123	21	3	18	53	174	9	16	3	228	307	378	685	150	296	29	9	306	93	-5	+2	-1	+2	+13	1.2
2030	26	MLB MLE	SEA	54%	627	558	128	22	3	19	55	179	9	16	3	229	309	382	690	152	296	29	9	307	94	-4	+2	-1	+2	+14	1.3
2031	27	MLB MLE	SEA	54%	629	559	128	22	3	19	56	180	9	16	3	229	309	381	690	152	296	29	9	307	94	-4	+2	-1	+2	+14	1.3
2032	28	MLB MLE	SEA	54%	626	555	125	21	2	19	57	180	9	15	3	225	308	373	681	148	295	29	9	306	93	-5	+2	-2	+2	+14	1.1
2033	29	MLB MLE	SEA	53%	617	547	123	21	2	18	56	179	9	14	3	225	307	369	676	144	294	29	9	304	92	-6	+2	-2	+2	+13	0.9
2034	30	MLB MLE	SEA	52%	607	539	120	20	2	18	55	177	8	13	3	223	304	367	671	145	293	29	9	301	90	-7	+1	-3	+2	+13	0.7
2035	31	MLB MLE	SEA	52%	594	527	116	19	2	17	54	175	8	12	2	220	302	361	663	140	290	29	9	297	87	-9	+2	-4	+2	+13	0.4
2027	23	MLB CTX	SEA	34%	179	158	36	6	1	5	16	54	3	5	1	228	311	373	684	146	293	30	9	284	87	-3	+1	-0	+1	+4	0.2
2028	24	MLB CTX	SEA	46%	259	230	51	9	1	7	23	75	4	7	1	222	304	361	664	139	294	29	9	289	91	-3	+1	-0	+1	+6	0.4
2029	25	MLB CTX	SEA	52%	313	279	62	10	1	9	27	90	4	8	2	222	300	362	662	140	294	29	9	292	93	-3	+1	-0	+1	+7	0.6
2030	26	MLB CTX	SEA	54%	340	302	67	11	1	10	30	97	5	9	2	222	303	364	667	142	293	29	9	294	94	-2	+1	-1	+1	+7	0.7
2031	27	MLB CTX	SEA	54%	341	303	67	11	1	10	30	98	5	8	2	221	302	363	665	142	293	29	9	294	94	-2	+1	-1	+1	+7	0.7
2032	28	MLB CTX	SEA	54%	340	301	67	11	1	10	31	98	5	8	2	223	306	365	671	143	293	29	9	293	93	-3	+1	-1	+1	+7	0.6
2033	29	MLB CTX	SEA	53%	328	290	65	11	1	10	30	95	5	7	1	224	308	372	680	148	292	29	9	291	92	-3	+1	-1	+1	+7	0.5
2034	30	MLB CTX	SEA	52%	318	282	62	10	1	9	29	93	4	7	1	220	302	358	660	138	290	29	9	288	90	-4	+1	-2	+1	+7	0.4
2035	31	MLB CTX	SEA	52%	309	274	60	10	1	9	28	91	4	6	1	219	301	361	662	142	288	29	9	284	87	-5	+1	-2	+1	+7	0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2727	2419	537	89	9	79	244	791	39	65	13	222	303	364	668	142	293	29	9	290	91	-27	+8	-8	+10	+59	4.2
/ 162G	—	A+C		—	650	577	128	21	2	19	58	189	9	15	3	222	303	364	667	142	292	29	9	290	91	-6	+2	-2	+2	+14	1.0
Career	—	MLE		—	5399	4797	1079	182	21	159	481	1567	76	134	26	225	306	371	677	146	297	29	9	303	91	-55	+16	-15	+19	+117	8.4
/ 162G	—	MLE		—	650	578	130	22	3	19	58	189	9	16	3	225	305	372	677	147	298	29	9	303	91	-7	+2	-2	+2	+14	1.0

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Manuel Margotlast yr '24 career totals — 8 seasons, 3,154 PA	4.8	3,154	56	94	254	307	380	-5	+27	8.4	8.8
/162	664	12	20	-1.1	+5.6	1.8	pk7: 9
#2Will Venablelast yr '15 career totals — 8 seasons, 3,127 PA	4.7	3,127	81	135	251	317	406	-20	-4	8.9	8.7
/162	664	17	29	-4.2	-0.8	1.9	pk7: 9
#3Desmond Jenningslast yr '16 career totals — 6 seasons, 2,327 PA	3.5	2,327	55	93	245	323	394	-9	+10	8.1	8.1
/162	664	16	27	-2.5	+2.7	2.3	pk7: 8
#4Michael Saunderslast yr '17 career totals — 8 seasons, 2,711 PA	4.1	2,711	81	55	233	305	399	-12	-13	4.1	4.5
/162	664	20	13	-2.9	-3.2	1.0	pk7: 5
#5Gregory Polancolast yr '21 career totals — 8 seasons, 3,220 PA	4.8	3,220	96	98	241	309	409	-34	-28	3.8	4.4
/162	664	20	20	-7.1	-5.8	0.8	pk7: 5
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	4.6	3,047	89	74	225	302	371	-15	+6	4.2	3.9
/162	664	19	16	-3.3	+1.4	0.9	pk7: 4
#6Dustin Ackleylast yr '16 career totals — 6 seasons, 2,347 PA	3.5	2,347	46	31	241	304	367	-5	+7	3.8	3.8
/162	664	13	9	-1.3	+1.9	1.1	pk7: 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
Korbyn Dickerson (OGILVIE)	22	20→39	40→51	60→58	47	212/293/339	127	294	8	16	31%	9%	81	-0.0	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Tim Tawa 2022 · A	23	45→44	47→55	58→50	45	221/289/359	138	303	14	18	30%	8%	83	+0.1	211/273/334	123	271	14	11	27%	7%	72	-0.7	224/287/394	170	271	21	14	25%	7%	89	+0.4
✕Aaron Luna 2009 · A	22	42→45	50	51→45	45	210/316/367	157	290	18	7	32%	8%	97	+1.1	216/320/366	150	270	16	7	25%	8%	98	+1.2	214/321/360	146	266	16	7	24%	8%	95	+0.6
✕Phillip Ervin 2014 · A	22	47→51	48→50	54→55	46	237/301/379	142	295	16	14	25%	8%	93	+0.8	207/275/323	116	264	10	20	24%	7%	70	-0.9	235/299/371	136	298	13	21	24%	7%	86	+0.3
✕Juan Mora 2022 · A	22	46	44→45	55	46	225/303/346	121	300	11	14	27%	8%	86	+0.3	225/283/333	108	304	9	9	28%	5%	75	-0.5	222/278/328	106	295	10	8	27%	5%	70	-0.4
●Ronny Simon 2022 · A	22	40→50	49→50	53→60	43	206/265/356	150	272	16	14	30%	7%	74	-0.6	220/270/357	137	283	15	22	27%	6%	75	-0.5	266/329/370	104	332	7	30	21%	8%	98	+0.9
✕Ceddanne Rafaela 2022 · A	21	42→52	46→55	59→55	39	213/256/347	134	267	12	15	26%	4%	68	-1.0	239/275/393	154	305	16	22	27%	4%	85	+0.2	253/291/409	156	303	17	19	22%	4%	93	+0.8
✕Johan Lopez 2022 · A	22	43	44→45	56→55	44	209/290/327	118	301	11	16	32%	8%	76	-0.4	195/268/294	99	299	9	12	35%	8%	61	-1.5	172/246/253	81	260	7	12	34%	7%	41	-1.1
✕Andy Burns 2013 · A	22	43→53	47→50	54→55	42	211/280/356	145	296	13	13	32%	7%	80	-0.2	234/282/362	128	290	11	16	22%	6%	80	-0.1	243/288/359	116	293	9	15	20%	5%	80	-0.1
✕Mario Lisson 2006 · A	22	46→49	43→50	57→55	49	219/303/341	122	299	9	19	28%	10%	84	+0.2	220/282/334	114	289	10	21	26%	7%	75	-0.5	230/303/360	129	300	15	8	27%	8%	88	+0.3
✕Alex Castellanos 2009 · A	22	43→51	46→55	58→50	35	215/264/350	135	301	13	18	32%	4%	72	-0.7	217/269/350	133	312	11	15	33%	4%	74	-0.6	233/294/405	172	309	17	15	29%	6%	94	+0.7
✕Blaze Alexander 2021 · A	22	45→48	42→45	51→50	42	215/281/322	107	301	9	11	30%	7%	72	-0.7	206/277/331	125	321	14	12	37%	7%	73	-0.6	239/319/362	123	339	12	15	30%	8%	93	+0.6
✕Derek Fisher 2016 · A	22	43→50	50→55	55	42	218/282/367	149	303	18	18	33%	8%	82	+0.0	229/299/385	156	321	18	19	32%	8%	93	+0.8	225/302/403	177	309	23	18	33%	9%	95	+0.7
✕Daz Cameron 2018 · A	21	40→45	45→50	53→55	40	202/262/329	127	284	11	19	32%	6%	66	-1.1	201/268/318	117	295	9	17	33%	7%	66	-1.1	225/296/393	168	284	19	27	27%	8%	91	+0.3
●Matt McLain 2022 · A	22	45→55	44→55	53→55	48	220/298/335	115	296	11	20	28%	9%	81	-0.1	235/317/411	176	321	19	22	30%	9%	106	+1.8	231/315/396	166	310	19	23	30%	9%	99	+1.1
●Zack Gelof 2022 · A	22	48→50	49→55	54→55	43	235/299/383	148	333	16	17	33%	8%	93	+0.8	233/296/404	171	326	21	20	33%	8%	97	+1.1	229/294/405	176	316	22	24	33%	8%	93	+0.7
✕Cooper Bowman 2022 · A	22	44→43	45	56→60	41	213/288/344	131	301	12	19	32%	7%	80	-0.2	199/275/314	115	285	11	34	32%	8%	68	-1.0	202/274/318	116	272	11	40	28%	8%	66	-0.7
✕Jabari Henry 2013 · A	22	42→41	46→55	49→45	44	211/272/346	135	274	13	6	28%	7%	74	-0.6	207/286/361	154	270	17	6	28%	9%	83	+0.1	192/278/355	163	249	19	6	30%	10%	76	-0.3
✕Jason Taylor 2009 · A	21	42→39	46→45	53→55	51	210/295/335	126	263	13	20	25%	10%	80	-0.1	211/270/323	112	266	10	17	24%	7%	68	-1.0	202/249/302	100	249	8	18	21%	5%	53	-0.7
✕Michael Guldberg 2022 · A	23	45	44→45	55	44	221/288/339	118	278	11	16	24%	6%	78	-0.3	214/270/297	83	283	6	12	25%	6%	61	-1.5	205/257/264	59	274	3	10	25%	6%	46	-0.7
✕Jonny DeLuca 2022 · A	24	40→37	53→60	56→55	45	216/275/390	173	253	21	15	24%	7%	85	+0.2	224/289/407	183	256	22	16	22%	7%	95	+0.9	221/290/400	179	249	21	19	21%	7%	91	+0.4

Career Stats + Projections

Career Comps

Career Path Comps