Michael Conforto

RF Chicago Cubs

Age 34 L/R 5'11" / 215 lbs MLB HR -8% Svc 10.250 · Ctrl thru 2027

Overview

MLB40-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	31	MLBSF	488	.237/.311/.450	20	0	117	1.0
2025	32	MLBLAD	486	.199/.306/.333	12	1	88	-1.0
2026	33	MLBCHC	314	.240/.335/.469	15	1	120	1.0
2027PROJ	34	MLBCHC	265	.242/.333/.443	10	2	118	0.9
2028PROJ	35	MLBCHC	203	.229/.319/.414	7	0	107	-0.2

Last 3 seasons WAR 0.9 · Next 2 projected WAR 0.7Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service10.250First FA2028

2027Ext / FA-deal$6M

Skills · percentileStatcast 2024-2026

xwOBA77

Barrel%69

Bat Spd68

Avg EV63

Speed17

Form.260/.345/.466 ▲ rolling true talent (60d window) · proj .241/.330/.445

CompsDavid Dellucci (age 34) · Matt Joyce (age 34) · Yadiel Hernandez (age 34)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 118118vR 117

AVG/OBP/SLG.242 / .333 / .443

PA265

HR10

K%25

BB%11

BABIP289

ISO199

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Recent Form · Splits · ContractCON 50 / POW 55

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT50

xAVG

390.242

POWER55

Barrel%

6911.0

Avg EV

6390.0

Bat Spd

6873.3

EYE55

scouting grade only

SPEED40

Sprint

1725.9

Recent Formrolling true talent ⓘ

K%19%▲▲14% over 71 PA (60d) · proj 25%

BB%10%·10% over 71 PA (60d) · proj 10%

ISO.206·.213 over 61 AB (60d) · proj .203

HR/BB6.2%·5.8% over 52 BBE (60d) · proj 6.4%

BABIP.286·.286 over 49 BIP (60d) · proj .286

SLASH.260/.345/.466▲proj .241/.330/.445

Platoon Splits2024-2026 · 1005 PA

vs LHP

vs RHP

Edge

184

821

—

wRC+

134

◀◀L

wOBA

366

301

◀◀L

ISO

204

165

◀◀L

BABIP

334

256

◀◀L

25.0%

24.7%

—

BB%

9.8%

10.5%

▶R

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

Status FA

MLB Debut 2015

Service 10.250 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$6M	+0.8	$3M	-$2M
Totals		$6M		$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.

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)
2015	22	MLB	New York Mets	—	194	174	47	14	0	9	17	39	1	0	1	270	339	506	844	236	297	20	9	366	140	+9	-0	+4	-6	+4	1.0
2015	22	AA	Binghamton Mets	—	197	173	55	12	3	5	23	35	1	1	0	318	401	509	910	191	376	18	12	402	114	—	—	—	—	—	—
2015	22	A+	St. Lucie Mets	—	206	184	52	12	0	7	17	26	3	0	1	283	353	462	815	179	294	13	8	359	80	—	—	—	—	—	—
2016	23	MLB	New York Mets	—	348	304	67	21	1	12	36	89	5	2	1	220	313	414	728	194	267	26	10	322	107	+3	+0	+1	-5	+8	0.6
2016	23	AAA	Las Vegas 51s	—	144	128	54	8	2	9	13	18	2	2	2	422	479	727	1.206	305	446	12	9	517	169	—	—	—	—	—	—
2017	24	MLB	New York Mets	—	440	373	104	20	1	27	57	113	8	2	0	279	386	555	941	276	328	26	13	409	162	+32	+0	+1	-5	+10	4.0
2018	25	MLB	New York Mets	—	638	543	132	25	1	28	84	159	7	3	4	243	352	448	799	204	289	25	13	355	125	+19	-1	+2	-7	+14	2.7
2019	26	MLB	New York Mets	—	648	549	141	29	1	33	84	149	10	7	2	257	365	494	859	237	290	23	13	377	142	+32	+1	-0	-7	+14	4.1
2020	27	MLB	New York Mets	—	233	202	65	12	0	9	24	57	7	3	3	322	412	515	927	193	412	24	10	411	170	+20	-1	-3	-2	+5	1.9
2021	28	MLB	New York Mets	—	479	406	94	20	0	14	59	104	12	1	0	232	346	384	730	153	276	22	12	332	112	+7	+0	-2	-5	+10	1.0
2023	30	MLB	San Francisco Giants	—	470	406	97	14	0	15	53	106	7	4	0	239	337	384	721	145	284	23	11	325	107	+4	+1	-3	-5	+10	0.7
2024	31	MLB	San Francisco Giants	—	488	438	104	27	3	20	42	118	5	0	1	237	311	450	761	212	277	24	9	334	117	+10	-0	-5	-5	+11	1.0
2025	32	MLB	Los Angeles Dodgers	—	486	418	83	20	0	12	56	121	9	1	0	199	306	333	639	134	247	25	12	293	88	-7	+0	-9	-5	+11	-1.0
2026	33	MLB	Chicago Cubs	—	314	271	65	17	0	15	35	80	4	1	0	240	335	469	804	229	278	25	11	351	120	+8	+0	-2	-3	+7	1.0
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	4738	4084	999	219	7	194	547	1135	75	24	12	245	344	444	789	200	289	24	12	350	123	+129	+0	-16	-57	+103	16.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2015	22	MLB MLE	New York Mets	—	194	174	49	15	0	9	17	39	1	0	1	282	349	523	872	241	297	20	9	375	140	+9	-0	+4	-6	+4	1.0
2015	22	AA MLE	Binghamton Mets	—	197	180	50	10	3	4	16	44	1	1	0	278	340	433	773	156	350	22	8	336	114	—	—	—	—	—	—
2015	22	A+ MLE	St. Lucie Mets	—	206	193	45	11	0	5	8	37	3	0	1	233	275	368	642	135	260	18	4	287	80	—	—	—	—	—	—
2016	23	MLB MLE	New York Mets	—	348	306	69	22	1	12	34	89	5	2	1	225	313	422	735	196	267	26	10	326	107	+3	+0	+1	-5	+8	0.6
2016	23	AAA MLE	Las Vegas 51s	—	144	132	47	6	2	7	10	24	2	2	2	356	410	591	1.001	235	394	17	7	418	169	—	—	—	—	—	—
2017	24	MLB MLE	New York Mets	—	440	378	106	21	1	27	52	113	8	2	0	280	379	556	935	275	328	26	12	408	162	+32	+0	+1	-5	+10	4.0
2018	25	MLB MLE	New York Mets	—	638	551	136	27	1	28	76	159	7	3	4	247	345	452	797	205	289	25	12	352	125	+19	-1	+2	-7	+14	2.7
2019	26	MLB MLE	New York Mets	—	648	554	145	31	1	33	79	149	10	7	2	262	364	500	864	238	290	23	12	378	142	+32	+1	-0	-7	+14	4.1
2020	27	MLB MLE	New York Mets	—	233	202	67	13	0	9	24	57	7	3	3	332	421	530	950	198	412	24	10	420	170	+20	-1	-3	-2	+5	1.9
2021	28	MLB MLE	New York Mets	—	479	409	97	21	0	14	56	104	12	1	0	237	346	391	737	154	276	22	12	334	112	+7	+0	-2	-5	+10	1.0
2023	30	MLB MLE	San Francisco Giants	—	470	410	99	14	0	16	49	106	7	4	0	241	333	393	725	151	284	23	10	326	107	+4	+1	-3	-5	+10	0.7
2024	31	MLB MLE	San Francisco Giants	—	488	439	107	27	3	22	41	118	5	0	1	244	315	469	785	226	277	24	8	341	117	+10	-0	-5	-5	+11	1.0
2025	32	MLB MLE	Los Angeles Dodgers	—	486	418	85	21	0	12	56	121	9	1	0	203	311	340	650	136	247	25	12	298	88	-7	+0	-9	-5	+11	-1.0
2026	33	MLB MLE	Chicago Cubs	—	314	274	66	17	0	16	32	80	4	1	0	241	329	478	807	237	278	25	10	346	120	+8	+0	-2	-3	+7	1.0
2015	22	A+ MLE	3 teams	—	597	547	144	36	3	18	41	120	5	1	2	263	320	439	759	176	305	20	7	332	111	—	—	—	—	—	—
2015	22	A+ RAW	3 teams	—	597	531	154	38	3	21	57	100	5	1	2	290	364	492	856	202	321	17	10	375	111	—	—	—	—	—	—
2016	23	MLB MLE	2 teams	—	492	438	116	28	3	19	44	113	7	4	3	265	342	473	814	208	314	23	9	353	125	+15	-0	+1	-5	+11	2.1
2016	23	MLB RAW	2 teams	—	492	432	121	29	3	21	49	107	7	4	3	280	362	507	869	227	326	22	10	379	125	+15	-0	+1	-5	+11	2.1
2017	24	MLB MLE	New York Mets	—	440	378	106	21	1	27	52	113	8	2	0	280	379	556	935	275	329	26	12	408	162	+32	+0	+1	-5	+10	4.0
2017	24	MLB RAW	New York Mets	—	440	373	104	20	1	27	57	113	8	2	0	279	386	555	941	276	328	26	13	409	162	+32	+0	+1	-5	+10	4.0
2018	25	MLB MLE	New York Mets	—	638	551	136	27	1	28	76	159	7	3	4	247	345	452	797	205	293	25	12	352	125	+19	-1	+2	-7	+14	2.7
2018	25	MLB RAW	New York Mets	—	638	543	132	25	1	28	84	159	7	3	4	243	352	448	799	204	289	25	13	355	125	+19	-1	+2	-7	+14	2.7
2019	26	MLB MLE	New York Mets	—	648	554	145	31	1	33	79	149	10	7	2	262	364	500	864	238	297	23	12	378	142	+32	+1	-0	-7	+14	4.1
2019	26	MLB RAW	New York Mets	—	648	549	141	29	1	33	84	149	10	7	2	257	365	494	859	237	290	23	13	377	142	+32	+1	-0	-7	+14	4.1
2020	27	MLB MLE	New York Mets	—	233	202	67	13	0	9	24	57	7	3	3	332	421	530	950	198	426	24	10	420	170	+20	-1	-3	-2	+5	1.9
2020	27	MLB RAW	New York Mets	—	233	202	65	12	0	9	24	57	7	3	3	322	412	515	927	193	412	24	10	411	170	+20	-1	-3	-2	+5	1.9
2021	28	MLB MLE	New York Mets	—	479	409	97	21	0	14	56	104	12	1	0	237	346	391	737	154	283	22	12	334	112	+7	+0	-2	-5	+10	1.0
2021	28	MLB RAW	New York Mets	—	479	406	94	20	0	14	59	104	12	1	0	232	346	384	730	153	276	22	12	332	112	+7	+0	-2	-5	+10	1.0
2023	30	MLB MLE	San Francisco Giants	—	470	410	99	14	0	16	49	106	7	4	0	241	333	393	725	151	284	23	10	326	107	+4	+1	-3	-5	+10	0.7
2023	30	MLB RAW	San Francisco Giants	—	470	406	97	14	0	15	53	106	7	4	0	239	337	384	721	145	284	23	11	325	107	+4	+1	-3	-5	+10	0.7
2024	31	MLB MLE	San Francisco Giants	—	488	439	107	27	3	22	41	118	5	0	1	244	315	469	785	226	281	24	8	341	117	+10	-0	-5	-5	+11	1.0
2024	31	MLB RAW	San Francisco Giants	—	488	438	104	27	3	20	42	118	5	0	1	237	311	450	761	212	277	24	9	334	117	+10	-0	-5	-5	+11	1.0
2025	32	MLB MLE	Los Angeles Dodgers	—	486	418	85	21	0	12	56	121	9	1	0	203	311	340	650	136	253	25	12	298	88	-7	+0	-9	-5	+11	-1.0
2025	32	MLB RAW	Los Angeles Dodgers	—	486	418	83	20	0	12	56	121	9	1	0	199	306	333	639	134	247	25	12	293	88	-7	+0	-9	-5	+11	-1.0
2026	33	MLB MLE	Chicago Cubs	—	314	274	66	17	0	16	32	80	4	1	0	241	329	478	807	237	275	25	10	346	120	+8	+0	-2	-3	+7	1.0
2026	33	MLB RAW	Chicago Cubs	—	314	271	65	17	0	15	35	80	4	1	0	240	335	469	804	229	278	25	11	351	120	+8	+0	-2	-3	+7	1.0
2015	22	A+ MLE	3 teams	—	597	546	144	36	3	18	41	120	5	1	2	264	320	440	760	176	302	20	7	332	111	—	—	—	—	—	—
2016	23	MLB MLE	2 teams	—	492	438	116	28	3	19	44	113	7	4	3	265	342	473	814	208	304	23	9	353	125	—	—	—	—	—	—
2017	24	MLB MLE	New York Mets	—	440	377	106	21	1	27	52	113	8	2	0	281	379	557	936	276	328	26	12	408	162	—	—	—	—	—	—
2018	25	MLB MLE	New York Mets	—	638	550	136	27	1	28	76	159	7	3	4	247	345	453	798	205	289	25	12	352	125	—	—	—	—	—	—
2019	26	MLB MLE	New York Mets	—	648	554	145	31	1	33	79	149	10	7	2	262	364	500	864	238	290	23	12	378	142	—	—	—	—	—	—
2020	27	MLB MLE	New York Mets	—	233	200	67	13	0	9	24	57	7	3	3	335	421	535	956	200	412	24	10	420	170	—	—	—	—	—	—
2021	28	MLB MLE	New York Mets	—	479	408	97	21	0	14	56	104	12	1	0	238	346	392	738	154	276	22	12	334	112	—	—	—	—	—	—
2023	30	MLB MLE	San Francisco Giants	—	470	411	99	14	0	16	49	106	7	4	0	241	333	392	724	151	284	23	10	326	107	—	—	—	—	—	—
2024	31	MLB MLE	San Francisco Giants	—	488	439	107	27	3	22	41	118	5	0	1	244	315	469	785	226	277	24	8	341	117	—	—	—	—	—	—
2025	32	MLB MLE	Los Angeles Dodgers	—	486	418	85	21	0	12	56	121	9	1	0	203	311	340	650	136	247	25	12	298	88	—	—	—	—	—	—
2026	33	MLB MLE	Chicago Cubs	—	314	275	66	17	0	16	32	80	4	1	0	240	329	476	805	236	278	25	10	346	120	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	31	MLB MLE	San Francisco Giants	—	488	439	107	27	3	22	41	118	5	0	1	244	315	469	785	226	277	24	8	341	117	—	—	—	—	—	—
2025	32	MLB MLE	Los Angeles Dodgers	—	486	418	85	21	0	12	56	121	9	1	0	203	311	340	650	136	247	25	12	298	88	—	—	—	—	—	—
2026	33	MLB MLE	Chicago Cubs	—	314	275	66	17	0	16	32	80	4	1	0	240	329	476	805	236	278	25	10	346	120	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	34	MLB MLE	CHC	100%	374	327	79	19	1	15	39	92	5	2	1	242	332	445	777	203	286	25	10	343	118	+8	+0	-0	-4	+8	0.8
▸ 2027 — real world (MLB)
2027	34	MLB CTX	CHC	100%	265	231	56	14	1	10	28	65	4	2	1	242	333	443	775	200	289	25	11	342	118	+6	+0	-0	-3	+6	0.9
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	35	MLB MLE	CHC	100%	203	177	41	10	0	8	21	52	3	0	0	228	318	416	734	188	274	26	10	326	107	+2	+0	-6	-2	+4	-0.2
2028	35	MLB CTX	CHC	100%	203	177	40	10	0	7	21	52	3	0	0	229	319	414	733	185	276	26	10	325	107	+2	+0	-6	-2	+4	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	4941	4261	1039	229	7	201	568	1187	78	24	12	244	343	442	786	199	288	24	11	349	122	+130	+0	-22	-59	+107	16.0
/ 162G	—	A+C		—	650	561	136	30	1	26	75	156	10	3	2	242	342	439	781	196	287	24	12	349	122	+17	+0	-3	-8	+14	2.1
Career	—	MLE		—	5753	5028	1266	280	13	233	599	1357	88	29	16	252	342	452	793	200	297	24	10	349	122	+136	+0	-22	-62	+113	16.9
/ 162G	—	MLE		—	650	568	143	32	1	26	68	153	10	3	2	252	342	449	791	197	298	24	10	349	122	+17	+0	-3	-8	+14	2.1

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.

2016 AAALas Vegas 51s · 144 PAwOBA .502 → .418 (−84)K% 12.5% → 16.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.50%	÷0.971	×1.290	—	—	16.60%
BB% (unintentional) /PA	9.03%	÷0.962	×0.710	—	×1.050	7.00%
HBP% /PA	1.39%	—	×0.980	—	×1.050	1.43%
Singles /BIP	31.82%	÷0.994	×0.900	×0.991	×1.050	29.98%
Doubles /BIP	7.27%	÷1.128	×0.810	×0.991	×1.050	5.43%
Triples /BIP	1.82%	÷0.980	×0.810	×0.991	×1.050	1.56%
Home runs /BIP	8.18%	÷1.088	×0.780	—	×1.050	6.16%

Factors used: league row PCL. Park (home-season share, regressed): HR 118, 1B 99, 2B 126, 3B 96, K 94, BB 92 — applied at half strength. Age: age 23 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (4.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.991.

Result: wOBA .502 → .418; ISO .305 → .228; BABIP .446 → .394. 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).

2015 A+St. Lucie Mets · 206 PAwOBA .342 → .287 (−55)K% 12.6% → 18.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.62%	÷0.992	×1.420	—	—	18.07%
BB% (unintentional) /PA	5.34%	÷1.023	×0.750	—	×1.012	3.96%
HBP% /PA	1.46%	—	×0.930	—	×1.012	1.37%
Singles /BIP	20.89%	÷1.049	×0.920	×0.999	×1.012	18.51%
Doubles /BIP	7.59%	÷1.055	×0.960	×0.999	×1.012	6.99%
Triples /BIP	0.00%	÷0.900	×0.810	×0.999	×1.012	0.00%
Home runs /BIP	4.43%	÷1.269	×0.880	—	×1.012	3.11%

Factors used: league row FSL. Park (home-season share, regressed): HR 154, 1B 110, 2B 111, 3B 80, K 98, BB 105 — applied at half strength. Age: age 22 vs a level average of 22.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.999.

Result: wOBA .342 → .287; ISO .179 → .140; BABIP .294 → .260. 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).

2015 AABinghamton Mets · 197 PAwOBA .390 → .336 (−54)K% 17.8% → 22.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.77%	÷0.974	×1.220	—	—	22.26%
BB% (unintentional) /PA	11.17%	÷0.988	×0.700	—	×1.042	8.24%
HBP% /PA	0.51%	—	×0.850	—	×1.042	0.45%
Singles /BIP	25.36%	÷1.030	×0.970	×0.978	×1.042	24.35%
Doubles /BIP	8.70%	÷1.034	×0.860	×0.978	×1.042	7.37%
Triples /BIP	2.17%	÷0.900	×0.950	×0.978	×1.042	2.34%
Home runs /BIP	3.62%	÷1.088	×0.780	—	×1.042	2.71%

Factors used: league row EL. Park (home-season share, regressed): HR 118, 1B 106, 2B 107, 3B 80, K 95, BB 98 — applied at half strength. Age: age 22 vs a level average of 24.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.978.

Result: wOBA .390 → .336; ISO .191 → .159; BABIP .376 → .350. 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
#1Jeromy Burnitz'93-'06 * career totals — 13 seasons, 6,579 PA	9.9	6,579	315	74	243*	330*	466*	-62	-31	22.9	21.7
/162	664	32	7	-6.3	-3.1	2.3	pk7: 20
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 13 projected seasons	7.8	5,206	212	26	245	340	446	-56	-31	21.9	19.8
/162	664	27	3	-7.1	-4.0	2.8	pk7: 18
#2Brad Wilkersonlast yr '08 career totals — 8 seasons, 3,753 PA	5.7	3,753	122	53	247	350	440	-35	-8	15.8	16.3
/162	664	22	9	-6.2	-1.4	2.8	pk7: 17
#3Trot Nixon'96-'08 * career totals — 9 seasons, 4,224 PA	6.4	4,224	137	30	263*	353*	451*	-41	-18	16.1	16.0
/162	664	22	5	-6.5	-2.9	2.5	pk7: 16
#4Seth Smithlast yr '17 career totals — 10 seasons, 4,076 PA	6.1	4,076	126	22	260	343	445	-44	-36	14.0	13.3
/162	664	21	4	-7.1	-5.9	2.3	pk7: 13
#5Ryan Ludwicklast yr '14 career totals — 11 seasons, 3,938 PA	5.9	3,938	150	17	261	330	451	-42	-34	11.9	12.8
/162	664	25	3	-7.0	-5.8	2.0	pk7: 14
#6John Milner'71-'82 * career totals — 11 seasons, 3,985 PA	6.0	3,985	131	31	245*	340*	448*	-58	+1	13.0	12.5
/162	664	22	5	-9.7	+0.2	2.2	pk7: 12

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 Conforto (OGILVIE)	34	50	55	40	55	239/329/441	201	286	11	2	25%	10%	118	+1.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕David Dellucci 2008 · MLB	34	49→46	56→65	46→50	54	255/337/460	205	293	23	6	21%	10%	124	+3.1	237/304/389	152	286	15	7	22%	7%	96	+1.0	230/297/374	144	280	14	6	22%	6%	90	+0.3
✕Matt Joyce 2019 · MLB	34	44→52	56→60	41→50	59	236/334/434	198	264	24	4	21%	13%	118	+2.6	249/349/395	146	305	17	4	22%	13%	114	+2.3	249/363/371	122	311	14	1	22%	15%	115	+0.7
✕Yadiel Hernandez 2022 · MLB	34	49→54	53→55	46→45	46	254/308/422	168	300	23	7	24%	7%	105	+1.7	249/297/389	140	311	16	7	24%	6%	93	+0.8	266/311/405	139	325	16	4	23%	6%	103	+0.8
✕Eduardo Escobar 2023 · MLB	34	47→57	55→60	43→50	47	246/301/439	193	282	23	2	22%	7%	106	+1.8	237/290/391	154	292	17	6	24%	7%	91	+0.6	224/269/341	117	286	11	4	25%	6%	71	-0.4
✕Garrett Jones 2015 · MLB	34	49→52	54→60	46→50	48	251/306/442	191	289	21	3	22%	7%	109	+2.0	240/296/403	163	288	18	5	23%	7%	96	+1.0	213/255/353	139	254	18	0	24%	5%	70	-0.2
✕Eric Hinske 2012 · MLB	34	47→55	55→60	42→50	50	244/319/429	185	293	23	3	25%	9%	111	+2.1	218/287/360	142	283	15	5	27%	9%	83	+0.1	191/257/303	112	257	9	0	28%	8%	59	-0.4
✕John Mabry 2005 · MLB	34	50	56→60	41→30	49	263/326/453	190	298	25	3	21%	8%	118	+2.7	233/299/388	155	282	18	3	23%	8%	93	+0.8	218/284/359	141	266	15	0	23%	8%	82	+0.0
●Robinson Chirinos 2017 · MLB	33	43→46	56→60	40→50	49	229/308/427	198	263	24	3	23%	8%	107	+1.8	236/339/446	210	295	26	4	28%	10%	122	+3.0	229/342/435	206	294	26	2	29%	11%	120	+1.8
✕Mark Reynolds 2018 · MLB	34	51→56	54→65	40→50	51	255/336/436	181	327	23	3	28%	10%	118	+2.7	233/319/411	178	307	23	5	30%	11%	107	+1.8	206/298/378	173	267	23	3	31%	11%	93	+0.3
●Jeromy Burnitz 2003 · MLB	34	43→51	57→65	41→45	54	230/321/426	196	259	25	7	23%	11%	111	+2.1	250/314/471	221	273	30	7	21%	8%	119	+2.7	256/317/483	227	273	31	5	19%	7%	124	+3.0
✕Stephen Vogt 2020 · MLB	35	47→57	56→60	47→40	49	246/306/449	203	282	22	6	22%	8%	110	+2.1	216/287/381	165	257	19	5	23%	9%	88	+0.4	179/259/328	149	204	20	1	24%	9%	66	-0.4
✕Seth Smith 2017 · MLB	34	50→55	52→60	46→50	55	252/339/430	178	292	19	2	20%	10%	118	+2.6	251/329/419	168	295	19	5	21%	9%	112	+2.2	250/329/414	164	295	19	3	21%	9%	112	+1.3
✕Kole Calhoun 2022 · MLB	34	43→53	60	46→50	52	235/317/448	213	262	29	5	24%	10%	115	+2.4	217/282/369	152	272	18	4	26%	7%	83	+0.1	207/270/350	143	261	16	2	27%	7%	74	-0.4
✕Dexter Fowler 2020 · MLB	34	45→55	53→55	45→55	57	231/330/403	172	275	20	9	24%	12%	109	+2.0	243/327/399	156	303	19	10	25%	10%	107	+1.8	236/319/400	165	293	26	6	28%	10%	106	+0.3
●Robin Ventura 2001 · MLB	34	44→47	57→55	38→40	58	233/320/431	197	241	25	5	17%	11%	112	+2.2	237/337/424	187	256	24	4	18%	13%	116	+2.5	236/341/416	180	257	24	2	18%	14%	117	+2.2
✕Charlie Blackmon 2020 · MLB	34	56→59	58→60	45→55	49	287/346/501	214	315	25	7	18%	7%	137	+4.0	267/328/425	158	303	17	5	17%	7%	113	+2.3	253/324/385	132	288	13	4	16%	8%	104	+1.4
●Tino Martinez 2002 · MLB	34	51→53	57→55	43→40	50	268/320/463	195	273	25	3	13%	7%	119	+2.7	263/329/441	178	273	22	3	13%	8%	117	+2.6	258/335/429	171	267	21	3	13%	9%	117	+2.4
✕Greg Norton 2007 · MLB	35	49	56→60	33→40	51	258/327/448	189	291	25	3	21%	9%	118	+2.6	250/339/395	145	302	16	5	21%	12%	110	+2.1	236/342/350	113	292	11	2	21%	14%	102	+0.5
✕Kelly Johnson 2016 · MLB	34	48→58	52→55	44→50	47	247/307/412	165	295	21	6	24%	8%	102	+1.5	251/309/409	158	294	19	8	21%	7%	102	+1.5	251/307/396	146	288	18	7	20%	7%	99	+0.7
✕José Cruz Jr. 2006 · MLB	32	47→50	55→65	42→50	60	244/340/436	192	277	21	6	20%	13%	120	+2.8	232/324/384	152	279	15	10	21%	12%	102	+1.5	225/317/358	133	275	11	13	21%	12%	94	+0.5

Michael Conforto

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps