Luis De Los Santos

3B Syracuse Mets

Age 29 R/R 6'2" / 160 lbs AAA H -5% Svc 3.000 · Ctrl thru 2029

Overview

AAAROOKIEArb-1FA 2030

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2023	25	AAA/AATOR	340	.229/.334/.384	8	4	68	—	.197/.278/.315
2024	26	AAA/INTL2 orgs	236	.238/.336/.391	7	4	84	—	.235/.320/.360
2024	26	MLBTOR	31	.172/.226/.241	0	0	32	-0.1
2025	27	AAA/INTL2 orgs	431	.237/.283/.329	8	4	42	—	.215/.250/.281
2026	28	No MLB games played
2027PROJ10% MLB	29	MLBNYM	16	.212/.257/.300	0	0	60	-0.0
2028PROJ27% MLB	30	MLBNYM	73	.210/.256/.297	1	1	59	-0.2

Last 3 seasons WAR -0.1 · Next 2 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2029Service3.000First FA2030

2027Arb-1$0.2M2028Arb-2$0.4M2029Ext$0.6M

Skills · percentileMiLB Statcast 2025 AAA

Max EV97

Z-Con%70

Speed45

K%44

Whiff%42

BB%12

CompsJason Delay (age 28) · Jesús Sucre (age 29) · Jeff Mathis (age 29)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†60

AVG/OBP/SLG.212 / .257 / .300

PA16

HR0

K%25

BB%6

BABIP281

ISO76

MLB%10%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit-$1M ctrl surplus

Tools · ContractCON 45 / POW 40

Toolsscout grade · Statcast %ile · 2024

CONTACT45

xAVG

100.185

POWER40

Avg EV

1084.9

Bat Spd

7473.8

EYE25

scouting grade only

SPEED45

Sprint

4227.1

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

Status Arb-1

MLB Debut 2024

Service 3.000 yrs.days

Team Control Through 2029

First FA Year 2030

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-1	$0.2M	—	—	—
2028	Arb-2	$0.4M	—	—	—
2029	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$-0.9M	+$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)
2016	18	ROK	DSL Blue Jays	—	211	189	55	7	1	1	10	32	9	5	2	291	356	354	710	63	346	15	5	322	33	—	—	—	—	—	—
2017	19	A	Lansing Lugnuts	—	24	21	3	0	0	0	0	6	0	0	0	143	143	143	286		188	25	0	113	-36	—	—	—	—	—	—
2017	19	ROK	GCL Blue Jays	—	200	184	53	11	3	1	6	42	6	7	0	288	332	397	728	109	361	21	3	320	42	—	—	—	—	—	—
2018	20	ROK	Bluefield Blue Jays	—	260	232	57	8	5	7	15	59	7	9	2	246	310	414	724	168	296	23	6	315	40	—	—	—	—	—	—
2019	21	A	Lansing Lugnuts	—	84	78	16	4	1	0	6	19	0	1	2	205	262	282	544	77	271	23	7	249	13	—	—	—	—	—	—
2021	23	A+	Vancouver Canadians	—	407	376	95	25	2	12	16	93	10	4	5	253	301	426	727	173	301	23	4	318	63	—	—	—	—	—	—
2022	24	AAA	Buffalo Bisons	—	16	15	1	1	0	0	1	3	0	1	0	67	125	133	258	67	83	19	6	124	-47	—	—	—	—	—	—
2022	24	AA	New Hampshire Fisher Cats	—	449	406	107	19	2	10	34	99	3	7	4	264	325	394	719	131	320	22	8	319	80	—	—	—	—	—	—
2023	25	AAA	Buffalo Bisons	—	255	214	47	12	1	7	32	54	7	1	0	220	340	383	723	164	258	21	13	327	72	—	—	—	—	—	—
2023	25	AA	New Hampshire Fisher Cats	—	85	78	20	7	0	1	7	26	0	3	2	256	318	385	702	128	373	31	8	315	55	—	—	—	—	—	—
2024	26	MLB	Toronto Blue Jays	—	31	29	5	2	0	0	2	10	0	0	0	172	226	241	467	69	263	32	6	215	32	-3	+0	+0	+1	+1	-0.1
2024	26	AAA	Buffalo Bisons	—	154	127	33	5	0	6	21	35	3	3	1	260	373	441	813	181	310	23	14	362	94	—	—	—	—	—	—
2024	26	INTL	Leones del Escogido	—	82	75	15	5	0	1	7	23	0	1	1	200	268	307	575	107	275	28	9	263	64	—	—	—	—	—	—
2025	27	AAA	Syracuse Mets	—	382	356	86	11	0	8	18	95	5	3	1	242	287	340	627	98	307	25	5	282	42	—	—	—	—	—	—
2025	27	INTL	Leones del Escogido	—	49	45	9	2	0	0	2	13	1	1	1	200	250	244	494	44	281	27	4	225	39	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	31	29	5	2	0	0	2	10	0	0	0	172	226	241	467	69	263	32	6	215	32	-3	+0	+0	+1	+1	-0.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2016	18	ROK MLE	DSL Blue Jays	—	211	192	38	4	1	0	7	39	9	5	2	198	260	229	489	31	239	18	3	217	33	—	—	—	—	—	—
2017	19	A MLE	Lansing Lugnuts	—	24	21	3	0	0	0	0	8	0	0	0	143	143	143	286		183	33	0	115	-36	—	—	—	—	—	—
2017	19	ROK MLE	GCL Blue Jays	—	200	186	39	7	2	1	4	60	6	7	0	210	250	285	535	75	290	30	2	230	42	—	—	—	—	—	—
2018	20	ROK MLE	Bluefield Blue Jays	—	260	238	43	6	3	5	10	84	7	9	2	181	235	294	529	113	238	32	4	228	40	—	—	—	—	—	—
2019	21	A MLE	Lansing Lugnuts	—	84	80	13	3	1	0	4	27	0	1	2	163	202	225	427	62	244	32	5	187	13	—	—	—	—	—	—
2021	23	A+ MLE	Vancouver Canadians	—	407	381	81	21	1	10	11	127	10	4	5	213	254	352	605	139	279	31	3	262	63	—	—	—	—	—	—
2022	24	AAA MLE	Buffalo Bisons	—	16	15	1	1	0	0	1	4	0	1	0	67	125	133	258	67	74	25	6	98	-47	—	—	—	—	—	—
2022	24	AA MLE	New Hampshire Fisher Cats	—	449	414	103	16	2	8	26	119	3	7	4	249	298	355	653	106	319	27	6	286	80	—	—	—	—	—	—
2023	25	AAA MLE	Buffalo Bisons	—	255	223	42	10	1	5	23	67	7	1	0	188	285	309	594	121	243	26	9	274	72	—	—	—	—	—	—
2023	25	AA MLE	New Hampshire Fisher Cats	—	85	81	18	6	0	1	4	33	0	3	2	222	259	333	592	111	354	39	5	250	55	—	—	—	—	—	—
2024	26	MLB MLE	Toronto Blue Jays	—	31	29	5	2	0	0	2	10	0	0	0	172	226	241	467	69	263	32	6	215	32	-3	+0	+0	+1	+1	-0.1
2024	26	AAA MLE	Buffalo Bisons	—	154	136	32	5	0	4	14	42	3	3	1	235	320	360	681	125	302	27	9	307	94	—	—	—	—	—	—
2025	27	AAA MLE	Syracuse Mets	—	382	363	78	9	0	5	12	116	5	3	1	215	250	281	531	66	295	30	3	231	42	—	—	—	—	—	—
2016	18	ROK MLE	DSL Blue Jays	—	211	192	38	4	1	0	7	39	9	5	2	198	260	229	489	31	248	18	3	217	33	—	—	—	—	—	—
2016	18	ROK RAW	DSL Blue Jays	—	211	189	55	7	1	1	10	32	9	5	2	291	356	354	710	63	346	15	5	322	33	—	—	—	—	—	—
2017	19	ROK MLE	2 teams	—	224	207	42	7	2	1	4	69	6	7	0	203	240	271	510	68	291	31	2	218	33	—	—	—	—	—	—
2017	19	ROK RAW	2 teams	—	224	205	56	11	3	1	6	48	6	7	0	273	313	371	684	98	344	21	3	298	33	—	—	—	—	—	—
2018	20	ROK MLE	Bluefield Blue Jays	—	260	238	43	6	3	5	10	84	7	9	2	181	235	294	529	113	250	32	4	228	40	—	—	—	—	—	—
2018	20	ROK RAW	Bluefield Blue Jays	—	260	232	57	8	5	7	15	59	7	9	2	246	310	414	724	168	296	23	6	315	40	—	—	—	—	—	—
2019	21	A MLE	Lansing Lugnuts	—	84	80	13	3	1	0	4	27	0	1	2	163	202	225	427	62	245	32	5	187	13	—	—	—	—	—	—
2019	21	A RAW	Lansing Lugnuts	—	84	78	16	4	1	0	6	19	0	1	2	205	262	282	544	77	271	23	7	249	13	—	—	—	—	—	—
2021	23	A+ MLE	Vancouver Canadians	—	407	381	81	21	1	10	11	127	10	4	5	213	254	352	605	139	285	31	3	262	63	—	—	—	—	—	—
2021	23	A+ RAW	Vancouver Canadians	—	407	376	95	25	2	12	16	93	10	4	5	253	301	426	727	173	301	23	4	318	63	—	—	—	—	—	—
2022	24	AA MLE	2 teams	—	465	429	104	17	2	8	27	123	3	8	4	242	292	347	639	105	316	26	6	280	75	—	—	—	—	—	—
2022	24	AA RAW	2 teams	—	465	421	108	20	2	10	35	102	3	8	4	257	318	385	703	128	311	22	8	312	75	—	—	—	—	—	—
2023	25	AAA MLE	2 teams	—	340	303	60	16	1	6	28	99	7	4	2	198	281	317	598	119	270	29	8	268	68	—	—	—	—	—	—
2023	25	AAA RAW	2 teams	—	340	292	67	19	1	8	39	80	7	4	2	229	334	384	718	154	286	24	11	324	68	—	—	—	—	—	—
2024	26	AAA MLE	3 teams	—	267	239	53	10	0	6	24	75	3	4	2	222	301	339	640	117	296	28	9	292	84	—	—	—	—	—	—
2024	26	AAA RAW	3 teams	—	267	231	53	12	0	7	30	68	3	4	2	229	323	372	696	143	293	25	11	314	84	—	—	—	—	—	—
2025	27	AAA MLE	2 teams	—	431	408	87	10	0	5	14	131	6	4	2	213	250	275	525	61	300	30	3	231	42	—	—	—	—	—	—
2025	27	AAA RAW	2 teams	—	431	401	95	13	0	8	20	108	6	4	2	237	283	329	612	92	304	25	5	275	42	—	—	—	—	—	—
2016	18	ROK MLE	DSL Blue Jays	—	211	193	38	4	1	0	7	39	9	5	2	197	260	228	488	31	239	18	3	217	33	—	—	—	—	—	—
2017	19	ROK MLE	2 teams	—	224	212	42	7	2	1	4	69	6	7	0	198	240	264	504	66	279	31	2	218	33	—	—	—	—	—	—
2018	20	ROK MLE	Bluefield Blue Jays	—	260	241	43	6	3	5	10	84	7	9	2	178	235	290	526	112	238	32	4	228	40	—	—	—	—	—	—
2019	21	A MLE	Lansing Lugnuts	—	84	80	13	3	1	0	4	27	0	1	2	163	202	225	427	62	244	32	5	187	13	—	—	—	—	—	—
2021	23	A+ MLE	Vancouver Canadians	—	407	383	81	21	1	10	11	127	10	4	5	211	254	350	604	138	279	31	3	262	63	—	—	—	—	—	—
2022	24	AA MLE	2 teams	—	465	432	104	17	2	8	27	123	3	8	4	241	292	345	637	104	311	26	6	280	75	—	—	—	—	—	—
2023	25	AAA MLE	2 teams	—	340	302	60	16	1	6	28	99	7	4	2	199	281	318	599	119	271	29	8	268	68	—	—	—	—	—	—
2024	26	AAA MLE	3 teams	—	267	238	53	10	0	6	24	75	3	4	2	223	301	340	641	118	295	28	9	292	84	—	—	—	—	—	—
2025	27	AAA MLE	2 teams	—	431	408	87	10	0	5	14	131	6	4	2	213	250	275	525	61	295	30	3	231	42	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	26	AAA MLE	3 teams	—	267	238	53	10	0	6	24	75	3	4	2	223	301	340	641	118	295	28	9	292	84	—	—	—	—	—	—
2025	27	AAA MLE	2 teams	—	431	408	87	10	0	5	14	131	6	4	2	213	250	275	525	61	295	30	3	231	42	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	29	MLB MLE	NYM	10%	375	350	77	12	1	6	17	104	5	4	1	218	263	308	571	90	290	28	5	257	60	-18	+0	-0	+1	+8	-0.3
▸ 2027 — real world (MLB)
2027	29	MLB CTX	NYM	10%	16	15	2	0	0	0	1	4	0	0	0	212	257	300	557	87	281	25	6	251	60	-1	+0	-0	+0	+0	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	30	MLB MLE	NYM	27%	268	251	55	9	1	4	12	74	3	2	1	217	262	305	567	88	288	28	4	256	59	-13	+0	-2	+1	+6	-0.9
2028	30	MLB CTX	NYM	27%	73	69	14	2	0	1	3	20	1	1	0	210	256	297	553	86	279	27	4	250	59	-4	+0	-1	+0	+2	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	104	98	19	4	0	1	5	30	1	1	0	194	240	265	506	71	269	29	5	239	56	-6	+0	-1	+1	+2	-0.3
/ 162G	—	A+C		—	650	612	119	25	0	6	31	188	6	6	0	194	240	265	505	70	270	29	5	239	56	-38	+1	-3	+8	+14	-1.9
Career	—	MLE		—	3112	2873	607	108	12	47	148	891	56	50	23	211	264	306	570	95	286	29	5	252	56	-23	+0	-2	+2	+10	-1.3
/ 162G	—	MLE		—	650	600	128	23	3	10	31	186	12	10	5	213	266	312	578	98	289	29	5	252	56	-33	+0	-3	+4	+14	-1.9

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.

2025 AAASyracuse Mets · 382 PAwOBA .275 → .231 (−44)K% 24.9% → 30.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.87%	÷0.981	×1.200	—	—	30.43%
BB% (unintentional) /PA	4.71%	÷1.005	×0.690	—	×1.003	3.24%
HBP% /PA	1.31%	—	×0.940	—	×1.003	1.23%
Singles /BIP	25.67%	÷0.975	×0.930	×1.040	×1.003	25.54%
Doubles /BIP	4.21%	÷1.022	×0.830	×1.040	×1.003	3.57%
Triples /BIP	0.00%	÷0.959	×0.970	×1.040	×1.003	0.00%
Home runs /BIP	3.07%	÷1.167	×0.700	—	×1.003	1.84%

Factors used: league row International League. Park (home-season share, regressed): HR 133, 1B 95, 2B 104, 3B 92, K 96, BB 101 — applied at half strength. Age: age 27 vs a level average of 27.2 → +0.3% on BB/HBP/hit rates (0.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.040.

Result: wOBA .275 → .231; ISO .098 → .064; BABIP .307 → .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).

2024 AAABuffalo Bisons · 154 PAwOBA .355 → .307 (−48)K% 22.7% → 27.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.73%	÷1.004	×1.200	—	—	27.16%
BB% (unintentional) /PA	13.64%	÷1.028	×0.690	—	×1.018	9.32%
HBP% /PA	1.95%	—	×0.940	—	×1.018	1.86%
Singles /BIP	23.91%	÷0.988	×0.930	×1.050	×1.018	24.06%
Doubles /BIP	5.43%	÷0.959	×0.830	×1.050	×1.018	5.03%
Triples /BIP	0.00%	÷1.150	×0.970	×1.050	×1.018	0.00%
Home runs /BIP	6.52%	÷0.990	×0.700	—	×1.018	4.69%

Factors used: league row International League. Park (home-season share, regressed): HR 98, 1B 98, 2B 92, 3B 130, K 101, BB 106 — 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 ×1.050.

Result: wOBA .355 → .307; ISO .181 → .143; BABIP .310 → .302. 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 AAABuffalo Bisons · 255 PAwOBA .322 → .274 (−48)K% 21.2% → 26.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.18%	÷0.973	×1.200	—	—	26.12%
BB% (unintentional) /PA	12.55%	÷0.984	×0.690	—	×1.033	9.09%
HBP% /PA	2.75%	—	×0.940	—	×1.033	2.67%
Singles /BIP	16.88%	÷1.018	×0.930	×1.047	×1.033	16.68%
Doubles /BIP	7.50%	÷1.033	×0.830	×1.047	×1.033	6.52%
Triples /BIP	0.62%	÷1.150	×0.970	×1.047	×1.033	0.57%
Home runs /BIP	4.38%	÷0.916	×0.700	—	×1.033	3.45%

Factors used: league row International League. Park (home-season share, regressed): HR 83, 1B 104, 2B 107, 3B 130, K 95, BB 97 — 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 ×1.047.

Result: wOBA .322 → .274; ISO .164 → .133; BABIP .258 → .243. 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 AANew Hampshire Fisher Cats · 85 PAwOBA .307 → .250 (−57)K% 30.6% → 38.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.59%	÷0.967	×1.220	—	—	38.57%
BB% (unintentional) /PA	8.24%	÷1.105	×0.700	—	×0.998	5.21%
HBP% /PA	0.00%	—	×0.850	—	×0.998	0.00%
Singles /BIP	23.08%	÷1.023	×0.970	×1.029	×0.998	22.47%
Doubles /BIP	13.46%	÷0.963	×0.860	×1.029	×0.998	12.35%
Triples /BIP	0.00%	÷1.033	×0.950	×1.029	×0.998	0.00%
Home runs /BIP	1.92%	÷1.000	×0.780	—	×0.998	1.50%

Factors used: league row EL. Park (home-season share, regressed): HR 100, 1B 105, 2B 93, 3B 107, K 93, BB 121 — applied at half strength. Age: age 25 vs a level average of 24.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.029.

Result: wOBA .307 → .250; ISO .128 → .103; BABIP .373 → .354. 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 AANew Hampshire Fisher Cats · 449 PAwOBA .315 → .286 (−29)K% 22.0% → 26.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.05%	÷1.012	×1.220	—	—	26.57%
BB% (unintentional) /PA	7.57%	÷0.911	×0.700	—	×1.012	5.89%
HBP% /PA	0.67%	—	×0.850	—	×1.012	0.57%
Singles /BIP	24.76%	÷0.991	×0.970	×1.050	×1.012	25.75%
Doubles /BIP	6.19%	÷1.067	×0.860	×1.050	×1.012	5.30%
Triples /BIP	0.65%	÷0.900	×0.950	×1.050	×1.012	0.73%
Home runs /BIP	3.26%	÷1.027	×0.780	—	×1.012	2.50%

Factors used: league row EL. Park (home-season share, regressed): HR 105, 1B 98, 2B 113, 3B 80, K 102, BB 82 — applied at half strength. Age: age 24 vs a level average of 24.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .315 → .286; ISO .131 → .106; BABIP .320 → .319. 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 AAABuffalo Bisons · 16 PAwOBA .121 → .098 (−23)K% 18.8% → 22.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.75%	÷1.018	×1.200	—	—	22.10%
BB% (unintentional) /PA	6.25%	÷1.032	×0.690	—	×1.048	4.38%
HBP% /PA	0.00%	—	×0.940	—	×1.048	0.00%
Singles /BIP	0.00%	÷0.960	×0.930	—	×1.048	0.00%
Doubles /BIP	8.33%	÷0.984	×0.830	—	×1.048	7.37%
Triples /BIP	0.00%	÷1.149	×0.970	—	×1.048	0.00%
Home runs /BIP	0.00%	÷0.951	×0.700	—	×1.048	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 90, 1B 92, 2B 97, 3B 130, K 104, BB 106 — 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).

Result: wOBA .121 → .098; ISO .067 → .058; BABIP .083 → .074. 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).

2021 A+Vancouver Canadians · 407 PAwOBA .312 → .262 (−50)K% 22.9% → 31.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.85%	÷0.991	×1.350	—	—	31.13%
BB% (unintentional) /PA	3.69%	÷0.944	×0.710	—	×0.998	2.77%
HBP% /PA	2.46%	—	×0.810	—	×0.998	1.99%
Singles /BIP	19.79%	÷0.974	×0.910	×1.020	×0.998	18.83%
Doubles /BIP	8.83%	÷0.938	×0.830	×1.020	×0.998	7.96%
Triples /BIP	0.71%	÷1.049	×0.820	×1.020	×0.998	0.56%
Home runs /BIP	4.24%	÷0.909	×0.830	—	×0.998	3.86%

Factors used: level-wide A+ factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 82, 1B 95, 2B 88, 3B 110, K 98, BB 89 — applied at half strength. Age: age 23 vs a level average of 22.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.020.

Result: wOBA .312 → .262; ISO .173 → .144; BABIP .301 → .279. 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).

2019 ALansing Lugnuts · 84 PAwOBA .242 → .187 (−55)K% 22.6% → 32.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.62%	÷0.950	×1.360	—	—	32.37%
BB% (unintentional) /PA	7.14%	÷1.016	×0.690	—	×1.015	4.92%
HBP% /PA	0.00%	—	×0.780	—	×1.015	0.00%
Singles /BIP	18.64%	÷0.972	×0.920	×0.965	×1.015	17.29%
Doubles /BIP	6.78%	÷0.979	×0.830	×0.965	×1.015	5.63%
Triples /BIP	1.69%	÷1.050	×0.910	×0.965	×1.015	1.44%
Home runs /BIP	0.00%	÷1.113	×0.800	—	×1.015	0.00%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 123, 1B 94, 2B 96, 3B 110, K 90, BB 103 — applied at half strength. Age: age 21 vs a level average of 22.0 → +1.5% on BB/HBP/hit rates (1.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.965.

Result: wOBA .242 → .187; ISO .077 → .057; BABIP .271 → .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).

Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .

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
Luis De Los Santos (OGILVIE)	29	45	40	45	25	217/261/306	89	290	2	2	28%	4%	60	-0.4	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Jason Delay 2023 · MLB	28	41	39→45	42→40	40	202/250/286	84	278	6	5	29%	6%	51	-2.3	221/278/305	84	288	5	5	23%	6%	65	-1.2	212/268/277	65	275	2	2	22%	6%	54	-0.7
✕Jesús Sucre 2017 · MLB	29	47	39→40	42→40	42	227/265/312	85	273	7	4	20%	4%	62	-1.4	229/271/332	103	266	11	6	18%	4%	70	-0.9	219/257/298	79	256	8	3	17%	4%	56	-0.7
✕Jeff Mathis 2012 · MLB	29	38→48	41→50	43→45	40	191/239/288	96	249	9	6	27%	5%	48	-2.5	203/251/328	125	271	14	4	29%	6%	61	-1.5	208/255/312	104	282	8	1	28%	5%	60	-0.4
✕Tomás Nido 2024 · MLB	30	46→45	41→45	47→30	40	224/263/313	89	286	9	3	25%	5%	61	-1.5	211/251/313	102	271	12	3	26%	4%	57	-1.8	194/232/285	90	252	11	0	27%	4%	42	-1.0
✕Gerardo Bustamante 2015 · AAA	29	42	41→40	47→50	37	212/246/301	90	271	10	8	26%	4%	53	-2.1	220/269/335	115	286	13	14	27%	5%	70	-0.8	209/259/309	100	261	12	24	24%	5%	56	-0.4
✕Eli Whiteside 2010 · MLB	30	41	45→50	46→40	37	208/247/328	120	267	13	5	27%	4%	59	-1.6	210/262/332	122	270	12	6	26%	5%	67	-1.1	193/249/296	103	247	9	3	25%	5%	54	-0.7
✕Carlos Eduardo Gonzalez 2014 · AAA	29	45	38→40	42→50	38	215/254/298	83	289	4	9	27%	4%	55	-2.0	210/265/305	95	276	8	9	25%	6%	61	-1.5	205/258/292	87	257	7	6	22%	6%	51	-0.7
✕Luis Bustillos 2007 · AAA	29	46	41→40	42→40	40	222/265/321	99	292	9	9	27%	5%	65	-1.2	219/258/307	88	295	7	7	27%	4%	59	-1.7	216/252/283	66	293	4	4	27%	4%	49	-0.7
✕Jeff Bianchi 2015 · MLB	28	47→57	40→45	45→50	42	230/268/317	87	281	8	10	21%	5%	64	-1.3	219/264/294	75	281	6	9	23%	6%	57	-1.8	213/257/256	43	279	2	7	23%	6%	43	-0.9
✕Deven Marrero 2019 · MLB	28	40→50	40→45	49→50	38	198/241/285	87	278	7	11	31%	5%	47	-2.5	198/253/312	114	277	13	11	32%	7%	59	-1.7	184/243/283	99	253	12	10	31%	7%	45	-1.2
✕Chris Valaika 2015 · MLB	29	42→52	43→45	43→40	40	214/259/321	108	266	12	5	25%	4%	63	-1.4	221/270/335	114	282	12	6	25%	5%	70	-0.8	212/259/316	104	272	9	1	25%	4%	61	-1.0
✕Juan Graterol 2018 · MLB	29	48	38→40	46→30	42	230/263/308	78	266	6	6	16%	3%	60	-1.6	233/267/305	72	258	5	4	12%	3%	61	-1.5	235/271/284	48	260	3	0	10%	3%	55	-0.7
✕Horacio Vasquez 2015 · AAA	29	45	39→40	41→40	39	219/251/300	81	279	7	7	24%	4%	54	-2.0	219/255/291	72	287	5	9	24%	4%	53	-2.1	218/245/258	40	286	2	6	24%	3%	39	-0.9
✕Leury Bonilla 2014 · AAA	29	47	38→45	41→50	42	223/267/295	72	291	6	9	25%	6%	59	-1.7	215/257/289	74	279	5	9	24%	5%	54	-2.0	209/248/275	66	269	4	7	23%	4%	43	-1.5
✕Tommy Manzella 2012 · MLB	29	43→53	39→40	47→50	39	207/256/289	83	291	7	9	31%	6%	54	-2.0	185/235/251	66	302	4	8	38%	6%	37	-3.3	164/210/204	40	279	1	4	39%	5%	15	-2.3
✕Gookie Dawkins 2008 · AAA	29	46→48	41→45	46→50	41	226/267/327	101	286	9	12	24%	5%	66	-1.1	202/247/300	98	283	9	9	30%	5%	53	-2.1	184/237/290	106	258	11	9	32%	6%	45	-1.6
✕Gift Ngoepe 2018 · MLB	28	43→44	43→45	42→50	39	206/264/322	117	316	10	6	36%	7%	65	-1.2	187/258/298	111	337	11	8	44%	8%	58	-1.7	136/221/221	84	272	10	7	49%	9%	25	-1.2
✕Guillermo Quiroz 2011 · MLB	29	45	43→45	41→50	41	221/265/335	114	275	10	3	24%	5%	68	-1.0	214/266/339	125	280	12	3	27%	6%	70	-0.8	204/260/329	125	265	13	1	27%	6%	64	-0.6
✕Pete Kozma 2017 · MLB	29	40→47	36→45	46→50	44	193/245/256	63	241	4	12	21%	6%	42	-2.9	193/243/278	85	243	6	9	22%	5%	47	-2.6	188/235/276	88	231	6	6	21%	5%	41	-2.0
✕Tyler Ladendorf 2017 · MLB	29	43→49	38→40	49→50	42	209/254/285	77	273	6	7	25%	6%	52	-2.2	203/258/283	80	259	6	8	23%	6%	54	-2.0	190/246/274	84	240	7	4	23%	6%	44	-0.9