Marcos Terrero

C DSL Mets Blue

Age 21 L/R 5'11" / 155 lbs ROK H -5% Svc 0.0 · Ctrl thru 2038

Overview

ROKPROSPECTMiLBFA 2039

OGV OFP35OGV rank#1257ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2023	17	ROKDSL Mets Oran…	59	.292/.404/.417	0	1	50	—	.196/.281/.275
2024	18	ROKDSL Mets Oran…	104	.247/.402/.383	1	5	56	—	.163/.294/.244
2025	19	ROKDSL Mets Blue	95	.243/.424/.314	0	3	48	—	.171/.315/.224
2027PROJMLE	21	MLBNYM	205	.212/.297/.292	1	5	70	0.0
2028PROJ34% MLB	22	MLBNYM	24	.209/.294/.297	0	1	74	0.0
2029PROJ48% MLB	23	MLBNYM	75	.213/.297/.309	1	2	78	0.1

Next 3 projected WAR 0.2Projected 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 2025 Rk

Chase%98

Z-Con%93

BB%91

Whiff%88

wOBA66

Speed63

CompsDarrien Miller (age 21) · Tsung-Che Cheng (age 21) · Leo Jiménez (age 22)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 35 proj PA

wRC+†70

AVG/OBP/SLG.210 / .294 / .290

PA35

HR0

K%26

BB%10

ISO81

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$16M ctrl surplus

Tools · 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	+0.5	$1M	+$0.8M
2034	Pre-Arb	$1.0M	+0.4	$0.9M	+$0.5M
2035	Pre-Arb	$1.0M	+0.3	$0.7M	+$0.2M
2036	Arb-1	$1M	+0.2	$0.4M	+$0.0M
2037	Arb-2	$0.7M	—	—	—
2038	Ext	beyond projection horizon · no WAR estimate
Totals		$4M		$3M	+$2M

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. Catcher framing: only 2027 Statcast framing is modeled (Baseball Savant server-caches the leaderboard to the current season); prior-year framing is unmodeled — projections for established framers may run 1-3 WAR low.

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	17	ROK	DSL Mets Orange	—	59	48	14	6	0	0	9	13	0	1	0	292	404	417	820	125	378	22	15	360	50	—	—	—	—	—	—
2024	18	ROK	DSL Mets Orange	—	104	81	20	4	2	1	19	14	2	5	2	247	402	383	785	136	279	13	18	355	56	—	—	—	—	—	—
2025	19	ROK	DSL Mets Blue	—	95	70	17	3	1	0	20	20	2	3	0	243	424	314	738	71	321	21	21	344	48	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2023	17	ROK MLE	DSL Mets Orange	—	59	51	10	4	0	0	6	16	0	1	0	196	281	275	555	78	243	27	10	242	50	—	—	—	—	—	—
2024	18	ROK MLE	DSL Mets Orange	—	104	86	14	2	1	1	14	17	2	5	2	163	294	244	538	81	189	16	13	251	56	—	—	—	—	—	—
2025	19	ROK MLE	DSL Mets Blue	—	95	76	13	2	1	0	14	25	2	3	0	171	315	224	539	53	205	26	15	239	48	—	—	—	—	—	—
2023	17	ROK MLE	DSL Mets Orange	—	59	51	10	4	0	0	6	16	0	1	0	196	281	275	555	78	270	27	10	242	50	—	—	—	—	—	—
2023	17	ROK RAW	DSL Mets Orange	—	59	48	14	6	0	0	9	13	0	1	0	292	404	417	820	125	378	22	15	360	50	—	—	—	—	—	—
2024	18	ROK MLE	DSL Mets Orange	—	104	86	14	2	1	1	14	17	2	5	2	163	294	244	538	81	186	16	13	251	56	—	—	—	—	—	—
2024	18	ROK RAW	DSL Mets Orange	—	104	81	20	4	2	1	19	14	2	5	2	247	402	383	785	136	279	13	18	355	56	—	—	—	—	—	—
2025	19	ROK MLE	DSL Mets Blue	—	95	76	13	2	1	0	14	25	2	3	0	171	315	224	539	53	241	26	15	239	48	—	—	—	—	—	—
2025	19	ROK RAW	DSL Mets Blue	—	95	70	17	3	1	0	20	20	2	3	0	243	424	314	738	71	321	21	21	344	48	—	—	—	—	—	—
2023	17	ROK MLE	DSL Mets Orange	—	59	53	10	4	0	0	6	16	0	1	0	189	281	264	545	75	243	27	10	242	50	—	—	—	—	—	—
2024	18	ROK MLE	DSL Mets Orange	—	104	87	14	2	1	1	14	17	2	5	2	161	294	241	535	80	189	16	13	251	56	—	—	—	—	—	—
2025	19	ROK MLE	DSL Mets Blue	—	95	79	13	2	1	0	14	25	2	3	0	165	315	215	530	51	205	26	15	239	48	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	18	ROK MLE	DSL Mets Orange	—	104	87	14	2	1	1	14	17	2	5	2	161	294	241	535	80	189	16	13	251	56	—	—	—	—	—	—
2025	19	ROK MLE	DSL Mets Blue	—	95	79	13	2	1	0	14	25	2	3	0	165	315	215	530	51	205	26	15	239	48	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	21	MLB MLE	NYM	0%	205	181	38	6	2	1	20	53	2	5	1	212	297	292	589	81	287	26	10	271	70	-7	+1	+0	+4	+4	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	22	MLB MLE	NYM	34%	71	63	14	2	1	1	7	18	1	2	0	216	300	306	607	91	288	25	10	278	74	-2	+0	+0	+1	+2	0.1
2029	23	MLB MLE	NYM	48%	155	137	31	5	2	2	15	39	2	4	1	219	303	318	621	99	289	25	10	284	78	-4	+0	+0	+3	+3	0.3
2030	24	MLB MLE	NYM	53%	237	209	46	8	2	3	23	59	3	6	1	222	306	329	634	106	291	25	10	289	81	-5	+1	+0	+4	+5	0.5
2031	25	MLB MLE	NYM	55%	307	272	61	10	3	5	29	77	3	8	2	225	307	337	644	112	291	25	9	292	84	-6	+1	+0	+5	+7	0.7
2032	26	MLB MLE	NYM	56%	356	315	71	12	3	6	34	88	4	9	2	226	308	343	652	117	291	25	10	295	86	-6	+1	+0	+6	+8	0.9
2033	27	MLB MLE	NYM	55%	379	336	75	12	3	7	36	94	4	10	2	225	307	341	648	116	290	25	9	293	85	-7	+1	+0	+7	+8	0.9
2034	28	MLB MLE	NYM	55%	387	343	76	13	3	6	37	97	4	10	3	223	305	336	641	113	289	25	10	291	83	-8	+1	-1	+7	+8	0.8
2035	29	MLB MLE	NYM	53%	385	342	75	12	3	6	36	98	4	9	3	221	302	329	632	109	288	25	9	287	80	-9	+1	-1	+7	+8	0.6
2036	30	MLB MLE	NYM	53%	377	335	73	12	3	6	35	97	4	9	3	217	299	321	620	104	286	26	9	282	77	-10	+1	-2	+7	+8	0.3
2037	31	MLB MLE	NYM	56%	348	310	67	11	3	5	32	91	3	8	3	213	294	311	605	98	282	26	9	276	73	-11	+0	-3	+6	+8	0.0
2028	22	MLB CTX	NYM	34%	24	22	4	1	0	0	2	6	0	1	0	209	294	297	592	88	279	25	8	272	74	-1	+0	+0	+0	+1	0.0
2029	23	MLB CTX	NYM	48%	75	67	14	2	1	1	7	19	1	2	0	213	297	309	606	96	280	25	9	278	78	-2	+0	+0	+1	+2	0.1
2030	24	MLB CTX	NYM	53%	125	111	24	4	1	2	12	31	1	3	1	216	300	319	619	103	282	25	10	282	81	-3	+0	+0	+2	+3	0.2
2031	25	MLB CTX	NYM	55%	168	148	33	5	2	3	16	42	2	4	1	218	301	327	629	109	282	25	10	286	84	-3	+0	+0	+3	+4	0.4
2032	26	MLB CTX	NYM	56%	198	175	38	6	2	3	19	49	2	5	1	220	302	334	636	114	282	25	10	289	86	-3	+1	+0	+4	+4	0.5
2033	27	MLB CTX	NYM	55%	208	184	40	6	2	4	20	52	2	5	1	218	301	331	633	113	281	25	10	287	85	-4	+1	+0	+4	+5	0.5
2034	28	MLB CTX	NYM	55%	212	188	41	6	2	4	20	53	2	5	1	217	299	326	626	110	280	25	9	285	83	-4	+1	-0	+4	+5	0.4
2035	29	MLB CTX	NYM	53%	205	182	39	6	2	3	19	52	2	5	1	214	297	320	617	106	279	25	9	281	80	-5	+1	-1	+4	+4	0.3
2036	30	MLB CTX	NYM	53%	198	176	38	6	2	3	18	51	2	5	1	211	293	312	605	101	277	26	9	276	77	-5	+1	-1	+4	+4	0.2
2037	31	MLB CTX	NYM	56%	197	175	37	6	2	3	18	51	2	4	2	207	288	302	590	96	274	26	9	270	73	-6	+0	-2	+4	+4	-0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1610	1428	308	48	16	26	151	406	16	39	9	216	298	326	624	111	281	25	9	282	78	-37	+4	-4	+29	+35	2.8
/ 162G	—	A+C		—	650	577	123	19	6	10	61	164	6	16	4	213	295	319	614	106	278	25	9	282	78	-15	+2	-2	+12	+14	1.1
Career	—	MLE		—	3295	2907	632	106	28	48	321	825	36	85	22	217	303	323	626	105	284	25	10	284	78	-70	+7	-7	+54	+66	5.2
/ 162G	—	MLE		—	650	573	125	21	6	9	63	163	7	17	4	218	303	323	626	105	286	25	10	284	78	-15	+2	-1	+12	+14	1.1

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.

2025 DSLDSL Mets Blue · 95 PAwOBA .348 → .239 (−109)K% 21.1% → 25.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.05%	÷0.994	×1.220	—	—	25.83%
BB% (unintentional) /PA	21.05%	÷1.011	×0.700	—	×0.985	14.35%
HBP% /PA	2.11%	—	×0.700	—	×0.985	1.45%
Singles /BIP	26.00%	÷0.984	×0.680	×1.003	×0.985	17.74%
Doubles /BIP	6.00%	÷1.301	×0.600	×1.003	×0.985	2.73%
Triples /BIP	2.00%	÷1.000	×0.600	×1.003	×0.985	1.19%
Home runs /BIP	0.00%	÷1.085	×0.470	—	×0.985	0.00%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 117, 1B 97, 2B 160, 3B 100, K 99, BB 102 — applied at half strength. Age: age 20 vs a level average of 18.5 → −1.5% on BB/HBP/hit rates (1.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.003.

Result: wOBA .348 → .239; ISO .071 → .040; BABIP .321 → .205. 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).

2024 DSLDSL Mets Orange · 104 PAwOBA .354 → .251 (−103)K% 13.5% → 16.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.46%	÷0.990	×1.220	—	—	16.60%
BB% (unintentional) /PA	18.27%	÷0.950	×0.700	—	×0.995	13.39%
HBP% /PA	1.92%	—	×0.700	—	×0.995	1.34%
Singles /BIP	19.40%	÷0.953	×0.680	×1.013	×0.995	13.95%
Doubles /BIP	5.97%	÷1.064	×0.600	×1.013	×0.995	3.39%
Triples /BIP	2.99%	÷0.921	×0.600	×1.013	×0.995	1.96%
Home runs /BIP	1.49%	÷0.996	×0.470	—	×0.995	0.70%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 99, 1B 91, 2B 113, 3B 84, K 98, BB 90 — 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 ×1.013.

Result: wOBA .354 → .251; ISO .136 → .083; BABIP .279 → .189. 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).

2023 DSLDSL Mets Orange · 59 PAwOBA .364 → .242 (−121)K% 22.0% → 27.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.03%	÷0.975	×1.220	—	—	27.57%
BB% (unintentional) /PA	15.25%	÷1.052	×0.700	—	×1.008	10.22%
HBP% /PA	0.00%	—	×0.700	—	×1.008	0.00%
Singles /BIP	22.86%	÷1.020	×0.680	—	×1.008	15.36%
Doubles /BIP	17.14%	÷1.012	×0.600	—	×1.008	10.24%
Triples /BIP	0.00%	÷0.949	×0.600	—	×1.008	0.00%
Home runs /BIP	0.00%	÷1.084	×0.470	—	×1.008	0.00%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 117, 1B 104, 2B 102, 3B 90, K 95, BB 110 — applied at half strength. Age: age 18 vs a level average of 18.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average).

Result: wOBA .364 → .242; ISO .125 → .078; BABIP .378 → .243. 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
#1Jacob Stallingslast yr '25 career totals — 7 seasons, 1,850 PA	2.8	1,850	33	0	229	310	340	+33	+50	10.3	10.3
/162	664	12	0	+11.9	+17.9	3.7	pk7: 10
#2Curt Casalilast yr '24 career totals — 10 seasons, 1,566 PA	2.4	1,566	47	2	217	311	367	+28	+19	7.8	7.9
/162	664	20	1	+11.9	+7.9	3.3	pk7: 8
#3Sandy Leónlast yr '22 career totals — 9 seasons, 1,648 PA	2.5	1,648	31	1	209	276	313	+29	+56	6.4	6.7
/162	664	12	0	+11.9	+22.4	2.6	pk7: 7
#4Fred Kendall'69-'80 * career totals — 8 seasons, 2,823 PA	4.3	2,823	31	5	231*	283*	340*	+48	+1	5.0	5.9
/162	664	7	1	+11.2	+0.1	1.2	pk7: 7
#5Jake Gibbs'63-'71 * career totals — 7 seasons, 1,795 PA	2.7	1,795	25	28	244*	299*	362*	+32	+0	5.4	5.4
/162	664	9	10	+11.9	+0.0	2.0	pk7: 5
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	2.5	1,646	25	40	222	301	331	+29	+24	4.0	3.8
/162	664	10	16	+11.9	+9.7	1.6	pk7: 4
#6Ben Davis'98-'04 * career totals — 6 seasons, 1,698 PA	2.6	1,698	38	9	228*	295*	352*	+30	-0	3.6	3.6
/162	664	15	4	+11.5	-0.0	1.4	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
Marcos Terrero (OGILVIE)	21	—	—	—	—	210/294/290	80	287	0	1	26%	10%	70	-0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Darrien Miller 2022 · A	21	45→42	45	50→45	48	218/318/334	116	300	13	8	30%	10%	90	+0.6	197/302/311	114	264	12	6	28%	9%	79	-0.2	179/320/285	107	245	9	4	27%	12%	79	-0.1
✕Tsung-Che Cheng 2022 · A	21	49→48	44→45	51→55	57	239/322/359	120	270	11	17	16%	10%	95	+1.0	224/293/340	116	299	9	19	26%	8%	80	-0.2	217/286/335	118	290	10	20	27%	8%	73	-0.5
✕Leo Jiménez 2023 · A	22	48→52	41→45	48→45	51	225/337/325	100	294	8	9	24%	9%	95	+1.0	235/325/347	112	296	10	7	23%	7%	95	+0.9	237/330/347	110	299	10	5	22%	7%	95	+0.5
✕Cooper Ingle 2024 · A	22	51→56	39→50	48→40	60	236/332/330	94	292	5	11	19%	12%	93	+0.8	248/339/379	131	306	11	5	21%	12%	106	+1.8	245/342/386	141	308	13	3	23%	12%	106	+1.4
✕James Skelton 2008 · A	22	53→57	42→40	51→50	53	255/323/364	109	305	8	13	19%	9%	97	+1.1	234/327/323	89	310	7	13	24%	12%	89	+0.5	226/327/311	85	298	5	10	23%	12%	86	+0.1
✕Ricardo Olivar 2024 · A	22	49→50	44→45	51→50	45	233/311/357	125	326	10	9	30%	8%	91	+0.7	224/296/352	128	290	14	9	26%	9%	84	+0.2	215/289/349	134	265	17	10	25%	9%	78	-0.2
✕Juan Brito 2023 · A	21	48→50	45→50	48→45	53	234/319/371	136	287	12	11	22%	10%	97	+1.1	231/311/367	136	281	13	9	21%	10%	93	+0.8	225/308/360	135	270	13	9	21%	10%	89	+0.4
✕Yeiner Fernandez 2024 · A	21	52→53	41→40	44→45	49	250/315/344	94	297	8	4	18%	7%	88	+0.5	228/291/299	71	271	4	6	16%	7%	70	-0.8	223/288/281	58	263	3	5	15%	6%	62	-1.0
✕Patrick Mazeika 2016 · A	22	51	42→45	48→30	47	246/315/364	118	282	8	4	16%	6%	94	+0.9	241/317/340	99	287	8	3	18%	8%	90	+0.6	234/314/330	96	274	9	1	17%	8%	83	+0.1
✕Alexander Albertus 2024 · A	19	49	41→45	47→45	61	232/339/328	96	275	9	11	18%	13%	95	+1.0	228/315/321	93	292	7	9	22%	10%	84	+0.2	225/311/319	93	294	7	6	24%	10%	80	-0.1
✕Cam Maron 2013 · A	22	54→58	40	46→40	49	257/325/347	90	328	7	4	22%	8%	93	+0.8	233/303/307	74	307	4	3	23%	9%	76	-0.4	247/317/312	65	316	4	2	21%	9%	79	-0.1
✕Mark Karaviotis 2017 · A	21	50	41→40	40	47	235/330/340	105	319	7	6	26%	8%	95	+1.0	227/303/318	91	327	7	4	30%	8%	79	-0.2	221/297/300	80	317	6	3	30%	8%	72	-0.5
✕Brian Jeroloman 2008 · A	23	50→39	38→40	46→40	65	229/346/309	80	296	5	3	22%	15%	94	+0.9	220/316/315	95	307	8	2	27%	12%	84	+0.1	210/310/309	99	304	9	0	30%	12%	78	-0.2
●Kyle Teel 2024 · AA	22	54→57	40→45	52→45	50	251/328/347	96	346	7	12	27%	10%	95	+0.9	255/336/376	121	350	13	10	28%	10%	105	+1.7	256/343/380	124	351	15	9	28%	11%	106	+1.2
✕Jimmy Crooks 2023 · A	22	48→47	47→50	51→40	43	229/308/368	139	326	14	6	32%	8%	93	+0.8	238/300/361	123	328	12	4	29%	7%	88	+0.4	240/311/381	141	337	17	2	32%	8%	94	+0.6
✕Noah Cardenas 2023 · A	23	46→45	44→45	47→45	54	223/326/344	120	286	11	9	24%	11%	95	+0.9	203/302/303	100	275	8	8	27%	10%	76	-0.4	185/290/277	92	251	8	6	27%	11%	63	-0.7
✕Jesus Rodriguez 2024 · A	22	52→61	43→45	53→50	48	249/311/362	113	301	9	14	20%	7%	91	+0.7	256/314/367	111	304	10	14	18%	7%	94	+0.9	261/323/368	107	303	10	16	17%	7%	95	+0.6
✕Jamie Ritchie 2016 · A	23	52→53	39→40	45	57	240/337/331	91	317	6	8	24%	12%	95	+0.9	235/319/321	86	314	6	6	25%	10%	86	+0.3	247/328/340	93	319	6	3	22%	9%	90	+0.3
✕Jeremy Lucas 2014 · AA	23	47→44	43→45	50→30	53	228/309/347	120	288	9	4	23%	10%	88	+0.4	224/290/346	122	277	12	3	22%	8%	80	-0.1	219/286/340	120	267	13	1	22%	7%	75	-0.3
✕Zack Collins 2017 · A	22	46→42	47→50	47→40	49	217/309/351	135	339	14	6	37%	12%	89	+0.5	194/292/340	146	302	16	3	37%	12%	81	-0.1	199/306/353	154	293	17	2	34%	13%	89	+0.4

Marcos Terrero

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps