Kendall George — OGILVIE

Kendall GeorgeOF Tulsa Drillers

Age 21 L/L 5'9" / 170 lbs AA HR +15%K -3% Svc 0.0 · Ctrl thru 2034 peak 2.2 · 2031

wRC+†93

AVG/OBP/SLG.227 / .311 / .296

PA320

HR3

SB33

K%23

BB%10

MLB%2%

Scouting · now → future

HIT

40↗51

PWR

30↗31

SPD

70↗76

FLD

40↗56

EYE

59↘55

trajectory · 10 yrs

2.2peak

2031

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	Arb-1	$0.8M	+1.8	$16M	+$15M
2030	Arb-2	$0.9M	+2.0	$18M	+$17M
2031	Arb-3	$0.9M	+2.2	$20M	+$20M
2032	Ext / FA-deal	$4M	+2.1	$20M	+$16M
2033	Ext / FA-deal	$7M	+2.0	$20M	+$13M
2034	Ext / FA-deal	$9M	+1.7	$17M	+$8M
Totals		$23M		$111M	+$88M

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
2023	18	ROK	2 teams	121	106	33	4	0	0	11	28	1	17	6	.311	.381	.349	.730	.038	.412	23	9	.324	106	+1	+1	+0	-1	+3	0.5
2024	19	A	Rancho Cucamonga Quakes	404	355	76	5	3	1	43	115	3	36	12	.214	.304	.254	.558	.039	.310	28	11	.255	53	-21	+2	+0	-2	+11	-1.0
2025	20	A+	Great Lakes Loons	514	450	119	8	5	2	58	101	1	100	24	.264	.350	.318	.667	.053	.333	20	11	.307	93	-4	+10	+0	-3	+15	1.8
▸ 2026 Season (actual · ROS · total)
2026	21	AA	Tulsa Drillers	73	64	22	3	0	0	8	17	0	12	1	.344	.417	.391	.807	.047	.468	23	11	.346	123	+2	+2	+0	-0	+2	0.6
ROS	21	MLB	LAD	247	218	55	6	2	2	26	57	1	21	4	.252	.335	.326	.660	.073	.321	23	11	.295	84	-4	+3	-0	-1	+7	0.3
TOT	21	MLB	LAD	320	282	77	9	2	2	34	74	1	33	5	.273	.353	.340	.694	.067	.362	23	11	.307	93	-3	+5	-0	-2	+9	0.9
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	22	MLB 12%	LAD	544	478	118	12	3	6	58	118	3	41	8	.247	.332	.322	.654	.075	.313	22	11	.300	88	-7	+5	-1	-3	+15	0.9
2028	23	MLB 29%	LAD	588	516	131	14	4	9	64	125	3	39	8	.254	.340	.349	.688	.095	.312	21	11	.311	96	-3	+5	-1	-4	+17	1.4
2029	24	MLB 46%	LAD	617	541	138	15	4	11	68	130	3	37	7	.255	.342	.359	.700	.104	.312	21	11	.317	101	+0	+5	-1	-4	+17	1.8
2030	25	MLB 61%	LAD	633	553	142	16	4	12	71	132	4	34	7	.257	.346	.365	.711	.108	.312	21	11	.321	104	+3	+4	-1	-4	+18	2.0
2031	26	MLB 78%	LAD	641	559	144	16	4	13	73	134	4	32	6	.258	.347	.370	.718	.113	.313	21	11	.323	105	+4	+4	-1	-4	+18	2.2
2032	27	MLB 93%	LAD	641	558	144	16	4	13	74	135	4	29	6	.258	.349	.371	.720	.113	.313	21	12	.323	105	+4	+3	-1	-4	+18	2.1
2033	28	MLB	LAD	636	553	141	15	4	12	74	135	4	27	5	.255	.347	.362	.709	.107	.313	21	12	.322	104	+3	+3	-2	-4	+18	2.0
2034	29	MLB	LAD	626	544	138	15	3	12	73	134	4	24	4	.254	.346	.358	.705	.105	.312	21	12	.320	103	+2	+3	-2	-4	+18	1.7
2035	30	MLB	LAD	616	536	133	14	3	11	72	134	3	22	3	.248	.340	.347	.687	.099	.311	22	12	.317	100	+0	+3	-3	-4	+17	1.5
2036	31	MLB	LAD	602	524	130	14	3	11	70	134	3	19	2	.248	.340	.349	.689	.101	.310	22	12	.313	98	-2	+3	-4	-4	+17	1.1
2037	32	MLB	LAD	583	508	124	13	3	10	67	133	3	17	2	.244	.336	.341	.676	.096	.309	23	11	.308	94	-4	+3	-4	-3	+17	0.8
2038	33	MLB	LAD	553	481	117	12	3	9	64	130	3	15	1	.243	.336	.337	.673	.094	.308	24	12	.303	90	-6	+3	-5	-3	+16	0.4
2039	34	MLB	LAD	506	441	104	10	3	7	58	123	2	13	0	.236	.327	.320	.647	.084	.307	24	11	.298	86	-8	+3	-6	-3	+14	0.0
2040	35	MLB	LAD	449	393	91	9	2	6	51	114	2	12	0	.232	.323	.310	.633	.079	.306	25	11	.291	81	-10	+2	-6	-3	+13	-0.4
▸ Career Totals (MLE all levels + projections)
Career	—			9521	8314	2078	214	57	147	1075	2112	51	535	105	.250	.339	.342	.682	.092	.316	22	11	.310	95	-52	+65	-37	-57	+270	19.2
/ 162G	—			650	568	142	15	4	10	73	144	3	37	7	.250	.338	.343	.681	.093	.317	22	11	.310	95	-4	+5	-3	-4	+18	1.3

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
2023	18	A	Rancho Cucamonga Quakes	50	42	16	2	0	0	6	9	1	6	2	.381	.469	.429	.898	.048	.485	18	12	.403	167	+4	+0	—	—	+1	0.6
2023	18	ROK	ACL Dodgers	71	58	21	3	0	0	11	11	0	11	4	.362	.464	.414	.878	.052	.429	15	15	.392	158	+5	+1	—	—	+2	0.7
2024	19	A	Rancho Cucamonga Quakes	404	341	95	6	4	1	57	83	3	36	12	.279	.387	.328	.715	.050	.362	21	14	.332	112	+6	+2	—	—	+11	2.0
2025	20	A+	Great Lakes Loons	514	424	125	9	7	3	84	78	1	100	24	.295	.413	.370	.783	.075	.352	15	16	.359	133	+19	+10	—	—	+15	4.5

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
Kendall George (OGILVIE)	21	40→51	30→31	70→76	55	.227/.311/.296	.069	.296	3	23	23%	10%	74	-0.0	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Billy Hamilton 2013 · AA	22	53→60	36→40	75→70	46	.245/.303/.322	.077	.335	2	68	26%	8%	76	+0.0	.240/.287/.323	.083	.309	4	68	22%	6%	69	-0.4	.242/.301/.319	.077	.310	4	55	22%	8%	70	-0.3
●Mallex Smith 2015 · A	22	53→61	39→45	62→65	49	.248/.318/.334	.087	.322	6	43	24%	8%	86	+0.8	.260/.319/.354	.094	.336	5	43	22%	7%	91	+1.1	.265/.331/.373	.108	.337	5	43	21%	8%	96	+1.1
✕Gabriel Mejia 2015 · A	20	53	34→30	62→70	50	.243/.313/.300	.057	.324	1	41	24%	9%	75	-0.0	.245/.304/.300	.055	.313	1	34	20%	7%	70	-0.3	.241/.292/.280	.039	.299	0	29	18%	6%	57	-0.4
✕Jorge Mateo 2016 · A	21	44→46	39→50	66→65	41	.212/.261/.302	.090	.288	5	43	27%	6%	53	-1.5	.201/.244/.309	.108	.289	7	32	32%	5%	48	-1.9	.217/.264/.366	.149	.272	14	44	25%	5%	70	-0.2
✕Jayce Easley 2022 · A	22	47→46	36→30	64→65	53	.215/.311/.284	.069	.306	3	42	28%	11%	72	-0.2	.192/.284/.260	.068	.275	4	33	28%	10%	54	-1.4	.160/.255/.207	.047	.236	3	32	30%	10%	27	-1.4
✕Delino DeShields 2015 · AA	22	47→53	42→45	63→65	45	.226/.295/.333	.107	.303	9	42	27%	8%	76	+0.1	.228/.304/.326	.098	.306	7	32	25%	9%	79	+0.3	.226/.309/.316	.089	.304	7	31	25%	10%	75	-0.0
✕Wes Rogers 2016 · A	22	46→51	39→40	64→65	43	.219/.275/.306	.087	.286	6	33	25%	6%	60	-1.0	.220/.275/.309	.089	.294	6	34	25%	6%	61	-1.0	.216/.270/.302	.086	.290	6	36	26%	6%	55	-1.1
✕José Peraza 2015 · AA	21	56→64	36→45	64→65	42	.263/.291/.339	.076	.307	3	39	15%	3%	74	-0.1	.262/.289/.341	.079	.300	4	32	14%	3%	74	-0.1	.273/.311/.358	.084	.306	7	25	13%	4%	84	+0.6
✕Antoan Richardson 2007 · A	23	53→60	36→40	62→60	48	.244/.312/.308	.064	.312	3	36	22%	8%	76	+0.1	.235/.314/.307	.072	.319	4	32	25%	9%	78	+0.2	.260/.355/.324	.063	.348	1	30	22%	11%	95	+1.0
✕Travis Jankowski 2014 · A	23	53→61	35→40	61→65	45	.245/.293/.308	.064	.317	2	36	23%	6%	67	-0.5	.250/.307/.320	.070	.319	3	34	21%	7%	77	+0.1	.259/.337/.327	.068	.330	4	29	20%	10%	86	+0.4
✕Rochest Cruz 2019 · A	20	48	37→40	60→65	54	.225/.302/.299	.073	.268	4	32	17%	9%	70	-0.3	.206/.275/.270	.064	.286	3	24	27%	8%	52	-1.6	.144/.214/.156	.012	.235	0	30	35%	6%	-5	-1.2
✕Johan Rojas 2023 · AA	22	43→53	42→45	63→65	42	.213/.261/.318	.105	.268	9	34	24%	5%	58	-1.2	.245/.287/.352	.107	.309	8	37	22%	5%	77	+0.1	.258/.299/.360	.102	.324	7	41	22%	5%	80	+0.3
✕Nasim Nuñez 2023 · AA	22	49→50	35→30	61→65	51	.220/.310/.276	.056	.330	3	42	31%	11%	69	-0.4	.210/.291/.274	.064	.291	5	42	27%	10%	59	-1.1	.203/.277/.267	.064	.267	7	52	25%	9%	49	-1.3
✕Eric Young Jr. 2008 · A	23	51→60	40→45	63→65	45	.243/.300/.345	.101	.306	6	40	22%	6%	81	+0.4	.250/.313/.343	.093	.315	5	42	21%	7%	86	+0.8	.265/.336/.357	.092	.321	3	47	17%	9%	97	+1.1
✕Yhoswar Garcia 2023 · A	21	42	38→30	61→70	39	.197/.263/.279	.082	.306	5	36	35%	7%	49	-1.8	.204/.255/.272	.068	.280	3	37	27%	5%	43	-2.2	.203/.249/.256	.053	.266	2	51	23%	5%	33	-1.4
●Dee Strange-Gordon 2011 · AA	23	54→64	36→40	60→65	43	.255/.294/.328	.073	.311	3	33	19%	4%	73	-0.1	.251/.292/.313	.062	.309	2	45	18%	5%	69	-0.4	.308/.341/.394	.087	.364	3	55	15%	4%	106	+2.0
●Brett Gardner 2007 · AA	23	55→59	35→55	62→65	51	.251/.323/.320	.069	.334	2	36	24%	9%	84	+0.6	.255/.324/.342	.087	.330	3	40	21%	9%	90	+1.0	.248/.332/.422	.175	.280	19	16	18%	10%	111	+2.5
✕Rafael Bautista 2015 · A	22	51→56	37→30	60	43	.242/.287/.311	.070	.297	4	35	20%	5%	66	-0.6	.243/.284/.305	.062	.297	3	33	18%	4%	63	-0.9	.251/.294/.300	.049	.315	2	32	20%	5%	62	-0.5
✕Everth Cabrera 2009 · A	22	48→58	38→40	60→65	43	.228/.283/.312	.085	.304	5	32	26%	6%	66	-0.6	.238/.305/.329	.091	.310	4	33	22%	8%	79	+0.3	.260/.326/.339	.079	.330	3	54	20%	8%	86	+0.5
✕Micah Johnson 2014 · AA	23	51→59	40→45	61→60	43	.241/.289/.339	.099	.318	6	33	26%	6%	74	-0.1	.254/.299/.351	.097	.327	6	28	23%	6%	82	+0.5	.254/.299/.343	.089	.327	6	27	23%	6%	76	+0.0

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)