Seiya Suzuki

RF Chicago Cubs

Age 32 R/R 5'11" / 182 lbs MLB HR -8% Svc 5.000 · Ctrl thru 2027

Overview

MLB40-MANArb-3FA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	29	MLBCHC	585	.283/.368/.482	21	16	136	2.9
2025	30	MLBCHC	651	.245/.330/.478	32	5	124	2.4
2026	31	MLBCHC	634	.270/.369/.473	26	3	136	3.5
2027PROJ	32	MLBCHC	528	.260/.350/.472	23	6	131	2.7
2028PROJ	33	MLBCHC	496	.251/.340/.451	21	2	123	1.6
2029PROJ	34	MLBCHC	436	.240/.328/.427	17	1	113	0.7

Last 3 seasons WAR 8.9 · Next 3 projected WAR 5.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service5.000First FA2028NTC

2027Arb-3$14M

Skills · percentileStatcast 2024-2026

xwOBA83

Barrel%82

Avg EV70

Bat Spd68

Speed63

Form.262/.364/.461 · rolling true talent (60d window) · proj .259/.347/.474

CompsSteve Pearce (age 32) · Josh Willingham (age 32) · C.J. Cron (age 32)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 134131vR 120

AVG/OBP/SLG.260 / .350 / .472

PA528

HR23

SB6

K%25

BB%11

BABIP311

ISO211

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Recent Form · Splits · ContractCON 50 / POW 60

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT50

xAVG

460.248

POWER60

Barrel%

8213.0

Avg EV

7090.5

Bat Spd

6873.3

EYE60

scouting grade only

SPEED60

Sprint

6328.0

Recent Formrolling true talent ⓘ

K%22%▲▲21% over 118 PA (60d) · proj 25%

BB%13%▲▲15% over 118 PA (60d) · proj 11%

ISO.198▼.172 over 99 AB (60d) · proj .215

HR/BB6.4%▼5.4% over 74 BBE (60d) · proj 7.1%

BABIP.308·.300 over 70 BIP (60d) · proj .309

SLASH.262/.364/.461·proj .259/.347/.474

Platoon Splits2024-2026 · 1298 PA

vs LHP

vs RHP

Edge

346

952

—

wRC+

137

127

◀L

wOBA

371

356

◀L

ISO

216

—

BABIP

300

334

▶R

21.7%

27.6%

◀◀L

BB%

13.9%

9.5%

◀◀L

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

Status Arb-3

MLB Debut 2022

Service 5.000 yrs.days

Team Control Through 2027

First FA Year 2028

NTC

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-3	$14M	+2.8	$24M	+$10M
Totals		$14M		$24M	+$10M

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)
2022	27	MLB	Chicago Cubs	—	446	397	104	22	2	14	42	110	4	9	5	262	339	433	772	171	326	25	9	342	114	+7	-0	-4	-5	+10	0.8
2023	28	MLB	Chicago Cubs	—	583	515	147	31	6	20	59	130	2	6	7	285	361	485	847	200	341	22	10	369	132	+22	-2	-4	-6	+13	2.4
2023	28	AAA	Iowa Cubs	—	15	13	4	0	0	1	1	2	0	0	0	308	357	538	896	231	273	13	7	366	107	—	—	—	—	—	—
2024	29	MLB	Chicago Cubs	—	585	512	145	27	6	21	63	160	6	16	6	283	368	482	851	199	370	27	11	374	136	+25	+1	-4	-6	+13	2.9
2025	30	MLB	Chicago Cubs	—	651	571	140	31	3	32	71	164	1	5	2	245	330	478	808	233	282	25	11	351	124	+18	+0	-2	-7	+14	2.4
2026	31	MLB	Chicago Cubs	—	634	545	147	31	1	26	81	155	5	3	0	270	369	473	843	204	330	24	13	373	136	+27	+1	-0	-7	+14	3.5
2026	31	AA	Knoxville Smokies	—	17	14	6	2	0	0	2	3	0	0	0	429	500	571	1.071	143	500	18	12	446	164	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	2899	2540	683	142	18	113	316	719	18	39	20	269	354	472	826	204	329	25	11	363	132	+109	-0	-13	-31	+63	12.9
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2022	27	MLB MLE	Chicago Cubs	—	446	400	104	21	2	15	39	110	4	9	5	260	332	435	767	175	326	25	9	337	114	+7	-0	-4	-5	+10	0.8
2023	28	MLB MLE	Chicago Cubs	—	583	518	146	30	5	21	56	130	2	6	7	282	354	481	835	199	341	22	10	364	132	+22	-2	-4	-6	+13	2.4
2023	28	AAA MLE	Iowa Cubs	—	15	13	4	0	0	1	1	2	0	0	0	308	357	538	896	231	239	13	7	327	107	—	—	—	—	—	—
2024	29	MLB MLE	Chicago Cubs	—	585	515	144	26	5	22	60	160	6	16	6	280	361	478	839	198	370	27	10	369	136	+25	+1	-4	-6	+13	2.9
2025	30	MLB MLE	Chicago Cubs	—	651	572	140	30	3	33	70	164	1	5	2	245	328	481	809	236	282	25	11	351	124	+18	+0	-2	-7	+14	2.4
2026	31	MLB MLE	Chicago Cubs	—	634	549	147	30	1	27	77	155	5	3	0	268	363	474	837	206	330	24	12	369	136	+27	+1	-0	-7	+14	3.5
2026	31	AA MLE	Knoxville Smokies	—	17	15	6	2	0	0	1	4	0	0	0	400	438	533	971	133	434	24	6	410	164	—	—	—	—	—	—
2022	27	MLB MLE	Chicago Cubs	—	446	400	104	21	2	15	39	110	4	9	5	260	332	435	767	175	320	25	9	337	114	+7	-0	-4	-5	+10	0.8
2022	27	MLB RAW	Chicago Cubs	—	446	397	104	22	2	14	42	110	4	9	5	262	339	433	772	171	326	25	9	342	114	+7	-0	-4	-5	+10	0.8
2023	28	MLB MLE	2 teams	—	598	531	150	30	5	22	57	132	2	6	7	282	354	482	836	200	332	22	10	363	132	+23	-2	-4	-6	+13	2.4
2023	28	MLB RAW	2 teams	—	598	528	151	31	6	21	60	132	2	6	7	286	361	487	848	201	339	22	10	369	132	+23	-2	-4	-6	+13	2.4
2024	29	MLB MLE	Chicago Cubs	—	585	515	144	26	5	22	60	160	6	16	6	280	361	478	839	198	362	27	10	369	136	+25	+1	-4	-6	+13	2.9
2024	29	MLB RAW	Chicago Cubs	—	585	512	145	27	6	21	63	160	6	16	6	283	368	482	851	199	370	27	11	374	136	+25	+1	-4	-6	+13	2.9
2025	30	MLB MLE	Chicago Cubs	—	651	572	140	30	3	33	70	164	1	5	2	245	328	481	809	236	279	25	11	351	124	+18	+0	-2	-7	+14	2.4
2025	30	MLB RAW	Chicago Cubs	—	651	571	140	31	3	32	71	164	1	5	2	245	330	478	808	233	282	25	11	351	124	+18	+0	-2	-7	+14	2.4
2026	31	MLB MLE	2 teams	—	651	564	153	32	1	27	78	159	5	3	0	271	365	475	840	204	330	24	12	370	137	+28	+1	-0	-7	+14	3.7
2026	31	MLB RAW	2 teams	—	651	559	153	33	1	26	83	158	5	3	0	274	372	476	848	202	335	24	13	375	137	+28	+1	-0	-7	+14	3.7
2022	27	MLB MLE	Chicago Cubs	—	446	400	104	21	2	15	39	110	4	9	5	260	332	435	767	175	326	25	9	337	114	—	—	—	—	—	—
2023	28	MLB MLE	2 teams	—	598	534	150	30	5	22	57	132	2	6	7	281	354	479	834	199	339	22	10	363	132	—	—	—	—	—	—
2024	29	MLB MLE	Chicago Cubs	—	585	514	144	26	5	22	60	160	6	16	6	280	361	479	840	198	370	27	10	369	136	—	—	—	—	—	—
2025	30	MLB MLE	Chicago Cubs	—	651	575	140	30	3	33	70	164	1	5	2	243	328	478	806	235	282	25	11	351	124	—	—	—	—	—	—
2026	31	MLB MLE	2 teams	—	651	563	153	32	1	27	78	159	5	3	0	272	365	476	841	204	332	24	12	370	137	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	29	MLB MLE	Chicago Cubs	—	585	514	144	26	5	22	60	160	6	16	6	280	361	479	840	198	370	27	10	369	136	—	—	—	—	—	—
2025	30	MLB MLE	Chicago Cubs	—	651	575	140	30	3	33	70	164	1	5	2	243	328	478	806	235	282	25	11	351	124	—	—	—	—	—	—
2026	31	MLB MLE	2 teams	—	651	563	153	32	1	27	78	159	5	3	0	272	365	476	841	204	332	24	12	370	137	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	32	MLB MLE	CHC	100%	590	514	133	26	2	27	67	146	4	7	2	260	349	474	823	214	309	25	11	361	131	+22	+1	+1	-6	+13	2.8
▸ 2027 — real world (MLB)
2027	32	MLB CTX	CHC	100%	528	460	119	24	2	23	60	130	3	6	1	260	350	472	822	211	311	25	11	361	131	+19	+1	+1	-6	+11	2.7
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	33	MLB MLE	CHC	100%	496	434	109	21	2	21	56	125	3	2	1	251	340	454	793	203	300	25	11	350	123	+13	+0	-4	-5	+11	1.6
2029	34	MLB MLE	CHC	100%	436	383	92	17	1	18	48	113	2	1	1	239	328	429	757	190	289	26	11	335	113	+7	-0	-4	-5	+9	0.7
2030	35	MLB MLE	CHC	100%	365	320	73	13	1	14	40	98	2	1	0	227	315	403	717	176	278	27	11	319	102	+1	+0	-5	-4	+8	-0.0
2028	33	MLB CTX	CHC	100%	496	434	109	21	2	21	56	125	3	2	1	251	340	451	791	200	303	25	11	349	123	+13	+0	-4	-5	+11	1.6
2029	34	MLB CTX	CHC	100%	436	383	91	17	1	17	48	113	2	1	1	240	328	427	755	187	292	26	11	334	113	+7	-0	-4	-5	+9	0.7
2030	35	MLB CTX	CHC	100%	365	320	72	13	1	13	40	98	2	1	0	227	315	400	715	173	280	27	11	318	102	+1	+0	-5	-4	+8	-0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	4196	3677	955	193	22	164	460	1055	25	43	22	260	346	458	804	198	318	25	11	354	125	+130	-0	-26	-45	+91	15.2
/ 162G	—	A+C		—	650	570	147	30	3	25	71	163	4	7	3	258	344	453	797	195	315	25	11	354	125	+20	-0	-4	-7	+14	2.4
Career	—	MLE		—	4756	4179	1085	214	22	196	508	1191	28	49	23	260	344	462	806	202	314	25	11	353	125	+149	+1	-26	-51	+102	17.9
/ 162G	—	MLE		—	650	571	148	29	3	27	69	163	4	7	3	259	343	462	806	203	313	25	11	353	125	+21	+0	-4	-7	+14	2.5

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 AAKnoxville Smokies · 17 PAwOBA .462 → .410 (−52)K% 17.6% → 21.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.65%	÷1.000	×1.220	—	—	21.53%
BB% (unintentional) /PA	11.76%	÷1.000	×0.680	—	×0.940	7.52%
HBP% /PA	0.00%	—	×0.840	—	×0.940	0.00%
Singles /BIP	36.36%	÷1.000	×0.920	—	×0.940	31.45%
Doubles /BIP	18.18%	÷1.000	×0.910	—	×0.940	15.55%
Triples /BIP	0.00%	÷1.000	×0.880	—	×0.940	0.00%
Home runs /BIP	0.00%	÷1.000	×0.800	—	×0.940	0.00%

Factors used: league row SL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 32 vs a level average of 24.8 → −6.0% on BB/HBP/hit rates (7.2 yr older than average).

Result: wOBA .462 → .410; ISO .143 → .134; BABIP .500 → .434. 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).

2023 AAAIowa Cubs · 15 PAwOBA .381 → .327 (−54)K% 13.3% → 15.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.33%	÷1.019	×1.200	—	—	15.70%
BB% (unintentional) /PA	6.67%	÷1.014	×0.690	—	×0.982	4.45%
HBP% /PA	0.00%	—	×0.940	—	×0.982	0.00%
Singles /BIP	27.27%	÷1.025	×0.930	—	×0.982	24.31%
Doubles /BIP	0.00%	÷1.049	×0.830	—	×0.982	0.00%
Triples /BIP	0.00%	÷0.916	×0.970	—	×0.982	0.00%
Home runs /BIP	9.09%	÷0.965	×0.700	—	×0.982	6.47%

Factors used: league row International League. Park (home-season share, regressed): HR 93, 1B 105, 2B 110, 3B 83, K 104, BB 103 — applied at half strength. Age: age 29 vs a level average of 27.2 → −1.8% on BB/HBP/hit rates (1.8 yr older than average).

Result: wOBA .381 → .327; ISO .231 → .179; BABIP .273 → .239. 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
#1Ryan Klesko'92-'07 * career totals — 13 seasons, 6,516 PA	9.8	6,516	278	91	267*	355*	487*	-92	-37	33.7	29.2
/162	664	28	9	-9.3	-3.8	3.4	pk7: 25
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 9 projected seasons	7.1	4,724	190	49	261	344	463	-51	-34	22.0	21.1
/162	664	27	7	-7.1	-4.8	3.1	pk7: 20
#2Josh Willinghamlast yr '14 career totals — 9 seasons, 4,559 PA	6.9	4,559	194	35	253	358	467	-49	-71	18.8	18.0
/162	664	28	5	-7.1	-10.4	2.7	pk7: 17
#3Yasiel Puiglast yr '19 career totals — 7 seasons, 3,376 PA	5.1	3,376	132	79	277	348	475	-36	-12	17.1	17.1
/162	664	26	16	-7.1	-2.3	3.4	pk7: 17
#4Leon Durham'80-'89 * career totals — 9 seasons, 4,067 PA	6.1	4,067	147	106	272*	353*	511*	-54	-20	17.3	17.0
/162	664	24	17	-8.9	-3.3	2.8	pk7: 17
#5Yoenis Cespedeslast yr '18 career totals — 7 seasons, 3,456 PA	5.2	3,456	163	43	274	328	498	-37	-13	16.8	16.8
/162	664	31	8	-7.1	-2.4	3.2	pk7: 17
#6Trot 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

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
Seiya Suzuki (OGILVIE)	32	50	60	60	60	257/347/470	212	309	24	6	25%	11%	131	+3.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
●Steve Pearce 2015 · MLB	32	52→58	57→60	49→50	53	269/348/477	208	302	25	8	20%	10%	132	+3.6	251/324/445	194	282	24	4	20%	9%	116	+2.5	261/343/453	192	288	24	0	18%	10%	126	+1.7
●Josh Willingham 2011 · MLB	32	50→53	57→65	50→45	60	260/366/465	206	293	23	8	20%	12%	136	+3.9	249/348/473	224	290	29	5	24%	11%	131	+3.6	238/343/462	224	279	29	3	25%	11%	128	+3.1
✕C.J. Cron 2022 · MLB	32	49→53	60→65	47→40	52	259/343/480	222	291	28	3	22%	10%	131	+3.6	248/308/439	191	295	25	2	24%	7%	109	+2.0	241/294/426	184	287	25	0	25%	6%	102	+1.1
●Mark Canha 2021 · MLB	32	51→56	58→60	48→50	58	261/374/474	213	302	25	6	22%	12%	141	+4.3	254/364/414	160	297	17	9	19%	11%	124	+3.1	254/363/401	147	297	15	9	18%	10%	122	+2.7
●Eric Thames 2019 · MLB	32	45→54	63→65	53→45	50	242/329/486	244	306	31	9	31%	11%	127	+3.3	240/326/454	214	312	26	7	30%	10%	120	+2.8	235/328/452	217	305	27	4	30%	10%	120	+1.4
✕Corey Hart 2014 · MLB	32	52→56	59→65	48→55	47	270/331/488	218	314	26	7	23%	7%	128	+3.4	223/278/380	157	274	19	6	26%	6%	84	+0.2	199/249/337	138	242	18	3	26%	5%	62	-0.5
✕Jonny Gomes 2013 · MLB	32	48→53	57→60	46→50	52	247/343/446	198	308	26	8	28%	11%	124	+3.1	238/332/400	162	306	21	4	27%	11%	109	+2.0	226/323/364	138	295	17	1	27%	11%	99	+0.6
✕Zack Cozart 2018 · MLB	32	52→56	56→60	50	56	269/342/471	202	288	22	5	16%	10%	128	+3.3	231/305/381	150	258	15	5	16%	8%	95	+0.9	188/263/293	105	214	8	0	16%	7%	59	-0.5
✕Alex Dickerson 2022 · MLB	32	49→56	58→60	49→45	48	257/324/462	206	292	26	4	22%	8%	120	+2.8	217/275/369	152	264	18	5	25%	7%	80	-0.1	183/235/311	127	226	14	1	25%	6%	49	-1.6
●Brian Dozier 2019 · MLB	32	46→56	58→65	50	54	245/326/452	207	270	25	13	20%	10%	118	+2.7	238/326/419	181	275	22	8	22%	11%	111	+2.1	235/335/426	190	268	25	4	22%	12%	117	+2.1
●Christian Walker 2024 · MLB	33	44→53	61→65	50→45	52	244/321/466	222	259	30	7	20%	9%	120	+2.8	240/311/447	207	274	28	4	24%	8%	112	+2.2	232/303/431	199	268	28	1	25%	8%	107	+1.8
✕Justin Upton 2020 · MLB	32	47→57	60→65	46→55	52	249/336/463	214	311	29	8	29%	11%	124	+3.1	221/306/413	192	277	26	6	29%	10%	103	+1.5	195/285/378	183	241	26	4	30%	9%	88	+0.2
●Mitch Haniger 2021 · MLB	30	49→56	59→65	51→50	51	256/338/473	216	305	26	9	25%	10%	128	+3.3	245/312/457	212	283	30	3	25%	8%	115	+2.4	238/306/444	206	274	29	1	25%	8%	110	+1.4
✕Steven Souza Jr. 2020 · MLB	31	46→56	55→60	54→55	53	236/328/426	191	298	22	14	28%	11%	113	+2.3	222/303/393	171	309	19	11	32%	9%	97	+1.1	198/285/370	171	275	19	9	33%	9%	83	+0.0
✕Jason Bay 2011 · MLB	32	53→59	57→65	56→50	56	267/360/476	209	321	23	12	23%	12%	136	+3.9	235/316/389	154	287	19	12	24%	10%	101	+1.4	219/302/364	146	261	20	12	24%	10%	91	+0.4
●David Dellucci 2006 · MLB	32	46	60→65	50	59	247/349/470	223	281	28	11	23%	13%	130	+3.5	254/336/457	203	294	23	6	21%	10%	123	+3.0	250/322/435	185	291	19	4	20%	8%	114	+1.1
✕Dean Palmer 2001 · MLB	32	48→47	59→60	45→50	53	253/334/461	208	294	28	6	24%	10%	124	+3.1	234/318/412	178	282	22	8	25%	10%	107	+1.8	222/317/426	204	253	27	10	24%	11%	111	+0.9
✕Scott Hairston 2013 · MLB	33	48→51	59→60	50	45	255/304/472	217	284	27	11	21%	6%	116	+2.5	233/284/424	191	273	25	9	25%	6%	97	+1.1	184/235/398	214	183	34	7	25%	5%	74	-0.2
✕Brad Miller 2022 · MLB	32	43→53	60	50	52	235/323/453	218	286	29	6	28%	11%	118	+2.6	221/299/370	149	285	19	8	28%	10%	90	+0.6	198/275/305	107	258	15	6	28%	9%	65	-0.4
✕Mike Yastrzemski 2023 · MLB	32	43→50	57→65	50	52	231/316/440	209	272	24	6	25%	10%	112	+2.2	234/316/436	202	281	23	6	24%	10%	111	+2.1	233/319/434	200	275	23	5	23%	10%	112	+1.8

Seiya Suzuki

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps