Enmanuel Tejeda

SS Hudson Valley Renegades

Age 22 R/R 5'9" / 158 lbs A+ HR +14% Svc 0.0 · Ctrl thru 2033

Overview

A+PROSPECTMiLBFA 2034

OGV OFP40OGV rank#179ETA2028MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	19	A/ROKNYY	203	.326/.375/.408	2	26	82	—	.279/.315/.347
2025	20	A/ROK/INTL2 orgs	266	.252/.398/.355	4	27	88	—	.199/.309/.282
2026	21	A+/ANYY	491	.224/.346/.342	9	38	54	—	.184/.271/.278
2027PROJMLE	22	MLBNYY	1	.226/.307/.330	0	0	81	0.0
2028PROJ43% MLB	23	MLBNYY	185	.231/.312/.347	4	8	87	0.4
2029PROJ58% MLB	24	MLBNYY	272	.234/.315/.357	6	12	90	0.7

Next 3 projected WAR 1.1Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2033Service0.0First FA2034

2027MiLB2028Pre-Arb$0.8M2029Pre-Arb$0.8M2030Pre-Arb$0.8M2031Arb-1$4M2032Arb-2$6M2033Arb-3$8M

Skills · percentileMiLB Statcast 2026 A+

Chase%84

K%80

Whiff%80

Z-Con%79

BB%55

Speed54

Career WAR0.0 WAR median (P10 -0.1 / P90 6.7, comp-based) · star 1% · didn't stick 87%

CompsMasyn Winn (age 21) · Jakob Marsee (age 22) · Ryan Brett (age 22)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†81

AVG/OBP/SLG.226 / .307 / .330

PA1

HR0

K%23

BB%9

BABIP282

ISO102

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$18M ctrl surplus

Tools · ContractCON 52 / POW 44

Toolsscout grade

CONTACT52

scouting grade only

POWER44

scouting grade only

EYE61

scouting grade only

SPEED66

scouting grade only

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

Status MiLB

MLB Debut 2028

Service 0 yrs (est)

Team Control Through 2033

First FA Year 2034

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2028
2028	Pre-Arb	$0.8M	+0.4	$1M	+$0.8M
2029	Pre-Arb	$0.8M	+0.7	$2M	+$2M
2030	Pre-Arb	$0.8M	+0.9	$3M	+$2M
2031	Arb-1	$4M	+1.0	$6M	+$4M
2032	Arb-2	$6M	+0.9	$2M	+$0.0M (cut)
2033	Arb-3	$8M	+0.8	$2M	+$0.0M (cut)
Totals		$6M		$17M	+$8M

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 NYY Bombers	—	188	142	41	6	7	3	41	25	5	11	6	289	463	493	956	204	333	13	22	426	70	—	—	—	—	—	—
2023	18	ROK	FCL Yankees	—	217	166	51	4	3	5	44	44	6	24	6	307	468	458	925	151	390	20	20	418	81	—	—	—	—	—	—
2024	19	A	Tampa Tarpons	—	185	168	52	7	0	1	11	36	2	24	4	310	357	369	726	60	381	19	6	324	74	—	—	—	—	—	—
2024	19	ROK	FCL Yankees	—	18	16	8	2	0	1	2	2	0	2	0	500	556	812	1.368	312	538	11	11	587	162	—	—	—	—	—	—
2025	20	A	Tampa Tarpons	—	149	120	29	3	0	3	26	20	3	12	3	242	389	342	731	100	268	13	17	344	72	—	—	—	—	—	—
2025	20	ROK	FCL Yankees	—	32	27	8	3	0	0	4	7	1	2	2	296	406	407	814	111	400	22	12	372	50	—	—	—	—	—	—
2025	20	INTL	Mesa Solar Sox	—	85	67	17	4	0	1	16	19	2	13	2	254	412	358	770	104	340	22	19	361	131	—	—	—	—	—	—
2026	21	A+	Hudson Valley Renegades	—	347	295	65	10	0	7	42	64	6	26	8	220	328	325	653	105	257	18	12	301	45	—	—	—	—	—	—
2026	21	A	Tampa Tarpons	—	144	112	26	9	1	2	28	30	2	12	4	232	392	384	776	152	296	21	19	354	74	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2022	17	ROK MLE	DSL NYY Bombers	—	188	153	27	4	4	1	30	31	5	11	6	176	330	275	604	98	205	16	16	271	70	—	—	—	—	—	—
2023	18	ROK MLE	FCL Yankees	—	217	182	39	3	2	3	28	67	6	24	6	214	338	302	640	88	311	31	13	288	81	—	—	—	—	—	—
2024	19	A MLE	Tampa Tarpons	—	185	173	47	6	0	1	7	51	2	24	4	272	308	324	631	52	360	28	4	277	74	—	—	—	—	—	—
2024	19	ROK MLE	FCL Yankees	—	18	17	6	1	0	1	1	3	0	2	0	353	389	588	977	235	405	17	6	408	162	—	—	—	—	—	—
2025	20	A MLE	Tampa Tarpons	—	149	127	25	2	0	3	19	27	3	12	3	197	315	283	599	87	226	18	13	274	72	—	—	—	—	—	—
2025	20	ROK MLE	FCL Yankees	—	32	29	6	2	0	0	2	10	1	2	2	207	281	276	557	69	293	31	6	242	50	—	—	—	—	—	—
2026	21	A+ MLE	Hudson Valley Renegades	—	347	314	57	8	0	6	25	84	6	26	8	182	255	264	519	83	221	24	7	235	45	—	—	—	—	—	—
2026	21	A MLE	Tampa Tarpons	—	144	122	23	7	1	2	19	41	2	12	4	189	308	311	619	123	258	28	13	277	74	—	—	—	—	—	—
2022	17	ROK MLE	DSL NYY Bombers	—	188	153	27	4	4	1	30	31	5	11	6	176	330	275	604	98	215	16	16	271	70	—	—	—	—	—	—
2022	17	ROK RAW	DSL NYY Bombers	—	188	142	41	6	7	3	41	25	5	11	6	289	463	493	956	204	333	13	22	426	70	—	—	—	—	—	—
2023	18	ROK MLE	FCL Yankees	—	217	182	39	3	2	3	28	67	6	24	6	214	338	302	640	88	319	31	13	288	81	—	—	—	—	—	—
2023	18	ROK RAW	FCL Yankees	—	217	166	51	4	3	5	44	44	6	24	6	307	468	458	925	151	390	20	20	418	81	—	—	—	—	—	—
2024	19	A MLE	2 teams	—	203	190	52	7	0	1	8	54	2	26	4	274	310	326	636	53	370	27	4	289	81	—	—	—	—	—	—
2024	19	A RAW	2 teams	—	203	184	60	9	0	2	13	38	2	26	4	326	375	408	783	82	395	19	6	348	81	—	—	—	—	—	—
2025	20	A MLE	3 teams	—	266	229	44	6	0	4	31	55	6	27	7	192	305	271	575	79	235	21	12	268	68	—	—	—	—	—	—
2025	20	A RAW	3 teams	—	266	214	54	10	0	4	46	46	6	27	7	252	398	355	754	103	305	17	17	353	68	—	—	—	—	—	—
2026	21	A+ MLE	2 teams	—	491	435	79	15	1	8	45	125	8	38	12	182	270	276	546	94	233	25	9	247	54	—	—	—	—	—	—
2026	21	A+ RAW	2 teams	—	491	407	91	19	1	9	70	94	8	38	12	224	346	342	688	118	267	19	14	317	54	—	—	—	—	—	—
2022	17	ROK MLE	DSL NYY Bombers	—	188	151	27	4	4	1	30	31	5	11	6	179	330	278	608	99	205	16	16	271	70	—	—	—	—	—	—
2023	18	ROK MLE	FCL Yankees	—	217	181	39	3	2	3	28	67	6	24	6	215	338	304	642	88	311	31	13	288	81	—	—	—	—	—	—
2024	19	A MLE	2 teams	—	203	191	52	7	0	1	8	54	2	26	4	272	310	325	635	52	364	27	4	289	81	—	—	—	—	—	—
2025	20	A MLE	3 teams	—	266	227	44	6	0	4	31	55	6	27	7	194	305	273	578	79	238	21	12	268	68	—	—	—	—	—	—
2026	21	A+ MLE	2 teams	—	491	435	79	15	1	8	45	125	8	38	12	182	270	276	546	94	232	25	9	247	54	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	19	A MLE	2 teams	—	203	191	52	7	0	1	8	54	2	26	4	272	310	325	635	52	364	27	4	289	81	—	—	—	—	—	—
2025	20	A MLE	3 teams	—	266	227	44	6	0	4	31	55	6	27	7	194	305	273	578	79	238	21	12	268	68	—	—	—	—	—	—
2026	21	A+ MLE	2 teams	—	491	435	79	15	1	8	45	125	8	38	12	182	270	276	546	94	232	25	9	247	54	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	22	MLB MLE	NYY	0%	551	489	110	20	1	9	50	125	7	24	7	226	306	326	633	101	283	23	9	288	81	-12	+2	+0	+6	+12	0.4
▸ 2027 — real world (MLB)
2027	22	MLB CTX	NYY	0%	1	1	0	0	0	0	0	0	0	0	0	226	307	330	637	104	282	0	0	290	81	-0	+0	+0	+0	+0	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	23	MLB MLE	NYY	43%	427	380	87	16	1	8	39	95	5	19	5	230	311	342	653	112	284	22	9	296	87	-7	+2	+0	+5	+9	0.9
2029	24	MLB MLE	NYY	58%	469	417	97	18	1	10	43	103	6	20	6	233	314	352	666	119	285	22	9	301	90	-6	+2	+0	+5	+10	1.1
2030	25	MLB MLE	NYY	65%	494	439	103	19	1	11	46	109	6	21	6	235	315	357	673	123	286	22	9	304	92	-5	+2	+0	+5	+11	1.3
2031	26	MLB MLE	NYY	68%	506	448	106	19	2	11	47	111	6	22	6	235	316	360	675	124	286	22	9	305	92	-5	+2	+0	+5	+11	1.4
2032	27	MLB MLE	NYY	68%	509	451	106	19	2	11	47	113	6	21	6	235	315	360	675	125	286	22	9	304	92	-5	+2	+0	+5	+11	1.4
2033	28	MLB MLE	NYY	68%	505	447	104	19	1	11	47	113	6	19	6	233	313	355	668	122	285	22	9	302	90	-6	+1	-1	+5	+11	1.2
2034	29	MLB MLE	NYY	66%	494	440	101	19	1	10	45	112	6	16	5	231	311	349	660	118	284	23	9	298	88	-7	+1	-1	+5	+11	0.9
2035	30	MLB MLE	NYY	66%	482	430	98	18	1	10	44	111	5	13	4	228	307	342	649	114	282	23	9	294	85	-9	+1	-2	+5	+10	0.6
2036	31	MLB MLE	NYY	65%	466	416	93	17	1	9	42	109	5	8	3	224	303	332	635	108	280	23	9	288	81	-10	+0	-3	+5	+10	0.2
2037	32	MLB MLE	NYY	65%	445	398	88	16	1	8	40	106	4	4	3	219	297	320	617	101	276	24	9	281	76	-13	-0	-4	+5	+10	-0.2
2028	23	MLB CTX	NYY	43%	185	164	39	7	1	4	17	41	2	8	2	231	312	347	659	115	284	22	9	298	87	-3	+1	+0	+2	+4	0.4
2029	24	MLB CTX	NYY	58%	272	242	57	10	1	6	25	60	3	12	3	234	315	357	672	123	285	22	9	304	90	-3	+1	+0	+3	+6	0.7
2030	25	MLB CTX	NYY	65%	320	283	67	12	1	7	30	70	4	14	4	236	316	363	679	127	285	22	9	306	92	-3	+1	+0	+3	+7	0.9
2031	26	MLB CTX	NYY	68%	344	305	72	13	1	8	32	76	4	15	4	236	317	365	682	129	286	22	9	307	92	-3	+1	+0	+4	+7	1.0
2032	27	MLB CTX	NYY	68%	346	307	72	13	1	8	32	77	4	14	4	236	316	365	682	129	286	22	9	307	92	-3	+1	+0	+4	+7	0.9
2033	28	MLB CTX	NYY	68%	343	304	72	13	1	8	32	77	4	13	4	234	314	361	675	127	285	22	9	304	90	-4	+1	-0	+4	+7	0.8
2034	29	MLB CTX	NYY	66%	328	291	67	12	1	7	30	74	4	11	3	232	312	354	666	123	284	23	9	301	88	-5	+1	-1	+4	+7	0.6
2035	30	MLB CTX	NYY	66%	316	281	65	12	1	7	29	73	3	8	3	229	308	347	655	118	282	23	9	296	85	-6	+0	-1	+3	+7	0.4
2036	31	MLB CTX	NYY	65%	303	270	61	11	1	6	27	71	3	5	2	225	303	337	640	112	280	23	9	290	81	-7	+0	-2	+3	+7	0.1
2037	32	MLB CTX	NYY	65%	288	257	57	10	1	5	26	69	3	3	2	220	297	324	622	105	276	24	9	283	76	-8	-0	-2	+3	+6	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3045	2704	629	113	10	66	280	688	34	103	31	233	312	355	667	122	286	23	9	300	83	-45	+8	-7	+33	+66	5.7
/ 162G	—	A+C		—	650	577	134	24	2	14	60	147	7	22	7	232	312	354	666	121	286	23	9	300	83	-10	+2	-1	+7	+14	1.2
Career	—	MLE		—	6372	5641	1267	223	20	119	601	1462	85	298	88	225	309	335	643	110	281	23	9	291	83	-75	+13	-10	+54	+108	9.1
/ 162G	—	MLE		—	650	575	129	23	2	12	61	149	9	30	9	224	308	334	642	110	281	23	9	291	83	-10	+2	-1	+7	+14	1.2

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 A+Hudson Valley Renegades · 347 PAwOBA .296 → .235 (−61)K% 18.4% → 24.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.44%	÷1.000	×1.310	—	—	24.16%
BB% (unintentional) /PA	12.10%	÷1.000	×0.600	—	×1.012	7.35%
HBP% /PA	1.73%	—	×0.770	—	×1.012	1.35%
Singles /BIP	20.78%	÷1.000	×0.870	×0.999	×1.012	18.27%
Doubles /BIP	4.33%	÷1.000	×0.780	×0.999	×1.012	3.41%
Triples /BIP	0.00%	÷1.000	×0.850	×0.999	×1.012	0.00%
Home runs /BIP	3.03%	÷1.000	×0.880	—	×1.012	2.70%

Factors used: league row South Atlantic League. Park (home-season share, regressed): no park row on file (treated as neutral) — 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 ×0.999.

Result: wOBA .296 → .235; ISO .105 → .091; BABIP .257 → .221. 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).

2026 ATampa Tarpons · 144 PAwOBA .349 → .277 (−72)K% 20.8% → 28.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.83%	÷1.000	×1.360	—	—	28.33%
BB% (unintentional) /PA	19.44%	÷1.000	×0.690	—	—	13.42%
HBP% /PA	1.39%	—	×0.780	—	—	1.08%
Singles /BIP	17.07%	÷1.000	×0.920	×0.989	—	15.53%
Doubles /BIP	10.98%	÷1.000	×0.830	×0.989	—	9.01%
Triples /BIP	1.22%	÷1.000	×0.910	×0.989	—	1.10%
Home runs /BIP	2.44%	÷1.000	×0.800	—	—	1.95%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 22 vs a level average of 22.0 → +0.0% on BB/HBP/hit rates (0.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.989.

Result: wOBA .349 → .277; ISO .152 → .125; BABIP .296 → .258. 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 ATampa Tarpons · 149 PAwOBA .336 → .274 (−62)K% 13.4% → 18.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.42%	÷1.000	×1.360	—	—	18.26%
BB% (unintentional) /PA	17.45%	÷0.971	×0.690	—	×1.015	12.59%
HBP% /PA	2.01%	—	×0.780	—	×1.015	1.59%
Singles /BIP	23.00%	÷1.119	×0.920	×1.014	×1.015	19.47%
Doubles /BIP	3.00%	÷1.046	×0.830	×1.014	×1.015	2.45%
Triples /BIP	0.00%	÷0.913	×0.910	×1.014	×1.015	0.00%
Home runs /BIP	3.00%	÷0.842	×0.800	—	×1.015	2.89%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 68, 1B 124, 2B 109, 3B 83, K 100, BB 94 — 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 ×1.014.

Result: wOBA .336 → .274; ISO .100 → .093; BABIP .268 → .226. 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 ROKFCL Yankees · 32 PAwOBA .363 → .242 (−121)K% 21.9% → 31.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.88%	÷1.001	×1.440	—	—	31.48%
BB% (unintentional) /PA	12.50%	÷1.000	×0.620	—	×0.985	7.63%
HBP% /PA	3.12%	—	×0.720	—	×0.985	2.22%
Singles /BIP	25.00%	÷1.056	×0.820	—	×0.985	19.12%
Doubles /BIP	15.00%	÷1.043	×0.720	—	×0.985	10.20%
Triples /BIP	0.00%	÷1.008	×0.720	—	×0.985	0.00%
Home runs /BIP	0.00%	÷2.059	×0.780	—	×0.985	0.00%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 312, 1B 111, 2B 109, 3B 102, K 100, BB 100 — applied at half strength. Age: age 21 vs a level average of 19.5 → −1.5% on BB/HBP/hit rates (1.5 yr older than average).

Result: wOBA .363 → .242; ISO .111 → .071; BABIP .400 → .293. 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 ATampa Tarpons · 185 PAwOBA .319 → .277 (−43)K% 19.5% → 27.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.46%	÷0.959	×1.360	—	—	27.60%
BB% (unintentional) /PA	5.41%	÷1.061	×0.690	—	×1.030	3.62%
HBP% /PA	1.08%	—	×0.780	—	×1.030	0.87%
Singles /BIP	33.33%	÷1.035	×0.920	×1.050	×1.030	32.04%
Doubles /BIP	5.30%	÷1.028	×0.830	×1.050	×1.030	4.63%
Triples /BIP	0.00%	÷0.971	×0.910	×1.050	×1.030	0.00%
Home runs /BIP	0.76%	÷0.979	×0.800	—	×1.030	0.64%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 96, 1B 107, 2B 106, 3B 94, K 92, BB 112 — applied at half strength. Age: age 20 vs a level average of 22.0 → +3.0% on BB/HBP/hit rates (2.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .319 → .277; ISO .060 → .049; BABIP .381 → .360. 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 ROKFCL Yankees · 18 PAwOBA .571 → .408 (−162)K% 11.1% → 16.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.11%	÷0.972	×1.440	—	—	16.45%
BB% (unintentional) /PA	11.11%	÷0.988	×0.620	—	×0.995	6.94%
HBP% /PA	0.00%	—	×0.720	—	×0.995	0.00%
Singles /BIP	35.71%	÷1.002	×0.820	—	×0.995	29.09%
Doubles /BIP	14.29%	÷1.087	×0.720	—	×0.995	9.42%
Triples /BIP	0.00%	÷0.970	×0.720	—	×0.995	0.00%
Home runs /BIP	7.14%	÷1.142	×0.780	—	×0.995	4.86%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 128, 1B 100, 2B 117, 3B 94, K 94, BB 98 — applied at half strength. Age: age 20 vs a level average of 19.5 → −0.5% on BB/HBP/hit rates (0.5 yr older than average).

Result: wOBA .571 → .408; ISO .312 → .207; BABIP .538 → .405. 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 ROKFCL Yankees · 217 PAwOBA .411 → .288 (−123)K% 20.3% → 30.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.28%	÷0.951	×1.440	—	—	30.71%
BB% (unintentional) /PA	20.28%	÷0.995	×0.620	—	×1.008	12.73%
HBP% /PA	2.76%	—	×0.720	—	×1.008	2.01%
Singles /BIP	31.97%	÷0.994	×0.820	×0.996	×1.008	26.48%
Doubles /BIP	3.28%	÷1.106	×0.720	×0.996	×1.008	2.14%
Triples /BIP	2.46%	÷0.900	×0.720	×0.996	×1.008	1.97%
Home runs /BIP	4.10%	÷1.383	×0.780	—	×1.008	2.33%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 177, 1B 99, 2B 121, 3B 80, K 90, BB 99 — applied at half strength. Age: age 19 vs a level average of 19.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.996.

Result: wOBA .411 → .288; ISO .151 → .093; BABIP .390 → .311. 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 NYY Bombers · 188 PAwOBA .417 → .271 (−146)K% 13.3% → 16.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.30%	÷0.987	×1.220	—	—	16.43%
BB% (unintentional) /PA	21.81%	÷0.977	×0.700	—	×1.008	15.75%
HBP% /PA	2.66%	—	×0.700	—	×1.008	1.88%
Singles /BIP	21.37%	÷1.023	×0.680	×0.996	×1.008	14.26%
Doubles /BIP	5.13%	÷1.057	×0.600	×0.996	×1.008	2.92%
Triples /BIP	5.98%	÷1.150	×0.600	×0.996	×1.008	3.13%
Home runs /BIP	2.56%	÷1.608	×0.470	—	×1.008	0.76%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 222, 1B 105, 2B 111, 3B 130, K 97, BB 95 — applied at half strength. Age: age 18 vs a level average of 18.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.996.

Result: wOBA .417 → .271; ISO .204 → .100; BABIP .333 → .205. 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
#1Freddie Patek'68-'81 * career totals — 13 seasons, 6,246 PA	9.4	6,246	41	385	242*	311*	356*	+66	-5	14.7	15.3
/162	664	4	41	+7.0	-0.5	1.6	pk7: 16
#2Bobby Crosbylast yr '10 career totals — 7 seasons, 2,832 PA	4.3	2,832	62	34	238	305	374	+28	+33	11.6	11.6
/162	664	15	8	+6.7	+7.7	2.7	pk7: 12
#3Danny Espinosalast yr '17 career totals — 8 seasons, 3,267 PA	4.9	3,267	98	64	221	297	378	+16	+36	11.0	11.4
/162	664	20	13	+3.2	+7.3	2.2	pk7: 12
#4Cliff Penningtonlast yr '17 career totals — 10 seasons, 3,108 PA	4.7	3,108	36	84	243	310	341	+28	+29	9.2	9.5
/162	664	8	18	+5.9	+6.2	2.0	pk7: 10
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	4.6	3,047	63	102	231	308	349	+33	+18	7.9	7.3
/162	664	14	22	+7.1	+3.9	1.7	pk7: 7
#5Damian Jackson'96-'06 * career totals — 7 seasons, 2,509 PA	3.8	2,509	32	133	232*	309*	342*	+10	+11	5.7	6.0
/162	664	8	35	+2.5	+3.0	1.5	pk7: 6
#6Pokey Reese'97-'04 * career totals — 8 seasons, 3,138 PA	4.7	3,138	44	144	238*	292*	339*	+19	+41	4.0	4.7
/162	664	9	30	+4.0	+8.7	0.8	pk7: 5

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
Enmanuel Tejeda (OGILVIE)	22	47→52	39→44	61→66	61	224/304/323	100	283	3	9	23%	9%	81	-0.0	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Masyn Winn 2023 · AA	21	48→53	44→50	61→55	46	231/292/359	128	308	9	28	27%	8%	84	+0.1	243/298/376	133	291	13	16	20%	7%	90	+0.6	248/309/365	117	296	11	11	19%	7%	93	+0.8
●Jakob Marsee 2023 · A	22	44→49	42→45	58→60	54	211/313/323	113	290	8	21	28%	12%	85	+0.2	220/320/345	125	277	13	33	24%	11%	93	+0.8	217/321/350	133	273	12	37	23%	11%	92	+0.8
✕Ryan Brett 2014 · AA	22	52→58	42→45	59→60	45	252/297/361	110	301	8	27	19%	5%	86	+0.3	247/284/354	107	302	8	18	20%	4%	79	-0.2	237/269/336	99	295	8	15	22%	3%	66	-0.6
✕Taylor Motter 2012 · A	22	48→49	42→50	55	53	232/307/339	107	284	9	20	21%	10%	85	+0.2	227/290/330	103	280	8	20	21%	8%	76	-0.4	245/294/375	130	284	13	21	18%	6%	86	+0.2
●Maikel Garcia 2022 · A	22	51→58	39→45	58→60	51	240/305/333	93	302	5	22	21%	9%	82	-0.0	250/306/350	100	317	7	27	22%	8%	86	+0.3	260/322/390	130	293	10	24	14%	8%	102	+1.4
✕Adrian Pinto 2023 · A	20	47	40→45	60→65	53	222/313/322	100	267	5	29	18%	9%	84	+0.1	234/309/354	120	293	11	18	23%	8%	90	+0.6	231/312/342	111	292	7	11	21%	9%	84	+0.0
✕José Rodríguez 2023 · AA	22	52→54	46→50	58→55	44	257/295/390	132	298	12	28	18%	5%	91	+0.7	238/272/362	124	290	14	26	22%	4%	76	-0.4	233/262/350	117	285	14	27	24%	3%	68	-0.5
✕Mario Lisson 2006 · A	22	46→49	43→50	57→55	50	221/307/345	123	302	9	19	28%	10%	86	+0.3	220/283/335	115	289	10	21	26%	7%	75	-0.5	222/292/345	123	288	15	8	27%	7%	80	-0.1
✕Tyler Pastornicky 2011 · AA	21	49→59	39→45	58→60	49	233/290/320	87	278	6	29	18%	7%	74	-0.6	262/305/359	97	304	7	19	16%	6%	88	+0.4	278/316/373	95	318	7	16	14%	5%	93	+0.5
●Peter Bourjos 2010 · AA	23	52→56	42→50	62→60	43	251/294/371	121	310	8	28	22%	5%	86	+0.3	251/299/394	143	310	12	24	22%	5%	94	+0.9	250/301/400	150	307	13	24	22%	5%	95	+0.8
✕Garrett Hampson 2018 · A	23	53→57	38→45	59→60	47	252/301/339	87	309	5	28	20%	6%	82	-0.0	247/300/356	109	317	9	27	23%	7%	85	+0.2	244/299/360	116	315	10	29	25%	7%	85	+0.2
✕Tsung-Che Cheng 2023 · A	22	48	42→45	57→55	50	227/304/340	113	301	7	21	26%	9%	84	+0.2	218/283/329	111	294	9	18	27%	8%	74	-0.6	209/274/311	102	283	9	19	28%	8%	63	-1.1
✕Jett Williams 2024 · AA	20	44→48	45→50	60→55	54	209/324/338	129	296	11	25	30%	12%	93	+0.8	216/310/345	129	299	10	23	28%	11%	88	+0.4	214/300/348	134	288	11	26	27%	10%	82	+0.0
●Fernando Perez 2006 · A	23	51→61	39→45	60	48	244/296/340	96	295	6	27	19%	7%	80	-0.2	260/324/359	99	359	6	26	27%	8%	95	+1.0	268/336/371	103	383	6	30	29%	9%	98	+1.2
✕Luisangel Acuña 2024 · AA	22	54→60	43→45	60	45	257/310/365	108	337	10	37	26%	7%	91	+0.7	249/290/337	88	311	6	35	21%	5%	77	-0.3	246/284/323	77	302	5	38	20%	5%	70	-0.6
●Desmond Jennings 2009 · A	22	51→61	43→50	56→60	49	248/311/364	116	295	10	25	19%	7%	92	+0.7	263/329/395	132	311	10	34	18%	8%	105	+1.7	264/336/406	142	313	11	37	18%	8%	108	+1.9
✕Delino DeShields 2015 · AA	22	49→56	42→45	62→65	47	234/308/343	109	312	9	41	26%	8%	86	+0.3	236/312/335	99	316	7	32	25%	9%	86	+0.3	240/319/333	93	321	6	34	25%	10%	85	+0.2
✕Adalberto Santos 2012 · A	24	51→55	43→45	59→55	48	244/303/364	120	295	8	21	20%	7%	88	+0.5	256/317/349	93	320	6	20	20%	7%	91	+0.6	262/325/343	81	331	5	21	21%	8%	89	+0.3
✕Dru Baker 2023 · A	23	49→57	44→40	58→60	45	236/301/356	120	326	11	24	30%	8%	86	+0.3	240/293/333	93	336	8	32	29%	6%	78	-0.3	239/291/316	77	338	6	36	29%	5%	70	-0.7
✕Noel Cuevas 2014 · A	22	47→52	43→45	56→55	41	231/276/347	116	293	10	24	24%	5%	75	-0.5	229/266/325	96	296	7	17	24%	4%	65	-1.2	254/287/363	108	316	8	12	22%	3%	80	-0.1

Enmanuel Tejeda

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps