Eddys Leonard

SS Sacramento River Cats

Age 26 R/R 5'10" / 201 lbs AAA HR -15%H -3% Svc 0.0 · Ctrl thru 2034

Overview

AAAPROSPECTMiLBFA 2035

OGV OFP35OGV rank#1117ETA2029MLB%10%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	23	AAA/A+/A/INTL2 orgs	367	.246/.327/.418	11	9	68	—	.201/.259/.357
2025	24	AAAATL	494	.239/.310/.435	20	11	69	—	.210/.262/.356
2026	25	AAASF	408	.261/.343/.469	18	8	81	—	.223/.286/.376
2027PROJ10% MLB	26	MLBSF	16	.231/.287/.380	0	0	91	0.0
2028PROJ38% MLB	27	MLBSF	84	.230/.288/.379	2	1	91	0.2
2029PROJ52% MLB	28	MLBSF	132	.229/.287/.376	4	2	90	0.2

Next 3 projected WAR 0.4Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2034Service0.0First FA2035

2027MiLB2028MiLB2029Pre-Arb$0.8M2030Pre-Arb$0.8M2031Pre-Arb$0.9M2032Arb-1$0.4M2033Ext$5M2034Ext$7M

Skills · percentileMiLB Statcast 2026 AAA

Max EV83

K%70

Z-Con%67

Speed63

Whiff%53

BB%39

Career WAR0.0 WAR median (P10 -0.3 / P90 3.4, comp-based) · star 1% · didn't stick 87%

CompsJohn Hester (age 26) · Luis Torrens (age 26) · Scott Kingery (age 27)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†91

AVG/OBP/SLG.231 / .287 / .380

PA16

HR0

K%25

BB%6

BABIP278

ISO67

MLB%10%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$3M ctrl surplus

Tools · ContractCON 50 / POW 60

Toolsscout grade

CONTACT50

scouting grade only

POWER60

scouting grade only

EYE35

scouting grade only

SPEED50

scouting grade only

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

Status MiLB

MLB Debut 2029

Service 0 yrs (est)

Team Control Through 2034

First FA Year 2035

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2029
2028	MiLB	still in minors · estimated debut 2029
2029	Pre-Arb	$0.8M	+0.2	$0.7M	+$0.0M
2030	Pre-Arb	$0.8M	+0.2	$0.6M	+$0.0M
2031	Pre-Arb	$0.9M	+0.1	$0.3M	+$0.0M (cut)
2032	Arb-1	$0.4M	—	—	—
2033	Ext	beyond projection horizon · no WAR estimate
2034	Ext	beyond projection horizon · no WAR estimate
Totals		$2M		$2M	+$0.0M

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)
2018	17	ROK	DSL Dodgers Guerrero	—	182	149	37	10	0	4	28	33	5	13	6	248	385	396	781	148	295	18	15	358	38	—	—	—	—	—	—
2019	18	ROK	AZL Dodgers Lasorda	—	200	168	47	7	4	3	27	48	2	2	4	280	386	423	808	143	367	24	14	359	52	—	—	—	—	—	—
2021	20	A+	Great Lakes Loons	—	184	164	49	10	2	8	17	42	3	3	1	299	375	530	905	232	360	23	9	397	108	—	—	—	—	—	—
2021	20	A	Rancho Cucamonga Quakes	—	308	261	77	19	2	14	34	74	12	6	2	295	401	544	945	249	362	24	11	413	97	—	—	—	—	—	—
2021	20	INTL	Leones del Escogido	—	20	18	2	1	0	0	1	4	0	0	0	111	158	167	325	56	133	20	5	144	-16	—	—	—	—	—	—
2022	21	A+	Great Lakes Loons	—	566	496	131	32	4	15	45	119	21	4	4	264	351	435	786	171	317	21	8	350	75	—	—	—	—	—	—
2022	21	INTL	Leones del Escogido	—	43	35	7	1	1	0	5	7	2	0	1	200	333	286	619	86	250	16	12	288	81	—	—	—	—	—	—
2023	22	AAA	Toledo Mud Hens	—	171	149	45	10	0	8	17	37	2	2	1	302	381	530	911	228	346	22	10	393	114	—	—	—	—	—	—
2023	22	AA	Tulsa Drillers	—	388	350	89	20	1	11	29	85	9	3	3	254	327	411	739	157	307	22	7	331	70	—	—	—	—	—	—
2024	23	AAA	Toledo Mud Hens	—	282	255	67	15	2	10	17	74	8	7	3	263	329	455	783	192	329	26	6	345	74	—	—	—	—	—	—
2024	23	A+	West Michigan Whitecaps	—	20	18	3	1	0	1	2	4	0	0	0	167	250	389	639	222	154	20	10	283	36	—	—	—	—	—	—
2024	23	A	Lakeland Flying Tigers	—	32	28	6	2	0	0	2	8	2	2	0	214	312	286	598	71	300	25	6	283	22	—	—	—	—	—	—
2024	23	INTL	Aguilas Cibaenas	—	33	24	4	1	0	0	6	6	2	0	0	167	375	208	583	42	222	18	18	293	84	—	—	—	—	—	—
2025	24	AAA	Gwinnett Stripers	—	494	439	105	18	4	20	36	95	9	11	5	239	310	435	745	196	255	19	7	324	69	—	—	—	—	—	—
2026	25	AAA	Sacramento River Cats	—	408	360	94	17	2	18	39	78	6	8	6	261	343	469	813	208	287	19	10	357	81	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2018	17	ROK MLE	DSL Dodgers Guerrero	—	182	157	23	6	0	2	20	40	5	13	6	146	264	223	487	76	182	22	11	224	38	—	—	—	—	—	—
2019	18	ROK MLE	AZL Dodgers Lasorda	—	200	178	34	5	3	2	17	69	2	2	4	191	269	287	556	96	277	34	8	245	52	—	—	—	—	—	—
2021	20	A+ MLE	Great Lakes Loons	—	184	169	44	9	1	7	12	56	3	3	1	260	321	450	770	189	345	30	7	328	108	—	—	—	—	—	—
2021	20	A MLE	Rancho Cucamonga Quakes	—	308	271	61	12	2	11	24	99	12	6	2	225	316	406	722	181	305	32	8	312	97	—	—	—	—	—	—
2022	21	A+ MLE	Great Lakes Loons	—	566	508	111	26	3	12	33	147	21	4	4	219	294	352	646	134	273	26	6	279	75	—	—	—	—	—	—
2023	22	AAA MLE	Toledo Mud Hens	—	171	154	43	8	0	7	12	45	2	2	1	279	339	468	807	188	323	26	7	337	114	—	—	—	—	—	—
2023	22	AA MLE	Tulsa Drillers	—	388	358	77	17	1	8	21	101	9	3	3	215	276	335	611	120	280	26	5	271	70	—	—	—	—	—	—
2024	23	AAA MLE	Toledo Mud Hens	—	282	260	55	12	2	9	12	87	8	7	3	212	268	377	645	165	272	31	4	278	74	—	—	—	—	—	—
2024	23	A+ MLE	West Michigan Whitecaps	—	20	19	3	1	0	1	1	5	0	0	0	158	200	368	568	211	136	25	5	222	36	—	—	—	—	—	—
2024	23	A MLE	Lakeland Flying Tigers	—	32	29	4	1	0	0	1	11	2	2	0	138	219	172	391	34	244	34	3	200	22	—	—	—	—	—	—
2025	24	AAA MLE	Gwinnett Stripers	—	494	452	95	13	4	15	23	117	9	11	5	210	262	356	619	146	236	24	5	270	69	—	—	—	—	—	—
2026	25	AAA MLE	Sacramento River Cats	—	408	372	83	14	2	13	27	93	6	8	6	223	286	376	663	153	261	23	7	288	81	—	—	—	—	—	—
2018	17	ROK MLE	DSL Dodgers Guerrero	—	182	157	23	6	0	2	20	40	5	13	6	146	264	223	487	76	183	22	11	224	38	—	—	—	—	—	—
2018	17	ROK RAW	DSL Dodgers Guerrero	—	182	149	37	10	0	4	28	33	5	13	6	248	385	396	781	148	295	18	15	358	38	—	—	—	—	—	—
2019	18	ROK MLE	AZL Dodgers Lasorda	—	200	178	34	5	3	2	17	69	2	2	4	191	269	287	556	96	291	34	8	245	52	—	—	—	—	—	—
2019	18	ROK RAW	AZL Dodgers Lasorda	—	200	168	47	7	4	3	27	48	2	2	4	280	386	423	808	143	367	24	14	359	52	—	—	—	—	—	—
2021	20	A MLE	3 teams	—	512	458	110	22	3	19	37	161	15	9	3	240	318	426	743	186	325	31	7	318	101	—	—	—	—	—	—
2021	20	A RAW	3 teams	—	512	443	128	30	4	22	52	120	15	9	3	289	382	524	906	235	350	23	10	397	101	—	—	—	—	—	—
2022	21	A+ MLE	2 teams	—	609	546	120	28	3	13	35	158	23	4	5	220	295	353	648	134	282	26	6	279	75	—	—	—	—	—	—
2022	21	A+ RAW	2 teams	—	609	531	138	33	5	15	50	126	23	4	5	260	349	426	775	166	312	21	8	345	75	—	—	—	—	—	—
2023	22	AA MLE	2 teams	—	559	511	120	25	1	15	34	146	11	5	4	235	297	376	672	141	297	26	6	291	83	—	—	—	—	—	—
2023	22	AA RAW	2 teams	—	559	499	134	30	1	19	46	122	11	5	4	269	344	447	790	178	319	22	8	350	83	—	—	—	—	—	—
2024	23	AAA MLE	4 teams	—	367	336	68	15	2	11	16	113	12	9	3	202	264	357	621	155	266	31	4	267	67	—	—	—	—	—	—
2024	23	AAA RAW	4 teams	—	367	325	80	19	2	11	27	92	12	9	3	246	327	418	745	172	308	25	7	331	67	—	—	—	—	—	—
2025	24	AAA MLE	Gwinnett Stripers	—	494	452	95	13	4	15	23	117	9	11	5	210	262	356	619	146	243	24	5	270	69	—	—	—	—	—	—
2025	24	AAA RAW	Gwinnett Stripers	—	494	439	105	18	4	20	36	95	9	11	5	239	310	435	745	196	255	19	7	324	69	—	—	—	—	—	—
2026	25	AAA MLE	Sacramento River Cats	—	408	372	83	14	2	13	27	93	6	8	6	223	286	376	663	153	262	23	7	288	81	—	—	—	—	—	—
2026	25	AAA RAW	Sacramento River Cats	—	408	360	94	17	2	18	39	78	6	8	6	261	343	469	813	208	287	19	10	357	81	—	—	—	—	—	—
2018	17	ROK MLE	DSL Dodgers Guerrero	—	182	155	23	6	0	2	20	40	5	13	6	148	264	226	490	77	182	22	11	224	38	—	—	—	—	—	—
2019	18	ROK MLE	AZL Dodgers Lasorda	—	200	179	34	5	3	2	17	69	2	2	4	190	269	285	554	95	277	34	8	245	52	—	—	—	—	—	—
2021	20	A MLE	3 teams	—	512	455	110	22	3	19	37	161	15	9	3	242	318	429	746	187	320	31	7	318	101	—	—	—	—	—	—
2022	21	A+ MLE	2 teams	—	609	546	120	28	3	13	35	158	23	4	5	220	295	353	648	134	273	26	6	279	75	—	—	—	—	—	—
2023	22	AA MLE	2 teams	—	559	509	120	25	1	15	34	146	11	5	4	236	297	377	674	141	293	26	6	291	83	—	—	—	—	—	—
2024	23	AAA MLE	4 teams	—	367	336	68	15	2	11	16	113	12	9	3	202	264	357	621	155	261	31	4	267	67	—	—	—	—	—	—
2025	24	AAA MLE	Gwinnett Stripers	—	494	459	95	13	4	15	23	117	9	11	5	207	262	351	613	144	236	24	5	270	69	—	—	—	—	—	—
2026	25	AAA MLE	Sacramento River Cats	—	408	372	83	14	2	13	27	93	6	8	6	223	286	376	663	153	261	23	7	288	81	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	23	AAA MLE	4 teams	—	367	336	68	15	2	11	16	113	12	9	3	202	264	357	621	155	261	31	4	267	67	—	—	—	—	—	—
2025	24	AAA MLE	Gwinnett Stripers	—	494	459	95	13	4	15	23	117	9	11	5	207	262	351	613	144	236	24	5	270	69	—	—	—	—	—	—
2026	25	AAA MLE	Sacramento River Cats	—	408	372	83	14	2	13	27	93	6	8	6	223	286	376	663	153	261	23	7	288	81	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	26	MLB MLE	SF	10%	380	350	83	14	3	12	21	91	6	7	4	236	292	393	684	157	282	24	6	303	91	-4	-0	+0	+4	+8	0.4
▸ 2027 — real world (MLB)
2027	26	MLB CTX	SF	10%	16	15	3	1	0	0	1	4	0	0	0	231	287	380	667	149	278	25	6	296	91	-0	+0	+0	+0	+0	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	27	MLB MLE	SF	38%	225	206	48	8	1	7	13	54	4	4	2	235	292	391	683	156	282	24	6	303	91	-2	+0	+0	+2	+5	0.5
2029	28	MLB MLE	SF	52%	253	232	56	10	2	8	15	61	4	4	2	234	292	388	679	154	282	24	6	301	90	-3	+0	-1	+3	+5	0.5
2030	29	MLB MLE	SF	57%	263	241	57	10	2	8	16	64	4	3	2	232	290	383	673	150	281	24	6	299	88	-4	-0	-1	+3	+6	0.3
2031	30	MLB MLE	SF	60%	269	247	58	10	2	8	16	66	4	2	2	230	288	377	665	147	280	25	6	296	86	-4	-0	-2	+3	+6	0.2
2032	31	MLB MLE	SF	62%	259	237	54	10	1	7	16	64	4	0	1	227	285	369	655	142	278	25	6	291	83	-5	-0	-3	+3	+6	0.0
2028	27	MLB CTX	SF	38%	84	78	18	3	1	2	5	20	1	1	1	230	288	379	666	148	278	24	6	296	91	-1	-0	+0	+1	+2	0.2
2029	28	MLB CTX	SF	52%	132	121	28	5	1	4	8	32	2	2	1	229	287	376	663	146	278	24	6	295	90	-2	+0	-0	+1	+3	0.2
2030	29	MLB CTX	SF	57%	150	138	32	6	1	4	9	36	2	2	1	228	286	371	657	143	277	24	6	292	88	-2	+0	-1	+2	+3	0.2
2031	30	MLB CTX	SF	60%	162	149	33	6	1	4	10	40	2	1	1	226	284	365	650	140	276	25	6	290	86	-3	-0	-1	+2	+4	0.1
2032	31	MLB CTX	SF	62%	160	147	33	6	1	4	10	40	2	0	1	223	281	358	640	135	274	25	6	285	83	-3	-0	-2	+2	+3	-0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	688	633	144	26	5	18	42	168	9	6	5	227	285	370	655	142	279	24	6	291	80	-10	-1	-4	+7	+15	0.7
/ 162G	—	A+C		—	650	598	137	25	5	17	40	159	9	6	5	229	288	373	661	144	282	24	6	291	80	-10	-1	-4	+7	+14	0.7
Career	—	MLE		—	4755	4315	960	182	27	133	294	1243	106	77	46	222	288	370	658	147	279	26	6	286	80	-20	-1	-7	+15	+31	1.8
/ 162G	—	MLE		—	650	590	131	25	4	18	40	170	14	11	6	222	287	369	656	147	278	26	6	286	80	-9	-0	-3	+7	+14	0.8

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 AAASacramento River Cats · 408 PAwOBA .348 → .288 (−60)K% 19.1% → 22.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.12%	÷1.000	×1.200	—	—	22.94%
BB% (unintentional) /PA	9.31%	÷1.000	×0.690	—	×1.018	6.54%
HBP% /PA	1.47%	—	×0.940	—	×1.018	1.41%
Singles /BIP	20.21%	÷1.000	×0.930	×1.003	×1.018	19.19%
Doubles /BIP	6.03%	÷1.000	×0.830	×1.003	×1.018	5.11%
Triples /BIP	0.71%	÷1.000	×0.970	×1.003	×1.018	0.70%
Home runs /BIP	6.38%	÷1.000	×0.700	—	×1.018	4.55%

Factors used: league row International League. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 26 vs a level average of 27.2 → +1.8% on BB/HBP/hit rates (1.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.003.

Result: wOBA .348 → .288; ISO .208 → .158; BABIP .287 → .261. 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).

2025 AAAGwinnett Stripers · 494 PAwOBA .321 → .270 (−51)K% 19.2% → 23.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.23%	÷0.976	×1.200	—	—	23.64%
BB% (unintentional) /PA	7.29%	÷1.140	×0.690	—	×1.033	4.56%
HBP% /PA	1.82%	—	×0.940	—	×1.033	1.77%
Singles /BIP	18.31%	÷0.968	×0.930	×0.995	×1.033	18.08%
Doubles /BIP	5.23%	÷1.162	×0.830	×0.995	×1.033	3.84%
Triples /BIP	1.16%	÷0.900	×0.970	×0.995	×1.033	1.29%
Home runs /BIP	5.81%	÷0.961	×0.700	—	×1.033	4.37%

Factors used: league row International League. Park (home-season share, regressed): HR 92, 1B 94, 2B 132, 3B 80, K 95, BB 128 — applied at half strength. Age: age 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.995.

Result: wOBA .321 → .270; ISO .196 → .154; BABIP .255 → .236. 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).

2024 AAAToledo Mud Hens · 282 PAwOBA .338 → .278 (−60)K% 26.2% → 30.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.24%	÷1.022	×1.200	—	—	30.82%
BB% (unintentional) /PA	6.03%	÷1.016	×0.690	—	×1.048	4.29%
HBP% /PA	2.84%	—	×0.940	—	×1.048	2.79%
Singles /BIP	22.10%	÷1.117	×0.930	×0.961	×1.048	18.53%
Doubles /BIP	8.29%	÷1.049	×0.830	×0.961	×1.048	6.61%
Triples /BIP	1.10%	÷1.070	×0.970	×0.961	×1.048	1.01%
Home runs /BIP	5.52%	÷0.792	×0.700	—	×1.048	5.12%

Factors used: league row International League. Park (home-season share, regressed): HR 58, 1B 123, 2B 110, 3B 114, K 104, BB 103 — 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 ×0.961.

Result: wOBA .338 → .278; ISO .192 → .165; BABIP .329 → .272. 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).

2024 ALakeland Flying Tigers · 32 PAwOBA .276 → .200 (−76)K% 25.0% → 33.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷1.028	×1.360	—	—	33.08%
BB% (unintentional) /PA	6.25%	÷1.061	×0.690	—	×0.980	3.98%
HBP% /PA	6.25%	—	×0.780	—	×0.980	4.78%
Singles /BIP	20.00%	÷0.980	×0.920	—	×0.980	18.40%
Doubles /BIP	10.00%	÷1.351	×0.830	—	×0.980	6.02%
Triples /BIP	0.00%	÷1.106	×0.910	—	×0.980	0.00%
Home runs /BIP	0.00%	÷1.099	×0.800	—	×0.980	0.00%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 120, 1B 96, 2B 170, 3B 121, K 106, BB 112 — applied at half strength. Age: age 24 vs a level average of 22.0 → −2.0% on BB/HBP/hit rates (2.0 yr older than average).

Result: wOBA .276 → .200; ISO .071 → .040; BABIP .300 → .244. 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).

2024 A+West Michigan Whitecaps · 20 PAwOBA .275 → .222 (−53)K% 20.0% → 26.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.00%	÷0.957	×1.270	—	—	26.55%
BB% (unintentional) /PA	10.00%	÷1.026	×0.710	—	×0.988	6.84%
HBP% /PA	0.00%	—	×0.790	—	×0.988	0.00%
Singles /BIP	7.14%	÷1.021	×0.920	—	×0.988	6.36%
Doubles /BIP	7.14%	÷0.892	×0.810	—	×0.988	6.41%
Triples /BIP	0.00%	÷0.900	×0.850	—	×0.988	0.00%
Home runs /BIP	7.14%	÷0.889	×0.800	—	×0.988	6.35%

Factors used: league row Midwest League. Park (home-season share, regressed): HR 78, 1B 104, 2B 78, 3B 80, K 91, BB 105 — applied at half strength. Age: age 24 vs a level average of 22.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average).

Result: wOBA .275 → .222; ISO .222 → .189; BABIP .154 → .136. 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 AATulsa Drillers · 388 PAwOBA .323 → .271 (−52)K% 21.9% → 26.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.91%	÷1.023	×1.220	—	—	26.11%
BB% (unintentional) /PA	7.47%	÷0.973	×0.700	—	×1.027	5.52%
HBP% /PA	2.32%	—	×0.870	—	×1.027	2.07%
Singles /BIP	21.51%	÷0.992	×0.920	×0.974	×1.027	19.95%
Doubles /BIP	7.55%	÷0.942	×0.840	×0.974	×1.027	6.73%
Triples /BIP	0.38%	÷0.900	×0.940	×0.974	×1.027	0.39%
Home runs /BIP	4.15%	÷1.083	×0.800	—	×1.027	3.15%

Factors used: league row TL. Park (home-season share, regressed): HR 117, 1B 98, 2B 88, 3B 80, K 105, BB 95 — 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 ×0.974.

Result: wOBA .323 → .271; ISO .157 → .125; BABIP .307 → .280. 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 AAAToledo Mud Hens · 171 PAwOBA .389 → .337 (−52)K% 21.6% → 26.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.64%	÷0.995	×1.200	—	—	26.09%
BB% (unintentional) /PA	9.94%	÷1.006	×0.690	—	×1.050	7.16%
HBP% /PA	1.17%	—	×0.940	—	×1.050	1.15%
Singles /BIP	24.11%	÷0.965	×0.930	×1.005	×1.050	24.53%
Doubles /BIP	8.93%	÷1.156	×0.830	×1.005	×1.050	6.77%
Triples /BIP	0.00%	÷1.150	×0.970	×1.005	×1.050	0.00%
Home runs /BIP	7.14%	÷0.901	×0.700	—	×1.050	5.83%

Factors used: league row International League. Park (home-season share, regressed): HR 80, 1B 93, 2B 131, 3B 130, K 99, BB 101 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.005.

Result: wOBA .389 → .337; ISO .228 → .183; BABIP .346 → .323. 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).

2022 A+Great Lakes Loons · 566 PAwOBA .343 → .279 (−64)K% 21.0% → 25.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.02%	÷1.033	×1.270	—	—	25.85%
BB% (unintentional) /PA	7.95%	÷0.980	×0.710	—	×1.012	5.83%
HBP% /PA	3.71%	—	×0.790	—	×1.012	2.97%
Singles /BIP	21.22%	÷1.026	×0.920	×0.986	×1.012	18.99%
Doubles /BIP	8.49%	÷0.985	×0.810	×0.986	×1.012	6.97%
Triples /BIP	1.06%	÷1.150	×0.850	×0.986	×1.012	0.78%
Home runs /BIP	3.98%	÷1.013	×0.800	—	×1.012	3.18%

Factors used: league row Midwest League. Park (home-season share, regressed): HR 103, 1B 105, 2B 97, 3B 130, K 107, BB 96 — 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 ×0.986.

Result: wOBA .343 → .279; ISO .171 → .135; BABIP .317 → .273. 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
#1Kyle Farmerlast yr '25 career totals — 8 seasons, 2,367 PA	3.6	2,367	63	16	247	306	388	+17	+23	8.9	9.0
/162	664	18	4	+4.7	+6.4	2.5	pk7: 9
#2Shane Halter'97-'04 * career totals — 7 seasons, 2,109 PA	3.2	2,109	45	17	238*	295*	375*	+6	+26	5.3	5.3
/162	664	14	5	+2.0	+8.3	1.7	pk7: 5
#3Ed Spiezio'64-'72 * career totals — 7 seasons, 1,716 PA	2.6	1,716	39	16	238*	304*	389*	+5	+8	4.7	4.9
/162	664	15	6	+1.9	+3.3	1.8	pk7: 5
#4Adam Rosaleslast yr '17 career totals — 9 seasons, 1,756 PA	2.6	1,756	47	16	227	293	367	+6	+8	3.0	3.5
/162	664	18	6	+2.4	+3.0	1.1	pk7: 4
#5Chris Woodward'99-'11 * career totals — 9 seasons, 1,896 PA	2.9	1,896	33	9	230*	288*	354*	+9	+15	1.1	2.4
/162	664	12	3	+3.1	+5.4	0.4	pk7: 4
#6Ryan Goinslast yr '19 career totals — 7 seasons, 1,680 PA	2.5	1,680	22	6	230	279	335	+9	+21	2.0	2.0
/162	664	9	2	+3.7	+8.5	0.8	pk7: 2
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 3 projected seasons	1.1	704	20	6	233	287	382	+8	+9	1.5	1.5
/162	664	19	6	+7.1	+8.5	1.4	pk7: 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
Eddys Leonard (OGILVIE)	26	50	60	50	35	234/289/389	156	282	5	3	24%	6%	91	+0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕John Hester 2010 · MLB	26	50	48→55	51→50	39	246/283/398	152	312	14	12	26%	4%	89	+0.5	230/284/361	131	304	13	7	27%	6%	81	-0.1	210/271/326	116	281	12	2	29%	7%	68	-0.5
✕Luis Torrens 2022 · MLB	26	46→49	53→50	45→40	46	238/296/411	173	288	21	3	25%	8%	98	+1.2	233/287/378	145	304	17	3	28%	7%	87	+0.4	235/293/375	140	282	15	2	22%	6%	89	+0.2
✕Scott Kingery 2021 · MLB	27	46→52	50→55	51→55	43	231/286/395	164	297	17	13	28%	6%	91	+0.6	198/268/319	121	296	11	18	34%	8%	66	-1.1	188/230/314	126	255	15	17	32%	5%	48	-1.3
✕Andrew Knizner 2021 · MLB	26	49	47→50	49→40	46	244/301/376	132	279	16	7	19%	6%	92	+0.7	217/292/330	113	266	12	5	22%	8%	78	-0.3	229/296/347	118	278	13	3	22%	6%	83	+0.0
✕Emmanuel Rivera 2022 · MLB	26	46→56	49→55	51→45	43	234/281/379	145	278	17	8	23%	6%	84	+0.2	243/302/392	149	294	16	5	22%	7%	95	+1.0	241/305/377	136	291	14	3	22%	7%	93	+0.5
✕Wilin Rosario 2015 · MLB	26	50→54	53→60	44→45	42	260/293/433	173	293	22	5	20%	4%	101	+1.4	247/282/398	151	298	17	6	23%	4%	89	+0.5	245/272/397	152	289	19	3	23%	3%	84	+0.1
✕Mike Brosseau 2020 · MLB	26	49→56	51→55	44→45	44	251/310/416	166	297	19	8	22%	6%	104	+1.6	237/311/404	167	303	20	8	27%	8%	102	+1.5	212/287/333	121	269	18	3	27%	7%	76	-0.2
✕J.R. Towles 2010 · MLB	26	45→53	47→50	45→50	47	225/304/364	140	264	15	9	21%	7%	91	+0.6	211/291/332	121	248	12	8	19%	7%	79	-0.2	195/276/292	97	225	8	5	17%	7%	62	-0.6
✕Matthew Brown 2009 · MLB	26	46→49	52→55	41→45	42	238/290/411	174	296	19	6	26%	6%	96	+1.0	207/262/346	139	274	15	6	29%	6%	70	-0.8	183/242/307	124	247	13	4	30%	6%	51	-1.1
✕Nick Hundley 2010 · MLB	26	43→45	51→55	48→40	46	222/280/382	159	266	19	5	24%	7%	85	+0.2	238/297/390	152	299	15	4	24%	7%	93	+0.8	259/299/420	161	312	16	3	22%	5%	102	+0.8
✕Christian Arroyo 2021 · MLB	26	48→58	52→50	46→45	45	246/303/416	169	293	21	6	24%	7%	101	+1.4	239/289/379	140	288	15	8	22%	5%	88	+0.4	232/275/351	119	279	12	7	21%	4%	76	-0.2
✕Ronny Rodríguez 2019 · MLB	27	50→53	47→55	48→50	39	253/281/393	139	301	15	13	22%	4%	87	+0.4	247/281/440	193	296	25	11	25%	4%	99	+1.3	240/269/467	227	280	32	9	27%	4%	101	+1.1
✕Jose Leon 2003 · MLB	26	48	50→55	50→30	44	245/295/395	150	285	19	10	22%	6%	94	+0.9	230/279/355	125	297	15	6	27%	5%	78	-0.3	259/310/420	162	299	22	2	21%	6%	102	+0.5
✕Alan Espinoza 2017 · AAA	26	44	50	50→45	43	227/278/384	156	263	18	7	22%	5%	84	+0.2	245/287/383	138	286	16	6	20%	4%	88	+0.4	259/295/392	133	298	16	2	19%	4%	91	+0.4
✕Raudy Read 2021 · AAA	27	43→46	53→55	47→45	39	230/267/401	170	268	21	5	24%	4%	84	+0.2	241/300/423	182	297	22	5	26%	7%	103	+1.5	244/310/433	190	296	23	0	25%	7%	107	+0.7
✕Coco Montes 2024 · MLB	27	46→50	48→50	49→50	43	226/293/372	145	316	15	11	32%	8%	88	+0.4	229/288/350	121	320	11	10	30%	7%	80	-0.1	224/280/329	105	310	8	9	29%	6%	70	-0.5
✕Michael Massey 2023 · MLB	25	47→54	51→55	52→50	42	240/294/405	165	292	19	12	25%	6%	96	+1.0	242/286/399	157	280	19	8	21%	5%	91	+0.7	256/290/404	148	283	18	3	17%	4%	94	+0.6
✕Blake Sabol 2024 · MLB	26	49→50	51→55	49→50	42	242/304/403	161	339	19	9	33%	7%	99	+1.3	213/280/329	116	300	13	12	31%	8%	73	-0.6	195/265/291	95	279	10	14	32%	8%	56	-1.1
✕Aledmys Díaz 2017 · MLB	26	52→57	51→55	43→45	49	263/319/432	169	287	18	7	16%	6%	111	+2.1	252/300/414	162	272	19	7	15%	6%	100	+1.3	253/309/421	168	270	20	3	15%	6%	106	+1.0
✕Tim Olson 2006 · MLB	27	46	48→50	45→50	45	233/292/380	148	284	15	12	24%	7%	89	+0.5	225/269/352	127	292	14	12	27%	5%	74	-0.6	203/242/308	104	268	12	12	28%	5%	51	-0.9

Eddys Leonard

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps