Eugenio Suárez

3B Cincinnati Reds

Age 36 R/R 5'11" / 213 lbs MLB HR +16%BB +6% Svc 12.355 · Ctrl thru 2027

Overview

MLB40-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	33	INTLLeones del Ca…	65	.345/.446/.891	8	3	260	—
2024	33	MLBARI	640	.256/.324/.469	30	2	118	3.5
2025	34	MLBSEA	657	.228/.302/.526	49	4	129	3.9
2026	35	MLBCIN	498	.212/.309/.433	26	1	101	1.2
2027PROJ	36	MLBCIN	350	.229/.313/.480	21	2	114	1.5
2028PROJ	37	MLBCIN	238	.216/.299/.447	13	0	102	-0.1

Last 3 seasons WAR 8.6 · Next 2 projected WAR 1.4Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service12.355First FA2028Options3

2027Ext / FA-deal$9M

Skills · percentileStatcast 2024-2026

Barrel%80

xwOBA60

Avg EV53

Bat Spd45

Speed23

Form.237/.328/.503 ▲▲ rolling true talent (60d window) · proj .224/.307/.460

CompsRobinson Chirinos (age 36) · Olmedo Saenz (age 36) · Ruben Mateo (age 36)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 114114vR 114

AVG/OBP/SLG.229 / .313 / .480

PA350

HR21

K%31

BB%9

BABIP275

ISO249

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Recent Form · Splits · Contract

ToolsStatcast %ile · 2024-2026

CONTACT

xAVG

130.221

POWER

Barrel%

8012.7

Avg EV

5389.3

Bat Spd

4570.8

SPEED

Sprint

2326.2

Recent Formrolling true talent ⓘ

K%29%▲▲28% over 83 PA (60d) · proj 31%

BB%10%▲12% over 83 PA (60d) · proj 9%

ISO.266▲.333 over 69 AB (60d) · proj .236

HR/BB11.3%▲15.2% over 46 BBE (60d) · proj 9.6%

BABIP.272·.256 over 39 BIP (60d) · proj .273

SLASH.237/.328/.503▲▲proj .224/.307/.460

Platoon Splits2024-2026 · 1397 PA

vs LHP

vs RHP

Edge

400

997

—

wRC+

107

123

▶R

wOBA

327

350

▶R

ISO

237

251

▶R

BABIP

243

291

▶▶R

31.7%

27.6%

▶R

BB%

11.0%

5.8%

◀◀L

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

Status FA

MLB Debut 2014

Service 12.355 yrs.days

Team Control Through 2027

First FA Year 2028

OPT

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$9M	+1.4	$11M	+$2M
Totals		$9M		$11M	+$2M

Options · projected decision
2027	MUTUAL OPT	$9.2M / $0.0M buyout	DECLINE
2028	MUTUAL OPT	$16.0M / $0.0M buyout	DECLINE
2029	CLUB OPT	$15.0M / $2.0M buyout	DECLINE

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)
2009	18	ROK	VSL Tigers	—	240	206	54	9	3	1	17	32	15	8	4	262	361	350	711	87	305	13	7	327	38	—	—	—	—	—	—
2010	19	ROK	VSL Tigers	—	261	225	70	12	2	1	23	44	7	8	6	311	392	396	788	84	379	17	9	351	47	—	—	—	—	—	—
2011	20	ROK	GCL Tigers	—	50	44	15	7	0	2	3	4	2	2	0	341	408	636	1.045	295	342	8	6	443	107	—	—	—	—	—	—
2012	21	A	West Michigan Whitecaps	—	604	511	147	34	5	6	65	116	15	21	9	288	383	409	792	121	356	19	11	352	80	—	—	—	—	—	—
2013	22	AA	Erie SeaWolves	—	496	442	112	24	4	9	46	98	6	9	11	253	332	387	719	133	307	20	9	323	76	—	—	—	—	—	—
2013	22	A+	Lakeland Flying Tigers	—	122	103	32	6	2	1	14	25	4	2	3	311	413	437	850	126	397	20	11	381	103	—	—	—	—	—	—
2014	23	MLB	Detroit Tigers	—	277	244	59	9	1	4	22	67	5	3	2	242	317	336	653	94	316	24	8	293	86	-5	-0	+3	+6	+6	1.1
2014	23	AAA	Toledo Mud Hens	—	52	43	13	4	0	2	6	9	2	2	0	302	412	535	947	233	333	17	12	409	138	—	—	—	—	—	—
2014	23	AA	Erie SeaWolves	—	170	155	44	14	1	6	15	38	0	7	2	284	347	503	850	219	342	22	9	373	91	—	—	—	—	—	—
2014	23	INTL	Leones del Caracas	—	74	60	15	3	3	1	12	12	1	0	0	250	384	450	834	200	298	16	16	367	134	—	—	—	—	—	—
2015	24	MLB	Cincinnati Reds	—	398	372	104	19	2	13	17	94	3	4	1	280	316	446	763	167	341	24	4	332	107	+3	+0	-6	+7	+9	1.3
2015	24	AAA	Louisville Bats	—	238	203	52	9	2	8	26	40	3	3	4	256	349	438	788	182	282	17	11	343	90	—	—	—	—	—	—
2016	25	MLB	Cincinnati Reds	—	627	565	140	25	2	21	51	155	8	11	5	248	319	411	730	163	304	25	8	325	102	+1	+0	+5	+2	+14	2.3
2017	26	MLB	Cincinnati Reds	—	632	534	139	25	2	26	84	147	9	4	5	260	370	461	831	200	309	23	13	368	128	+21	-1	+5	+2	+14	4.2
2018	27	MLB	Cincinnati Reds	—	606	527	149	22	2	34	64	142	9	1	1	283	370	526	896	243	322	23	11	389	137	+27	-0	+2	+2	+13	4.4
2019	28	MLB	Cincinnati Reds	—	662	575	156	22	2	49	70	189	11	3	2	271	361	572	933	301	312	29	11	401	146	+36	-0	+1	+2	+14	5.4
2020	29	MLB	Cincinnati Reds	—	231	198	40	8	0	15	30	67	2	2	0	202	313	470	783	268	214	29	13	343	108	+2	+0	+1	+1	+5	0.9
2021	30	MLB	Cincinnati Reds	—	574	505	100	23	0	31	56	171	8	0	1	198	288	428	716	230	224	30	10	315	92	-5	-0	-5	+2	+12	0.4
2022	31	MLB	Seattle Mariners	—	629	543	128	24	2	31	73	196	8	0	0	236	335	459	793	223	302	31	12	349	125	+19	+0	+1	+2	+14	3.7
2022	31	INTL	Leones del Caracas	—	48	44	17	4	0	4	4	8	0	0	0	386	438	750	1.188	364	406	17	8	508	230	—	—	—	—	—	—
2023	32	MLB	Seattle Mariners	—	694	598	139	29	0	22	70	214	15	2	1	232	328	391	719	159	314	31	10	321	105	+4	+0	+9	+2	+15	3.2
2024	33	MLB	Arizona Diamondbacks	—	640	571	146	28	2	30	49	176	9	2	1	256	324	469	794	214	309	28	8	344	118	+13	+0	+4	+3	+14	3.5
2024	33	INTL	Leones del Caracas	—	65	55	19	6	0	8	9	14	1	3	0	345	446	891	1.337	545	333	22	14	552	260	—	—	—	—	—	—
2025	34	MLB	Seattle Mariners	—	657	588	134	28	0	49	46	196	16	4	1	228	302	526	827	298	243	30	7	355	129	+22	+0	-1	+2	+14	3.9
2026	35	MLB	Cincinnati Reds	—	498	434	92	18	0	26	52	169	9	1	1	212	309	433	742	221	273	34	10	328	101	+1	-0	-1	+2	+11	1.2
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	7125	6254	1526	280	15	351	684	1983	112	37	21	244	329	462	791	218	295	28	10	347	121	+176	-1	+18	+36	+154	39.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2009	18	ROK MLE	VSL Tigers	—	240	211	38	6	2	0	12	39	15	8	4	180	273	227	501	47	213	16	5	225	38	—	—	—	—	—	—
2010	19	ROK MLE	VSL Tigers	—	261	233	48	8	1	0	15	54	7	8	6	206	275	249	523	43	256	21	6	237	47	—	—	—	—	—	—
2011	20	ROK MLE	GCL Tigers	—	50	45	12	5	0	2	2	6	2	2	0	267	327	511	838	244	258	12	4	326	107	—	—	—	—	—	—
2012	21	A MLE	West Michigan Whitecaps	—	604	534	128	28	5	6	43	161	15	21	9	240	314	345	659	105	314	27	7	286	80	—	—	—	—	—	—
2013	22	AA MLE	Erie SeaWolves	—	496	456	107	22	4	7	32	119	6	9	11	235	294	346	640	112	300	24	6	280	76	—	—	—	—	—	—
2013	22	A+ MLE	Lakeland Flying Tigers	—	122	107	28	6	1	1	10	35	4	2	3	262	347	364	712	103	376	29	8	320	103	—	—	—	—	—	—
2014	23	MLB MLE	Detroit Tigers	—	277	245	60	9	1	4	21	67	5	3	2	245	317	339	656	94	316	24	8	295	86	-5	-0	+3	+6	+6	1.1
2014	23	AAA MLE	Toledo Mud Hens	—	52	45	13	4	0	2	4	11	2	2	0	289	373	511	884	222	310	21	8	372	138	—	—	—	—	—	—
2014	23	AA MLE	Erie SeaWolves	—	170	159	38	12	1	5	11	45	0	7	2	239	288	421	710	182	305	26	6	302	91	—	—	—	—	—	—
2015	24	MLB MLE	Cincinnati Reds	—	398	372	103	19	2	12	17	94	3	4	1	277	314	435	749	159	341	24	4	326	107	+3	+0	-6	+7	+9	1.3
2015	24	AAA MLE	Louisville Bats	—	238	211	50	8	2	7	18	49	3	3	4	237	306	393	699	156	263	21	8	301	90	—	—	—	—	—	—
2016	25	MLB MLE	Cincinnati Reds	—	627	565	138	25	2	19	51	155	8	11	5	244	316	396	712	152	304	25	8	318	102	+1	+0	+5	+2	+14	2.3
2017	26	MLB MLE	Cincinnati Reds	—	632	535	137	25	2	24	83	147	9	4	5	256	365	445	810	189	309	23	13	358	128	+21	-1	+5	+2	+14	4.2
2018	27	MLB MLE	Cincinnati Reds	—	606	534	146	22	2	31	57	142	9	1	1	273	353	496	850	223	322	23	9	371	137	+27	-0	+2	+2	+13	4.4
2019	28	MLB MLE	Cincinnati Reds	—	662	579	152	22	2	45	66	189	11	3	2	263	349	541	890	278	312	29	10	383	146	+36	-0	+1	+2	+14	5.4
2020	29	MLB MLE	Cincinnati Reds	—	231	199	39	8	0	14	29	67	2	2	0	196	304	447	752	251	214	29	13	328	108	+2	+0	+1	+1	+5	0.9
2021	30	MLB MLE	Cincinnati Reds	—	574	505	98	23	0	29	56	171	8	0	1	194	285	412	697	218	224	30	10	305	92	-5	-0	-5	+2	+12	0.4
2022	31	MLB MLE	Seattle Mariners	—	629	543	129	24	2	32	73	196	8	0	0	238	337	466	802	228	302	31	12	353	125	+19	+0	+1	+2	+14	3.7
2023	32	MLB MLE	Seattle Mariners	—	694	598	140	29	0	23	70	214	15	2	1	234	329	398	727	164	314	31	10	324	105	+4	+0	+9	+2	+15	3.2
2024	33	MLB MLE	Arizona Diamondbacks	—	640	571	145	25	2	32	49	176	9	2	1	254	323	473	796	219	309	28	8	342	118	+13	+0	+4	+3	+14	3.5
2025	34	MLB MLE	Seattle Mariners	—	657	590	135	28	0	50	44	196	16	4	1	229	300	531	831	302	243	30	7	358	129	+22	+0	-1	+2	+14	3.9
2026	35	MLB MLE	Cincinnati Reds	—	498	435	90	18	0	24	51	169	9	1	1	207	303	414	717	207	273	34	10	317	101	+1	-0	-1	+2	+11	1.2
2009	18	ROK MLE	VSL Tigers	—	240	211	38	6	2	0	12	39	15	8	4	180	273	227	501	47	220	16	5	225	38	—	—	—	—	—	—
2009	18	ROK RAW	VSL Tigers	—	240	206	54	9	3	1	17	32	15	8	4	262	361	350	711	87	305	13	7	327	38	—	—	—	—	—	—
2010	19	ROK MLE	VSL Tigers	—	261	233	48	8	1	0	15	54	7	8	6	206	275	249	523	43	265	21	6	237	47	—	—	—	—	—	—
2010	19	ROK RAW	VSL Tigers	—	261	225	70	12	2	1	23	44	7	8	6	311	392	396	788	84	379	17	9	351	47	—	—	—	—	—	—
2011	20	ROK MLE	GCL Tigers	—	50	45	12	5	0	2	2	6	2	2	0	267	327	511	838	244	270	12	4	326	107	—	—	—	—	—	—
2011	20	ROK RAW	GCL Tigers	—	50	44	15	7	0	2	3	4	2	2	0	341	408	636	1.045	295	342	8	6	443	107	—	—	—	—	—	—
2012	21	A MLE	West Michigan Whitecaps	—	604	534	128	28	5	6	43	161	15	21	9	240	314	345	659	105	326	27	7	286	80	—	—	—	—	—	—
2012	21	A RAW	West Michigan Whitecaps	—	604	511	147	34	5	6	65	116	15	21	9	288	383	409	792	121	356	19	11	352	80	—	—	—	—	—	—
2013	22	AA MLE	2 teams	—	618	563	136	28	6	8	42	154	10	11	14	242	306	355	661	114	318	25	7	288	81	—	—	—	—	—	—
2013	22	AA RAW	2 teams	—	618	545	144	30	6	10	60	123	10	11	14	264	348	396	744	132	324	20	10	335	81	—	—	—	—	—	—
2014	23	MLB MLE	4 teams	—	573	515	127	28	2	13	42	141	8	12	4	247	313	384	698	138	314	25	7	305	93	-5	+1	+3	+6	+12	1.8
2014	23	MLB RAW	4 teams	—	573	502	131	30	5	13	55	126	8	12	4	261	343	418	762	157	323	22	10	337	93	-5	+1	+3	+6	+12	1.8
2015	24	MLB MLE	2 teams	—	636	583	152	27	4	19	35	143	6	7	5	261	309	419	728	158	314	22	6	317	101	+0	-1	-6	+7	+14	1.5
2015	24	MLB RAW	2 teams	—	636	575	156	28	4	21	43	134	6	7	5	271	329	443	772	172	319	21	7	336	101	+0	-1	-6	+7	+14	1.5
2016	25	MLB MLE	Cincinnati Reds	—	627	565	138	25	2	19	51	155	8	11	5	244	316	396	712	152	302	25	8	318	102	+1	+0	+5	+2	+14	2.3
2016	25	MLB RAW	Cincinnati Reds	—	627	565	140	25	2	21	51	155	8	11	5	248	319	411	730	163	304	25	8	325	102	+1	+0	+5	+2	+14	2.3
2017	26	MLB MLE	Cincinnati Reds	—	632	535	137	25	2	24	83	147	9	4	5	256	365	445	810	189	306	23	13	358	128	+21	-1	+5	+2	+14	4.2
2017	26	MLB RAW	Cincinnati Reds	—	632	534	139	25	2	26	84	147	9	4	5	260	370	461	831	200	309	23	13	368	128	+21	-1	+5	+2	+14	4.2
2018	27	MLB MLE	Cincinnati Reds	—	606	534	146	22	2	31	57	142	9	1	1	273	353	496	850	223	313	23	9	371	137	+27	-0	+2	+2	+13	4.4
2018	27	MLB RAW	Cincinnati Reds	—	606	527	149	22	2	34	64	142	9	1	1	283	370	526	896	243	322	23	11	389	137	+27	-0	+2	+2	+13	4.4
2019	28	MLB MLE	Cincinnati Reds	—	662	579	152	22	2	45	66	189	11	3	2	263	349	541	890	278	305	29	10	383	146	+36	-0	+1	+2	+14	5.4
2019	28	MLB RAW	Cincinnati Reds	—	662	575	156	22	2	49	70	189	11	3	2	271	361	572	933	301	312	29	11	401	146	+36	-0	+1	+2	+14	5.4
2020	29	MLB MLE	Cincinnati Reds	—	231	199	39	8	0	14	29	67	2	2	0	196	304	447	752	251	210	29	13	328	108	+2	+0	+1	+1	+5	0.9
2020	29	MLB RAW	Cincinnati Reds	—	231	198	40	8	0	15	30	67	2	2	0	202	313	470	783	268	214	29	13	343	108	+2	+0	+1	+1	+5	0.9
2021	30	MLB MLE	Cincinnati Reds	—	574	505	98	23	0	29	56	171	8	0	1	194	285	412	697	218	223	30	10	305	92	-5	-0	-5	+2	+12	0.4
2021	30	MLB RAW	Cincinnati Reds	—	574	505	100	23	0	31	56	171	8	0	1	198	288	428	716	230	224	30	10	315	92	-5	-0	-5	+2	+12	0.4
2022	31	MLB MLE	2 teams	—	677	585	139	26	2	34	79	211	8	0	0	238	336	463	800	226	304	31	12	353	125	+20	+0	+1	+2	+15	3.9
2022	31	MLB RAW	2 teams	—	677	587	145	28	2	35	77	204	8	0	0	247	342	480	823	233	312	30	11	360	125	+20	+0	+1	+2	+15	3.9
2023	32	MLB MLE	Seattle Mariners	—	694	598	140	29	0	23	70	214	15	2	1	234	329	398	727	164	315	31	10	324	105	+4	+0	+9	+2	+15	3.2
2023	32	MLB RAW	Seattle Mariners	—	694	598	139	29	0	22	70	214	15	2	1	232	328	391	719	159	314	31	10	321	105	+4	+0	+9	+2	+15	3.2
2024	33	MLB MLE	2 teams	—	705	630	158	27	2	35	54	194	10	5	1	251	320	467	787	216	299	28	8	342	118	+15	+1	+4	+3	+15	3.8
2024	33	MLB RAW	2 teams	—	705	626	165	34	2	38	58	190	10	5	1	264	336	506	842	243	311	27	8	363	118	+15	+1	+4	+3	+15	3.8
2025	34	MLB MLE	Seattle Mariners	—	657	590	135	28	0	50	44	196	16	4	1	229	300	531	831	302	242	30	7	358	129	+22	+0	-1	+2	+14	3.9
2025	34	MLB RAW	Seattle Mariners	—	657	588	134	28	0	49	46	196	16	4	1	228	302	526	827	298	243	30	7	355	129	+22	+0	-1	+2	+14	3.9
2026	35	MLB MLE	Cincinnati Reds	—	498	435	90	18	0	24	51	169	9	1	1	207	303	414	717	207	269	34	10	317	101	+1	-0	-1	+2	+11	1.2
2026	35	MLB RAW	Cincinnati Reds	—	498	434	92	18	0	26	52	169	9	1	1	212	309	433	742	221	273	34	10	328	101	+1	-0	-1	+2	+11	1.2
2009	18	ROK MLE	VSL Tigers	—	240	211	38	6	2	0	12	39	15	8	4	180	273	227	501	47	213	16	5	225	38	—	—	—	—	—	—
2010	19	ROK MLE	VSL Tigers	—	261	237	48	8	1	0	15	54	7	8	6	203	275	245	519	42	256	21	6	237	47	—	—	—	—	—	—
2011	20	ROK MLE	GCL Tigers	—	50	46	12	5	0	2	2	6	2	2	0	261	327	500	827	239	258	12	4	326	107	—	—	—	—	—	—
2012	21	A MLE	West Michigan Whitecaps	—	604	541	128	28	5	6	43	161	15	21	9	237	314	340	654	104	314	27	7	286	80	—	—	—	—	—	—
2013	22	AA MLE	2 teams	—	618	561	136	28	6	8	42	154	10	11	14	242	306	357	662	114	315	25	7	288	81	—	—	—	—	—	—
2014	23	MLB MLE	4 teams	—	573	518	127	28	2	13	42	141	8	12	4	245	313	382	696	137	312	25	7	305	93	—	—	—	—	—	—
2015	24	MLB MLE	2 teams	—	636	590	152	27	4	19	35	143	6	7	5	258	309	414	723	156	312	22	6	317	101	—	—	—	—	—	—
2016	25	MLB MLE	Cincinnati Reds	—	627	563	138	25	2	19	51	155	8	11	5	245	316	398	714	153	304	25	8	318	102	—	—	—	—	—	—
2017	26	MLB MLE	Cincinnati Reds	—	632	535	137	25	2	24	83	147	9	4	5	256	365	445	810	189	309	23	13	358	128	—	—	—	—	—	—
2018	27	MLB MLE	Cincinnati Reds	—	606	535	146	22	2	31	57	142	9	1	1	273	353	495	849	222	322	23	9	371	137	—	—	—	—	—	—
2019	28	MLB MLE	Cincinnati Reds	—	662	580	152	22	2	45	66	189	11	3	2	262	349	540	889	278	312	29	10	383	146	—	—	—	—	—	—
2020	29	MLB MLE	Cincinnati Reds	—	231	198	39	8	0	14	29	67	2	2	0	197	304	449	754	253	214	29	13	328	108	—	—	—	—	—	—
2021	30	MLB MLE	Cincinnati Reds	—	574	505	98	23	0	29	56	171	8	0	1	194	285	412	697	218	224	30	10	305	92	—	—	—	—	—	—
2022	31	MLB MLE	2 teams	—	677	585	139	26	2	34	79	211	8	0	0	238	336	463	800	226	302	31	12	353	125	—	—	—	—	—	—
2023	32	MLB MLE	Seattle Mariners	—	694	604	140	29	0	23	70	214	15	2	1	232	329	394	723	162	314	31	10	324	105	—	—	—	—	—	—
2024	33	MLB MLE	2 teams	—	705	635	158	27	2	35	54	194	10	5	1	249	320	463	783	214	309	28	8	342	118	—	—	—	—	—	—
2025	34	MLB MLE	Seattle Mariners	—	657	592	135	28	0	50	44	196	16	4	1	228	300	529	829	301	243	30	7	358	129	—	—	—	—	—	—
2026	35	MLB MLE	Cincinnati Reds	—	498	435	90	18	0	24	51	169	9	1	1	207	303	414	717	207	273	34	10	317	101	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	33	MLB MLE	2 teams	—	705	635	158	27	2	35	54	194	10	5	1	249	320	463	783	214	309	28	8	342	118	—	—	—	—	—	—
2025	34	MLB MLE	Seattle Mariners	—	657	592	135	28	0	50	44	196	16	4	1	228	300	529	829	301	243	30	7	358	129	—	—	—	—	—	—
2026	35	MLB MLE	Cincinnati Reds	—	498	435	90	18	0	24	51	169	9	1	1	207	303	414	717	207	273	34	10	317	101	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	36	MLB MLE	CIN	100%	442	391	88	18	0	25	40	138	8	3	1	224	309	460	770	236	273	31	9	337	114	+7	+0	-0	+2	+10	1.4
▸ 2027 — real world (MLB)
2027	36	MLB CTX	CIN	100%	350	309	71	14	0	21	31	109	7	2	1	229	313	480	793	250	275	31	9	346	114	+6	+0	-0	+1	+8	1.5
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	37	MLB MLE	CIN	100%	238	211	44	9	0	12	21	76	4	0	0	211	295	430	725	218	260	32	9	319	102	+1	+0	-7	+1	+5	-0.1
2028	37	MLB CTX	CIN	100%	238	211	46	9	0	13	21	76	4	0	0	216	299	447	747	231	261	32	9	327	102	+1	+0	-7	+1	+5	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	7363	6465	1572	289	15	364	705	2059	116	37	21	243	328	461	790	218	294	28	10	346	107	+177	-1	+11	+37	+160	39.1
/ 162G	—	A+C		—	650	571	139	26	1	32	62	182	10	3	2	243	328	461	789	217	295	28	10	346	107	+16	-0	+1	+3	+14	3.5
Career	—	MLE		—	10133	8959	2126	406	32	407	883	2738	179	104	61	237	318	426	744	189	292	27	9	326	107	+182	-1	+11	+38	+167	40.6
/ 162G	—	MLE		—	650	575	136	26	2	26	57	176	11	7	4	237	317	424	742	188	291	27	9	326	107	+15	-0	+1	+3	+14	3.4

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.

2015 AAALouisville Bats · 238 PAwOBA .334 → .301 (−33)K% 16.8% → 20.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.81%	÷0.991	×1.200	—	—	20.35%
BB% (unintentional) /PA	10.50%	÷1.023	×0.690	—	×1.048	7.43%
HBP% /PA	1.26%	—	×0.940	—	×1.048	1.24%
Singles /BIP	20.25%	÷0.999	×0.930	×0.975	×1.048	19.25%
Doubles /BIP	5.52%	÷0.975	×0.830	×0.975	×1.048	4.80%
Triples /BIP	1.23%	÷0.922	×0.970	×0.975	×1.048	1.32%
Home runs /BIP	4.91%	÷1.009	×0.840	—	×1.048	4.28%

Factors used: league row IL. Park (home-season share, regressed): HR 102, 1B 100, 2B 95, 3B 84, K 98, BB 105 — applied at half strength. Age: age 24 vs a level average of 27.2 → +4.8% on BB/HBP/hit rates (3.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.975.

Result: wOBA .334 → .301; ISO .182 → .169; BABIP .282 → .263. 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).

2014 AAErie SeaWolves · 170 PAwOBA .362 → .302 (−61)K% 22.4% → 26.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.35%	÷1.020	×1.220	—	—	26.75%
BB% (unintentional) /PA	8.82%	÷0.981	×0.700	—	×1.027	6.46%
HBP% /PA	0.00%	—	×0.850	—	×1.027	0.00%
Singles /BIP	19.66%	÷1.042	×0.970	×0.950	×1.027	17.86%
Doubles /BIP	11.97%	÷0.945	×0.860	×0.950	×1.027	10.62%
Triples /BIP	0.85%	÷1.150	×0.950	×0.950	×1.027	0.69%
Home runs /BIP	5.13%	÷0.975	×0.780	—	×1.027	4.21%

Factors used: league row EL. Park (home-season share, regressed): HR 95, 1B 108, 2B 89, 3B 130, K 104, BB 96 — applied at half strength. Age: age 23 vs a level average of 24.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .362 → .302; ISO .219 → .180; BABIP .342 → .305. 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).

2014 AAAToledo Mud Hens · 52 PAwOBA .407 → .372 (−34)K% 17.3% → 20.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.31%	÷1.017	×1.200	—	—	20.42%
BB% (unintentional) /PA	11.54%	÷1.053	×0.690	—	×1.050	7.94%
HBP% /PA	3.85%	—	×0.940	—	×1.050	3.80%
Singles /BIP	20.59%	÷0.999	×0.930	—	×1.050	20.13%
Doubles /BIP	11.76%	÷1.031	×0.830	—	×1.050	9.95%
Triples /BIP	0.00%	÷1.049	×0.970	—	×1.050	0.00%
Home runs /BIP	5.88%	÷0.899	×0.840	—	×1.050	5.77%

Factors used: league row IL. Park (home-season share, regressed): HR 80, 1B 100, 2B 106, 3B 110, K 103, BB 111 — 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).

Result: wOBA .407 → .372; ISO .233 → .224; BABIP .333 → .310. 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).

2013 AAErie SeaWolves · 496 PAwOBA .315 → .280 (−35)K% 19.8% → 24.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.76%	÷1.004	×1.220	—	—	24.01%
BB% (unintentional) /PA	9.27%	÷1.034	×0.700	—	×1.042	6.54%
HBP% /PA	1.21%	—	×0.850	—	×1.042	1.07%
Singles /BIP	21.80%	÷0.998	×0.970	×0.983	×1.042	21.71%
Doubles /BIP	6.98%	÷0.965	×0.860	×0.983	×1.042	6.37%
Triples /BIP	1.16%	÷0.902	×0.950	×0.983	×1.042	1.25%
Home runs /BIP	2.62%	÷1.020	×0.780	—	×1.042	2.09%

Factors used: league row EL. Park (home-season share, regressed): HR 104, 1B 100, 2B 93, 3B 80, K 101, BB 107 — 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 ×0.983.

Result: wOBA .315 → .280; ISO .133 → .116; BABIP .307 → .300. 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).

2013 A+Lakeland Flying Tigers · 122 PAwOBA .375 → .320 (−55)K% 20.5% → 28.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.49%	÷1.018	×1.420	—	—	28.59%
BB% (unintentional) /PA	11.48%	÷1.045	×0.750	—	×1.012	8.34%
HBP% /PA	3.28%	—	×0.930	—	×1.012	3.09%
Singles /BIP	29.49%	÷1.011	×0.920	×1.022	×1.012	27.76%
Doubles /BIP	7.69%	÷0.944	×0.960	×1.022	×1.012	8.09%
Triples /BIP	2.56%	÷1.150	×0.810	×1.022	×1.012	1.87%
Home runs /BIP	1.28%	÷1.067	×0.880	—	×1.012	1.07%

Factors used: league row FSL. Park (home-season share, regressed): HR 113, 1B 102, 2B 89, 3B 130, K 104, BB 109 — 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 ×1.022.

Result: wOBA .375 → .320; ISO .126 → .107; BABIP .397 → .376. 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).

2012 AWest Michigan Whitecaps · 604 PAwOBA .347 → .286 (−61)K% 19.2% → 26.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.21%	÷0.978	×1.360	—	—	26.72%
BB% (unintentional) /PA	10.43%	÷1.034	×0.690	—	×1.015	7.07%
HBP% /PA	2.48%	—	×0.780	—	×1.015	1.97%
Singles /BIP	25.82%	÷1.020	×0.920	×0.976	×1.015	23.06%
Doubles /BIP	8.61%	÷0.990	×0.830	×0.976	×1.015	7.14%
Triples /BIP	1.27%	÷0.900	×0.910	×0.976	×1.015	1.27%
Home runs /BIP	1.52%	÷0.865	×0.800	—	×1.015	1.43%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 73, 1B 104, 2B 98, 3B 80, K 96, BB 107 — applied at half strength. Age: age 21 vs a level average of 22.0 → +1.5% on BB/HBP/hit rates (1.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.976.

Result: wOBA .347 → .286; ISO .121 → .106; BABIP .356 → .314. 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).

2011 ROKGCL Tigers · 50 PAwOBA .430 → .326 (−104)K% 8.0% → 11.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	8.00%	÷1.000	×1.440	—	—	11.52%
BB% (unintentional) /PA	6.00%	÷1.000	×0.620	—	×0.995	3.70%
HBP% /PA	4.00%	—	×0.720	—	×0.995	2.87%
Singles /BIP	15.00%	÷1.000	×0.820	—	×0.995	12.24%
Doubles /BIP	17.50%	÷1.000	×0.720	—	×0.995	12.54%
Triples /BIP	0.00%	÷1.000	×0.720	—	×0.995	0.00%
Home runs /BIP	5.00%	÷1.000	×0.780	—	×0.995	3.88%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 20 vs a level average of 19.5 → −0.5% on BB/HBP/hit rates (0.5 yr older than average).

Result: wOBA .430 → .326; ISO .295 → .225; BABIP .342 → .258. 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).

2010 DSLVSL Tigers · 261 PAwOBA .344 → .237 (−106)K% 16.9% → 20.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.86%	÷1.000	×1.220	—	—	20.57%
BB% (unintentional) /PA	8.43%	÷1.000	×0.700	—	×0.995	5.87%
HBP% /PA	2.68%	—	×0.700	—	×0.995	1.87%
Singles /BIP	30.39%	÷1.000	×0.680	×1.026	×0.995	21.10%
Doubles /BIP	6.63%	÷1.000	×0.600	×1.026	×0.995	4.06%
Triples /BIP	1.10%	÷1.000	×0.600	×1.026	×0.995	0.68%
Home runs /BIP	0.55%	÷1.000	×0.470	—	×0.995	0.26%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 19 vs a level average of 18.5 → −0.5% on BB/HBP/hit rates (0.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.026.

Result: wOBA .344 → .237; ISO .084 → .051; BABIP .379 → .256. 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).

Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Matt Williams'87-'03 * career totals — 17 seasons, 7,595 PA	11.4	7,595	378	53	260*	308*	493*	+29	+41	44.3	37.9
/162	664	33	5	+2.6	+3.6	3.9	pk7: 31
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 15 projected seasons	11.6	7,713	383	39	243	324	462	+22	+32	41.9	36.1
/162	664	33	3	+1.9	+2.7	3.6	pk7: 30
#2Doug DeCinces'73-'87 * career totals — 13 seasons, 6,534 PA	9.8	6,534	237	58	255*	329*	470*	+20	+32	38.7	34.4
/162	664	24	6	+2.0	+3.2	3.9	pk7: 30
#3Kyle Seagerlast yr '21 career totals — 11 seasons, 6,204 PA	9.3	6,204	242	55	251	321	442	+22	+55	35.4	32.4
/162	664	26	6	+2.4	+5.8	3.8	pk7: 29
#4Tim Wallach'80-'96 * career totals — 16 seasons, 8,908 PA	13.4	8,908	260	51	253*	313*	441*	+20	+21	34.7	30.1
/162	664	19	4	+1.5	+1.5	2.6	pk7: 26
#5Dan Ugglalast yr '15 career totals — 10 seasons, 5,509 PA	8.3	5,509	235	26	241	336	447	+20	-17	28.7	28.7
/162	664	28	3	+2.4	-2.1	3.5	pk7: 29
#6Todd Frazierlast yr '20 career totals — 10 seasons, 4,909 PA	7.4	4,909	218	73	242	319	448	+18	+35	27.6	26.2
/162	664	29	10	+2.4	+4.7	3.7	pk7: 25

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
Eugenio Suárez (OGILVIE)	36	—	—	—	—	222/307/456	234	273	19	2	31%	9%	114	+1.4	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Robinson Chirinos 2020 · MLB	36	45→46	57→60	43→50	51	233/340/433	200	301	25	4	29%	11%	120	+2.8	220/312/387	167	293	20	4	30%	10%	99	+1.3	192/283/338	146	265	17	2	32%	9%	78	-0.1
✕Olmedo Saenz 2007 · MLB	36	51	60	42→30	48	270/335/494	224	301	28	3	21%	7%	132	+3.6	244/324/428	184	279	22	6	21%	9%	112	+2.2	184/295/333	149	200	18	0	19%	12%	82	+0.0
✕Ruben Mateo 2014 · AAA	36	47→50	60	41→45	43	254/309/471	217	272	29	3	20%	5%	118	+2.6	233/295/388	155	267	20	4	21%	5%	93	+0.8	219/285/345	126	253	17	2	21%	4%	77	-0.2
✕Mark Reynolds 2019 · MLB	35	49→56	56→65	43→50	50	251/329/439	189	316	25	3	28%	10%	116	+2.5	226/314/391	165	306	20	8	30%	11%	100	+1.3	159/283/285	126	237	13	7	35%	14%	69	-0.3
✕José Hernández 2005 · MLB	36	51→60	53→55	44→45	45	256/318/429	173	335	22	5	29%	8%	110	+2.1	237/293/376	139	296	17	5	25%	7%	88	+0.5	230/285/340	110	295	11	6	25%	6%	75	-0.3
✕Kurt Suzuki 2020 · MLB	36	50→60	58→60	40→45	50	265/327/467	202	261	27	2	12%	6%	123	+3.0	241/313/392	151	262	18	4	16%	7%	100	+1.3	217/297/333	116	245	13	1	17%	7%	82	+0.0
✕Ramon Castro 2010 · MLB	34	45	58→55	46→40	49	244/306/444	200	273	27	4	22%	8%	109	+2.0	247/311/445	198	288	27	6	24%	8%	112	+2.2	252/309/461	209	269	36	4	22%	8%	115	+0.6
✕Rod Barajas 2012 · MLB	36	43→47	56→60	46→30	43	232/274/418	186	243	26	2	18%	4%	92	+0.7	225/287/386	161	250	21	4	20%	7%	89	+0.5	202/270/342	140	220	20	0	19%	7%	74	-0.3
✕Josh Willingham 2014 · MLB	35	44→53	58→65	45	56	236/344/446	210	280	26	4	25%	12%	124	+3.1	228/337/410	182	287	22	6	27%	12%	114	+2.3	208/330/391	183	260	24	3	28%	13%	107	+1.2
✕Kit Pellow 2009 · AAA	35	49→55	59→60	45→40	45	264/325/469	205	288	28	5	20%	6%	123	+3.0	245/294/385	140	275	16	5	18%	5%	91	+0.7	232/273/340	108	250	12	1	13%	3%	71	-0.5
✕John Lindsey 2013 · AAA	36	45→51	57→60	43→30	41	241/302/437	196	290	25	2	27%	6%	107	+1.8	224/299/413	189	280	25	3	29%	7%	101	+1.4	204/288/394	190	253	27	0	30%	7%	90	+0.4
✕Chris Iannetta 2018 · MLB	35	44→54	55→60	43→45	54	231/325/416	186	282	23	2	26%	11%	110	+2.1	226/320/395	169	287	20	3	27%	11%	103	+1.6	206/309/357	151	264	17	0	27%	11%	94	+0.4
✕Ron Gant 2001 · MLB	36	46→45	62→60	43→45	57	251/333/481	230	264	30	8	19%	11%	128	+3.3	251/328/455	204	284	26	9	21%	10%	120	+2.8	254/335/461	207	289	26	8	22%	11%	124	+1.7
✕Todd Greene 2006 · MLB	35	48	59→65	46→30	44	260/296/462	202	273	28	4	18%	5%	110	+2.1	258/305/414	156	316	16	6	23%	6%	101	+1.4	284/318/420	136	383	7	0	26%	4%	107	+0.5
✕Greg Vaughn 2002 · MLB	37	45→47	59→60	47→50	57	242/336/453	212	275	27	11	23%	12%	122	+3.0	216/316/400	184	263	22	9	26%	12%	103	+1.6	161/283/311	149	201	16	6	28%	13%	73	-0.3
✕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
✕Evan Longoria 2022 · MLB	36	49→57	57→65	42→50	50	259/327/461	202	295	25	4	22%	9%	121	+2.9	246/314/447	201	306	27	3	28%	9%	113	+2.3	235/304/437	202	293	29	0	30%	9%	108	+0.9
✕Eduardo Perez 2006 · MLB	36	49	59→60	40→50	58	261/352/469	208	277	27	6	18%	11%	132	+3.6	252/327/445	193	270	25	6	17%	9%	118	+2.6	246/314/440	194	255	26	0	16%	8%	113	+0.8
✕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
✕Doug Mirabelli 2006 · MLB	35	50	56→50	49→30	49	254/329/453	199	316	24	6	27%	9%	120	+2.8	224/298/387	163	292	21	5	29%	8%	94	+0.9	195/271/339	144	251	20	0	30%	8%	73	-0.2

Eugenio Suárez

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps