Josue De Paula

CF Tulsa Drillers

Age 22 L/L 6'3" / 185 lbs AA HR +8%BB -8% Svc 0.070 · Ctrl thru 2032

Overview

AA40-MANROOKIEPre-ArbFA 2033

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	19	A+/A2 orgs	481	.268/.407/.405	10	27	88	—	.223/.333/.325
2025	20	AA/A+LAD	445	.250/.392/.400	12	32	87	—	.216/.324/.337
2026	21	AALAD	588	.303/.403/.547	27	31	126	—	.271/.347/.473
2026	21	MLBLAD	42	.323/.500/.581	1	1	218	0.9
2027PROJ10% MLB	22	MLBLAD	21	.259/.346/.450	1	1	126	0.1
2028PROJ59% MLB	23	MLBLAD	362	.263/.350/.466	15	13	131	2.1
2029PROJ73% MLB	24	MLBLAD	446	.266/.352/.475	19	16	133	2.8

Last 3 seasons WAR 0.9 · Next 3 projected WAR 5.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2032Service0.070First FA2033

2027Pre-Arb$0.8M2028Pre-Arb$0.8M2029Pre-Arb$0.8M2030Arb-1$10M2031Arb-2$17M2032Arb-3$25M

Skills · percentileMiLB Statcast 2026 AA

Whiff%97

K%94

wOBA92

wRC+92

Z-Con%90

ISO88

Form.269/.381/.471 ▲▲ rolling true talent (60d window) · proj .262/.347/.453

Career WAR8.8 WAR median (P10 0.0 / P90 53, comp-based) · star 15% · didn't stick 26%

CompsCarlos Correa (age 22) · Gleyber Torres (age 22) · Adrian Beltré (age 22)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†126

AVG/OBP/SLG.259 / .346 / .450

PA21

HR1

K%19

BB%10

BABIP284

ISO211

MLB%10%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$61M ctrl surplus

Tools · Recent Form · Contract

ToolsStatcast %ile · 2026

CONTACT

xAVG

900.311

POWER

Barrel%

7211.5

Avg EV

5189.2

SPEED

Sprint

4227.1

Recent Formrolling true talent ⓘ

K%15%▲▲12% over 42 PA (60d) · proj 18%

BB%15%▲▲26% over 42 PA (60d) · proj 11%

ISO.202▲.258 over 31 AB (60d) · proj .191

BABIP.293·.360 over 25 BIP (60d) · proj .291

SLASH.269/.381/.471▲▲proj .262/.347/.453

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

Status Pre-Arb

MLB Debut 2026

Service 0.070 yrs.days

Team Control Through 2032

First FA Year 2033

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Pre-Arb	$0.8M	+0.1	$0.5M	+$0.0M (cut)
2028	Pre-Arb	$0.8M	+2.1	$16M	+$15M
2029	Pre-Arb	$0.8M	+2.8	$21M	+$20M
2030	Arb-1	$10M	+3.1	$23M	+$16M
2031	Arb-2	$17M	+3.2	$22M	+$11M
2032	Arb-3	$25M	+3.0	$18M	+$4M
Totals		$53M		$100M	+$65M

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)
2022	17	ROK	DSL LAD Bautista	—	223	186	65	13	2	5	32	31	3	16	6	349	452	522	974	172	395	14	14	429	82	—	—	—	—	—	—
2023	18	A	Rancho Cucamonga Quakes	—	340	282	80	15	2	2	46	61	8	14	3	284	396	372	769	89	353	18	14	352	95	—	—	—	—	—	—
2024	19	A+	Great Lakes Loons	—	230	177	45	6	0	4	50	38	2	13	3	254	424	356	780	102	301	17	22	365	93	—	—	—	—	—	—
2024	19	A	Rancho Cucamonga Quakes	—	251	208	58	11	3	6	34	57	5	14	0	279	391	447	838	168	351	23	14	371	84	—	—	—	—	—	—
2025	20	AA	Tulsa Drillers	—	19	18	0	0	0	0	1	5	0	0	0		53		53			26	5	37	-97	—	—	—	—	—	—
2025	20	A+	Great Lakes Loons	—	426	342	90	16	1	12	81	86	2	32	8	263	407	421	828	158	318	20	19	376	95	—	—	—	—	—	—
2026	21	MLB	Los Angeles Dodgers	—	42	31	10	3	1	1	11	5	0	1	1	323	500	581	1.081	258	360	12	26	470	218	+6	-0	+0	+2	+1	0.9
2026	21	AA	Tulsa Drillers	—	588	501	152	37	2	27	81	87	3	31	10	303	403	547	950	244	321	15	14	414	126	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	42	31	10	3	1	1	11	5	0	1	1	323	500	581	1.081	258	360	12	26	470	204	+5	-0	+0	+2	+1	0.8
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2022	17	ROK MLE	DSL LAD Bautista	—	223	194	43	9	1	2	24	37	3	16	6	222	317	309	626	88	261	17	11	289	82	—	—	—	—	—	—
2023	18	A MLE	Rancho Cucamonga Quakes	—	340	296	78	13	2	2	34	85	8	14	3	264	355	341	696	78	352	25	10	308	95	—	—	—	—	—	—
2024	19	A+ MLE	Great Lakes Loons	—	230	192	44	6	0	3	35	49	2	13	3	229	354	307	661	78	283	21	15	306	93	—	—	—	—	—	—
2024	19	A MLE	Rancho Cucamonga Quakes	—	251	217	47	9	3	4	26	80	5	14	0	217	315	341	656	124	308	32	10	292	84	—	—	—	—	—	—
2025	20	AA MLE	Tulsa Drillers	—	19	18	0	0	0	0	1	6	0	0	0		53		53			32	5	25	-97	—	—	—	—	—	—
2025	20	A+ MLE	Great Lakes Loons	—	426	364	82	14	1	10	59	112	2	32	8	225	336	352	688	126	295	26	14	309	95	—	—	—	—	—	—
2026	21	MLB MLE	Los Angeles Dodgers	—	42	31	10	3	1	1	11	5	0	1	1	323	500	581	1.081	258	360	12	26	490	218	+6	-0	+0	+2	+1	0.9
2026	21	AA MLE	Tulsa Drillers	—	588	524	142	33	2	23	58	106	3	31	10	271	347	473	820	202	298	18	10	355	126	—	—	—	—	—	—
2022	17	ROK MLE	DSL LAD Bautista	—	223	194	43	9	1	2	24	37	3	16	6	222	317	309	626	88	261	17	11	289	82	—	—	—	—	—	—
2022	17	ROK RAW	DSL LAD Bautista	—	223	186	65	13	2	5	32	31	3	16	6	349	452	522	974	172	395	14	14	429	82	—	—	—	—	—	—
2023	18	A MLE	Rancho Cucamonga Quakes	—	340	296	78	13	2	2	34	85	8	14	3	264	355	341	696	78	360	25	10	308	95	—	—	—	—	—	—
2023	18	A RAW	Rancho Cucamonga Quakes	—	340	282	80	15	2	2	46	61	8	14	3	284	396	372	769	89	353	18	14	352	95	—	—	—	—	—	—
2024	19	A MLE	2 teams	—	481	409	92	15	3	8	61	129	7	27	3	225	335	335	670	110	304	27	13	299	88	—	—	—	—	—	—
2024	19	A RAW	2 teams	—	481	385	103	17	3	10	84	95	7	27	3	268	407	405	812	138	327	20	17	369	88	—	—	—	—	—	—
2025	20	A+ MLE	2 teams	—	445	383	82	14	1	10	59	118	2	32	8	214	322	334	656	120	281	27	13	297	87	—	—	—	—	—	—
2025	20	A+ RAW	2 teams	—	445	360	90	16	1	12	82	91	2	32	8	250	392	400	792	150	302	20	18	362	87	—	—	—	—	—	—
2026	21	AA MLE	2 teams	—	630	555	152	36	3	24	69	111	3	32	11	274	357	479	837	205	303	18	11	364	132	—	—	—	—	—	—
2026	21	AA RAW	2 teams	—	630	532	162	40	3	28	92	92	3	32	11	305	410	549	959	244	323	15	15	418	132	—	—	—	—	—	—
2022	17	ROK MLE	DSL LAD Bautista	—	223	194	43	9	1	2	24	37	3	16	6	222	317	309	626	88	261	17	11	289	82	—	—	—	—	—	—
2023	18	A MLE	Rancho Cucamonga Quakes	—	340	295	78	13	2	2	34	85	8	14	3	264	355	342	697	78	352	25	10	308	95	—	—	—	—	—	—
2024	19	A MLE	2 teams	—	481	410	92	15	3	8	61	129	7	27	3	224	335	334	670	110	296	27	13	299	88	—	—	—	—	—	—
2025	20	A+ MLE	2 teams	—	445	381	82	14	1	10	59	118	2	32	8	215	322	336	658	121	282	27	13	297	87	—	—	—	—	—	—
2026	21	AA MLE	2 teams	—	630	553	152	36	3	24	69	111	3	32	11	275	357	481	838	206	302	18	11	364	132	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	19	A MLE	2 teams	—	481	410	92	15	3	8	61	129	7	27	3	224	335	334	670	110	296	27	13	299	88	—	—	—	—	—	—
2025	20	A+ MLE	2 teams	—	445	381	82	14	1	10	59	118	2	32	8	215	322	336	658	121	282	27	13	297	87	—	—	—	—	—	—
2026	21	AA MLE	2 teams	—	630	553	152	36	3	24	69	111	3	32	11	275	357	481	838	206	302	18	11	364	132	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	22	MLB MLE	LAD	10%	648	567	149	33	3	23	72	117	4	23	6	263	349	453	803	191	291	18	11	354	126	+20	+2	-6	+2	+14	1.2
▸ 2027 — real world (MLB)
2027	22	MLB CTX	LAD	10%	21	19	5	1	0	1	2	4	0	1	0	259	346	450	795	191	284	19	10	351	126	+1	+0	-0	+0	+0	0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	23	MLB MLE	LAD	59%	614	538	144	31	3	24	68	109	3	22	6	267	353	469	822	202	292	18	11	361	131	+22	+2	-5	+2	+13	3.6
2029	24	MLB MLE	LAD	73%	614	537	145	31	3	25	68	109	4	22	6	269	355	478	833	209	293	18	11	365	133	+24	+2	-4	+2	+13	3.8
2030	25	MLB MLE	LAD	78%	614	537	146	31	3	26	68	110	4	22	6	270	355	481	836	211	293	18	11	367	134	+25	+2	-3	+2	+13	4.0
2031	26	MLB MLE	LAD	80%	614	538	145	30	3	26	67	111	4	22	6	269	354	480	835	211	293	18	11	366	134	+25	+2	-3	+2	+13	4.0
2032	27	MLB MLE	LAD	80%	614	538	144	30	3	25	67	114	4	21	6	267	352	474	826	207	293	19	11	362	131	+23	+2	-3	+2	+13	3.8
2033	28	MLB MLE	LAD	79%	603	529	140	29	3	24	65	113	4	18	5	265	350	470	819	204	292	19	11	360	130	+21	+2	-4	+2	+13	3.5
2034	29	MLB MLE	LAD	77%	582	511	135	28	3	23	63	111	3	15	5	263	347	464	811	201	291	19	11	357	127	+19	+1	-5	+2	+13	3.1
2035	30	MLB MLE	LAD	76%	561	493	128	27	2	22	60	108	3	11	4	260	344	456	800	196	290	19	11	352	125	+16	+1	-5	+2	+12	2.6
2036	31	MLB MLE	LAD	76%	546	480	124	26	2	21	58	108	3	7	3	256	339	446	785	190	287	20	11	347	121	+13	+0	-6	+2	+12	2.2
2037	32	MLB MLE	LAD	75%	531	468	117	24	2	19	56	107	2	3	2	251	333	433	766	183	283	20	11	339	115	+10	-0	-6	+2	+12	1.7
2038	33	MLB MLE	LAD	75%	476	422	103	21	2	16	49	99	2	2	2	244	325	417	742	173	279	21	10	329	109	+5	-0	-7	+2	+10	1.0
2039	34	MLB MLE	LAD	71%	419	373	87	17	1	13	42	90	1	1	1	235	315	397	712	162	272	21	10	317	101	+0	-0	-7	+1	+9	0.4
2040	35	MLB MLE	LAD	66%	351	312	70	13	1	10	35	78	1	1	1	225	304	375	679	149	265	22	10	304	92	-3	-0	-8	+1	+8	-0.2
2028	23	MLB CTX	LAD	59%	362	317	83	17	1	15	40	64	2	13	4	263	350	466	816	203	285	18	11	359	131	+13	+1	-3	+1	+8	2.1
2029	24	MLB CTX	LAD	73%	446	391	104	21	2	19	49	79	3	16	4	266	352	475	827	210	286	18	11	363	133	+18	+2	-3	+2	+10	2.8
2030	25	MLB CTX	LAD	78%	480	421	112	23	2	21	53	86	3	17	5	266	352	478	831	212	287	18	11	364	134	+20	+1	-3	+2	+10	3.1
2031	26	MLB CTX	LAD	80%	494	434	115	23	2	22	54	90	3	17	5	266	351	478	829	212	287	18	11	364	134	+20	+1	-3	+2	+11	3.2
2032	27	MLB CTX	LAD	80%	489	430	114	23	2	21	53	90	3	17	5	263	349	472	820	208	286	18	11	360	131	+18	+1	-3	+2	+11	3.0
2033	28	MLB CTX	LAD	79%	478	420	110	22	2	20	52	90	3	14	4	262	347	467	814	206	286	19	11	358	130	+17	+1	-3	+2	+10	2.8
2034	29	MLB CTX	LAD	77%	450	396	104	21	2	19	48	86	3	11	4	259	344	461	805	202	285	19	11	354	127	+15	+1	-4	+2	+10	2.4
2035	30	MLB CTX	LAD	76%	428	377	96	19	1	17	46	83	2	9	3	257	341	454	794	197	283	19	11	350	125	+12	+1	-4	+2	+9	2.0
2036	31	MLB CTX	LAD	76%	413	364	91	18	1	16	44	81	2	5	2	253	336	444	780	191	281	20	11	344	121	+10	+0	-4	+1	+9	1.7
2037	32	MLB CTX	LAD	75%	400	353	87	17	1	15	42	81	2	2	2	247	330	431	761	184	277	20	10	337	115	+7	-0	-5	+1	+9	1.2
2038	33	MLB CTX	LAD	75%	358	317	77	15	1	13	37	74	1	1	1	241	322	415	737	174	273	21	10	327	109	+4	-0	-5	+1	+8	0.8
2039	34	MLB CTX	LAD	71%	296	263	61	11	1	10	30	64	1	1	1	232	313	395	707	163	266	22	10	315	101	+0	-0	-5	+1	+6	0.3
2040	35	MLB CTX	LAD	66%	232	206	46	8	1	7	23	52	1	0	0	222	302	372	674	150	259	22	10	302	92	-2	+0	-5	+1	+5	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	5368	4720	1210	241	20	216	582	1025	29	124	41	256	342	453	795	197	284	19	11	350	119	+157	+8	-49	+21	+116	25.9
/ 162G	—	A+C		—	650	572	146	29	2	26	70	124	4	15	5	255	341	449	790	194	282	19	11	350	119	+19	+1	-6	+3	+14	3.1
Career	—	MLE		—	9468	8297	2123	436	42	327	1036	1885	62	295	86	256	343	437	780	181	293	20	11	344	119	+213	+13	-69	+28	+160	35.2
/ 162G	—	MLE		—	650	570	145	30	3	22	71	129	4	20	6	254	341	433	774	179	291	20	11	344	119	+19	+1	-6	+3	+14	3.1

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 AATulsa Drillers · 588 PAwOBA .404 → .355 (−49)K% 14.8% → 18.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.80%	÷1.000	×1.220	—	—	18.05%
BB% (unintentional) /PA	13.44%	÷1.000	×0.700	—	×1.050	9.88%
HBP% /PA	0.51%	—	×0.870	—	×1.050	0.47%
Singles /BIP	20.77%	÷1.000	×0.920	×0.999	×1.050	20.05%
Doubles /BIP	8.94%	÷1.000	×0.840	×0.999	×1.050	7.88%
Triples /BIP	0.48%	÷1.000	×0.940	×0.999	×1.050	0.48%
Home runs /BIP	6.52%	÷1.000	×0.800	—	×1.050	5.48%

Factors used: league row TL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 21 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.999.

Result: wOBA .404 → .355; ISO .244 → .212; BABIP .321 → .298. 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 A+Great Lakes Loons · 426 PAwOBA .368 → .309 (−60)K% 20.2% → 26.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.19%	÷0.980	×1.270	—	—	26.16%
BB% (unintentional) /PA	19.01%	÷1.023	×0.710	—	×1.042	13.76%
HBP% /PA	0.47%	—	×0.790	—	×1.042	0.39%
Singles /BIP	23.83%	÷1.000	×0.920	×0.987	×1.042	22.55%
Doubles /BIP	6.25%	÷0.927	×0.810	×0.987	×1.042	5.62%
Triples /BIP	0.39%	÷1.150	×0.850	×0.987	×1.042	0.30%
Home runs /BIP	4.69%	÷0.992	×0.800	—	×1.042	3.94%

Factors used: league row Midwest League. Park (home-season share, regressed): HR 98, 1B 100, 2B 85, 3B 130, K 96, BB 105 — applied at half strength. Age: age 20 vs a level average of 22.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.987.

Result: wOBA .368 → .309; ISO .158 → .134; BABIP .318 → .295. 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 AATulsa Drillers · 19 PAwOBA .036 → .025 (−11)K% 26.3% → 32.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.32%	÷0.984	×1.220	—	—	32.64%
BB% (unintentional) /PA	5.26%	÷1.061	×0.700	—	×1.050	3.64%
HBP% /PA	0.00%	—	×0.870	—	×1.050	0.00%
Singles /BIP	0.00%	÷0.968	×0.920	—	×1.050	0.00%
Doubles /BIP	0.00%	÷1.014	×0.840	—	×1.050	0.00%
Triples /BIP	0.00%	÷1.137	×0.940	—	×1.050	0.00%
Home runs /BIP	0.00%	÷0.957	×0.800	—	×1.050	0.00%

Factors used: league row TL. Park (home-season share, regressed): HR 91, 1B 94, 2B 103, 3B 127, K 97, BB 112 — applied at half strength. Age: age 20 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (4.8 yr younger than average).

Result: wOBA .036 → .025; ISO .000 → .000; BABIP .000 → .000. 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 ARancho Cucamonga Quakes · 251 PAwOBA .367 → .292 (−75)K% 22.7% → 32.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.71%	÷0.964	×1.360	—	—	32.03%
BB% (unintentional) /PA	13.55%	÷0.943	×0.690	—	×1.045	10.36%
HBP% /PA	1.99%	—	×0.780	—	×1.045	1.62%
Singles /BIP	25.17%	÷1.072	×0.920	×0.983	×1.045	22.20%
Doubles /BIP	7.28%	÷0.973	×0.830	×0.983	×1.045	6.39%
Triples /BIP	1.99%	÷0.973	×0.910	×0.983	×1.045	1.91%
Home runs /BIP	3.97%	÷1.072	×0.800	—	×1.045	3.10%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 114, 1B 114, 2B 95, 3B 95, K 93, BB 89 — applied at half strength. Age: age 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.983.

Result: wOBA .367 → .292; ISO .168 → .132; BABIP .351 → .308. 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+Great Lakes Loons · 230 PAwOBA .358 → .306 (−52)K% 16.5% → 21.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.52%	÷0.990	×1.270	—	—	21.20%
BB% (unintentional) /PA	21.30%	÷1.037	×0.710	—	×1.050	15.32%
HBP% /PA	0.87%	—	×0.790	—	×1.050	0.72%
Singles /BIP	25.18%	÷1.004	×0.920	×0.992	×1.050	24.03%
Doubles /BIP	4.32%	÷0.950	×0.810	×0.992	×1.050	3.83%
Triples /BIP	0.00%	÷0.948	×0.850	×0.992	×1.050	0.00%
Home runs /BIP	2.88%	÷1.036	×0.800	—	×1.050	2.33%

Factors used: league row Midwest League. Park (home-season share, regressed): HR 107, 1B 101, 2B 90, 3B 90, K 98, BB 107 — applied at half strength. Age: age 19 vs a level average of 22.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.992.

Result: wOBA .358 → .306; ISO .102 → .088; BABIP .301 → .283. 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 ARancho Cucamonga Quakes · 340 PAwOBA .346 → .308 (−38)K% 17.9% → 25.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.94%	÷0.973	×1.360	—	—	25.07%
BB% (unintentional) /PA	13.53%	÷0.976	×0.690	—	×1.050	10.04%
HBP% /PA	2.35%	—	×0.780	—	×1.050	1.93%
Singles /BIP	27.60%	÷0.955	×0.920	×1.013	×1.050	28.27%
Doubles /BIP	6.79%	÷0.990	×0.830	×1.013	×1.050	6.05%
Triples /BIP	0.90%	÷0.900	×0.910	×1.013	×1.050	0.97%
Home runs /BIP	0.90%	÷1.025	×0.800	—	×1.050	0.74%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 105, 1B 91, 2B 98, 3B 80, K 95, BB 95 — applied at half strength. Age: age 18 vs a level average of 22.0 → +5.0% on BB/HBP/hit rates (4.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.013.

Result: wOBA .346 → .308; ISO .089 → .078; BABIP .353 → .352. 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 DSLDSL LAD Bautista · 223 PAwOBA .422 → .289 (−133)K% 13.9% → 16.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.90%	÷1.025	×1.220	—	—	16.55%
BB% (unintentional) /PA	14.35%	÷0.942	×0.700	—	×1.022	10.90%
HBP% /PA	1.35%	—	×0.700	—	×1.022	0.96%
Singles /BIP	29.03%	÷1.028	×0.680	×1.000	×1.022	19.64%
Doubles /BIP	8.39%	÷0.937	×0.600	×1.000	×1.022	5.49%
Triples /BIP	1.29%	÷0.915	×0.600	×1.000	×1.022	0.87%
Home runs /BIP	3.23%	÷1.028	×0.470	—	×1.022	1.51%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 106, 1B 106, 2B 87, 3B 83, K 105, BB 88 — applied at half strength. Age: age 17 vs a level average of 18.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.000.

Result: wOBA .422 → .289; ISO .172 → .101; BABIP .395 → .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).

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Curtis Grandersonlast yr '19 AS×3SS career totals — 15 seasons, 8,278 PA	12.5	8,278	344	153	249	337	466	-10	-4	47.5	42.0
/162	664	28	12	-0.8	-0.3	3.8	pk7: 36
#2Amos Otis'67-'84 * career totals — 17 seasons, 8,246 PA	12.4	8,246	193	341	276*	345*	464*	+20	-8	46.5	40.4
/162	664	16	27	+1.6	-0.7	3.7	pk7: 34
#3Ray Lankford'90-'04 * career totals — 14 seasons, 6,674 PA	10.1	6,674	238	258	262*	353*	477*	-4	-10	42.0	37.5
/162	664	24	26	-0.4	-1.0	4.2	pk7: 33
#4Andy Van Slyke'83-'95 * career totals — 13 seasons, 6,478 PA	9.8	6,478	164	245	270*	347*	470*	-6	-17	37.8	33.7
/162	664	17	25	-0.6	-1.7	3.9	pk7: 30
#5Vernon Wellslast yr '13 career totals — 13 seasons, 7,118 PA	10.7	7,118	269	108	270	319	461	+0	-19	32.9	31.8
/162	664	25	10	+0.0	-1.8	3.1	pk7: 31
#6Adam Joneslast yr '19 AS×10SS×7HOF career totals — 14 seasons, 7,516 PA	11.3	7,516	282	97	277	317	454	+18	-33	33.3	29.4
/162	664	25	9	+1.6	-2.9	2.9	pk7: 26
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 10 projected seasons	8.1	5,348	207	125	260	341	457	+6	-37	32.6	28.0
/162	664	26	15	+0.8	-4.6	4.0	pk7: 23

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
Josue De Paula (OGILVIE)	22	—	—	—	—	260/347/449	189	291	7	7	18%	11%	126	+1.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
●Carlos Correa 2017 · MLB	22	54→61	54→60	54→55	53	273/345/463	190	316	21	17	20%	10%	128	+3.3	269/344/470	201	314	25	7	22%	10%	129	+3.4	263/344/444	182	303	22	0	20%	10%	124	+3.1
●Gleyber Torres 2019 · MLB	22	51→55	53→60	46→50	47	259/324/431	172	322	20	10	26%	8%	113	+2.3	262/329/447	185	304	24	9	22%	9%	118	+2.7	259/345/399	140	294	17	6	17%	11%	114	+2.6
★Adrian Beltré 2001 · MLB	22	55→62	53→65	48→50	56	279/347/459	180	297	21	12	14%	9%	127	+3.3	259/309/424	165	282	19	10	16%	6%	105	+1.7	298/336/528	230	297	31	1	12%	5%	140	+4.3
●Bo Bichette 2020 · MLB	22	55→62	51→60	52→55	45	274/322/446	172	332	16	21	22%	6%	115	+2.4	283/327/467	184	336	21	18	22%	6%	122	+3.0	296/338/473	177	346	22	13	20%	5%	129	+3.8
★Corey Seager 2017 · MLB	23	58→62	54→65	46→45	46	290/339/483	193	336	20	5	20%	6%	130	+3.5	286/350/471	185	335	20	4	20%	8%	131	+3.6	281/349/508	228	296	29	2	16%	9%	141	+3.8
✕Jeremy Hermida 2008 · MLB	24	54→59	52→55	46→50	53	271/349/447	177	324	18	8	22%	10%	125	+3.2	254/323/407	153	311	18	6	23%	9%	107	+1.8	250/317/396	146	313	17	4	25%	8%	101	+1.0
★Gunnar Henderson 2024 · MLB	23	49→56	55→60	55	49	250/326/449	199	320	22	13	28%	10%	117	+2.6	259/334/459	200	307	23	17	23%	9%	123	+3.0	252/331/444	192	295	22	17	22%	9%	119	+3.2
●Jason Heyward 2012 · MLB	22	50→59	53→55	50	57	255/346/432	177	292	20	11	20%	11%	120	+2.8	259/337/437	178	299	21	14	20%	10%	119	+2.7	264/342/431	167	302	19	15	19%	10%	120	+2.7
●Eric Chavez 2001 · MLB	23	51→53	58→65	44→45	54	268/337/476	207	284	26	4	17%	9%	128	+3.3	274/328/504	230	289	29	7	17%	7%	131	+3.6	271/346/497	226	283	29	7	16%	10%	137	+4.2
●Brian McCann 2007 · MLB	23	56→62	56→60	44→45	51	291/343/490	199	299	24	4	13%	7%	133	+3.7	281/337/480	199	294	22	4	13%	7%	128	+3.4	278/355/480	202	295	24	5	14%	10%	136	+3.7
★Ryan Zimmerman 2007 · MLB	22	58→59	52→65	42→45	49	288/339/467	179	328	17	8	18%	7%	126	+3.2	275/332/462	187	307	20	5	17%	8%	122	+3.0	289/358/487	198	317	24	3	17%	9%	139	+4.0
●Stephen Drew 2006 · AA	23	51→57	56→55	43→45	50	263/328/463	201	308	23	7	22%	8%	122	+2.9	257/308/420	163	296	16	6	18%	7%	103	+1.6	268/323/446	179	301	15	6	16%	7%	116	+2.6
★Adam Dunn 2003 · MLB	23	48→49	59→70	47→50	63	250/373/471	222	303	26	14	25%	15%	139	+4.2	242/361/498	256	285	33	9	27%	14%	141	+4.3	243/362/519	277	281	37	5	27%	15%	147	+5.4
●Colby Rasmus 2011 · MLB	24	49→54	55→65	46→50	49	254/319/438	184	302	22	11	24%	9%	112	+2.2	239/304/423	184	289	22	6	24%	8%	103	+1.6	243/309/466	223	315	29	3	32%	8%	116	+1.9
✕Logan O'Hoppe 2023 · MLB	23	46→48	53→55	45	50	238/315/406	168	271	22	7	21%	8%	104	+1.6	238/301/417	179	290	25	5	26%	7%	101	+1.4	230/285/405	175	287	26	2	29%	6%	94	+0.6
●Austin Kearns 2004 · MLB	24	55→64	55→60	47→45	58	280/370/467	186	321	22	9	20%	11%	137	+4.0	256/342/458	202	309	23	6	24%	11%	126	+3.2	258/346/445	187	301	20	4	20%	10%	125	+3.2
✕Andy LaRoche 2007 · AAA	23	53→57	54→55	45	50	271/333/448	178	304	22	8	19%	8%	120	+2.8	249/326/399	150	278	17	7	17%	10%	106	+1.8	240/324/380	140	265	15	5	15%	10%	101	+1.1
●Gabriel Moreno 2022 · AA	22	54→60	53→50	47→45	46	272/326/449	177	307	20	7	19%	6%	118	+2.6	279/338/393	114	335	11	9	19%	8%	108	+1.9	280/361/429	149	314	16	5	15%	10%	126	+2.2
●Evan Longoria 2008 · AAA	22	50→57	55→65	47→50	47	261/325/448	187	306	24	5	23%	7%	118	+2.6	268/337/486	218	311	26	9	22%	8%	130	+3.5	266/348/500	234	289	28	8	19%	10%	138	+4.4
★Justin Upton 2011 · MLB	23	54→59	54→65	51→55	51	269/343/457	188	340	21	16	26%	10%	126	+3.2	270/344/458	188	317	22	16	21%	9%	126	+3.2	259/337/490	231	323	31	10	29%	10%	132	+3.8

Josue De Paula

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps