Andreimi Antunez

SS FCL Rays

Age 20 R/R 5'10" / 143 lbs ROK HR -6%H +4% Svc 0.0 · Ctrl thru 2038

Overview

ROKPROSPECTMiLBFA 2039

OGV OFP40OGV rank#291ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2025	18	ROKDSL Tampa Bay	209	.369/.453/.517	1	13	72	—	.243/.325/.337
2026	19	A/ROKTB	363	.245/.358/.422	10	14	61	—	.190/.275/.320
2027PROJMLE	20	MLBTB	473	.224/.286/.352	10	8	79	0.2
2028PROJ34% MLB	21	MLBTB	111	.232/.295/.370	3	2	86	0.1
2029PROJ48% MLB	22	MLBTB	198	.236/.300/.383	5	3	91	0.4

Next 3 projected WAR 0.7Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2038Service0.0First FA2039

2027MiLB2028MiLB2029MiLB2030MiLB2031MiLB2032MiLB2033Pre-Arb$0.9M2034Pre-Arb$1.0M+4

Skills · percentileMiLB Statcast 2026 A

Speed86

Whiff%80

ISO75

K%72

Z-Con%72

wRC+34

Career WAR0.0 WAR median (P10 -0.0 / P90 15, comp-based) · star 2% · didn't stick 84%

CompsMiguel Amaya (age 20) · Dilson Herrera (age 20) · Agustín Ramírez (age 21)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 210 proj PA

wRC+†79

AVG/OBP/SLG.222 / .284 / .349

PA210

HR4

K%24

BB%7

ISO128

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$45M ctrl surplus

Contract

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

Status MiLB

MLB Debut 2033

Service 0 yrs (est)

Team Control Through 2038

First FA Year 2039

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2033
2028	MiLB	still in minors · estimated debut 2033
2029	MiLB	still in minors · estimated debut 2033
2030	MiLB	still in minors · estimated debut 2033
2031	MiLB	still in minors · estimated debut 2033
2032	MiLB	still in minors · estimated debut 2033
2033	Pre-Arb	$0.9M	+1.1	$6M	+$5M
2034	Pre-Arb	$1.0M	+1.0	$5M	+$4M
2035	Pre-Arb	$1.0M	+0.9	$2M	+$2M
2036	Arb-1	$3M	+0.7	$1M	+$0.1M
2037	Arb-2	$5M	+0.5	$0.9M	+$0.0M (cut)
2038	Arb-3	$4M	+0.3	$0.5M	+$0.0M (cut)
Totals		$6M		$15M	+$11M

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. 2027 = full-season projection (no games played yet). 2028+ 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)
2025	18	ROK	DSL Tampa Bay	—	209	176	65	9	7	1	16	29	11	13	5	369	453	517	970	148	430	14	8	419	72	—	—	—	—	—	—
2026	19	A	Charleston RiverDogs	—	125	114	25	8	2	3	9	25	1	2	0	219	282	404	686	184	253	20	7	301	48	—	—	—	—	—	—
2026	19	ROK	FCL Rays	—	238	192	50	8	2	7	35	31	9	12	1	260	398	432	831	172	277	13	15	374	68	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2025	18	ROK MLE	DSL Tampa Bay	—	209	181	44	6	4	1	11	35	11	13	5	243	325	337	662	94	271	17	5	275	72	—	—	—	—	—	—
2026	19	A MLE	Charleston RiverDogs	—	125	117	21	6	2	2	6	34	1	2	0	179	226	316	542	137	227	27	5	239	48	—	—	—	—	—	—
2026	19	ROK MLE	FCL Rays	—	238	205	40	6	1	6	22	45	9	12	1	195	301	322	623	127	211	19	9	269	68	—	—	—	—	—	—
2025	18	ROK MLE	DSL Tampa Bay	—	209	181	44	6	4	1	11	35	11	13	5	243	325	337	662	94	291	17	5	275	72	—	—	—	—	—	—
2025	18	ROK RAW	DSL Tampa Bay	—	209	176	65	9	7	1	16	29	11	13	5	369	453	517	970	148	430	14	8	419	72	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	363	322	60	12	3	8	28	79	10	14	1	186	272	317	589	130	219	22	8	259	61	—	—	—	—	—	—
2026	19	ROK RAW	2 teams	—	363	306	75	16	4	10	44	56	10	14	1	245	358	422	780	176	269	15	12	349	61	—	—	—	—	—	—
2025	18	ROK MLE	DSL Tampa Bay	—	209	185	44	6	4	1	11	35	11	13	5	238	325	330	655	92	271	17	5	275	72	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	363	322	60	12	3	8	28	79	10	14	1	186	272	317	589	130	217	22	8	259	61	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2025	18	ROK MLE	DSL Tampa Bay	—	209	185	44	6	4	1	11	35	11	13	5	238	325	330	655	92	271	17	5	275	72	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	363	322	60	12	3	8	28	79	10	14	1	186	272	317	589	130	217	22	8	259	61	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	20	MLB MLE	TB	0%	473	432	97	18	4	10	31	116	7	8	2	224	286	352	638	128	281	25	7	286	79	-12	+1	-4	+5	+10	0.2
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	21	MLB MLE	TB	34%	323	293	68	13	2	8	22	78	5	6	1	230	293	370	664	141	283	24	7	296	86	-5	+1	-2	+3	+7	0.4
2029	22	MLB MLE	TB	48%	408	371	87	16	3	11	28	97	6	7	2	234	298	384	682	150	284	24	7	303	91	-4	+1	-2	+4	+9	0.8
2030	23	MLB MLE	TB	54%	455	414	97	18	3	13	32	107	6	8	2	237	302	394	696	157	285	24	7	309	95	-3	+1	-1	+5	+10	1.2
2031	24	MLB MLE	TB	55%	505	457	109	20	4	15	36	118	7	8	2	239	305	401	706	161	287	23	7	313	98	-1	+1	+0	+5	+11	1.6
2032	25	MLB MLE	TB	56%	527	477	116	21	4	17	38	123	7	9	2	241	306	405	711	164	287	23	7	315	99	-0	+1	+0	+6	+11	1.8
2033	26	MLB MLE	TB	56%	538	487	117	21	4	17	39	125	7	9	2	241	307	407	713	166	287	23	7	316	100	-0	+1	+0	+6	+12	1.9
2034	27	MLB MLE	TB	55%	538	487	117	21	4	17	39	126	7	8	2	240	306	404	710	164	287	23	7	314	99	-1	+1	+0	+6	+12	1.8
2035	28	MLB MLE	TB	55%	533	482	116	21	4	17	39	126	7	7	2	238	304	400	704	161	286	24	7	312	97	-2	+1	-1	+6	+12	1.6
2036	29	MLB MLE	TB	53%	521	472	112	20	4	16	37	125	7	6	2	236	301	394	695	158	285	24	7	308	95	-3	+0	-1	+6	+11	1.3
2037	30	MLB MLE	TB	53%	507	460	108	20	3	15	36	123	6	6	2	233	298	386	684	153	283	24	7	304	92	-5	+0	-2	+5	+11	1.0
2038	31	MLB MLE	TB	52%	490	447	103	19	3	14	34	121	6	4	3	229	293	377	670	148	281	25	7	298	88	-7	-0	-3	+5	+11	0.6
2039	32	MLB MLE	TB	52%	469	429	95	17	3	12	32	118	5	3	9	224	287	365	652	141	277	25	7	291	83	-9	-3	-3	+5	+10	-0.1
2028	21	MLB CTX	TB	34%	111	101	24	4	1	3	7	27	2	2	0	232	295	370	665	138	286	24	6	297	86	-2	+0	-1	+1	+2	0.1
2029	22	MLB CTX	TB	48%	198	179	43	8	2	5	14	47	3	3	1	236	300	383	683	148	287	24	7	304	91	-2	+0	-1	+2	+4	0.4
2030	23	MLB CTX	TB	54%	247	225	54	10	2	7	17	58	3	4	1	239	303	393	696	154	289	23	7	309	95	-1	+0	-1	+3	+5	0.7
2031	24	MLB CTX	TB	55%	280	254	61	11	2	8	20	65	4	5	1	241	306	399	706	158	290	23	7	313	98	-1	+1	+0	+3	+6	0.9
2032	25	MLB CTX	TB	56%	295	268	65	12	2	9	21	69	4	5	1	242	308	403	711	161	290	23	7	315	99	-0	+1	+0	+3	+6	1.0
2033	26	MLB CTX	TB	56%	303	274	66	12	2	9	22	71	4	5	1	243	308	405	713	163	290	23	7	316	100	-0	+1	+0	+3	+7	1.1
2034	27	MLB CTX	TB	55%	298	270	65	12	2	9	22	70	4	5	1	242	307	403	710	161	290	23	7	315	99	-0	+1	+0	+3	+6	1.0
2035	28	MLB CTX	TB	55%	292	265	63	11	2	9	21	69	4	4	1	240	305	398	704	158	289	24	7	312	97	-1	+0	-0	+3	+6	0.9
2036	29	MLB CTX	TB	53%	278	252	60	11	2	8	20	66	4	3	1	238	303	392	695	155	288	24	7	309	95	-2	+0	-1	+3	+6	0.7
2037	30	MLB CTX	TB	53%	267	243	57	10	2	8	19	65	3	3	1	235	299	385	685	150	286	24	7	304	92	-3	+0	-1	+3	+6	0.5
2038	31	MLB CTX	TB	52%	255	232	53	9	2	7	18	63	3	2	2	231	295	376	671	145	284	25	7	299	88	-4	-0	-1	+3	+6	0.3
2039	32	MLB CTX	TB	52%	243	221	51	9	2	6	17	61	3	2	5	226	289	364	653	138	280	25	7	291	83	-5	-2	-2	+3	+5	-0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3067	2784	662	119	23	88	218	731	41	43	16	238	303	392	695	154	290	24	7	308	91	-20	+2	-7	+33	+66	7.5
/ 162G	—	A+C		—	650	590	141	25	5	19	46	155	9	9	3	239	304	395	699	156	291	24	7	308	91	-4	+0	-2	+7	+14	1.6
Career	—	MLE		—	6596	5970	1392	253	50	185	465	1552	100	112	38	233	299	385	685	152	283	24	7	303	91	-46	+4	-16	+65	+131	14.0
/ 162G	—	MLE		—	650	588	137	25	5	18	46	153	10	11	4	233	300	384	684	151	283	24	7	303	91	-5	+0	-2	+7	+14	1.5

How the minor-league lines were translated

One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.

2026 ROKFCL Rays · 238 PAwOBA .366 → .269 (−98)K% 13.0% → 18.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.03%	÷1.000	×1.440	—	—	18.76%
BB% (unintentional) /PA	14.71%	÷1.000	×0.620	—	×0.995	9.07%
HBP% /PA	3.78%	—	×0.720	—	×0.995	2.71%
Singles /BIP	20.50%	÷1.000	×0.820	×0.969	×0.995	16.20%
Doubles /BIP	4.97%	÷1.000	×0.720	×0.969	×0.995	3.45%
Triples /BIP	1.24%	÷1.000	×0.720	×0.969	×0.995	0.86%
Home runs /BIP	4.35%	÷1.000	×0.780	—	×0.995	3.37%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 20 vs a level average of 19.5 → −0.5% on BB/HBP/hit rates (0.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.969.

Result: wOBA .366 → .269; ISO .172 → .132; BABIP .277 → .211. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2026 ACharleston RiverDogs · 125 PAwOBA .295 → .239 (−56)K% 20.0% → 27.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.00%	÷1.000	×1.360	—	—	27.20%
BB% (unintentional) /PA	7.20%	÷1.000	×0.690	—	×1.030	5.12%
HBP% /PA	0.80%	—	×0.780	—	×1.030	0.64%
Singles /BIP	13.48%	÷1.000	×0.920	×0.989	×1.030	12.64%
Doubles /BIP	8.99%	÷1.000	×0.830	×0.989	×1.030	7.60%
Triples /BIP	2.25%	÷1.000	×0.910	×0.989	×1.030	2.08%
Home runs /BIP	3.37%	÷1.000	×0.800	—	×1.030	2.78%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 20 vs a level average of 22.0 → +3.0% on BB/HBP/hit rates (2.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.989.

Result: wOBA .295 → .239; ISO .184 → .148; BABIP .253 → .227. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2025 DSLDSL Tampa Bay · 209 PAwOBA .415 → .275 (−139)K% 13.9% → 16.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.88%	÷1.005	×1.220	—	—	16.85%
BB% (unintentional) /PA	7.66%	÷1.011	×0.700	—	×0.995	5.27%
HBP% /PA	5.26%	—	×0.700	—	×0.995	3.67%
Singles /BIP	32.65%	÷1.054	×0.680	×1.010	×0.995	21.17%
Doubles /BIP	6.12%	÷0.944	×0.600	×1.010	×0.995	3.91%
Triples /BIP	4.76%	÷1.150	×0.600	×1.010	×0.995	2.50%
Home runs /BIP	0.68%	÷0.952	×0.470	—	×0.995	0.33%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 90, 1B 111, 2B 89, 3B 130, K 101, BB 102 — applied at half strength. Age: age 19 vs a level average of 18.5 → −0.5% on BB/HBP/hit rates (0.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.010.

Result: wOBA .415 → .275; ISO .148 → .087; BABIP .430 → .271. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Didi Gregoriuslast yr '22 career totals — 10 seasons, 4,238 PA	6.4	4,238	134	37	256	308	421	+45	-10	17.0	17.2
/162	664	21	6	+7.1	-1.5	2.7	pk7: 18
#2Mike Bordick'90-'03 * career totals — 13 seasons, 6,484 PA	9.8	6,484	91	96	250*	311*	357*	+65	-10	12.7	14.0
/162	664	9	10	+6.7	-1.0	1.3	pk7: 15
#3Khalil Greenelast yr '09 career totals — 7 seasons, 2,835 PA	4.3	2,835	90	25	245	302	422	+30	+14	13.0	13.0
/162	664	21	6	+7.1	+3.2	3.0	pk7: 13
#4Alex Gonzalez'94-'06 * career totals — 12 seasons, 5,528 PA	8.3	5,528	137	97	232*	290*	379*	+55	+6	8.3	10.0
/162	664	16	12	+6.6	+0.8	1.0	pk7: 12
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 7 projected seasons	4.9	3,277	95	46	236	297	392	+35	-8	10.3	9.0
/162	664	19	9	+7.1	-1.6	2.1	pk7: 8
#5Kevin Elster'86-'00 * career totals — 9 seasons, 3,225 PA	4.9	3,225	88	14	223*	294*	388*	+34	+9	7.9	8.1
/162	664	18	3	+7.0	+1.9	1.6	pk7: 8
#6Tim Beckhamlast yr '19 career totals — 5 seasons, 1,743 PA	2.6	1,743	63	13	248	301	431	+19	-13	6.1	6.1
/162	664	24	5	+7.1	-4.8	2.3	pk7: 6

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
Andreimi Antunez (OGILVIE)	20	—	—	—	—	222/284/349	126	281	4	4	24%	7%	79	-0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Miguel Amaya 2019 · A	20	43	44→50	48→40	45	215/283/328	113	270	12	4	24%	7%	74	-0.5	216/296/343	127	275	13	4	25%	8%	83	+0.1	216/325/362	146	296	16	3	30%	10%	98	+0.3
●Dilson Herrera 2014 · A	20	44→54	45→55	49→50	41	220/273/347	128	293	12	11	29%	6%	74	-0.5	259/309/398	139	326	14	13	24%	6%	99	+1.3	267/319/412	145	327	15	13	22%	6%	104	+1.4
✕Agustín Ramírez 2023 · A	21	43→48	45→55	51→55	44	213/272/340	128	284	12	11	29%	7%	72	-0.7	233/294/390	157	279	18	13	23%	7%	93	+0.8	236/301/405	169	279	19	20	22%	7%	97	+1.1
●Andy Pages 2021 · A	20	43→53	46→60	46→50	46	215/300/346	131	277	14	9	26%	8%	85	+0.2	217/306/408	191	287	24	6	32%	9%	102	+1.5	269/326/453	184	315	23	10	22%	6%	121	+2.8
✕Brendan Rodgers 2017 · A	20	43→53	45→50	44→45	39	219/266/338	120	288	13	6	29%	5%	70	-0.9	243/287/379	136	307	15	6	25%	4%	87	+0.4	260/314/400	140	308	15	0	20%	6%	102	+1.0
✕Hao-Yu Lee 2023 · A	20	49→51	44→50	48→55	46	237/306/359	122	312	12	12	27%	8%	89	+0.5	247/312/378	131	315	13	16	24%	7%	96	+1.0	253/317/409	156	313	15	15	23%	7%	103	+1.2
✕Carter Kieboom 2018 · A	20	46→55	48→50	43→45	42	231/293/376	145	306	15	5	29%	7%	88	+0.5	241/311/374	133	318	15	6	27%	8%	95	+0.9	239/318/366	128	315	14	5	27%	9%	93	+0.6
✕Jeferson Quero 2023 · A	20	47	44→50	49→45	43	230/281/347	117	293	11	9	25%	6%	77	-0.3	232/290/369	137	282	16	7	23%	7%	86	+0.3	222/285/355	133	266	16	4	23%	7%	79	-0.1
✕Austin Hedges 2013 · A	20	46→41	43→60	45	42	226/274/339	114	275	10	12	22%	5%	73	-0.6	216/261/316	100	272	8	7	23%	5%	62	-1.4	230/269/417	186	275	25	4	26%	4%	90	+0.4
✕Wilin Rosario 2009 · A	20	42→52	44→60	44→45	38	212/256/323	111	292	12	5	31%	5%	62	-1.4	232/268/378	146	305	17	4	29%	4%	79	-0.2	260/293/445	185	295	25	4	21%	4%	106	+1.3
●Christian Vázquez 2012 · A	21	44→54	47→50	46→45	42	223/275/356	133	287	14	3	27%	6%	77	-0.3	238/296/342	104	299	9	4	22%	7%	81	-0.1	259/309/407	148	296	18	8	19%	7%	102	+1.0
✕Juan Apodaca 2006 · A	20	42→52	49→45	46→40	40	221/262/358	137	268	18	4	25%	5%	72	-0.7	226/281/329	103	287	11	5	24%	6%	73	-0.6	269/334/371	102	330	9	3	20%	8%	100	+0.7
●Alonzo Harris 2009 · A	20	44→52	46→50	49→60	40	222/276/345	124	295	14	11	29%	6%	75	-0.5	209/247/310	101	283	10	12	29%	4%	55	-1.9	234/290/378	144	282	15	35	22%	7%	85	+0.2
✕Bryan Ramos 2022 · A	20	41→42	45→50	49→50	42	206/277/332	126	281	12	8	30%	7%	73	-0.6	219/279/362	143	273	18	5	26%	6%	80	-0.1	214/275/354	140	261	19	5	25%	6%	74	-0.4
✕Juan Brito 2022 · A	20	44→50	41→50	47→45	46	215/282/311	96	276	9	12	25%	8%	70	-0.9	234/317/368	134	286	12	9	21%	10%	96	+1.0	231/317/370	139	276	13	9	20%	10%	94	+0.8
✕Nick Yorke 2023 · A	21	46→56	47→50	46→55	43	233/287/366	133	297	16	9	27%	7%	84	+0.1	246/303/366	120	328	12	15	27%	7%	89	+0.5	256/312/370	114	340	11	18	26%	7%	91	+0.6
✕Jeter Downs 2018 · A	20	42→41	43→50	47→55	47	209/276/317	108	258	11	9	23%	7%	69	-0.9	216/283/359	143	277	16	17	27%	7%	81	-0.1	176/270/315	139	246	15	26	33%	9%	66	-0.6
✕Michael Arroyo 2024 · A	19	44→51	40→50	46→50	49	208/316/308	101	279	6	7	25%	9%	84	+0.1	228/322/372	144	297	15	11	27%	8%	99	+1.3	232/324/382	150	294	16	12	25%	8%	100	+1.3
✕Yusniel Díaz 2017 · A	20	46→54	44→45	45→50	42	227/276/342	115	301	12	9	28%	6%	74	-0.6	238/295/357	119	312	12	8	26%	7%	84	+0.2	238/300/364	126	308	12	7	25%	8%	85	+0.2
✕Jake Smolinski 2009 · A	20	48→50	42→55	45	44	230/286/336	106	294	8	7	24%	6%	76	-0.4	235/293/350	115	284	9	6	20%	7%	82	-0.0	238/300/392	154	271	17	6	18%	7%	94	+0.6

Andreimi Antunez

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps