Mitch Haniger — OGILVIE

Mitch HanigerRF Seattle Mariners

Age 35 R/R 6'1" / 214 lbs MLB HR +3% Svc 10.000 · Ctrl thru 2026

wRC+†vL 2988vR 95

AVG/OBP/SLG.218 / .292 / .375

PA318

HR11

K%29

BB%9

xwOBA.298

Barrel%9.0%

MLB%100%

Scouting · now → future

HIT

40→40

PWR

50→50

SPD

40→40

EYE

54↗60

Barrel%

569.0

xwOBA

410.298

Avg EV

7290.6

Whiff%

290.133

Chase%

750.268

Speed

2326.2

Bat Spd

6572.9

Contract

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

Status FA

MLB Debut 2016

Service 10.000 yrs.days

Team Control Through 2026

First FA Year 2027

Year	Status	Salary	Proj WAR	Value	Surplus
2026	Ext / FA-deal	$1M	—	—	—
Totals		$1M		$-0.8M	-$2M

Career Projections (MLE)

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	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
2012	21	A	Wisconsin Timber Rattlers	58	51	12	3	0	1	5	17	1	1	0	.235	.316	.353	.669	.118	.324	29	9	.295	84	-1	+0	+0	-1	+2	0.0
2013	22	A+	3 teams	656	593	126	36	4	11	48	159	8	10	2	.212	.280	.342	.623	.130	.267	24	7	.274	68	-24	+1	+0	-7	+19	-1.2
2014	23	AA	2 teams	317	291	65	10	1	11	14	67	6	4	0	.223	.273	.378	.651	.155	.249	21	4	.279	72	-10	+1	+0	-3	+9	-0.4
2015	24	A+	2 teams	400	367	92	21	3	12	21	94	4	12	6	.251	.298	.422	.721	.172	.297	24	5	.313	98	-1	+0	+0	-4	+11	0.6
2016	25	AAA	3 teams	671	587	144	28	5	23	61	157	14	12	4	.245	.331	.428	.758	.182	.292	23	9	.327	108	+6	+1	+1	+2	+19	3.0
2017	26	MLB	2 teams	458	410	111	26	2	18	36	99	10	5	4	.271	.344	.476	.820	.205	.316	22	8	.354	129	+15	-1	-2	-5	+13	2.1
2018	27	MLB	Seattle Mariners	683	596	173	42	4	24	70	148	10	8	2	.290	.374	.495	.869	.205	.346	22	10	.369	140	+31	+1	-5	-7	+19	4.0
2019	28	MLB	Seattle Mariners	283	246	54	13	1	16	30	81	5	4	0	.220	.317	.476	.792	.256	.252	29	11	.334	114	+4	+1	+1	-3	+8	1.1
2021	30	MLB	Seattle Mariners	691	620	160	24	2	40	54	169	9	1	0	.258	.327	.497	.823	.239	.286	24	8	.352	128	+22	+0	-11	-7	+20	2.4
2022	31	MLB	2 teams	280	249	61	8	0	13	26	69	3	0	0	.245	.324	.434	.757	.189	.284	25	9	.326	108	+2	+0	-0	-3	+8	0.7
2023	32	MLB	2 teams	264	242	49	13	1	7	16	70	5	1	0	.202	.266	.351	.617	.149	.253	27	6	.276	69	-9	+0	-4	-3	+7	-0.8
2024	33	MLB	Seattle Mariners	423	380	80	12	0	12	40	126	2	0	0	.211	.289	.337	.626	.126	.280	30	9	.280	72	-13	+0	-6	-5	+12	-1.2
▸ 2026 Season
2026	35	MLB	SEA	318	285	64	12	1	11	27	91	3	2	1	.225	.298	.389	.688	.165	.280	29	8	.300	88	-4	+0	-4	-3	+9	-0.2
▸ Career Totals (MLE all levels + projections)
Career	—			5502	4917	1191	248	24	199	448	1347	80	60	19	.242	.316	.424	.740	.182	.290	24	8	.320	103	+18	+4	-29	-49	+156	10.2
/ 162G	—			650	581	141	29	3	24	53	159	9	7	2	.243	.316	.427	.743	.184	.290	24	8	.320	103	+2	+1	-3	-6	+18	1.2

Historical Stats — Raw (Per Stint)

Actual MLB + MiLB stats as they happened, one row per stint at each level. Use this to see what really got recorded; the table above shows MLB-equivalent translations + projections.

Year	Age	Lvl	Team	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
2012	21	A	Wisconsin Timber Rattlers	58	49	14	4	0	1	7	13	1	1	0	.286	.386	.429	.815	.143	.361	22	12	.362	135	+2	+0	—	—	+2	0.4
2013	22	A+	Brevard County Manatees	365	328	82	24	3	6	32	68	4	2	2	.250	.324	.396	.721	.146	.298	19	9	.323	105	+2	-0	—	—	+10	1.2
2013	22	A	Wisconsin Timber Rattlers	178	145	43	12	2	5	25	24	3	7	0	.297	.410	.510	.921	.214	.314	13	14	.396	161	+12	+1	—	—	+5	1.9
2013	22	INTL	Surprise Saguaros	113	100	28	8	0	4	11	18	1	1	0	.280	.357	.480	.837	.200	.304	16	10	.367	139	+5	+0	—	—	+3	0.9
2014	23	AA	Mobile BayBears	301	267	70	10	1	10	22	45	6	4	0	.262	.332	.419	.752	.157	.278	15	7	.330	111	+4	+1	—	—	+9	1.3
2014	23	ROK	ACL D-backs	16	15	3	1	0	1	1	6	0	0	0	.200	.250	.467	.717	.267	.250	38	6	.310	96	-0	+0	—	—	+0	0.0
2015	24	AA	Mobile BayBears	174	153	43	10	1	1	16	32	2	4	4	.281	.357	.379	.736	.098	.341	18	9	.329	110	+2	-1	—	—	+5	0.6
2015	24	A+	Visalia Rawhide	226	202	67	16	3	12	17	39	2	8	2	.332	.389	.619	1.008	.287	.353	17	8	.426	184	+21	+1	—	—	+6	2.9
2016	25	MLB	Arizona Diamondbacks	123	109	25	2	1	5	12	27	1	0	0	.229	.311	.404	.715	.174	.256	22	10	.318	101	+0	+0	+1	+2	+3	0.7
2016	25	AAA	Reno Aces	312	261	89	20	3	20	39	62	5	8	1	.341	.436	.670	1.107	.330	.373	20	12	.464	213	+40	+1	—	—	+9	5.1
2016	25	AA	Mobile BayBears	236	197	58	14	2	5	30	37	8	4	3	.294	.409	.462	.870	.168	.340	16	13	.389	156	+15	-0	—	—	+7	2.2
2017	26	MLB	Seattle Mariners	410	369	104	25	2	16	31	93	9	5	4	.282	.352	.491	.843	.209	.338	23	8	.371	142	+19	-1	-2	-5	+12	2.4
2017	26	AAA	Tacoma Rainiers	48	39	10	2	0	3	7	5	1	0	0	.256	.383	.538	.921	.282	.219	10	15	.395	160	+3	+0	—	—	+1	0.5
2018	27	MLB	Seattle Mariners	683	596	170	38	4	26	70	148	10	8	2	.285	.370	.493	.863	.208	.336	22	10	.378	147	+36	+1	-5	-7	+19	4.6
2019	28	MLB	Seattle Mariners	283	246	54	13	1	15	30	81	5	4	0	.220	.317	.463	.780	.244	.257	29	11	.342	120	+6	+1	+1	-3	+8	1.3
2021	30	MLB	Seattle Mariners	691	620	157	23	2	39	54	169	9	1	0	.253	.322	.485	.808	.232	.281	24	8	.351	127	+21	+0	-11	-7	+20	2.3
2022	31	MLB	Seattle Mariners	247	224	55	8	0	11	20	65	1	0	0	.246	.310	.429	.739	.183	.293	26	8	.326	107	+2	+0	-0	-3	+7	0.6
2022	31	AAA	Tacoma Rainiers	33	21	5	0	0	2	10	3	2	0	0	.238	.515	.524	1.039	.286	.188	9	30	.464	213	+4	+0	—	—	+1	0.5
2023	32	MLB	San Francisco Giants	229	211	44	13	1	6	15	65	2	1	0	.209	.268	.365	.632	.156	.270	28	7	.281	74	-7	+0	-4	-3	+6	-0.7
2023	32	AAA	Sacramento River Cats	35	30	5	0	0	2	2	4	3	0	0	.167	.286	.367	.652	.200	.125	11	6	.299	87	-1	+0	—	—	+1	0.0
2024	33	MLB	Seattle Mariners	423	380	79	12	0	12	40	126	2	0	0	.208	.287	.334	.621	.126	.276	30	9	.283	74	-12	+0	-6	-5	+12	-1.1
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			3089	2755	688	134	11	130	272	774	39	19	6	.250	.326	.448	.774	.198	.298	25	9	.341	119	+66	+1	-25	-31	+88	10.1

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
Mitch Haniger (OGILVIE)	35	40	50	40	60	.218/.292/.375	.157	.280	11	2	29%	9%	88	+0.5	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Valentino Pascucci 2013 · AAA	34	41→45	52→55	40→45	48	.212/.296/.376	.164	.302	21	2	35%	10%	89	+1.0	.219/.308/.390	.171	.317	23	4	35%	10%	98	+1.6	.205/.315/.394	.189	.279	29	0	36%	12%	98	+0.8
✕Matt McBride 2019 · MLB	34	40→50	50→55	42→40	45	.211/.268/.372	.161	.245	18	4	23%	6%	76	+0.0	.216/.266/.391	.175	.257	23	6	26%	6%	80	+0.4	.184/.222/.370	.186	.199	30	0	27%	4%	53	-0.4
●Scott McClain 2007 · MLB	35	39→45	54→55	43→40	43	.215/.265/.391	.175	.246	23	5	24%	6%	80	+0.4	.224/.284/.404	.180	.258	24	5	24%	8%	91	+1.1	.225/.292/.412	.187	.254	26	3	23%	8%	95	+1.3
✕Shelley Duncan 2013 · MLB	33	42→43	54→60	40→45	51	.223/.301/.401	.178	.257	23	4	24%	9%	98	+1.6	.197/.264/.333	.136	.240	16	4	25%	8%	64	-0.8	.164/.225/.275	.111	.202	12	0	26%	7%	30	-2.3
✕Kole Calhoun 2023 · MLB	35	41→51	52→60	44→50	46	.218/.290/.383	.164	.272	21	5	28%	8%	88	+0.9	.225/.290/.379	.154	.278	17	4	25%	7%	87	+0.8	.223/.290/.384	.161	.264	18	0	22%	7%	86	+0.6
●Andy Tracy 2009 · AAA	35	44→48	52→55	43→45	49	.231/.300/.399	.168	.274	20	5	24%	8%	96	+1.5	.231/.302/.413	.182	.280	23	6	25%	9%	101	+1.8	.220/.298/.407	.187	.267	24	5	27%	9%	97	+1.2
✕Adam Rosales 2019 · MLB	36	40→48	50→55	43→45	42	.212/.268/.367	.156	.271	19	6	29%	6%	75	-0.0	.203/.251/.328	.125	.275	15	6	31%	5%	57	-1.2	.172/.213/.259	.088	.245	12	2	34%	4%	19	-1.9
●Kevin Barker 2010 · MLB	35	44→47	53→55	44→40	47	.232/.294/.405	.173	.275	22	3	25%	8%	95	+1.4	.255/.320/.425	.170	.295	18	4	20%	8%	111	+2.5	.273/.342/.440	.167	.313	16	1	17%	9%	123	+1.9
✕Mike Hessman 2012 · MLB	34	37	55→65	47→45	42	.202/.273/.385	.183	.265	23	4	33%	7%	82	+0.5	.198/.253/.393	.195	.250	27	3	33%	6%	76	+0.1	.195/.260/.385	.189	.236	26	3	30%	7%	75	-0.0
✕Chad Mottola 2006 · MLB	34	41→44	51→55	40→45	41	.218/.260/.378	.160	.253	20	5	23%	5%	74	-0.1	.224/.263/.377	.153	.270	18	8	24%	5%	75	-0.0	.224/.262/.376	.153	.268	18	8	24%	4%	70	-0.2
✕Cody Ransom 2011 · MLB	35	42→41	53→55	48→50	44	.221/.281/.393	.172	.275	20	8	28%	7%	87	+0.8	.220/.290/.402	.182	.297	22	8	32%	8%	93	+1.3	.209/.290/.400	.192	.287	24	6	34%	10%	89	+0.5
✕Jonathan Aceves 2013 · AAA	35	44	49→55	41→30	42	.227/.275/.375	.148	.279	18	5	26%	6%	79	+0.3	.223/.277/.366	.143	.268	18	4	24%	6%	78	+0.2	.243/.313/.364	.121	.289	14	1	20%	7%	90	+0.5
✕Brooks Conrad 2015 · MLB	35	41→44	56→55	37→50	41	.220/.276/.411	.190	.285	25	3	32%	7%	89	+1.0	.194/.254/.321	.127	.261	14	6	30%	6%	57	-1.2	.146/.214/.229	.083	.201	8	3	30%	6%	14	-2.2
✕Adam Hyzdu 2006 · MLB	34	45→44	49→50	39→45	51	.227/.309/.373	.146	.293	17	6	27%	10%	93	+1.3	.222/.298/.372	.150	.280	17	8	26%	10%	88	+0.9	.210/.290/.359	.149	.258	17	7	25%	10%	81	+0.4
✕Shawn Wooten 2006 · MLB	34	46→45	47→50	38→30	46	.230/.284/.359	.128	.256	16	3	18%	6%	79	+0.3	.215/.262/.313	.098	.261	10	3	21%	5%	57	-1.2	.197/.245/.263	.066	.249	6	1	22%	5%	35	-1.1
✕Brian Burgamy 2016 · AAA	35	47→49	53→55	42→50	49	.242/.311/.412	.170	.293	21	5	25%	9%	104	+2.0	.232/.302/.359	.127	.312	13	9	28%	9%	86	+0.8	.232/.308/.346	.114	.318	10	10	28%	9%	86	+0.6
✕John Buck 2014 · MLB	34	42→52	51→55	43→30	51	.219/.300/.370	.151	.258	20	3	24%	9%	89	+1.0	.232/.300/.359	.127	.289	15	5	24%	8%	85	+0.7	.238/.300/.312	.074	.311	6	0	24%	7%	70	-0.1
✕Darnell McDonald 2013 · MLB	34	45→55	49→55	45→55	49	.227/.295/.376	.149	.271	16	10	23%	8%	88	+0.9	.215/.274/.325	.110	.264	10	10	22%	7%	66	-0.6	.209/.261/.294	.086	.257	6	12	21%	6%	50	-1.0
✕Jason Michaels 2011 · MLB	35	47→55	51→50	43→45	50	.239/.307/.409	.170	.270	18	5	19%	8%	102	+1.8	.222/.280/.352	.130	.260	13	5	19%	7%	76	+0.0	.190/.243/.274	.084	.229	7	2	20%	6%	34	-0.7
✕Ryan Raburn 2015 · MLB	34	43→53	50→60	45→50	47	.222/.287/.375	.153	.266	18	4	24%	8%	85	+0.7	.242/.321/.417	.175	.308	20	3	26%	10%	109	+2.4	.242/.330/.425	.182	.325	20	1	30%	10%	108	+0.8

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)