Zach McKinstry — OGILVIE

Zach McKinstry3B Detroit Tigers

Age 31 L/R 5'11" / 180 lbs MLB HR +5%H +3% Svc 4.576 · Ctrl thru 2027 peak 1.1 · 2026

wRC+†vL 10089vR 88

AVG/OBP/SLG.234 / .308 / .384

PA442

HR10

SB14

K%22

BB%9

MLB%100%

Scouting · now → future

HIT

50→50

PWR

40→40

SPD

55→55

EYE

51↘50

trajectory · 10 yrs

1.2peak

2026

Contract

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

Status Arb-2

MLB Debut 2021

Service 4.576 yrs.days

Team Control Through 2027

First FA Year 2027

Year	Status	Salary	Proj WAR	Value	Surplus
2026	Arb-2	$4M	+1.1	$9M	+$5M
2027	Arb-3	$4M	+0.7	$3M	+$0.0M (cut)
Totals		$7M		$12M	+$5M

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
2016	21	A	2 teams	182	163	37	4	3	0	11	41	5	6	2	.227	.296	.288	.584	.061	.301	23	6	.256	54	-9	+0	+0	+1	+5	-0.3
2017	22	A+	3 teams	469	429	83	16	1	3	33	141	5	7	3	.193	.259	.256	.516	.063	.280	30	7	.233	37	-34	+0	+0	+2	+13	-1.9
2018	23	A+	3 teams	273	238	53	8	3	5	26	78	9	2	1	.223	.322	.345	.667	.122	.310	29	10	.301	88	-4	+0	+0	+1	+8	0.5
2019	24	AA	2 teams	479	444	106	18	5	16	29	123	3	8	9	.239	.290	.410	.700	.171	.293	26	6	.302	89	-6	-2	+0	+2	+14	0.8
2021	26	MLB	2 teams	343	311	69	16	3	11	24	84	4	5	3	.222	.286	.399	.685	.177	.265	24	7	.293	82	-7	-0	-2	-4	+10	-0.3
2022	27	AAA	2 teams	408	367	88	14	6	8	33	94	3	7	3	.240	.308	.376	.684	.136	.299	23	8	.301	88	-5	+0	+2	+1	+12	1.0
2023	28	MLB	Detroit Tigers	518	464	108	21	4	9	44	113	5	16	6	.233	.306	.353	.659	.121	.287	22	8	.294	83	-10	+1	+4	+2	+15	1.2
2024	29	MLB	Detroit Tigers	325	297	64	13	5	4	24	69	2	16	0	.215	.279	.333	.612	.118	.265	21	7	.273	67	-12	+3	+4	+3	+9	0.7
2025	30	MLB	Detroit Tigers	511	452	112	22	10	11	46	111	7	19	5	.248	.327	.414	.740	.166	.301	22	9	.324	106	+3	+2	+1	+2	+14	2.3
▸ 2026 Season (actual · ROS · total)
2026	31	MLB	Detroit Tigers	46	43	9	2	0	1	3	10	0	0	0	.209	.261	.326	.586	.116	.250	22	7	.262	58	-2	+0	+1	+0	+1	-0.0
ROS	31	MLB	DET	396	356	83	16	5	9	33	85	4	14	3	.233	.305	.382	.687	.149	.281	21	8	.306	92	-3	+2	+0	+1	+11	1.1
TOT	31	MLB	DET	442	399	92	18	5	10	36	95	4	14	3	.231	.301	.376	.677	.145	.277	21	8	.302	89	-6	+2	+1	+2	+13	1.1
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	32	MLB	DET	423	381	87	16	6	9	35	84	4	13	3	.228	.300	.373	.673	.144	.270	20	8	.301	89	-5	+1	-3	+2	+12	0.6
2028	33	MLB	DET	393	354	80	15	5	8	32	81	4	11	2	.226	.297	.364	.662	.138	.268	21	8	.295	84	-7	+1	-4	+1	+11	0.3
2029	34	MLB	DET	348	314	69	13	5	6	28	74	3	8	1	.220	.290	.350	.640	.131	.266	21	8	.288	79	-8	+1	-5	+1	+10	-0.1
2030	35	MLB	DET	295	266	57	10	4	5	24	66	3	6	1	.214	.287	.338	.625	.124	.263	22	8	.280	73	-9	+1	-5	+1	+8	-0.4
▸ Career Totals (MLE all levels + projections)
Career	—			5363	4836	1096	202	65	104	422	1244	61	138	42	.227	.297	.360	.657	.133	.282	23	8	.291	81	-117	+11	-8	+17	+152	5.5
/ 162G	—			650	586	133	24	8	13	51	151	7	17	5	.227	.297	.362	.658	.135	.282	23	8	.291	81	-14	+1	-1	+2	+18	0.7

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
2016	21	A	Great Lakes Loons	165	142	37	5	2	0	15	29	5	6	1	.261	.352	.324	.676	.063	.325	18	9	.309	94	-1	+1	—	—	+5	0.5
2016	21	ROK	AZL Dodgers	17	17	3	0	1	0	0	3	0	0	1	.176	.176	.294	.471	.118	.214	18	0	.201	12	-2	-0	—	—	+0	-0.2
2017	22	AA	Tulsa Drillers	45	39	10	1	1	0	6	8	0	0	0	.256	.356	.333	.689	.077	.323	18	13	.318	102	+0	+0	—	—	+1	0.1
2017	22	A+	Rancho Cucamonga Quakes	355	319	72	13	0	3	29	87	5	5	2	.226	.300	.295	.595	.069	.300	25	8	.275	68	-13	+0	—	—	+10	-0.2
2017	22	A	Great Lakes Loons	69	52	16	7	0	1	17	10	0	2	1	.308	.478	.500	.978	.192	.366	14	25	.437	193	+7	+0	—	—	+2	0.9
2018	23	AA	Tulsa Drillers	87	83	16	2	1	2	4	21	0	0	0	.193	.230	.313	.543	.120	.233	24	5	.242	44	-6	+0	—	—	+2	-0.3
2018	23	A+	Rancho Cucamonga Quakes	114	91	28	7	1	2	17	22	6	0	0	.308	.447	.473	.920	.165	.388	19	15	.415	176	+10	+0	—	—	+3	1.3
2018	23	A	Great Lakes Loons	72	53	20	2	2	3	16	16	3	2	1	.377	.542	.660	1.202	.283	.500	22	22	.516	253	+12	+0	—	—	+2	1.5
2019	24	AAA	Oklahoma City Dodgers	95	89	34	8	2	7	6	18	0	0	1	.382	.421	.753	1.174	.371	.422	19	6	.501	242	+15	-0	—	—	+3	1.8
2019	24	AA	Tulsa Drillers	384	341	95	16	4	12	37	74	3	8	8	.279	.354	.455	.809	.176	.323	19	10	.357	131	+14	-2	—	—	+11	2.3
2021	26	MLB	Los Angeles Dodgers	172	158	34	9	0	7	10	50	1	1	1	.215	.266	.405	.671	.190	.262	29	6	.291	81	-4	-0	-2	-4	+5	-0.5
2021	26	AAA	Oklahoma City Dodgers	171	147	40	8	3	7	20	26	3	4	2	.272	.371	.510	.881	.238	.287	15	12	.385	152	+10	+0	—	—	+5	1.5
2022	27	MLB	Chicago Cubs	185	166	33	6	3	5	16	52	1	7	0	.199	.273	.361	.635	.163	.257	28	9	.281	73	-6	+1	+2	+1	+5	0.5
2022	27	AAA	Oklahoma City Dodgers	223	191	64	9	4	4	27	33	2	0	3	.335	.423	.487	.910	.152	.382	15	12	.400	164	+16	-1	—	—	+6	2.2
2023	28	MLB	Detroit Tigers	518	464	107	21	4	9	44	113	5	16	6	.231	.304	.351	.655	.121	.284	22	8	.295	84	-10	+1	+4	+2	+15	1.2
2024	29	MLB	Detroit Tigers	325	297	64	14	5	4	24	69	2	16	0	.215	.279	.337	.615	.121	.265	21	7	.276	69	-11	+3	+4	+3	+9	0.8
2025	30	MLB	Detroit Tigers	511	452	117	23	11	12	46	111	7	19	5	.259	.337	.438	.775	.179	.314	22	9	.340	118	+11	+2	+1	+2	+14	3.0
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			1711	1537	355	73	23	37	140	395	16	59	12	.231	.302	.381	.682	.150	.285	23	8	.303	90	-19	+7	+9	+5	+48	5.1

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
Zach McKinstry (OGILVIE)	31	50	40	55	50	.231/.303/.378	.147	.271	10	15	19%	8%	92	+0.9	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Jace Peterson 2021 · MLB	31	48→57	47→50	55	53	.236/.314/.383	.147	.285	14	19	22%	10%	98	+1.6	.235/.321/.376	.141	.299	15	18	24%	11%	98	+1.6	.224/.316/.346	.123	.287	12	20	25%	11%	82	+0.3
✕Andy Fox 2002 · MLB	31	46→53	45→40	51→60	54	.230/.314/.354	.125	.267	13	15	19%	10%	91	+1.1	.231/.314/.327	.096	.286	8	24	20%	9%	83	+0.6	.236/.322/.314	.078	.297	4	31	20%	9%	76	+0.0
✕Brian Bogusevic 2015 · MLB	31	49→55	45	52→55	49	.239/.312/.366	.128	.299	12	16	24%	8%	92	+1.2	.254/.303/.383	.129	.316	14	17	23%	6%	92	+1.2	.262/.303/.391	.128	.322	16	17	23%	5%	91	+0.8
✕Reggie Taylor 2008 · MLB	31	51→58	49→50	52→55	47	.256/.308/.405	.149	.294	17	24	20%	6%	101	+1.8	.248/.293/.396	.148	.290	17	18	20%	6%	92	+1.2	.233/.270/.371	.137	.276	14	12	21%	5%	75	+0.0
✕Leonys Martin 2019 · MLB	31	48→55	48→50	54→60	44	.242/.297/.386	.144	.302	16	22	25%	7%	91	+1.1	.227/.294/.380	.153	.288	18	13	27%	8%	89	+0.9	.195/.271/.338	.143	.246	21	9	30%	8%	68	-0.2
✕Tim Locastro 2022 · MLB	30	47→52	45	56→60	46	.231/.321/.355	.124	.275	11	25	20%	6%	95	+1.4	.213/.294/.340	.127	.263	12	24	23%	5%	80	+0.4	.211/.301/.325	.114	.266	11	36	23%	5%	76	+0.0
✕Chris Singleton 2003 · MLB	30	53→59	45→50	54→55	46	.261/.301/.397	.136	.293	11	20	16%	5%	95	+1.4	.248/.301/.367	.119	.292	8	15	17%	7%	87	+0.8	.239/.299/.331	.092	.287	2	12	16%	8%	69	-0.2
✕Rafael Ortega 2021 · MLB	30	45→54	48→55	53→55	49	.229/.291/.377	.147	.267	15	16	21%	8%	86	+0.8	.239/.315/.390	.151	.287	17	18	22%	10%	100	+1.7	.228/.317/.360	.132	.274	14	21	21%	11%	89	+0.7
✕Jordany Valdespin 2019 · AAA	31	53→54	41→50	51→55	46	.253/.303/.351	.097	.298	8	18	18%	6%	84	+0.6	.248/.289/.376	.128	.274	15	13	15%	5%	85	+0.7	.251/.284/.372	.121	.267	16	11	13%	4%	77	+0.1
✕Don Kelly 2011 · MLB	31	51→59	44→45	55	47	.248/.292/.367	.119	.274	12	15	15%	5%	83	+0.6	.230/.287/.346	.116	.254	14	11	15%	7%	76	+0.1	.213/.285/.315	.102	.231	12	8	14%	9%	65	-0.3
✕Adrian Brown 2005 · MLB	31	47→51	42→45	51→55	52	.226/.293/.335	.108	.261	9	19	17%	8%	76	+0.1	.240/.304/.343	.103	.278	8	24	16%	8%	82	+0.5	.242/.306/.333	.091	.281	6	28	15%	8%	77	+0.1
✕Chris Duffy 2010 · MLB	30	48→58	42→45	52→60	49	.230/.295/.342	.112	.278	9	19	20%	8%	79	+0.3	.225/.277/.339	.114	.314	9	14	30%	5%	70	-0.3	.224/.271/.332	.108	.319	7	16	31%	4%	63	-0.5
✕Ender Inciarte 2021 · MLB	30	49→59	44→45	52→60	54	.240/.311/.360	.120	.271	10	19	16%	9%	90	+1.0	.226/.290/.338	.112	.276	11	12	21%	8%	76	+0.0	.220/.277/.313	.093	.271	10	12	22%	7%	60	-0.3
●Ryan Roberts 2011 · MLB	30	48→52	45→50	52→55	51	.236/.306/.365	.128	.284	12	16	21%	9%	89	+1.0	.234/.307/.370	.136	.275	15	15	20%	9%	92	+1.2	.233/.307/.361	.129	.271	15	13	19%	10%	86	+0.6
✕Alejandro De Aza 2015 · MLB	31	53→61	46→50	52→55	48	.259/.322/.395	.136	.316	12	19	21%	8%	103	+1.9	.241/.311/.378	.137	.301	12	13	23%	8%	95	+1.4	.242/.306/.359	.117	.291	10	10	20%	7%	85	+0.2
✕Grégor Blanco 2015 · MLB	31	53→59	41→45	54→60	54	.253/.329/.357	.104	.308	7	21	19%	10%	96	+1.5	.254/.332/.364	.110	.308	8	19	18%	10%	99	+1.7	.250/.335/.352	.102	.309	6	24	19%	11%	88	+0.5
✕Gorkys Hernández 2019 · MLB	31	51→57	45	47→55	47	.248/.306/.372	.124	.304	12	15	22%	7%	91	+1.1	.211/.280/.347	.136	.288	15	16	30%	8%	74	-0.1	.182/.260/.306	.124	.260	14	19	34%	9%	53	-1.4
✕Pablo Ozuna 2005 · MLB	30	48	44→40	54→55	49	.236/.300/.359	.123	.261	11	15	15%	6%	85	+0.7	.264/.309/.356	.092	.294	6	23	12%	5%	88	+0.9	.288/.324/.385	.098	.319	4	16	10%	3%	98	+0.5
✕Jason Pridie 2015 · AAA	31	46→53	45→50	55	42	.232/.275/.356	.124	.290	13	18	25%	6%	73	-0.1	.245/.293/.397	.152	.300	18	19	24%	6%	92	+1.2	.257/.308/.427	.170	.309	21	19	23%	6%	105	+1.9
✕Roger Bernadina 2014 · MLB	30	47→57	45	55→60	47	.231/.299/.356	.124	.286	12	23	23%	8%	85	+0.7	.215/.294/.333	.118	.303	11	18	30%	9%	76	+0.1	.228/.296/.347	.119	.323	12	20	31%	8%	78	+0.1

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)