Dylan Leach — OGILVIE

Dylan LeachC Sydney Blue Sox

Age 23 S/R 5'11" / 205 lbs INTL Svc 0.0 · Ctrl thru 2036

2026 FULL-SEASON PROJECTIONpark-neutral Marcel · 60 proj PA

wRC+†48

AVG/OBP/SLG.191 / .257 / .260

PA5

HR0

K%33

BB%8

ISO69

MLB%0%

Value2026 · WAR

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

Tools · Contract

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	—	—	—
2032	Pre-Arb	$0.9M	—	—	—
2033	Ext	beyond projection horizon · no WAR estimate
2034	Ext	beyond projection horizon · no WAR estimate
2035	Ext	beyond projection horizon · no WAR estimate
2036	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$-0.8M	+$0.0M

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. Catcher framing: only 2026 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 below FG-DC by 1-3 WAR.

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	22	ROK	FCL Blue Jays	—	58	49	8	2	0	0	8	15	0	0	0	163	281	204	485	41	229	26	14	234	45	-4	+0	—	—	+1	-0.3
2025	22	INTL	Sydney Blue Sox	—	131	105	23	8	1	3	21	21	1	1	1	219	354	400	754	181	235	16	16	332	111	+2	-0	—	—	+3	0.4
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2025	22	ROK MLE	FCL Blue Jays	—	58	52	5	1	0	0	5	22	0	0	0	96	175	115	291	19	178	38	9	158	-7	-7	+0	—	—	+1	-0.6
2025	22	INTL MLE	2 teams	—	189	167	19	5	0	0	16	70	1	1	1	114	196	144	339	30	186	37	8	158	-7	—	—	—	—	—	—
2025	22	INTL RAW	2 teams	—	189	154	31	10	1	3	29	36	1	1	1	201	332	338	669	136	233	19	15	302	-7	—	—	—	—	—	—
2025	22	INTL MLE	2 teams	—	189	170	19	5	0	0	16	70	1	1	1	112	196	141	337	29	178	37	8	158	-7	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons + 2026 so far)
2025	22	INTL MLE	2 teams	—	189	170	19	5	0	0	16	70	1	1	1	112	196	141	337	29	178	37	8	158	-7	—	—	—	—	—	—
▸ 2026 season
2026	23	MLB MLE	TOR	0%	5	5	1	0	0	0	0	2	0	0	0	200	200	200	400		290	40	0	240	48	-0	+0	+0	+0	+0	-0.1
▸ Career projection (2027+) — MLB context, MLB playing time (PA × MLB%)
2027	24	MLB MLE	TOR	30%	133	121	25	5	1	1	10	42	1	1	0	207	273	289	562	83	291	32	8	250	55	-7	+0	+0	+2	+3	-0.2
2028	25	MLB MLE	TOR	44%	242	219	44	8	1	3	19	75	2	2	1	201	271	288	559	87	292	31	8	257	60	-12	+0	+0	+4	+5	-0.2
2029	26	MLB MLE	TOR	51%	319	289	59	11	2	4	25	98	2	3	1	204	272	298	570	93	291	31	8	261	63	-14	+0	+0	+6	+7	-0.1
2030	27	MLB MLE	TOR	52%	362	327	68	13	2	5	29	110	3	3	1	208	279	306	584	98	291	30	8	262	64	-16	+0	+0	+6	+8	-0.1
2031	28	MLB MLE	TOR	53%	387	350	72	14	2	5	31	118	3	3	1	206	276	300	576	94	291	30	8	261	63	-17	+0	-1	+7	+8	-0.2
2032	29	MLB MLE	TOR	53%	395	357	73	14	2	5	32	122	3	3	1	204	276	297	572	92	290	31	8	259	62	-18	+0	-1	+7	+9	-0.4
2027	24	MLB CTX	TOR	30%	40	37	6	1	0	0	3	13	0	0	0	162	225	189	414	27	293	32	8	246	55	-2	+0	+0	+1	+1	-0.1
2028	25	MLB CTX	TOR	44%	107	97	20	4	1	1	8	33	1	1	0	206	274	299	573	93	293	31	7	253	60	-5	+0	+0	+2	+2	-0.1
2029	26	MLB CTX	TOR	51%	162	147	31	6	1	2	13	50	1	1	1	211	280	306	586	95	293	31	8	256	63	-7	-0	+0	+3	+4	-0.1
2030	27	MLB CTX	TOR	52%	190	172	36	7	1	3	15	58	1	2	1	209	277	314	591	105	293	31	8	258	64	-8	+0	+0	+3	+4	-0.1
2031	28	MLB CTX	TOR	53%	206	186	38	7	1	3	17	63	1	2	1	204	275	301	576	97	292	31	8	257	63	-9	+0	-0	+4	+4	-0.1
2032	29	MLB CTX	TOR	53%	208	188	39	7	1	3	17	64	1	1	1	207	277	303	580	96	291	31	8	255	62	-9	-0	-1	+4	+5	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	913	827	170	32	5	12	73	281	5	7	4	206	274	300	574	94	293	31	8	256	55	-41	-0	-1	+16	+20	-0.7
/ 162G	—	A+C		—	650	589	122	23	4	9	52	200	4	5	3	207	276	306	582	98	294	31	8	256	55	-29	-0	-1	+12	+14	-0.5
Career	—	MLE		—	2032	1835	361	70	10	23	162	637	15	16	6	197	267	283	551	87	284	31	8	250	55	-84	+1	-2	+33	+40	-1.2
/ 162G	—	MLE		—	650	587	115	22	3	7	52	204	5	5	2	196	267	279	547	83	283	31	8	250	55	-30	+0	-1	+12	+14	-0.4

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Sandy 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
#2John McDonaldlast yr '14 career totals — 13 seasons, 2,596 PA	3.9	2,596	28	34	233	273	324	+20	+54	4.2	5.1
/162	664	7	9	+5.0	+13.9	1.1	pk7: 6
#3Adam Engellast yr '22 career totals — 6 seasons, 1,540 PA	2.3	1,540	30	47	225	280	350	+4	+33	4.1	4.1
/162	664	13	20	+1.8	+14.4	1.8	pk7: 4
#4Adam Rosaleslast yr '17 career totals — 9 seasons, 1,756 PA	2.6	1,756	47	16	227	293	367	+6	+8	3.0	3.5
/162	664	18	6	+2.4	+3.0	1.1	pk7: 4
#5Ryan Goinslast yr '19 career totals — 7 seasons, 1,680 PA	2.5	1,680	22	6	230	279	335	+9	+21	2.0	2.0
/162	664	9	2	+3.7	+8.5	0.8	pk7: 2
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 4 projected seasons	1.5	972	12	8	205	271	295	+17	+16	0.0	0.1
/162	664	8	5	+11.9	+10.9	0.0	pk7: 0
#6Alexi Amaristalast yr '17 career totals — 7 seasons, 1,901 PA	2.9	1,901	21	39	231	275	323	+14	-6	-1.1	-1.1
/162	664	7	14	+4.9	-2.1	-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
Dylan Leach (OGILVIE)	23	—	—	—	—	191/257/260	69	290	0	0	33%	8%	48	-0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Jobduan Morales 2014 · A	23	37	37→40	49→40	42	180/245/252	72	276	5	4	35%	8%	42	-2.9	199/259/286	87	302	7	5	34%	7%	55	-2.0	195/254/288	94	300	7	3	35%	7%	53	-1.0
✕Andy Yerzy 2021 · A	23	35	38→50	49→40	35	174/226/251	77	275	5	7	37%	5%	34	-3.5	188/272/333	145	263	18	6	34%	9%	72	-0.7	166/252/300	134	233	18	4	36%	9%	55	-1.0
✕Grayson Greiner 2016 · A	23	37	38→45	46→30	37	181/234/253	73	279	6	3	36%	6%	38	-3.2	211/265/312	101	293	9	3	29%	6%	63	-1.4	217/276/324	107	289	10	0	27%	7%	67	-0.6
✕Rey Bruguera 2015 · A	23	42	38→40	43→50	40	202/254/274	73	290	5	6	31%	6%	49	-2.4	192/257/261	69	297	5	5	34%	8%	49	-2.4	153/233/192	40	244	2	0	35%	9%	22	-1.8
✕Gerard Hall 2011 · A	23	41→39	37→40	49→50	44	196/256/272	76	277	4	12	29%	7%	50	-2.3	214/268/301	87	306	3	10	29%	7%	61	-1.5	225/275/316	91	323	0	8	28%	6%	64	-0.7
✕Taylor Gushue 2017 · A	23	39	41→45	44→30	39	194/238/290	96	255	8	3	27%	5%	47	-2.5	193/245/311	118	262	14	2	31%	6%	56	-1.9	199/260/327	128	276	15	0	32%	7%	64	-0.6
✕Alex Hall 2022 · A	23	41	40→45	46→40	36	195/245/288	93	313	6	6	38%	6%	50	-2.3	178/244/281	103	300	10	4	41%	7%	49	-2.4	146/220/247	101	233	12	1	41%	8%	30	-1.5
✕Alejandro Torres 2012 · A	23	37	37→40	46→40	35	182/219/253	71	267	5	5	33%	4%	31	-3.7	206/261/282	76	313	5	6	33%	6%	54	-2.0	206/271/236	30	326	0	0	34%	7%	47	-0.4
✕Chris Hess 2018 · A	23	39→34	37→45	48→30	39	187/246/269	82	279	3	5	32%	6%	46	-2.6	191/250/294	103	282	9	4	34%	5%	54	-2.0	178/238/288	110	257	11	1	34%	4%	47	-2.0
✕Ben Gobbel 2023 · A	23	42→41	36→45	47→50	41	197/257/265	68	280	4	7	30%	6%	49	-2.4	211/269/323	112	288	12	13	30%	6%	68	-1.0	212/261/335	123	271	15	11	27%	4%	64	-0.9
✕Nash Knight 2016 · A	23	40→48	38→40	46→40	46	190/265/264	74	283	6	5	33%	9%	53	-2.1	224/289/308	84	302	6	4	26%	8%	71	-0.8	223/289/297	75	292	5	2	24%	7%	66	-0.6
✕Raymel Flores 2018 · AA	23	41	36→45	46→50	37	194/246/262	68	296	4	11	34%	6%	44	-2.8	192/244/263	71	291	4	11	33%	6%	43	-2.8	149/197/187	38	232	0	13	34%	5%	5	-1.7
✕Kevin Dubler 2010 · A	23	40	35→50	49→40	43	189/255/252	62	273	3	7	30%	7%	46	-2.6	197/262/290	93	245	8	5	22%	7%	57	-1.8	187/253/282	95	221	9	3	20%	7%	50	-0.8
✕Arturo De Freitas 2023 · A	22	35	39→45	45→40	34	174/222/255	81	277	7	4	39%	5%	34	-3.5	184/241/265	81	306	8	5	40%	6%	44	-2.8	141/191/216	75	260	9	0	47%	5%	11	-1.0
✕Franklin Navarro 2018 · A	23	43	38→40	45→40	41	209/252/286	77	281	5	4	27%	5%	51	-2.2	208/245/298	90	334	7	6	38%	5%	51	-2.2	179/191/250	71	313	7	0	45%	2%	17	-1.1
✕David Lyon 2013 · A	23	41	36→45	46→30	43	195/258/265	70	278	3	5	29%	7%	50	-2.3	177/236/286	109	293	10	3	40%	6%	47	-2.6	143/217/271	128	240	15	2	45%	8%	35	-1.3
✕Shane Zeile 2016 · A	23	40	38→50	48→40	41	192/245/272	80	264	5	4	28%	6%	46	-2.6	208/256/314	106	282	8	6	28%	5%	59	-1.6	202/246/338	136	263	9	3	26%	4%	60	-0.6
✕Jerome Pena 2012 · A	23	43→34	36→40	42→45	45	203/268/275	72	283	3	6	28%	7%	55	-1.9	200/257/285	85	301	6	8	33%	7%	53	-2.1	189/252/304	115	318	10	7	41%	7%	54	-0.7
✕Marcus Littlewood 2014 · A	22	41	40→45	48→45	47	195/269/292	97	281	7	4	31%	9%	61	-1.5	206/271/315	109	271	10	5	26%	8%	66	-1.1	204/271/311	107	262	9	4	25%	8%	63	-0.7
✕Shervyen Newton 2022 · A	23	38→32	40→45	43→40	32	169/232/256	87	345	8	5	50%	7%	38	-3.2	174/239/293	119	319	13	4	46%	7%	50	-2.3	157/223/277	121	275	14	2	46%	7%	38	-1.9

Career Stats + Projections

Career Comps

Career Path Comps