Sabin Ceballos — OGILVIE

Sabin Ceballos3B Richmond Flying Squirrels

Age 23 R/R 6'2" / 236 lbs AA HR -15%H -3% Svc 0.0 · Ctrl thru 2034

2026 ROS PROJECTION500 act + 9 ros · stats below = ROS only

showingROS

wRC+†75

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

PA9

HR0

K%22

BB%11

BABIP235

ISO109

MLB%2%

Value2026 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$5M ctrl surplus

Tools · ContractCON 45 / POW 35

Toolsscout grade

CONTACT45

scouting grade only

POWER35

scouting grade only

EYE50

scouting grade only

SPEED45

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	+0.3	$1.0M	+$0.3M
2030	Pre-Arb	$0.9M	+0.3	$0.9M	+$0.3M
2031	Pre-Arb	$0.9M	+0.3	$0.8M	+$0.3M
2032	Arb-1	$1M	+0.2	$0.5M	+$0.0M (cut)
2033	Arb-2	$1M	—	—	—
2034	Arb-3	$0.6M	—	—	—
Totals		$3M		$3M	+$0.9M

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
▸ Career — actual stats, one row per stint (as recorded, no adjustments)
2023	20	A	Augusta GreenJackets	—	35	32	9	0	0	1	3	11	0	0	0	281	343	375	718	94	400	31	9	326	107	+0	+0	—	—	+1	0.1
2023	20	ROK	FCL Braves	—	15	8	3	0	0	0	6	3	1	2	0	375	667	375	1.042		600	20	40	509	231	+2	+0	—	—	+0	0.3
2024	21	A+	Eugene Emeralds	—	517	450	121	30	1	10	52	104	11	9	6	269	359	407	765	138	326	20	10	344	119	+12	-1	—	—	+11	2.3
2024	21	INTL	Indios de Mayaguez	—	17	14	3	0	0	0	2	5	1	0	0	214	353	214	567		333	29	12	285	79	-0	+0	—	—	+0	-0.0
2025	22	AA	Richmond Flying Squirrels	—	420	358	83	20	0	6	47	73	8	4	3	232	334	338	672	106	273	17	11	306	93	-3	-0	—	—	+9	0.5
2025	22	INTL	Gigantes de Carolina	—	48	45	9	1	0	1	3	9	0	1	2	200	250	289	539	89	229	19	6	246	52	-3	-1	—	—	+1	-0.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2023	20	A MLE	Augusta GreenJackets	—	35	33	7	0	0	1	2	16	0	0	0	212	257	303	560	91	390	46	6	244	51	-2	+0	—	—	+1	-0.1
2023	20	ROK MLE	FCL Braves	—	15	10	3	0	0	0	4	4	1	2	0	300	533	300	833		503	27	27	395	153	+1	+0	—	—	+0	0.2
2024	21	A+ MLE	Eugene Emeralds	—	517	470	95	22	1	8	32	150	11	9	6	202	269	304	573	102	269	29	6	250	55	-27	-1	—	—	+11	-1.7
2025	22	AA MLE	Richmond Flying Squirrels	—	420	371	76	18	0	4	34	87	8	4	3	205	286	286	571	81	249	21	8	256	59	-20	-0	—	—	+9	-1.2
2023	20	A MLE	2 teams	—	50	43	11	0	0	1	6	20	1	2	0	256	360	326	686	70	455	40	12	289	82	—	—	—	—	—	—
2023	20	A RAW	2 teams	—	50	40	12	0	0	1	9	14	1	2	0	300	440	375	815	75	440	28	18	381	82	—	—	—	—	—	—
2024	21	A+ MLE	2 teams	—	534	485	98	23	1	8	33	155	12	9	6	202	270	303	573	101	276	29	6	250	55	—	—	—	—	—	—
2024	21	A+ RAW	2 teams	—	534	464	124	30	1	10	54	109	12	9	6	267	358	401	759	134	327	20	10	342	55	—	—	—	—	—	—
2025	22	AA MLE	2 teams	—	468	416	86	20	0	5	37	97	8	5	5	207	284	291	575	84	256	21	8	256	59	—	—	—	—	—	—
2025	22	AA RAW	2 teams	—	468	403	92	21	0	7	50	82	8	5	5	228	325	333	658	104	268	18	11	300	59	—	—	—	—	—	—
2023	20	A MLE	2 teams	—	50	43	11	0	0	1	6	20	1	2	0	256	360	326	686	70	424	40	12	289	82	—	—	—	—	—	—
2024	21	A+ MLE	2 teams	—	534	484	98	23	1	8	33	155	12	9	6	202	270	304	574	101	269	29	6	250	55	—	—	—	—	—	—
2025	22	AA MLE	2 teams	—	468	420	86	20	0	5	37	97	8	5	5	205	284	288	572	83	249	21	8	256	59	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons + 2026 so far)
2023	20	A MLE	2 teams	—	50	43	11	0	0	1	6	20	1	2	0	256	360	326	686	70	424	40	12	289	82	—	—	—	—	—	—
2024	21	A+ MLE	2 teams	—	534	484	98	23	1	8	33	155	12	9	6	202	270	304	574	101	269	29	6	250	55	—	—	—	—	—	—
2025	22	AA MLE	2 teams	—	468	420	86	20	0	5	37	97	8	5	5	205	284	288	572	83	249	21	8	256	59	—	—	—	—	—	—
YTD	23	AA MLE	SF	—	500	434	82	14	0	14	49	110	13	11	2	189	290	318	608	129	217	22	10	273	71	-17	+1	+0	+2	+11	-0.3
▸ 2026 season
YTD	23	AA RAW	SF	—	500	411	92	16	0	18	72	90	13	11	2	224	357	394	751	170	242	18	14	341	71	—	—	—	—	—	—
ROS	23	AA MLE	SF	2%	9	8	1	0	0	0	1	2	0	0	0	125	222	125	347		240	22	11	280	75	-0	+0	+0	+0	+0	-0.0
TOT	23	AA MLE	SF	—	509	442	83	14	0	14	50	112	13	11	2	188	289	314	604	127	216	22	10	273	71	-18	+1	+0	+2	+11	-0.3
▸ Career projection (2027+) — MLB context, MLB playing time (PA × MLB%)
2027	24	MLB MLE	SF	31%	482	426	89	17	1	12	44	106	9	7	2	209	296	338	634	129	246	22	9	288	81	-11	+1	+0	+2	+10	0.2
2028	25	MLB MLE	SF	45%	510	448	96	18	1	14	47	111	10	8	2	214	303	353	656	138	249	22	9	293	85	-9	+1	+0	+2	+11	0.4
2029	26	MLB MLE	SF	51%	525	462	99	19	1	14	48	115	10	8	2	214	302	351	653	136	251	22	9	296	86	-8	+1	+0	+2	+11	0.6
2030	27	MLB MLE	SF	53%	530	466	100	19	1	14	49	116	10	8	2	215	303	350	653	135	252	22	9	297	87	-8	+1	+0	+2	+11	0.6
2031	28	MLB MLE	SF	53%	528	463	99	19	1	14	50	116	10	8	2	214	304	350	654	136	251	22	9	296	86	-9	+1	-1	+2	+11	0.5
2032	29	MLB MLE	SF	53%	521	458	98	19	1	14	49	116	9	7	2	214	302	352	654	138	250	22	9	294	85	-9	+1	-1	+2	+11	0.3
2033	30	MLB MLE	SF	52%	511	449	94	18	0	13	48	115	9	7	2	209	298	336	635	127	249	23	9	291	83	-10	+1	-2	+2	+11	0.1
2034	31	MLB MLE	SF	52%	498	439	90	17	0	13	47	114	9	6	2	205	295	333	628	128	246	23	9	286	80	-12	+0	-3	+2	+11	-0.2
2027	24	MLB CTX	SF	31%	149	131	26	5	0	3	14	33	3	2	1	198	291	305	596	107	241	22	9	267	81	-3	+0	+0	+1	+3	0.0
2028	25	MLB CTX	SF	45%	227	200	42	8	0	6	21	50	4	3	1	210	298	340	638	130	244	22	9	272	85	-4	+0	+0	+1	+5	0.2
2029	26	MLB CTX	SF	51%	267	235	49	9	0	7	25	58	5	4	1	209	298	336	634	128	246	22	9	275	86	-4	+0	+0	+1	+6	0.3
2030	27	MLB CTX	SF	53%	278	245	51	10	0	7	26	61	5	4	1	208	297	335	632	127	247	22	9	276	87	-4	+0	+0	+1	+6	0.3
2031	28	MLB CTX	SF	53%	282	248	51	10	0	7	27	62	5	4	1	206	296	331	627	125	246	22	10	275	86	-5	+0	-0	+1	+6	0.3
2032	29	MLB CTX	SF	53%	274	241	49	9	0	7	26	61	5	4	1	203	294	328	622	124	245	22	9	273	85	-5	+0	-1	+1	+6	0.2
2033	30	MLB CTX	SF	52%	266	234	47	9	0	6	25	60	5	3	1	201	292	316	608	115	244	23	9	271	83	-5	+0	-1	+1	+6	0.0
2034	31	MLB CTX	SF	52%	258	227	46	9	0	6	24	59	5	3	1	203	293	322	615	119	241	23	9	267	80	-6	+0	-1	+1	+6	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2001	1761	361	69	0	49	188	444	37	27	8	205	295	328	623	123	245	22	9	272	79	-37	+2	-4	+7	+43	1.2
/ 162G	—	A+C		—	650	572	117	22	0	16	61	144	12	9	3	205	295	327	621	122	243	22	9	272	79	-12	+1	-1	+2	+14	0.4
Career	—	MLE		—	5166	4563	961	189	7	122	459	1183	97	75	27	211	296	335	632	125	255	23	9	285	79	-77	+5	-7	+15	+89	2.5
/ 162G	—	MLE		—	650	574	121	24	1	15	58	149	12	9	3	211	297	334	631	124	256	23	9	285	79	-12	+1	-1	+2	+14	0.4

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Danny Espinosalast yr '17 career totals — 8 seasons, 3,267 PA	4.9	3,267	98	64	221	297	378	+16	+36	11.0	11.4
/162	664	20	13	+3.2	+7.3	2.2	pk7: 12
#2Luis Valbuenalast yr '18 career totals — 10 seasons, 3,527 PA	5.3	3,527	113	10	226	311	395	+13	+1	10.5	11.2
/162	664	21	2	+2.4	+0.1	2.0	pk7: 12
#3Gordon Beckhamlast yr '19 career totals — 10 seasons, 3,764 PA	5.7	3,764	80	34	237	301	368	+13	+19	8.2	8.4
/162	664	14	6	+2.4	+3.4	1.4	pk7: 9
#4Yolmer Sánchezlast yr '19 career totals — 6 seasons, 2,438 PA	3.7	2,438	31	30	244	299	357	+9	+26	5.4	5.4
/162	664	8	8	+2.4	+7.2	1.5	pk7: 5
#5Dustin 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
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 4 projected seasons	3.0	2,009	53	29	213	298	347	+7	+2	2.8	2.7
/162	664	18	10	+2.4	+0.7	0.9	pk7: 3
#6Nick Senzellast yr '24 career totals — 6 seasons, 1,633 PA	2.5	1,633	40	33	232	299	363	+6	-14	0.9	0.9
/162	664	16	13	+2.4	-5.8	0.4	pk7: 1

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
Sabin Ceballos (OGILVIE)	23	45	35	45	50	199/290/316	117	240	7	6	22%	9%	75	-0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Andre Lipcius 2022 · AA	24	43→49	44→45	48→45	46	214/273/331	117	273	11	7	25%	8%	70	-0.8	230/300/357	127	286	13	8	23%	9%	86	+0.3	229/301/358	129	284	15	7	24%	9%	85	+0.2
✕Alexander Campos 2022 · A	22	42	42→40	46→45	48	206/291/311	105	278	9	6	28%	9%	73	-0.6	220/302/308	88	316	7	6	30%	9%	76	-0.4	234/327/306	73	330	7	6	28%	11%	84	+0.1
✕Juan Fernandez 2022 · AA	23	42→52	44→40	47→50	43	212/273/330	118	270	12	7	26%	6%	70	-0.8	240/298/323	83	296	7	10	20%	6%	78	-0.3	250/309/316	66	305	5	11	19%	6%	76	-0.3
✕Alsander Womack 2023 · A	24	48→47	43→40	44→45	48	235/296/337	102	285	12	7	22%	8%	80	-0.1	223/287/304	81	281	8	9	22%	7%	70	-0.9	216/285/284	68	272	7	8	22%	7%	62	-0.8
✕Ivan Jimenez 2016 · AAA	23	48	41→40	46→55	41	229/276/326	97	307	8	10	28%	6%	70	-0.9	248/301/334	86	321	5	15	23%	6%	81	-0.1	266/330/343	77	341	2	18	21%	7%	89	+0.2
✕Colton Welker 2021 · AA	23	45→55	42→45	47→45	42	223/266/328	106	281	10	5	24%	5%	67	-1.1	215/286/322	107	283	10	6	26%	8%	74	-0.6	193/287/267	73	266	6	3	27%	10%	60	-0.4
✕Kevin Flores 2008 · AAA	23	45→50	41→40	47→45	42	220/264/321	101	277	9	10	24%	5%	64	-1.3	225/273/305	80	285	5	8	22%	6%	63	-1.3	267/309/348	81	315	7	1	17%	5%	83	+0.1
✕Ray Chang 2007 · AAA	23	43→53	42→40	45→40	43	212/272/315	103	278	9	5	27%	6%	66	-1.1	227/283/325	98	284	6	4	21%	5%	72	-0.7	254/313/347	92	297	6	1	15%	6%	86	+0.2
✕Taylor Krick 2011 · A	23	43	39→30	48→40	50	207/292/288	80	272	6	7	25%	9%	68	-1.0	227/312/290	63	312	3	5	26%	8%	76	-0.4	234/324/284	50	326	2	2	25%	8%	77	-0.1
✕Seth Mejias-Brean 2015 · AA	24	49→53	42→45	45	49	237/302/344	107	292	10	5	22%	8%	84	+0.1	228/287/315	87	297	7	7	24%	7%	72	-0.7	228/280/335	107	286	12	6	24%	6%	70	-0.6
✕Steve Tolleson 2007 · A	23	46→53	42→45	44→50	51	225/299/332	107	273	9	9	21%	9%	80	-0.1	242/309/341	99	307	7	14	22%	8%	86	+0.3	252/311/367	115	300	10	12	18%	7%	89	+0.4
✕Jasson Atondo 2019 · AAA	23	46→56	40→30	45→50	46	220/270/315	95	264	7	11	20%	6%	65	-1.2	271/306/347	76	305	6	12	13%	5%	85	+0.2	302/331/357	55	335	3	11	10%	4%	92	+0.6
✕Zelous Wheeler 2010 · A	23	47→53	42→45	47→45	47	228/298/335	107	291	9	9	24%	8%	81	-0.1	239/312/355	116	288	10	8	20%	8%	91	+0.7	241/315/362	122	283	12	7	18%	8%	91	+0.5
✕Chris Denove 2006 · A	23	44	40	46→40	46	211/286/303	92	280	7	5	26%	8%	70	-0.9	200/259/270	70	271	4	4	26%	6%	51	-2.2	245/303/334	88	297	6	3	18%	6%	79	-0.1
✕Leo Jiménez 2023 · A	22	46→49	40→45	48→45	49	216/322/312	96	283	8	9	24%	9%	86	+0.3	226/314/335	109	285	10	7	23%	7%	88	+0.4	228/319/335	107	286	10	5	22%	7%	87	+0.2
✕Aaron McKeithan 2023 · A	23	45	40	45→40	44	215/292/306	91	293	8	4	28%	7%	73	-0.6	217/295/297	80	271	8	4	22%	7%	72	-0.7	216/302/271	55	271	5	1	21%	8%	67	-0.3
✕Tyler Smith 2015 · AA	24	50→54	41→40	48→50	48	236/306/340	103	299	8	10	23%	8%	84	+0.2	231/289/313	82	294	6	8	22%	7%	72	-0.7	223/279/294	71	283	5	7	22%	6%	60	-1.2
✕Zach Voight 2014 · A	23	48	41→45	46→40	50	229/305/335	105	294	8	4	24%	9%	83	+0.1	207/260/298	91	292	7	4	30%	6%	58	-1.7	179/223/259	80	258	6	1	32%	5%	31	-1.6
✕Miguel Amaya 2022 · AA	23	43→41	43→50	50→40	50	212/304/325	114	273	10	7	25%	9%	82	-0.0	224/309/361	137	297	15	5	28%	8%	92	+0.7	229/300/373	144	272	16	1	22%	7%	90	+0.2
✕Michael Almanzar 2014 · AA	23	46→50	44→45	48→45	40	229/270/348	119	282	12	9	24%	4%	73	-0.6	213/257/313	100	270	9	5	24%	4%	60	-1.6	196/238/282	86	253	8	2	25%	4%	43	-1.9

Career Stats + Projections

Career Comps

Career Path Comps