Richard Matic

3B FCL Yankees

Age 20 R/R 6'0" / 200 lbs ROK HR +14% Svc 0.0 · Ctrl thru 2035

Overview

ROKPROSPECTMiLBFA 2036

OGV OFP35OGV rank#1262ETA2030MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	17	ROKDSL NYY Yanke…	186	.196/.335/.248	0	6	17	—	.125/.243/.156
2025	18	ROKDSL NYY Yanke…	191	.336/.495/.566	5	11	82	—	.192/.330/.301
2026	19	ROKNYY	264	.283/.394/.439	4	15	56	—	.190/.273/.291
2027PROJMLE	20	MLBNYY	374	.206/.280/.310	5	6	68	-0.2
2028PROJ25% MLB	21	MLBNYY	48	.214/.288/.339	1	1	76	-0.0
2029PROJ38% MLB	22	MLBNYY	115	.221/.295/.362	3	2	83	0.0

Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2035Service0.0First FA2036

2027MiLB2028MiLB2029MiLB2030Pre-Arb$0.8M2031Pre-Arb$0.9M2032Pre-Arb$0.9M2033Arb-1$2M2034Arb-2$4M+1

Skills · percentileMiLB Statcast 2026 Rk

Z-Con%86

Speed84

Whiff%72

ISO68

wRC+63

wOBA60

Career WAR0.0 WAR median (P10 0.0 / P90 4.1, comp-based) · star 2% · didn't stick 86%

CompsAgustín Ramírez (age 20) · Esmerlyn Valdez (age 19) · Tyler Nevin (age 20)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 146 proj PA

wRC+†68

AVG/OBP/SLG.204 / .278 / .308

PA146

HR2

K%27

BB%8

ISO104

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$2M ctrl surplus

Contract

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

Status MiLB

MLB Debut 2030

Service 0 yrs (est)

Team Control Through 2035

First FA Year 2036

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2030
2028	MiLB	still in minors · estimated debut 2030
2029	MiLB	still in minors · estimated debut 2030
2030	Pre-Arb	$0.8M	+0.1	$0.3M	+$0.0M (cut)
2031	Pre-Arb	$0.9M	+0.3	$0.9M	+$0.3M
2032	Pre-Arb	$0.9M	+0.4	$1M	+$0.6M
2033	Arb-1	$2M	+0.5	$1M	+$0.0M (cut)
2034	Arb-2	$4M	+0.4	$0.9M	+$0.0M (cut)
2035	Arb-3	$4M	+0.3	$0.7M	+$0.0M (cut)
Totals		$2M		$5M	+$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. 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)
2024	17	ROK	DSL NYY Yankees	—	186	153	30	8	0	0	23	43	9	6	2	196	335	248	584	52	270	23	12	284	17	—	—	—	—	—	—
2025	18	ROK	DSL NYY Yankees	—	191	143	48	12	3	5	40	43	5	11	6	336	495	566	1.061	231	439	23	21	459	82	—	—	—	—	—	—
2026	19	ROK	FCL Yankees	—	264	223	63	17	3	4	36	61	5	15	4	283	394	439	833	157	373	23	14	375	56	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2024	17	ROK MLE	DSL NYY Yankees	—	186	160	20	5	0	0	16	52	9	6	2	125	243	156	399	31	182	28	9	193	17	—	—	—	—	—	—
2025	18	ROK MLE	DSL NYY Yankees	—	191	156	30	7	2	2	27	53	5	11	6	192	330	301	631	109	258	28	14	289	82	—	—	—	—	—	—
2026	19	ROK MLE	FCL Yankees	—	264	237	45	11	2	3	22	88	5	15	4	190	273	291	564	101	285	33	8	251	56	—	—	—	—	—	—
2024	17	ROK MLE	DSL NYY Yankees	—	186	160	20	5	0	0	16	52	9	6	2	125	243	156	399	31	183	28	9	193	17	—	—	—	—	—	—
2024	17	ROK RAW	DSL NYY Yankees	—	186	153	30	8	0	0	23	43	9	6	2	196	335	248	584	52	270	23	12	284	17	—	—	—	—	—	—
2025	18	ROK MLE	DSL NYY Yankees	—	191	156	30	7	2	2	27	53	5	11	6	192	330	301	631	109	269	28	14	289	82	—	—	—	—	—	—
2025	18	ROK RAW	DSL NYY Yankees	—	191	143	48	12	3	5	40	43	5	11	6	336	495	566	1.061	231	439	23	21	459	82	—	—	—	—	—	—
2026	19	ROK MLE	FCL Yankees	—	264	237	45	11	2	3	22	88	5	15	4	190	273	291	564	101	288	33	8	251	56	—	—	—	—	—	—
2026	19	ROK RAW	FCL Yankees	—	264	223	63	17	3	4	36	61	5	15	4	283	394	439	833	157	373	23	14	375	56	—	—	—	—	—	—
2024	17	ROK MLE	DSL NYY Yankees	—	186	159	20	5	0	0	16	52	9	6	2	126	243	157	400	31	182	28	9	193	17	—	—	—	—	—	—
2025	18	ROK MLE	DSL NYY Yankees	—	191	157	30	7	2	2	27	53	5	11	6	191	330	299	629	108	258	28	14	289	82	—	—	—	—	—	—
2026	19	ROK MLE	FCL Yankees	—	264	235	45	11	2	3	22	88	5	15	4	191	273	294	566	102	285	33	8	251	56	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	17	ROK MLE	DSL NYY Yankees	—	186	159	20	5	0	0	16	52	9	6	2	126	243	157	400	31	182	28	9	193	17	—	—	—	—	—	—
2025	18	ROK MLE	DSL NYY Yankees	—	191	157	30	7	2	2	27	53	5	11	6	191	330	299	629	108	258	28	14	289	82	—	—	—	—	—	—
2026	19	ROK MLE	FCL Yankees	—	264	235	45	11	2	3	22	88	5	15	4	191	273	294	566	102	285	33	8	251	56	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	20	MLB MLE	NYY	0%	374	336	69	14	2	5	30	101	5	6	2	206	280	310	590	104	274	27	8	269	68	-14	+0	-3	+1	+8	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	21	MLB MLE	NYY	25%	193	172	37	7	1	4	16	51	3	3	1	213	288	334	622	121	276	26	8	281	76	-5	+0	-1	+1	+4	-0.2
2029	22	MLB MLE	NYY	38%	301	270	59	11	2	7	24	78	4	4	1	219	294	355	649	136	278	26	8	292	83	-6	+0	-2	+1	+7	-0.0
2030	23	MLB MLE	NYY	45%	383	344	76	14	2	10	31	99	5	5	1	224	299	371	670	147	280	26	8	300	89	-5	+1	-2	+1	+8	0.3
2031	24	MLB MLE	NYY	48%	438	393	90	17	3	13	36	112	6	5	2	228	302	383	685	155	282	26	8	306	93	-4	+0	-2	+2	+9	0.5
2032	25	MLB MLE	NYY	50%	467	419	97	18	3	15	39	118	6	5	2	230	305	391	696	161	283	25	8	310	96	-2	+0	-2	+2	+10	0.8
2033	26	MLB MLE	NYY	50%	482	433	100	18	3	16	40	122	6	5	2	231	305	395	701	164	283	25	8	311	97	-2	+0	-2	+2	+10	0.9
2034	27	MLB MLE	NYY	50%	487	438	101	19	3	16	40	124	6	5	2	230	304	392	697	162	282	25	8	310	96	-2	+0	-2	+2	+11	0.8
2035	28	MLB MLE	NYY	50%	485	436	99	18	3	15	40	125	6	4	2	228	302	387	690	159	281	26	8	307	94	-3	+0	-3	+2	+11	0.6
2036	29	MLB MLE	NYY	49%	475	427	96	18	3	14	39	123	6	4	2	225	299	381	680	156	279	26	8	303	91	-5	+0	-3	+2	+10	0.4
2037	30	MLB MLE	NYY	48%	463	417	92	17	2	14	38	122	5	3	2	222	295	373	668	151	277	26	8	298	88	-7	-0	-4	+2	+10	0.1
2038	31	MLB MLE	NYY	47%	447	403	88	16	2	13	36	119	5	2	7	218	290	362	653	145	273	27	8	292	84	-9	-2	-5	+2	+10	-0.4
2028	21	MLB CTX	NYY	25%	48	43	9	2	0	1	4	13	1	1	0	214	288	339	628	125	276	27	8	283	76	-1	+0	-0	+0	+1	-0.0
2029	22	MLB CTX	NYY	38%	115	103	23	4	1	3	9	30	2	2	0	221	295	362	657	141	278	26	8	294	83	-2	+0	-1	+0	+2	0.0
2030	23	MLB CTX	NYY	45%	174	156	36	7	1	5	14	45	2	2	1	226	300	378	678	153	281	26	8	303	89	-2	+0	-1	+1	+4	0.1
2031	24	MLB CTX	NYY	48%	211	189	44	8	1	7	17	54	3	3	1	230	304	391	695	161	282	26	8	309	93	-2	+0	-1	+1	+5	0.3
2032	25	MLB CTX	NYY	50%	232	208	48	9	1	8	19	59	3	3	1	232	306	399	706	167	283	25	8	313	96	-1	+0	-1	+1	+5	0.4
2033	26	MLB CTX	NYY	50%	243	218	50	9	1	8	20	62	3	3	1	233	307	404	711	171	283	26	8	315	97	-1	+0	-1	+1	+5	0.5
2034	27	MLB CTX	NYY	50%	244	219	50	9	1	8	20	62	3	3	1	232	306	401	707	169	282	25	8	314	96	-1	+0	-1	+1	+5	0.4
2035	28	MLB CTX	NYY	50%	241	216	49	9	1	8	20	62	3	2	1	230	304	396	700	166	281	26	8	311	94	-2	+0	-1	+1	+5	0.3
2036	29	MLB CTX	NYY	49%	230	206	46	8	1	7	19	60	3	2	1	227	301	389	690	162	279	26	8	307	91	-2	+0	-2	+1	+5	0.2
2037	30	MLB CTX	NYY	48%	221	198	44	8	1	7	18	58	3	1	1	224	297	381	678	157	277	26	8	302	88	-3	-0	-2	+1	+5	0.0
2038	31	MLB CTX	NYY	47%	211	190	41	7	1	6	17	56	2	1	3	219	292	370	662	151	274	27	8	296	84	-4	-1	-2	+1	+5	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2170	1946	440	80	10	68	177	561	28	23	11	226	300	382	682	156	280	26	8	307	86	-22	+0	-13	+8	+47	2.0
/ 162G	—	A+C		—	650	583	131	24	3	20	53	168	8	7	3	225	298	379	677	154	279	26	8	307	86	-7	+0	-4	+2	+14	0.6
Career	—	MLE		—	5408	4836	1057	201	32	144	456	1425	79	79	37	219	296	363	659	144	277	26	8	295	86	-56	-1	-29	+17	+103	3.5
/ 162G	—	MLE		—	650	581	127	24	4	17	55	171	9	9	4	219	296	361	657	143	278	26	8	295	86	-8	-0	-4	+2	+14	0.5

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 Yankees · 264 PAwOBA .366 → .251 (−115)K% 23.1% → 33.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.11%	÷1.000	×1.440	—	—	33.27%
BB% (unintentional) /PA	13.64%	÷1.000	×0.620	—	×1.008	8.52%
HBP% /PA	1.89%	—	×0.720	—	×1.008	1.37%
Singles /BIP	24.07%	÷1.000	×0.820	×0.970	×1.008	19.30%
Doubles /BIP	10.49%	÷1.000	×0.720	×0.970	×1.008	7.39%
Triples /BIP	1.85%	÷1.000	×0.720	×0.970	×1.008	1.30%
Home runs /BIP	2.47%	÷1.000	×0.780	—	×1.008	1.94%

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 19 vs a level average of 19.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.970.

Result: wOBA .366 → .251; ISO .157 → .106; BABIP .373 → .285. 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 NYY Yankees · 191 PAwOBA .455 → .289 (−166)K% 22.5% → 27.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.51%	÷0.988	×1.220	—	—	27.80%
BB% (unintentional) /PA	20.94%	÷1.066	×0.700	—	×1.008	13.86%
HBP% /PA	2.62%	—	×0.700	—	×1.008	1.85%
Singles /BIP	28.00%	÷1.113	×0.680	×1.002	×1.008	17.27%
Doubles /BIP	12.00%	÷1.069	×0.600	×1.002	×1.008	6.80%
Triples /BIP	3.00%	÷0.943	×0.600	×1.002	×1.008	1.93%
Home runs /BIP	5.00%	÷1.093	×0.470	—	×1.008	2.17%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 119, 1B 123, 2B 114, 3B 89, K 98, BB 113 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.002.

Result: wOBA .455 → .289; ISO .231 → .129; BABIP .439 → .258. 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 NYY Yankees · 186 PAwOBA .279 → .193 (−87)K% 23.1% → 28.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.12%	÷1.003	×1.220	—	—	28.11%
BB% (unintentional) /PA	12.37%	÷1.003	×0.700	—	×1.022	8.82%
HBP% /PA	4.84%	—	×0.700	—	×1.022	3.46%
Singles /BIP	20.00%	÷1.015	×0.680	×1.015	×1.022	13.90%
Doubles /BIP	7.27%	÷1.021	×0.600	×1.015	×1.022	4.44%
Triples /BIP	0.00%	÷1.000	×0.600	×1.015	×1.022	0.00%
Home runs /BIP	0.00%	÷0.952	×0.470	—	×1.022	0.00%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 90, 1B 103, 2B 104, 3B 100, K 101, BB 101 — applied at half strength. Age: age 17 vs a level average of 18.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.015.

Result: wOBA .279 → .193; ISO .052 → .032; BABIP .270 → .182. 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
#1Brad Millerlast yr '23 career totals — 11 seasons, 3,531 PA	5.3	3,531	123	43	236	314	416	+7	-38	8.8	9.4
/162	664	23	8	+1.4	-7.2	1.7	pk7: 10
#2Trevor Plouffelast yr '17 career totals — 7 seasons, 3,178 PA	4.8	3,178	103	12	243	306	411	+14	-18	8.4	8.4
/162	664	22	3	+2.8	-3.8	1.8	pk7: 8
#3Ed Sprague'91-'01 * career totals — 11 seasons, 4,587 PA	6.9	4,587	152	6	235*	304*	408*	+4	-62	4.1	5.3
/162	664	22	1	+0.6	-9.0	0.6	pk7: 7
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	3.5	2,316	67	24	226	296	377	+8	-24	4.4	4.2
/162	664	19	7	+2.4	-6.9	1.3	pk7: 4
#4Daniel Descalsolast yr '19 career totals — 9 seasons, 2,856 PA	4.3	2,856	48	25	235	320	363	+16	-36	3.5	4.0
/162	664	11	6	+3.8	-8.3	0.8	pk7: 4
#5Dale Sveum'86-'99 * career totals — 10 seasons, 2,810 PA	4.2	2,810	69	10	232*	295*	389*	+14	-23	1.4	2.4
/162	664	16	2	+3.4	-5.4	0.3	pk7: 4
#6Andujar Cedeno'90-'96 * career totals — 6 seasons, 2,233 PA	3.4	2,233	47	26	228*	284*	371*	+24	-20	1.3	1.3
/162	664	14	8	+7.1	-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
Richard Matic (OGILVIE)	20	—	—	—	—	204/278/308	103	274	2	2	27%	8%	68	-0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Agustín Ramírez 2022 · A	20	36→46	43→55	43→55	40	184/244/295	111	273	10	4	35%	7%	51	-2.2	225/286/365	140	284	15	12	25%	7%	84	+0.1	236/301/405	169	279	19	20	22%	7%	97	+1.1
●Esmerlyn Valdez 2023 · A	19	40→44	42→60	44→30	44	195/277/301	106	276	10	5	31%	8%	66	-1.1	199/274/334	135	301	16	4	37%	8%	73	-0.6	207/300/402	195	286	26	2	35%	10%	96	+0.8
✕Tyler Nevin 2017 · A	20	44→54	38→50	40→45	45	209/276/295	86	290	5	6	28%	8%	63	-1.3	239/291/345	106	307	9	7	24%	6%	80	-0.2	240/319/380	139	292	16	4	22%	8%	98	+0.8
✕Jesús Báez 2024 · A	19	35→41	40→55	45	46	177/246/265	88	234	7	9	27%	8%	46	-2.6	218/275/368	150	257	19	8	23%	6%	80	-0.1	226/279/407	181	249	27	8	22%	6%	89	+0.4
✕Kyle Higashioka 2011 · A	21	41→43	42→60	41→45	44	201/257/300	99	250	9	3	23%	6%	57	-1.8	198/245/316	118	243	13	4	24%	5%	57	-1.8	230/276/419	189	272	26	4	26%	6%	93	+0.4
✕Eddys Leonard 2021 · A	20	42→47	39→50	45→50	45	198/273/287	89	286	6	8	31%	8%	61	-1.5	229/297/377	148	305	16	5	29%	7%	91	+0.6	227/295/375	148	296	16	4	28%	6%	86	+0.3
✕Ramon Mendoza 2021 · A	20	45→51	38→45	40→45	45	210/282/297	87	291	5	4	28%	7%	66	-1.1	196/268/274	78	282	4	5	29%	8%	56	-1.9	232/310/341	109	301	10	3	24%	9%	83	+0.1
✕Eric Wood 2013 · A	20	44→50	43→55	42→45	43	217/276/330	113	284	10	6	27%	6%	72	-0.7	217/266/304	87	308	5	4	29%	6%	61	-1.5	212/274/375	163	269	18	7	28%	7%	79	-0.1
●Austin Dean 2014 · A	20	41→51	40→55	45	46	197/272/291	94	271	7	6	28%	8%	61	-1.5	236/283/332	96	298	7	6	22%	6%	74	-0.6	262/308/421	159	310	17	4	21%	5%	101	+1.0
●Jose Miranda 2018 · A	20	41→51	44→50	41→40	44	209/256/322	113	236	13	5	19%	5%	62	-1.4	223/268/331	108	255	10	2	17%	4%	68	-1.0	268/319/410	142	303	17	2	17%	5%	105	+1.4
●Daniel Robertson 2014 · A	20	47→57	43→45	37→40	45	231/292/342	111	292	10	3	24%	7%	80	-0.1	252/320/366	114	316	9	3	22%	7%	96	+1.0	256/329/366	110	321	8	2	21%	8%	96	+0.9
✕Raudy Read 2015 · A	21	40→46	39→55	39→45	43	195/238/278	83	227	7	5	18%	4%	45	-2.7	216/257/326	110	260	10	5	21%	5%	63	-1.4	233/285/428	196	272	25	1	25%	6%	97	+0.5
✕Jhostynxon Garcia 2023 · A	20	36→44	40→50	47→50	46	175/264/271	96	263	7	8	34%	10%	55	-2.0	204/267/339	135	290	14	10	33%	7%	70	-0.8	226/279/379	153	297	20	9	30%	5%	81	-0.0
✕Deivy Grullón 2017 · A	21	44→45	42→55	38→30	37	215/257/318	103	300	10	2	31%	5%	61	-1.5	233/271/374	141	313	17	2	30%	5%	80	-0.2	236/277/397	161	310	22	0	31%	5%	85	+0.2
✕Yu Chang 2016 · A	20	41→47	42→50	45	38	205/254/311	106	279	10	6	30%	5%	59	-1.7	206/263/350	144	289	15	8	33%	6%	72	-0.7	217/278/367	150	284	17	4	29%	7%	81	-0.0
✕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
✕Jacob Reimer 2024 · A	20	46→49	40→45	44→50	50	217/316/303	86	302	8	5	28%	10%	82	-0.0	226/307/346	120	303	11	9	27%	9%	87	+0.4	226/302/377	150	302	15	14	28%	8%	90	+0.5
✕Andy Paz 2014 · A	21	43	37→40	42→45	48	204/268/278	75	258	5	5	22%	8%	56	-1.9	201/260/271	70	280	4	5	28%	7%	51	-2.2	218/269/266	48	284	3	6	23%	7%	50	-0.7
✕Jhonkensy Noel 2021 · A	20	40→42	43→55	47→45	42	202/266/309	107	265	11	7	28%	6%	63	-1.3	222/273/394	172	288	23	5	31%	5%	86	+0.3	200/264/382	182	250	25	1	31%	6%	78	-0.3
●Cheslor Cuthbert 2013 · A	20	44→54	42→50	45	42	220/265/318	98	276	10	5	24%	6%	64	-1.3	227/272/334	107	279	10	7	21%	6%	70	-0.8	255/309/403	148	298	17	1	20%	7%	101	+0.7

Richard Matic

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps