Michael Dattalo — OGILVIE

Michael Dattalo3B Peoria Chiefs

Age 22 R/R 6'0" / 204 lbs A+ HR -14%BB -5% Svc 0.0 · Ctrl thru 2035

2026 ROS PROJECTION348 act + 9 ros · stats below = ROS only

showingROS

wRC+†81

AVG/OBP/SLG.125 / .222 / .125

PA9

HR0

K%22

BB%11

BABIP309

ISO95

MLB%0%

Value2026 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$12M ctrl surplus

Tools · ContractCON 57 / POW 36

Toolsscout grade

CONTACT57

scouting grade only

POWER36

scouting grade only

EYE50

scouting grade only

SPEED50

scouting grade only

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
2026	MiLB	still in minors · estimated debut 2030
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	$0.9M	+0.4	$1M	+$0.6M
2031	Pre-Arb	$0.9M	+0.5	$1M	+$0.8M
2032	Pre-Arb	$0.9M	+0.4	$1M	+$0.5M
2033	Arb-1	$2M	+0.3	$0.7M	+$0.0M (cut)
2034	Arb-2	$2M	+0.2	$0.4M	+$0.0M (cut)
2035	Arb-3	$2M	+0.1	$0.2M	+$0.0M (cut)
Totals		$3M		$5M	+$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. 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)
2025	21	A	Palm Beach Cardinals	—	65	58	15	4	0	0	4	11	3	0	0	259	338	328	666	69	319	17	6	309	95	-0	+0	—	—	+1	0.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2025	21	A MLE	Palm Beach Cardinals	—	65	59	14	4	0	0	3	16	3	0	0	237	308	305	613	68	323	25	5	277	74	-2	+0	—	—	+1	-0.1
2025	21	A MLE	Palm Beach Cardinals	—	65	59	14	4	0	0	3	16	3	0	0	237	308	305	613	68	326	25	5	277	74	—	—	—	—	—	—
2025	21	A RAW	Palm Beach Cardinals	—	65	58	15	4	0	0	4	11	3	0	0	259	338	328	666	69	319	17	6	309	74	—	—	—	—	—	—
2025	21	A MLE	Palm Beach Cardinals	—	65	59	14	4	0	0	3	16	3	0	0	237	308	305	613	68	323	25	5	277	74	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons + 2026 so far)
2025	21	A MLE	Palm Beach Cardinals	—	65	59	14	4	0	0	3	16	3	0	0	237	308	305	613	68	323	25	5	277	74	—	—	—	—	—	—
YTD	22	A+ MLE	STL	—	348	313	80	14	1	2	23	73	9	4	1	256	325	326	651	70	324	21	7	290	82	-7	+0	+0	+1	+8	0.2
▸ 2026 season
YTD	22	ROK RAW	STL	—	15	15	4	0	1	1	0	3	0	0	0	267	267	600	867	333	273	20	0	367	82	—	—	—	—	—	—
YTD	22	A RAW	STL	—	136	114	42	9	0	1	18	14	3	3	0	368	467	474	940	105	410	10	13	422	82	—	—	—	—	—	—
YTD	22	A+ RAW	STL	—	197	175	41	6	0	1	14	36	6	1	1	234	313	286	599	51	286	18	7	278	82	—	—	—	—	—	—
ROS	22	A+ MLE	STL	0%	9	8	1	0	0	0	1	2	0	0	0	125	222	125	347		309	22	11	287	81	-0	+0	+0	+0	+0	0.0
TOT	22	A+ MLE	STL	—	357	321	81	14	1	2	24	75	9	4	1	252	322	321	643	69	320	21	7	290	82	-7	+0	+0	+1	+8	0.2
▸ Career projection (2027+) — MLB context, MLB playing time (PA × MLB%)
2027	23	MLB MLE	STL	35%	305	275	67	13	1	4	21	69	6	4	1	244	311	342	653	98	307	23	7	295	86	-5	+0	+0	+1	+7	0.3
2028	24	MLB MLE	STL	46%	387	350	86	16	2	6	27	87	7	5	1	246	312	354	667	109	307	22	7	301	90	-5	+1	+0	+1	+8	0.6
2029	25	MLB MLE	STL	52%	425	383	96	18	2	8	31	95	8	5	1	251	320	371	691	120	306	22	7	304	92	-4	+1	+0	+2	+9	0.8
2030	26	MLB MLE	STL	54%	448	405	100	19	2	8	32	100	8	5	1	247	315	363	678	116	306	22	7	306	93	-4	+1	+0	+2	+10	0.8
2031	27	MLB MLE	STL	54%	454	410	101	19	2	8	33	102	8	5	1	246	315	361	676	115	306	22	7	306	93	-4	+1	+0	+2	+10	0.9
2032	28	MLB MLE	STL	54%	454	409	101	19	2	8	34	102	8	5	1	247	317	362	679	115	305	22	7	305	92	-4	+1	-1	+2	+10	0.7
2033	29	MLB MLE	STL	53%	446	401	98	18	2	8	34	101	8	5	1	244	316	359	675	115	304	23	8	303	91	-5	+1	-1	+2	+10	0.6
2034	30	MLB MLE	STL	52%	438	394	96	18	1	8	33	101	8	4	1	244	315	355	670	112	303	23	8	300	89	-6	+0	-2	+2	+9	0.4
2035	31	MLB MLE	STL	52%	424	382	91	17	1	7	32	99	7	3	1	238	309	343	652	105	301	23	8	296	86	-7	+0	-3	+2	+9	0.1
2036	32	MLB MLE	STL	52%	406	366	85	15	1	6	30	96	7	3	1	232	303	328	631	96	298	24	7	290	82	-9	+0	-4	+1	+9	-0.2
2027	23	MLB CTX	STL	35%	105	95	22	4	0	1	7	24	2	1	0	232	298	305	603	74	307	23	7	280	86	-2	+0	+0	+0	+2	0.1
2028	24	MLB CTX	STL	46%	179	161	40	7	1	3	13	40	3	2	1	248	316	360	677	112	306	22	7	285	90	-2	+0	+0	+1	+4	0.2
2029	25	MLB CTX	STL	52%	220	198	49	9	1	4	16	49	4	3	1	247	317	364	680	116	306	22	7	289	92	-2	+0	+0	+1	+5	0.4
2030	26	MLB CTX	STL	54%	243	219	54	10	1	4	18	54	4	3	1	247	315	356	672	110	305	22	7	290	93	-2	+0	+0	+1	+5	0.4
2031	27	MLB CTX	STL	54%	246	222	54	10	1	4	18	55	4	3	1	243	311	351	663	108	305	22	7	290	93	-2	+0	+0	+1	+5	0.5
2032	28	MLB CTX	STL	54%	246	222	54	10	1	4	18	55	4	3	1	243	311	351	663	108	304	22	7	289	92	-2	+0	-0	+1	+5	0.4
2033	29	MLB CTX	STL	53%	237	213	52	10	1	4	18	54	4	2	1	244	315	357	672	113	304	23	8	287	91	-3	+0	-1	+1	+5	0.3
2034	30	MLB CTX	STL	52%	230	207	50	9	1	4	17	53	4	2	1	242	311	353	664	111	302	23	7	284	89	-3	+0	-1	+1	+5	0.2
2035	31	MLB CTX	STL	52%	221	198	47	9	1	3	17	51	4	2	0	237	311	338	649	101	300	23	8	280	86	-4	+0	-1	+1	+5	0.1
2036	32	MLB CTX	STL	52%	210	188	44	8	1	3	16	50	4	1	0	234	308	335	643	101	297	24	8	275	82	-4	+0	-2	+1	+5	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2137	1923	466	86	9	34	158	485	37	22	7	242	312	349	662	107	306	23	7	286	90	-26	+2	-5	+8	+46	2.5
/ 162G	—	A+C		—	650	585	142	26	3	10	48	148	11	7	2	243	312	349	661	106	307	23	7	286	90	-8	+0	-2	+2	+14	0.8
Career	—	MLE		—	4261	3842	936	176	16	71	311	970	78	44	10	244	313	353	666	110	307	23	7	301	90	-51	+5	-10	+15	+91	5.0
/ 162G	—	MLE		—	650	586	143	27	2	11	47	148	12	7	2	244	313	353	666	109	307	23	7	301	90	-8	+1	-2	+2	+14	0.8

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Logan Forsythelast yr '19 career totals — 9 seasons, 3,502 PA	5.3	3,502	70	42	246	327	370	+5	-11	8.6	9.2
/162	664	13	8	+0.9	-2.2	1.6	pk7: 10
#2Gordon Beckhamlast yr '19 career totals — 10 seasons, 3,764 PA	5.7	3,764	80	34	237	301	368	+13	+19	8.2	8.4
/162	664	14	6	+2.4	+3.4	1.4	pk7: 9
#3Casey McGeheelast yr '16 career totals — 7 seasons, 3,061 PA	4.6	3,061	67	7	258	318	386	+3	+7	8.3	8.3
/162	664	15	2	+0.7	+1.4	1.8	pk7: 8
#4Yolmer Sánchezlast yr '19 career totals — 6 seasons, 2,438 PA	3.7	2,438	31	30	244	299	357	+9	+26	5.4	5.4
/162	664	8	8	+2.4	+7.2	1.5	pk7: 5
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 5 projected seasons	3.2	2,138	37	22	245	311	356	+8	+2	4.2	3.9
/162	664	11	7	+2.4	+0.8	1.3	pk7: 4
#5Dustin Ackleylast yr '16 career totals — 6 seasons, 2,347 PA	3.5	2,347	46	31	241	304	367	-5	+7	3.8	3.8
/162	664	13	9	-1.3	+1.9	1.1	pk7: 4
#6Jason Phillipslast yr '07 career totals — 5 seasons, 1,508 PA	2.3	1,508	29	0	248	314	368	+11	-10	2.7	2.7
/162	664	13	0	+4.7	-4.4	1.2	pk7: 3

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
Michael Dattalo (OGILVIE)	22	52→57	31→36	45→50	50	238/304/322	84	309	1	2	23%	7%	81	-0.0	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
●Jake Elmore 2009 · A	22	45→55	40	45→55	45	217/280/320	103	285	6	10	25%	7%	70	-0.8	235/305/309	74	287	3	14	18%	8%	77	-0.3	264/336/337	72	315	2	23	15%	9%	93	+0.7
✕Kelby Tomlinson 2012 · A	22	49→59	40	56→60	44	236/285/341	105	298	6	13	22%	6%	76	-0.4	219/275/277	58	298	2	21	25%	7%	57	-1.8	279/337/345	67	339	3	24	17%	7%	93	+0.6
✕Emerson Landoni 2011 · A	22	50→60	39→40	46→45	44	237/281/319	82	290	6	12	20%	5%	70	-0.9	229/270/308	79	289	6	6	22%	4%	63	-1.4	264/307/333	70	313	3	4	16%	5%	79	-0.1
✕Chesny Young 2015 · A	22	51→61	38→30	50	38	239/273/327	89	329	5	8	28%	4%	68	-1.0	270/318/336	66	319	3	12	15%	6%	87	+0.4	271/321/329	58	318	2	11	15%	6%	84	+0.1
✕Andruw Monasterio 2019 · A	22	47→54	36→45	46→55	46	220/278/282	62	278	3	9	21%	7%	61	-1.5	215/272/288	73	289	5	9	26%	7%	60	-1.6	240/320/337	97	310	8	23	24%	9%	88	+0.3
✕Ofilio Castro 2006 · A	22	47→56	39→40	46→45	44	225/278/312	87	303	6	6	27%	7%	68	-1.0	236/286/312	76	289	4	6	19%	6%	70	-0.8	258/300/327	69	306	3	3	16%	5%	76	-0.3
✕Isaias Velasquez 2010 · A	22	50→57	37→40	53→55	43	233/280/320	87	295	3	12	22%	5%	70	-0.9	244/295/328	84	304	3	19	19%	6%	77	-0.3	256/311/338	82	316	2	24	18%	7%	82	+0.0
✕Phil Gosselin 2011 · A	22	49→59	39→45	50→45	40	231/281/320	89	328	5	9	30%	6%	70	-0.8	224/268/307	83	286	5	8	22%	5%	62	-1.4	288/326/390	102	349	6	8	18%	5%	100	+0.7
●Jonathan Jones 2012 · A	22	50→60	39→45	50→55	45	235/298/319	83	307	6	16	24%	7%	76	-0.4	222/284/288	66	281	2	21	20%	6%	65	-1.2	254/314/375	121	304	11	25	19%	6%	92	+0.4
✕Brandon Lockridge 2019 · A	22	48→55	38→45	55→65	44	225/292/317	92	312	4	10	28%	7%	74	-0.5	209/258/329	120	307	11	14	34%	5%	64	-1.3	253/321/335	81	356	3	53	27%	8%	85	+0.2
✕Gilberto Celestino 2021 · A	22	46→52	41→45	47→55	45	223/275/325	102	278	8	10	23%	6%	70	-0.9	224/294/322	98	291	8	8	24%	8%	76	-0.4	234/311/308	74	302	5	10	22%	9%	76	-0.2
✕Wynton Bernard 2013 · A	22	43→53	39→45	52→60	42	206/267/294	87	298	6	10	31%	7%	59	-1.6	241/291/332	91	319	5	19	24%	6%	76	-0.4	250/298/375	125	305	12	37	21%	6%	86	+0.3
✕Vinny Capra 2019 · A	23	45→48	38→45	50	42	215/263/300	85	290	5	8	27%	6%	59	-1.7	211/264/304	93	280	7	12	26%	6%	61	-1.5	250/319/362	111	318	10	9	23%	8%	91	+0.3
✕Blaze Alexander 2021 · A	22	45→48	42→45	51→50	42	215/281/322	107	301	9	11	30%	7%	72	-0.7	206/277/331	125	321	14	12	37%	7%	73	-0.6	239/319/362	123	339	12	15	30%	8%	93	+0.6
✕Taylor Davis 2012 · A	22	47→54	38→45	53→40	48	220/281/310	90	268	4	6	19%	7%	68	-1.0	224/281/319	95	269	7	4	18%	7%	70	-0.8	263/308/380	117	298	9	1	14%	6%	91	+0.3
✕Tim Kennelly 2009 · A	22	48→51	38→40	50→40	42	224/278/311	87	312	5	6	28%	6%	67	-1.1	233/291/330	97	292	6	6	21%	6%	76	-0.4	231/289/327	96	286	5	5	20%	6%	73	-0.4
✕L.J. Hoes 2011 · A	21	50→60	36→40	47→50	45	235/286/302	67	304	3	11	23%	6%	68	-1.0	261/316/346	85	319	5	14	18%	7%	88	+0.5	274/333/360	86	328	5	15	17%	7%	95	+0.9
✕Matt Fiedler 2017 · A	22	49	41→45	50	44	235/284/342	107	292	8	9	22%	6%	76	-0.4	221/274/323	102	290	8	8	26%	6%	69	-0.9	210/266/312	102	274	9	8	26%	6%	61	-0.5
✕Albert Hernandez 2010 · A	21	48	41→40	49→45	47	230/293/329	99	279	7	7	20%	7%	77	-0.3	217/271/297	80	301	6	6	28%	6%	61	-1.5	193/237/228	35	286	3	2	32%	5%	29	-0.8
✕Landon Lassiter 2016 · A	23	49→50	40	51→50	47	231/302/325	94	311	6	8	26%	8%	80	-0.2	219/280/291	72	334	4	9	33%	6%	63	-1.3	214/275/277	62	335	3	9	34%	6%	56	-1.0

Career Stats + Projections

Career Comps

Career Path Comps