Mairoshendrick Martinus

Mairoshendrick MartinusSS Ontario Tower Buzzers

Age 21 R/R 6'1" / 161 lbs A HR +8%BB -8% Svc 0.0 · Ctrl thru 2036

2026 ROS PROJECTION539 act + 10 ros · stats below = ROS only

showingROS

wRC+†71

AVG/OBP/SLG.100 / .100 / .100

PA10

HR0

K%30

BB%5

BABIP297

ISO109

MLB%0%

Value2026 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$24M ctrl surplus

Tools · ContractCON 35 / POW 30

Toolsscout grade

CONTACT35

scouting grade only

POWER30

scouting grade only

EYE35

scouting grade only

SPEED50

scouting grade only

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

Status MiLB

MLB Debut 2031

Service 0 yrs (est)

Team Control Through 2036

First FA Year 2037

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2031
2027	MiLB	still in minors · estimated debut 2031
2028	MiLB	still in minors · estimated debut 2031
2029	MiLB	still in minors · estimated debut 2031
2030	MiLB	still in minors · estimated debut 2031
2031	Pre-Arb	$0.9M	+0.7	$2M	+$1M
2032	Pre-Arb	$0.9M	+0.7	$2M	+$1M
2033	Pre-Arb	$1.0M	+0.6	$1M	+$1.0M
2034	Arb-1	$3M	+0.5	$1M	+$0.0M (cut)
2035	Arb-2	$4M	+0.4	$0.8M	+$0.0M (cut)
2036	Arb-3	$3M	+0.2	$0.4M	+$0.0M (cut)
Totals		$3M		$7M	+$4M

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)
2022	17	ROK	DSL LAD Bautista	—	211	182	48	6	5	7	19	47	4	10	5	264	346	467	813	203	306	22	9	349	122	+6	+0	—	—	+5	1.0
2023	18	ROK	ACL Dodgers	—	170	154	36	6	1	3	13	65	1	10	1	234	298	344	642	110	375	38	8	288	81	-4	+2	—	—	+4	0.1
2024	19	ROK	ACL Dodgers	—	190	166	35	5	2	6	14	69	3	9	1	211	284	373	658	163	296	36	7	284	79	-5	+1	—	—	+4	0.1
2025	20	A+	Great Lakes Loons	—	26	22	6	0	1	0	4	5	0	1	2	273	385	364	748	91	353	19	15	343	119	+1	-1	—	—	+1	0.1
2025	20	A	Rancho Cucamonga Quakes	—	394	348	85	17	1	6	35	106	4	19	4	244	320	351	671	106	325	27	9	301	90	-5	+2	—	—	+9	0.6
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2022	17	ROK MLE	DSL LAD Bautista	—	211	189	36	4	4	5	12	66	4	10	5	190	254	333	587	143	237	31	6	255	59	-10	+0	—	—	+5	-0.6
2023	18	ROK MLE	ACL Dodgers	—	170	159	23	3	1	2	8	93	1	10	1	145	190	214	404	69	308	55	5	177	6	-19	+2	—	—	+4	-1.4
2024	19	ROK MLE	ACL Dodgers	—	190	172	22	3	1	4	8	101	3	9	1	128	180	227	407	99	216	53	4	178	7	-21	+1	—	—	+4	-1.6
2025	20	A+ MLE	Great Lakes Loons	—	26	23	5	0	1	0	3	7	0	1	2	217	308	304	612	87	310	27	12	263	64	-1	-1	—	—	+1	-0.1
2025	20	A MLE	Rancho Cucamonga Quakes	—	394	358	67	12	1	5	25	144	4	19	4	187	248	268	516	81	276	37	6	228	40	-28	+2	—	—	+9	-1.8
2022	17	ROK MLE	DSL LAD Bautista	—	211	189	36	4	4	5	12	66	4	10	5	190	254	333	587	143	250	31	6	255	59	—	—	—	—	—	—
2022	17	ROK RAW	DSL LAD Bautista	—	211	182	48	6	5	7	19	47	4	10	5	264	346	467	813	203	306	22	9	349	59	—	—	—	—	—	—
2023	18	ROK MLE	ACL Dodgers	—	170	159	23	3	1	2	8	93	1	10	1	145	190	214	404	69	318	55	5	177	6	—	—	—	—	—	—
2023	18	ROK RAW	ACL Dodgers	—	170	154	36	6	1	3	13	65	1	10	1	234	298	344	642	110	375	38	8	288	6	—	—	—	—	—	—
2024	19	ROK MLE	ACL Dodgers	—	190	172	22	3	1	4	8	101	3	9	1	128	180	227	407	99	243	53	4	178	7	—	—	—	—	—	—
2024	19	ROK RAW	ACL Dodgers	—	190	166	35	5	2	6	14	69	3	9	1	211	284	373	658	163	296	36	7	284	7	—	—	—	—	—	—
2025	20	A MLE	2 teams	—	420	381	72	12	1	5	28	151	4	20	6	189	252	265	517	76	289	36	7	230	42	—	—	—	—	—	—
2025	20	A RAW	2 teams	—	420	370	91	17	2	6	39	111	4	20	6	246	324	351	676	105	327	26	9	303	42	—	—	—	—	—	—
2022	17	ROK MLE	DSL LAD Bautista	—	211	193	36	4	4	5	12	66	4	10	5	187	254	326	580	140	237	31	6	255	59	—	—	—	—	—	—
2023	18	ROK MLE	ACL Dodgers	—	170	159	23	3	1	2	8	93	1	10	1	145	190	214	404	69	308	55	5	177	6	—	—	—	—	—	—
2024	19	ROK MLE	ACL Dodgers	—	190	177	22	3	1	4	8	101	3	9	1	124	180	220	401	96	216	53	4	178	7	—	—	—	—	—	—
2025	20	A MLE	2 teams	—	420	385	72	12	1	5	28	151	4	20	6	187	252	262	514	75	278	36	7	230	42	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons + 2026 so far)
2023	18	ROK MLE	ACL Dodgers	—	170	159	23	3	1	2	8	93	1	10	1	145	190	214	404	69	308	55	5	177	6	—	—	—	—	—	—
2024	19	ROK MLE	ACL Dodgers	—	190	177	22	3	1	4	8	101	3	9	1	124	180	220	401	96	216	53	4	178	7	—	—	—	—	—	—
2025	20	A MLE	2 teams	—	420	385	72	12	1	5	28	151	4	20	6	187	252	262	514	75	278	36	7	230	42	—	—	—	—	—	—
YTD	21	A MLE	LAD	—	539	513	124	21	6	17	16	168	7	32	9	242	274	405	680	164	323	31	3	290	83	-11	+3	+0	+6	+12	0.9
▸ 2026 season
YTD	21	A RAW	LAD	—	421	391	124	25	8	15	20	91	7	30	5	317	361	537	898	220	378	22	5	390	83	—	—	—	—	—	—
YTD	21	A+ RAW	LAD	—	118	115	31	3	1	6	3	34	0	2	4	270	288	470	758	200	333	29	3	331	83	—	—	—	—	—	—
ROS	21	A MLE	LAD	0%	10	10	1	0	0	0	0	3	0	0	0	100	100	100	200		303	30	0	274	71	-0	+0	+0	+0	+0	-0.0
TOT	21	A MLE	LAD	—	549	523	125	21	6	17	16	171	7	32	9	239	271	400	671	161	320	31	3	290	82	-12	+3	+0	+6	+12	0.9
▸ Career projection (2027+) — MLB context, MLB playing time (PA × MLB%)
2027	22	MLB MLE	LAD	34%	501	470	105	18	4	14	21	157	5	15	4	223	264	368	632	145	301	31	4	278	74	-15	+1	+0	+5	+11	0.2
2028	23	MLB MLE	LAD	48%	545	509	117	20	5	16	25	165	6	15	4	230	274	383	657	153	301	30	5	287	80	-13	+1	+0	+6	+12	0.6
2029	24	MLB MLE	LAD	53%	572	533	123	21	5	17	28	169	6	15	4	231	277	385	662	154	301	30	5	293	84	-11	+1	+0	+6	+12	0.9
2030	25	MLB MLE	LAD	55%	588	547	127	22	5	18	30	172	6	15	4	232	280	389	669	157	301	29	5	296	86	-10	+1	+0	+6	+13	1.1
2031	26	MLB MLE	LAD	56%	595	553	129	22	5	19	31	174	6	15	4	233	281	394	676	161	301	29	5	297	87	-9	+1	+0	+6	+13	1.2
2032	27	MLB MLE	LAD	55%	595	552	129	22	5	19	32	174	6	15	4	234	283	395	678	161	301	29	5	297	87	-9	+1	+0	+6	+13	1.2
2033	28	MLB MLE	LAD	55%	590	547	127	22	5	18	32	173	6	13	4	232	282	389	671	157	300	29	5	296	87	-9	+1	-1	+6	+13	1.0
2034	29	MLB MLE	LAD	58%	580	537	124	21	5	18	32	172	6	12	3	231	282	389	671	158	300	30	6	294	85	-10	+1	-1	+6	+13	0.9
2035	30	MLB MLE	LAD	60%	569	527	119	20	4	17	31	170	6	11	3	226	277	376	652	150	299	30	5	292	84	-11	+1	-2	+6	+12	0.6
2036	31	MLB MLE	LAD	62%	555	513	116	20	4	16	31	167	6	9	3	226	278	374	652	148	297	30	6	288	81	-13	+1	-3	+6	+12	0.3
2037	32	MLB MLE	LAD	63%	536	497	109	18	4	15	29	164	5	8	2	219	269	362	631	143	294	31	5	283	77	-14	+1	-4	+6	+12	0.0
2038	33	MLB MLE	LAD	63%	506	469	102	16	4	14	27	157	5	6	2	217	267	358	626	141	290	31	5	276	73	-16	+0	-4	+5	+11	-0.4
2027	22	MLB CTX	LAD	34%	172	161	36	6	1	5	7	54	2	5	1	224	265	366	631	143	296	31	4	268	74	-5	+1	+0	+2	+4	0.1
2028	23	MLB CTX	LAD	48%	264	247	55	9	2	8	12	80	3	7	2	223	267	372	640	150	296	30	5	277	80	-6	+1	+0	+3	+6	0.3
2029	24	MLB CTX	LAD	53%	302	281	65	11	2	10	15	89	3	8	2	231	278	391	669	160	296	29	5	283	84	-6	+1	+0	+3	+7	0.5
2030	25	MLB CTX	LAD	55%	322	299	69	12	2	10	17	94	3	8	2	231	279	385	664	154	296	29	5	287	86	-5	+1	+0	+3	+7	0.6
2031	26	MLB CTX	LAD	56%	331	308	71	12	2	11	17	97	3	8	2	231	277	390	667	159	296	29	5	288	87	-5	+1	+0	+4	+7	0.7
2032	27	MLB CTX	LAD	55%	327	303	70	12	2	11	18	96	3	8	2	231	281	393	674	162	296	29	6	288	87	-5	+1	+0	+4	+7	0.7
2033	28	MLB CTX	LAD	55%	322	298	69	12	2	11	18	95	3	7	2	232	282	396	678	164	295	30	6	287	87	-5	+1	-0	+3	+7	0.6
2034	29	MLB CTX	LAD	58%	336	312	71	12	2	11	18	99	3	7	2	228	276	385	661	157	295	29	5	285	85	-6	+1	-1	+4	+7	0.5
2035	30	MLB CTX	LAD	60%	342	316	72	12	2	11	19	102	4	6	2	228	280	383	663	155	294	30	6	283	84	-7	+0	-1	+4	+7	0.4
2036	31	MLB CTX	LAD	62%	342	317	71	12	2	11	19	103	3	6	2	224	274	379	653	155	292	30	6	279	81	-8	+0	-2	+4	+7	0.2
2037	32	MLB CTX	LAD	63%	336	312	68	11	2	10	18	103	3	5	1	218	267	362	629	144	289	31	5	274	77	-9	+1	-2	+4	+7	0.0
2038	33	MLB CTX	LAD	63%	321	298	64	10	2	9	17	100	3	4	1	215	264	352	616	138	285	31	5	267	73	-10	+0	-3	+3	+7	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3717	3452	781	131	23	118	195	1112	36	79	21	226	275	380	655	154	295	30	5	281	76	-77	+7	-9	+40	+81	4.2
/ 162G	—	A+C		—	650	604	137	23	4	21	34	194	6	14	4	227	275	382	657	156	295	30	5	281	76	-13	+1	-2	+7	+14	0.7
Career	—	MLE		—	7733	7165	1581	264	62	217	405	2428	81	198	54	221	270	366	636	145	298	31	5	281	76	-141	+13	-15	+72	+146	7.8
/ 162G	—	MLE		—	650	602	132	22	5	18	34	204	7	17	5	219	269	362	631	143	296	31	5	281	76	-14	+1	-1	+7	+14	0.7

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Miguel Olivolast yr '13 career totals — 11 seasons, 3,947 PA	5.9	3,947	144	53	241	275	417	+70	+53	19.1	18.9
/162	664	24	9	+11.9	+8.8	3.2	pk7: 19
#2Rod Barajaslast yr '12 career totals — 12 seasons, 3,753 PA	5.7	3,753	134	2	235	284	407	+60	+30	15.8	16.0
/162	664	24	0	+10.7	+5.3	2.8	pk7: 16
#3Rougned Odorlast yr '23 career totals — 10 seasons, 4,424 PA	6.7	4,424	178	70	230	288	422	+16	+32	15.2	15.0
/162	664	27	11	+2.4	+4.9	2.3	pk7: 15
#4Bobby Crosbylast yr '10 career totals — 7 seasons, 2,832 PA	4.3	2,832	62	34	238	305	374	+28	+33	11.6	11.6
/162	664	15	8	+6.7	+7.7	2.7	pk7: 12
#5Danny 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
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 8 projected seasons	6.1	4,038	118	89	226	272	376	+43	+24	6.6	6.0
/162	664	19	15	+7.1	+3.9	1.1	pk7: 6
#6J.P. Arencibialast yr '15 career totals — 5 seasons, 1,650 PA	2.5	1,650	78	2	213	260	414	+29	-4	4.2	4.2
/162	664	31	1	+11.9	-1.7	1.7	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
Mairoshendrick Martinus (OGILVIE)	21	35	30	50	35	219/258/357	138	303	8	15	32%	4%	71	-0.4	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Tucker Mitchell 2022 · A	21	42	40→45	51→45	39	201/262/293	92	296	7	7	33%	6%	57	-1.8	195/269/306	111	299	13	8	37%	7%	65	-1.2	180/257/292	111	259	15	7	35%	7%	55	-0.8
✕Imbewer Alvarez 2007 · A	21	41	39→40	45→55	37	197/251/289	92	304	6	8	36%	6%	53	-2.1	211/275/294	83	302	6	15	30%	6%	63	-1.4	216/288/295	79	292	7	22	26%	7%	65	-0.4
✕Pedruin Bautista 2006 · A	22	39	38→40	50→60	33	192/225/272	80	283	4	10	33%	4%	38	-3.2	197/277/272	75	275	3	17	27%	8%	59	-1.7	190/288/262	72	257	2	25	24%	10%	60	-0.6
✕Cutter Dykstra 2010 · A	21	40→50	40	47→55	43	198/260/282	84	275	8	11	30%	7%	54	-2.0	222/279/297	75	309	6	16	28%	6%	65	-1.2	239/307/326	86	317	6	16	24%	8%	79	-0.1
✕Corey Joyce 2021 · A	22	44	40	50	39	211/267/307	95	311	8	8	33%	6%	63	-1.4	201/290/309	108	293	11	12	33%	9%	74	-0.6	213/316/315	101	301	9	14	29%	10%	81	-0.0
✕Jose Cordoba 2023 · A	20	38	42→40	44→55	39	190/253/289	99	277	10	9	34%	6%	54	-2.0	206/263/300	94	283	6	11	28%	6%	59	-1.6	204/262/298	94	272	5	15	25%	6%	56	-0.8
✕James Harris 2015 · A	21	39→49	41→40	48→50	39	196/247/289	93	281	9	12	33%	6%	51	-2.3	222/283/313	91	316	7	13	30%	7%	70	-0.9	231/296/319	89	325	6	15	29%	8%	73	-0.5
✕Jorge Alcantara 2013 · A	21	42	41→45	50	43	201/271/299	98	298	8	11	33%	8%	63	-1.4	193/263/287	94	294	6	14	34%	8%	57	-1.8	147/226/244	97	221	6	25	34%	8%	33	-1.0
✕Ramon Soto 2009 · AAA	21	45	42→30	51→45	45	221/282/322	102	282	10	12	25%	7%	72	-0.7	234/281/300	66	286	5	8	19%	5%	65	-1.2	271/316/324	52	332	1	7	18%	5%	80	-0.1
✕Adrian Abreu 2012 · A	21	39	38→40	47→55	47	190/263/273	82	247	5	9	24%	8%	53	-2.1	212/292/300	88	256	8	17	19%	9%	71	-0.8	209/299/290	80	241	9	25	16%	10%	70	-0.3
✕Glenn Santiago 2023 · A	22	41	41→40	46→45	39	201/255/297	96	286	8	8	32%	6%	55	-1.9	198/263/285	87	291	7	9	32%	7%	57	-1.8	182/254/257	75	267	7	8	32%	8%	46	-1.1
✕Rafael Morel 2022 · A	20	38	40	51→50	39	187/249/281	94	269	8	13	32%	6%	51	-2.3	196/261/274	78	315	7	10	37%	7%	53	-2.1	188/258/263	75	295	9	10	37%	7%	47	-1.2
✕Kyle Nevin 2023 · A	21	41→38	40	52→50	39	198/250/294	96	274	6	10	29%	5%	53	-2.1	216/274/318	102	332	9	10	35%	7%	68	-1.0	210/271/306	96	328	9	12	36%	7%	61	-0.9
✕Rudy van Heydoorn 2010 · A	21	33	41→45	40→50	41	166/249/256	90	260	9	8	37%	8%	46	-2.6	199/274/309	110	312	10	5	36%	8%	67	-1.1	204/303/338	134	292	14	2	32%	11%	85	+0.1
✕Aaron McKeithan 2022 · A	22	41	38→40	49→40	40	195/262/275	80	276	6	7	30%	6%	54	-2.0	219/298/304	85	284	8	4	24%	7%	74	-0.5	216/302/271	55	271	5	1	21%	8%	67	-0.3
✕Ivan Jimenez 2015 · AAA	22	44	43→40	51→55	38	214/262/328	114	314	11	11	34%	6%	65	-1.2	241/290/330	89	318	6	13	25%	6%	76	-0.4	266/330/343	77	341	2	18	21%	7%	89	+0.2
✕Steven Baron 2012 · A	21	34	39→45	45→50	36	172/216/255	83	252	7	7	34%	5%	31	-3.7	189/226/284	95	266	6	9	30%	4%	41	-3.0	237/293/310	73	315	4	8	24%	7%	69	-0.4
✕Gorge Munoz 2017 · A	21	43	38→40	50→55	42	205/260/282	78	258	5	17	22%	5%	54	-2.0	206/257/291	85	297	7	10	31%	5%	55	-1.9	189/234/268	78	291	9	9	37%	3%	38	-0.8
✕Samad Taylor 2019 · A	21	38→48	41→45	54→65	45	190/253/296	106	249	8	22	26%	7%	55	-1.9	192/267/308	116	292	10	25	35%	8%	63	-1.3	235/311/365	130	323	13	46	29%	9%	92	+0.4
✕Braulio Vasquez 2019 · A	20	43	38→40	47→65	40	207/259/281	74	295	5	11	30%	6%	53	-2.1	191/260/268	77	304	6	15	36%	7%	51	-2.2	188/266/266	78	286	5	32	33%	7%	52	-0.9

Career Stats + Projections

Career Comps

Career Path Comps