Logan Wagner — OGILVIE

Logan WagnerSS Great Lakes Loons

Age 22 S/R 6'1" / 200 lbs A+ HR +15%K -3% Svc 0.0 · Ctrl thru 2035 peak 1.7 · 2030

wRC+†80

AVG/OBP/SLG.192 / .290 / .335

PA320

HR8

SB5

K%34

BB%10

MLB%0%

Scouting · now → future

HIT

20↗30

PWR

40↗55

SPD

40→40

FLD

30↗40

EYE

57↗60

trajectory · 10 yrs

2.3peak

2030

Contract

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

Status MiLB

MLB Debut 2030

Service 0 yrs (est)

Team Control Through 2035

First FA Year 2036

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2030
2027	MiLB	still in minors · estimated debut 2030
2028	MiLB	still in minors · estimated debut 2030
2029	MiLB	still in minors · estimated debut 2030
2030	Arb-2	$0.9M	+1.7	$15M	+$14M
2031	Arb-3	$0.9M	+1.7	$16M	+$15M
2032	Ext / FA-deal	$0.9M	+1.6	$15M	+$14M
2033	Ext / FA-deal	$3M	+1.3	$13M	+$10M
2034	Ext / FA-deal	$4M	+1.1	$11M	+$7M
2035	Ext / FA-deal	$4M	+0.8	$4M	-$0.3M
Totals		$14M		$74M	+$60M

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
2022	18	ROK	ACL Dodgers	58	53	8	1	0	0	4	17	1	2	1	.151	.224	.170	.394	.019	.222	29	7	.188	2	-6	+0	+0	+1	+2	-0.4
2023	19	ROK	ACL Dodgers	15	12	1	0	0	0	3	7	0	0	0	.083	.267	.083	.350	.000	.200	47	20	.161	-19	-2	+0	+0	+0	+0	-0.1
2024	20	A	Rancho Cucamonga Quakes	164	134	24	6	1	5	20	57	8	4	0	.179	.321	.351	.672	.172	.257	35	12	.300	88	-2	+1	+0	+2	+5	0.5
2025	21	A+	2 teams	601	524	89	21	2	13	61	205	11	20	3	.170	.270	.292	.562	.122	.244	34	10	.253	52	-33	+3	+0	+6	+17	-0.7
▸ 2026 Season (actual · ROS · total)
2026	22	A+	Great Lakes Loons	71	65	14	5	0	3	4	28	1	1	1	.215	.271	.431	.702	.215	.314	39	6	.296	85	-1	-0	+0	+1	+2	0.1
ROS	22	MLB	LAD	249	218	42	10	1	7	24	86	5	4	1	.193	.287	.344	.631	.151	.280	35	10	.288	78	-6	+0	-3	+3	+7	0.1
TOT	22	MLB	LAD	320	283	56	15	1	10	28	114	6	5	2	.198	.284	.364	.648	.166	.286	36	9	.289	80	-7	+0	-3	+3	+9	0.3
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	23	MLB 11%	LAD	473	414	85	20	2	14	48	145	8	8	2	.205	.300	.365	.665	.159	.274	31	10	.299	87	-7	+1	-5	+5	+13	0.7
2028	24	MLB 26%	LAD	512	446	95	21	2	17	52	152	9	8	2	.213	.308	.383	.691	.170	.277	30	10	.308	94	-4	+1	-5	+5	+15	1.2
2029	25	MLB 44%	LAD	532	463	100	22	2	18	55	155	9	8	2	.216	.311	.389	.700	.173	.279	29	10	.314	98	-1	+1	-6	+6	+15	1.5
2030	26	MLB 59%	LAD	542	471	103	23	2	19	57	157	9	8	2	.219	.315	.397	.712	.178	.280	29	11	.316	100	+0	+1	-6	+6	+15	1.7
2031	27	MLB 76%	LAD	543	471	103	23	2	19	58	158	9	8	2	.219	.316	.397	.713	.178	.280	29	11	.317	100	+0	+1	-6	+6	+15	1.7
2032	28	MLB 84%	LAD	539	467	100	22	2	18	58	158	9	7	1	.214	.313	.385	.698	.171	.280	29	11	.315	100	-0	+1	-6	+6	+15	1.6
2033	29	MLB 90%	LAD	530	459	99	22	2	18	57	157	9	6	1	.216	.314	.390	.704	.174	.279	30	11	.313	98	-1	+1	-7	+6	+15	1.3
2034	30	MLB	LAD	520	450	95	21	2	17	56	156	9	5	1	.211	.311	.380	.691	.169	.277	30	11	.310	96	-3	+1	-8	+6	+15	1.1
2035	31	MLB	LAD	506	439	91	20	2	16	54	154	8	4	0	.207	.305	.371	.677	.164	.275	30	11	.306	93	-4	+1	-8	+5	+14	0.8
2036	32	MLB	LAD	488	425	86	19	1	15	52	151	8	3	0	.202	.301	.358	.659	.155	.274	31	11	.302	89	-6	+1	-9	+5	+14	0.5
2037	33	MLB	LAD	458	399	80	18	1	14	49	145	7	3	0	.201	.299	.356	.655	.155	.272	32	11	.296	85	-8	+1	-9	+5	+13	0.1
2038	34	MLB	LAD	413	360	70	15	1	12	44	134	6	2	0	.194	.293	.342	.634	.147	.269	32	11	.289	80	-10	+0	-9	+4	+12	-0.2
2039	35	MLB	LAD	358	311	60	13	1	10	38	120	6	2	0	.193	.293	.338	.631	.145	.266	34	11	.281	73	-11	+0	-9	+4	+10	-0.6
2040	36	MLB	LAD	299	261	47	10	1	7	31	103	5	2	0	.180	.279	.307	.586	.126	.263	34	10	.272	66	-11	+0	-10	+3	+8	-0.9
▸ Career Totals (MLE all levels + projections)
Career	—			7800	6777	1378	307	27	239	821	2417	136	104	18	.203	.302	.362	.664	.159	.274	31	11	.299	87	-115	+14	-106	+84	+221	10.0
/ 162G	—			650	565	115	26	2	20	68	201	11	9	2	.204	.301	.363	.664	.159	.273	31	10	.299	87	-10	+1	-9	+7	+18	0.8

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
2022	18	ROK	ACL Dodgers	58	50	11	1	0	0	7	12	1	2	1	.220	.328	.240	.568	.020	.289	21	12	.275	69	-2	+0	—	—	+2	-0.0
2023	19	ROK	ACL Dodgers	15	11	1	0	0	0	4	5	0	0	0	.091	.333	.091	.424	.000	.167	33	27	.246	47	-1	+0	—	—	+0	-0.0
2024	20	A	Rancho Cucamonga Quakes	164	126	31	8	2	6	27	41	8	4	0	.246	.407	.484	.892	.238	.309	25	16	.392	158	+11	+1	—	—	+5	1.7
2025	21	A+	Great Lakes Loons	533	440	95	23	2	15	78	140	11	18	3	.216	.348	.380	.727	.164	.277	26	15	.331	111	+7	+2	—	—	+15	2.5
2025	21	INTL	Glendale Desert Dogs	68	55	12	2	1	2	12	17	0	2	0	.218	.358	.400	.758	.182	.270	25	18	.339	118	+1	+0	—	—	+2	0.4

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
Logan Wagner (OGILVIE)	22	20→30	40→55	40	60	.192/.290/.335	.143	.276	8	6	34%	10%	78	+0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Max Stassi 2013 · A	22	41→43	47→55	43→40	40	.210/.270/.343	.133	.290	15	4	32%	6%	69	-0.4	.216/.264/.358	.142	.286	17	3	30%	5%	70	-0.3	.208/.295/.359	.151	.271	20	0	30%	10%	81	+0.2
✕Isan Díaz 2018 · A	22	40	47→55	45	43	.203/.272/.335	.133	.289	14	8	34%	8%	68	-0.5	.205/.274/.346	.141	.290	16	8	33%	8%	72	-0.2	.204/.284/.367	.164	.263	21	5	30%	9%	75	+0.0
✕Kevin Padlo 2018 · A	22	36→40	45→55	44→50	48	.184/.270/.312	.128	.257	13	8	32%	10%	62	-0.9	.195/.278/.343	.148	.287	15	8	35%	9%	73	-0.1	.191/.263/.361	.170	.260	21	12	35%	8%	69	-0.3
✕Jose Lobatón 2007 · A	22	44	42→45	43→30	47	.212/.290/.319	.108	.298	9	5	30%	9%	71	-0.3	.217/.282/.343	.126	.297	13	3	29%	8%	74	-0.1	.241/.325/.370	.129	.305	12	0	23%	11%	94	+0.6
✕Marcus Greene Jr. 2017 · A	22	35	46→50	45→40	40	.185/.251/.313	.128	.265	15	5	35%	7%	53	-1.5	.209/.268/.329	.120	.279	13	4	28%	7%	65	-0.7	.211/.271/.321	.110	.275	12	2	27%	7%	61	-0.4
●Tom Murphy 2014 · AA	23	40→35	50→65	43→45	38	.208/.269/.365	.156	.292	18	6	34%	6%	75	-0.0	.209/.263/.380	.171	.291	21	5	35%	6%	76	+0.1	.244/.316/.459	.215	.308	30	2	30%	9%	117	+1.2
✕Eric Haase 2015 · A	22	39→41	48→65	42→40	38	.201/.253/.347	.146	.286	16	3	35%	6%	63	-0.9	.194/.252/.355	.161	.294	18	4	39%	6%	65	-0.7	.218/.277/.437	.219	.284	32	2	35%	7%	94	+0.9
✕Daniel Vellojin 2023 · AA	23	40	46→45	42→45	52	.200/.296/.328	.127	.281	14	6	32%	12%	76	+0.1	.179/.260/.279	.100	.257	10	6	32%	9%	49	-1.8	.150/.230/.230	.080	.212	8	4	32%	9%	21	-1.6
✕Yasel Antuna 2022 · A	22	39→35	46→45	43→50	43	.201/.261/.331	.130	.272	13	6	31%	7%	62	-0.9	.183/.264/.286	.103	.259	10	14	31%	9%	52	-1.6	.159/.253/.246	.087	.225	9	18	31%	10%	37	-1.7
✕Zack Collins 2018 · AA	23	37→42	47→50	42→40	46	.185/.275/.321	.137	.291	15	3	39%	11%	66	-0.6	.198/.295/.349	.151	.306	17	3	37%	12%	82	+0.5	.196/.301/.351	.156	.289	18	2	35%	13%	83	+0.4
✕Chris Williams 2019 · A	22	39→31	52→55	47→40	47	.209/.283/.369	.161	.261	21	5	29%	9%	82	+0.5	.183/.273/.325	.142	.272	16	4	36%	11%	67	-0.5	.180/.262/.367	.188	.250	27	4	39%	9%	71	-0.2
✕Johan Mieses 2017 · A	22	37→32	51→55	46→50	36	.200/.247/.364	.164	.270	19	9	34%	5%	65	-0.7	.183/.234/.337	.154	.257	20	4	37%	5%	53	-1.5	.194/.269/.375	.181	.237	26	7	31%	7%	74	-0.0
✕Isiah Gilliam 2018 · A	22	41→46	47→55	46→55	40	.208/.259/.344	.136	.280	14	6	30%	6%	64	-0.8	.196/.248/.317	.121	.315	13	7	40%	6%	53	-1.5	.217/.299/.399	.182	.339	23	19	40%	10%	92	+0.7
✕Randy Florentino 2021 · A	21	43	41→50	42→45	48	.206/.286/.310	.104	.297	8	6	31%	10%	67	-0.5	.180/.241/.263	.083	.269	8	5	34%	7%	36	-2.7	.183/.230/.260	.077	.238	8	4	26%	5%	28	-1.0
✕Brett Cumberland 2018 · A	23	41→39	46→50	38→30	36	.196/.291/.328	.133	.311	14	3	38%	6%	76	+0.1	.198/.294/.331	.133	.292	14	2	35%	8%	78	+0.2	.177/.295/.289	.111	.265	13	1	34%	8%	65	-0.3
✕Ian Rice 2017 · A	23	44→40	48→50	43→30	49	.219/.298/.359	.140	.287	16	5	28%	9%	85	+0.7	.205/.289/.350	.145	.278	18	3	31%	10%	80	+0.4	.184/.274/.315	.131	.252	17	0	32%	10%	62	-0.5
●Yonathan Perlaza 2022 · A	23	45→52	48→60	43→50	41	.226/.282/.367	.142	.310	16	7	32%	7%	80	+0.4	.229/.298/.413	.184	.301	21	11	29%	9%	99	+1.7	.235/.307/.417	.182	.303	19	12	28%	9%	100	+1.6
✕Omar Martinez 2023 · A	22	41→38	43→45	42→40	46	.202/.287/.312	.110	.290	11	5	32%	9%	69	-0.4	.196/.277/.322	.126	.291	15	5	35%	9%	67	-0.5	.180/.261/.303	.123	.268	16	3	37%	9%	53	-1.1
✕Sherten Apostel 2020 · A	21	37→32	47→50	44→40	45	.194/.269/.328	.134	.267	16	4	33%	9%	66	-0.6	.198/.261/.326	.128	.305	15	4	38%	7%	61	-1.0	.191/.253/.324	.132	.303	16	0	40%	6%	54	-0.7
✕Ryan Costello 2019 · A	23	42→39	50	43→30	48	.218/.288/.374	.156	.274	18	4	27%	9%	85	+0.7	.201/.278/.341	.140	.288	16	3	33%	9%	72	-0.2	.168/.257/.303	.134	.252	16	0	37%	10%	52	-1.1

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)