Eduardo Guerrero

SS Great Lakes Loons

Age 22 S/R 6'2" / 165 lbs A+ HR +8%BB -8% Svc 0.0 · Ctrl thru 2036

Overview

A+PROSPECTMiLBFA 2037

OGV OFP35OGV rank#508ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	19	A/ROK2 orgs	259	.234/.379/.283	0	9	51	—	.187/.293/.219
2025	20	AA/A+/A2 orgs	405	.214/.363/.291	3	8	60	—	.193/.308/.255
2026	21	A+LAD	467	.278/.374/.363	5	15	82	—	.253/.326/.323
2027PROJMLE	22	MLBLAD	1	.209/.297/.272	0	0	68	-0.0
2028PROJ35% MLB	23	MLBLAD	147	.216/.303/.297	2	3	76	0.1
2029PROJ46% MLB	24	MLBLAD	219	.221/.308/.313	3	4	81	0.2

Next 3 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2036Service0.0First FA2037

2027MiLB2028MiLB2029MiLB2030MiLB2031Pre-Arb$0.9M2032Pre-Arb$0.9M2033Pre-Arb$0.9M2034Arb-1$2M+2

Skills · percentileMiLB Statcast 2026 A+

Chase%88

Z-Con%87

Whiff%85

K%76

BB%59

wOBA49

Career WAR0.0 WAR median (P10 -0.1 / P90 5.9, comp-based) · star 1% · didn't stick 84%

CompsJeremy Arocho (age 22) · Noe Becerra (age 22) · Juan Mosquera (age 21)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†68

AVG/OBP/SLG.209 / .297 / .272

PA1

HR0

K%22

BB%10

BABIP269

ISO70

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$12M ctrl surplus

Tools · ContractCON 40 / POW 25

Toolsscout grade

CONTACT40

scouting grade only

POWER25

scouting grade only

EYE60

scouting grade only

SPEED45

scouting grade only

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

Status MiLB

MLB Debut 2031

Service 0 yrs (est)

Team Control Through 2036

First FA Year 2037

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2031
2028	MiLB	still in minors · estimated debut 2031
2029	MiLB	still in minors · estimated debut 2031
2030	MiLB	still in minors · estimated debut 2031
2031	Pre-Arb	$0.9M	+0.5	$1M	+$0.9M
2032	Pre-Arb	$0.9M	+0.5	$1M	+$0.8M
2033	Pre-Arb	$0.9M	+0.4	$1M	+$0.5M
2034	Arb-1	$2M	+0.2	$0.5M	+$0.0M (cut)
2035	Arb-2	$2M	+0.1	$0.2M	+$0.0M (cut)
2036	Arb-3	$1.0M	—	—	—
Totals		$3M		$4M	+$2M

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 Mega	—	202	172	51	4	0	1	23	32	3	6	4	297	389	337	726	41	350	16	11	332	46	—	—	—	—	—	—
2023	18	ROK	DSL LAD Mega	—	184	162	42	12	2	1	18	24	1	4	3	259	337	377	714	117	293	13	10	318	22	—	—	—	—	—	—
2024	19	A	Rancho Cucamonga Quakes	—	90	77	15	1	0	0	12	22	0	3	1	195	303	208	511	13	268	24	13	248	22	—	—	—	—	—	—
2024	19	ROK	ACL Dodgers	—	169	128	33	3	3	0	30	29	6	6	0	258	421	328	749	70	317	17	18	346	66	—	—	—	—	—	—
2025	20	AA	Tulsa Drillers	—	53	45	9	0	0	0	7	13	0	0	1	200	308	200	508		281	25	13	246	30	—	—	—	—	—	—
2025	20	A+	Great Lakes Loons	—	22	21	3	0	1	0	1	4	0	0	0	143	182	238	420	95	176	18	5	187	-14	—	—	—	—	—	—
2025	20	A	Rancho Cucamonga Quakes	—	330	257	57	8	3	3	63	51	5	8	5	222	385	311	696	89	262	15	19	327	70	—	—	—	—	—	—
2026	21	A+	Great Lakes Loons	—	467	399	111	15	2	5	59	90	2	15	6	278	374	363	737	85	342	19	13	334	82	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2022	17	ROK MLE	DSL LAD Mega	—	202	179	38	2	0	1	16	40	3	6	4	212	288	240	528	28	251	20	8	236	46	—	—	—	—	—	—
2023	18	ROK MLE	DSL LAD Mega	—	184	168	26	7	1	0	12	30	1	4	3	155	215	208	424	54	184	16	7	201	22	—	—	—	—	—	—
2024	19	A MLE	Rancho Cucamonga Quakes	—	90	80	13	1	0	0	9	31	0	3	1	163	247	175	422	12	249	34	10	200	22	—	—	—	—	—	—
2024	19	ROK MLE	ACL Dodgers	—	169	140	28	2	2	0	18	42	6	6	0	200	317	243	560	43	268	25	11	266	66	—	—	—	—	—	—
2025	20	AA MLE	Tulsa Drillers	—	53	47	9	0	0	0	5	16	0	0	1	191	269	191	461		281	30	9	212	30	—	—	—	—	—	—
2025	20	A+ MLE	Great Lakes Loons	—	22	21	3	0	1	0	1	5	0	0	0	143	182	238	420	95	158	23	5	147	-14	—	—	—	—	—	—
2025	20	A MLE	Rancho Cucamonga Quakes	—	330	274	54	7	3	2	46	70	5	8	5	197	323	266	590	69	244	21	14	271	70	—	—	—	—	—	—
2026	21	A+ MLE	Great Lakes Loons	—	467	415	105	13	2	4	43	114	2	15	6	253	326	323	649	70	324	24	9	289	82	—	—	—	—	—	—
2022	17	ROK MLE	DSL LAD Mega	—	202	179	38	2	0	1	16	40	3	6	4	212	288	240	528	28	261	20	8	236	46	—	—	—	—	—	—
2022	17	ROK RAW	DSL LAD Mega	—	202	172	51	4	0	1	23	32	3	6	4	297	389	337	726	41	350	16	11	332	46	—	—	—	—	—	—
2023	18	ROK MLE	DSL LAD Mega	—	184	168	26	7	1	0	12	30	1	4	3	155	215	208	424	54	184	16	7	201	22	—	—	—	—	—	—
2023	18	ROK RAW	DSL LAD Mega	—	184	162	42	12	2	1	18	24	1	4	3	259	337	377	714	117	293	13	10	318	22	—	—	—	—	—	—
2024	19	ROK MLE	2 teams	—	259	220	41	3	2	0	27	73	6	9	1	186	292	218	511	32	268	28	10	243	51	—	—	—	—	—	—
2024	19	ROK RAW	2 teams	—	259	205	48	4	3	0	42	51	6	9	1	234	379	283	662	49	300	20	16	312	51	—	—	—	—	—	—
2025	20	A MLE	3 teams	—	405	343	65	7	3	2	51	92	5	8	6	190	303	245	548	55	250	23	13	257	60	—	—	—	—	—	—
2025	20	A RAW	3 teams	—	405	323	69	8	4	3	71	68	5	8	6	214	363	291	654	77	259	17	18	309	60	—	—	—	—	—	—
2026	21	A+ MLE	Great Lakes Loons	—	467	415	105	13	2	4	43	114	2	15	6	253	326	323	649	70	333	24	9	289	82	—	—	—	—	—	—
2026	21	A+ RAW	Great Lakes Loons	—	467	399	111	15	2	5	59	90	2	15	6	278	374	363	737	85	342	19	13	334	82	—	—	—	—	—	—
2022	17	ROK MLE	DSL LAD Mega	—	202	181	38	2	0	1	16	40	3	6	4	210	288	238	525	28	251	20	8	236	46	—	—	—	—	—	—
2023	18	ROK MLE	DSL LAD Mega	—	184	169	26	7	1	0	12	30	1	4	3	154	215	207	423	53	184	16	7	201	22	—	—	—	—	—	—
2024	19	ROK MLE	2 teams	—	259	224	41	3	2	0	27	73	6	9	1	183	292	214	507	31	261	28	10	243	51	—	—	—	—	—	—
2025	20	A MLE	3 teams	—	405	346	65	7	3	2	51	92	5	8	6	188	303	243	546	55	244	23	13	257	60	—	—	—	—	—	—
2026	21	A+ MLE	Great Lakes Loons	—	467	419	105	13	2	4	43	114	2	15	6	251	326	320	646	69	324	24	9	289	82	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	19	ROK MLE	2 teams	—	259	224	41	3	2	0	27	73	6	9	1	183	292	214	507	31	261	28	10	243	51	—	—	—	—	—	—
2025	20	A MLE	3 teams	—	405	346	65	7	3	2	51	92	5	8	6	188	303	243	546	55	244	23	13	257	60	—	—	—	—	—	—
2026	21	A+ MLE	Great Lakes Loons	—	467	419	105	13	2	4	43	114	2	15	6	251	326	320	646	69	324	24	9	289	82	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	22	MLB MLE	LAD	0%	577	508	109	15	3	4	60	130	4	10	4	213	300	278	579	65	275	23	10	269	68	-22	+0	+0	+6	+13	0.0
▸ 2027 — real world (MLB)
2027	22	MLB CTX	LAD	0%	1	1	0	0	0	0	0	0	0	0	0	209	297	272	569	63	269	0	0	265	68	-0	+0	+0	+0	+0	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	23	MLB MLE	LAD	35%	426	376	82	11	2	5	44	94	3	8	3	220	307	302	609	82	277	22	10	280	76	-12	+0	+0	+5	+9	0.2
2029	24	MLB MLE	LAD	46%	474	419	93	13	2	7	49	103	3	9	4	224	311	318	629	94	278	22	10	288	81	-11	+0	+0	+5	+10	0.5
2030	25	MLB MLE	LAD	52%	521	458	105	15	3	9	54	113	4	9	4	227	313	328	641	102	279	22	10	293	84	-10	+0	+0	+6	+11	0.7
2031	26	MLB MLE	LAD	54%	534	470	108	15	3	10	55	116	4	9	4	228	314	334	648	106	280	22	10	295	86	-9	+0	+0	+6	+12	0.9
2032	27	MLB MLE	LAD	54%	537	473	109	16	3	10	55	118	4	9	4	228	313	335	648	107	280	22	10	295	86	-9	+0	+0	+6	+12	0.9
2033	28	MLB MLE	LAD	54%	533	469	107	15	3	10	55	118	4	7	4	226	311	331	642	104	279	22	10	292	84	-10	-0	-1	+6	+12	0.6
2034	29	MLB MLE	LAD	53%	522	461	103	15	2	9	53	117	3	5	3	224	309	325	633	101	278	22	10	289	82	-11	-0	-1	+6	+11	0.4
2035	30	MLB MLE	LAD	52%	510	450	99	14	2	8	52	116	3	3	3	221	305	317	622	96	277	23	10	285	79	-13	-1	-2	+5	+11	0.1
2036	31	MLB MLE	LAD	52%	493	438	94	13	2	7	49	114	3	2	2	217	300	308	608	90	274	23	10	279	75	-15	-0	-3	+5	+11	-0.2
2028	23	MLB CTX	LAD	35%	147	130	29	4	1	2	15	32	1	3	1	216	303	297	600	80	271	22	10	277	76	-4	+0	+0	+2	+3	0.1
2029	24	MLB CTX	LAD	46%	219	193	43	6	1	3	23	48	1	4	2	221	308	313	621	93	273	22	11	285	81	-5	+0	+0	+2	+5	0.2
2030	25	MLB CTX	LAD	52%	269	237	53	7	1	5	28	59	2	5	2	223	310	324	633	100	274	22	10	289	84	-5	+0	+0	+3	+6	0.4
2031	26	MLB CTX	LAD	54%	290	256	58	8	1	6	30	63	2	5	2	225	311	329	640	105	274	22	10	292	86	-5	+0	+0	+3	+6	0.5
2032	27	MLB CTX	LAD	54%	291	257	58	8	1	6	30	64	2	5	2	224	310	331	641	106	274	22	10	292	86	-5	+0	+0	+3	+6	0.5
2033	28	MLB CTX	LAD	54%	289	255	56	8	1	5	30	64	2	4	2	223	308	326	634	103	274	22	10	289	84	-5	+0	-0	+3	+6	0.4
2034	29	MLB CTX	LAD	53%	277	245	54	7	1	5	28	62	2	3	2	220	305	320	626	100	273	22	10	286	82	-6	-0	-1	+3	+6	0.2
2035	30	MLB CTX	LAD	52%	267	236	51	7	1	4	27	61	2	2	1	218	302	313	615	95	271	23	10	282	79	-7	+0	-1	+3	+6	0.1
2036	31	MLB CTX	LAD	52%	256	227	49	7	1	4	26	59	1	1	1	214	297	303	601	89	269	23	10	276	75	-8	-0	-1	+3	+6	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2305	2036	451	62	9	40	237	512	15	32	15	222	307	320	627	98	275	22	10	286	76	-50	+0	-4	+25	+50	2.2
/ 162G	—	A+C		—	650	574	127	17	3	11	67	144	4	9	4	221	307	319	626	98	275	22	10	286	76	-14	+0	-1	+7	+14	0.6
Career	—	MLE		—	6277	5524	1215	164	31	84	637	1405	49	107	53	220	306	306	613	87	277	22	10	280	76	-108	-0	-7	+51	+103	4.0
/ 162G	—	MLE		—	650	572	126	17	3	9	66	145	5	11	5	220	306	308	614	87	277	22	10	280	76	-15	-0	-1	+7	+14	0.5

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+Great Lakes Loons · 467 PAwOBA .330 → .289 (−41)K% 19.3% → 24.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.27%	÷1.000	×1.270	—	—	24.48%
BB% (unintentional) /PA	12.63%	÷1.000	×0.710	—	×1.027	9.21%
HBP% /PA	0.43%	—	×0.790	—	×1.027	0.35%
Singles /BIP	28.80%	÷1.000	×0.920	×1.023	×1.027	27.85%
Doubles /BIP	4.85%	÷1.000	×0.810	×1.023	×1.027	4.13%
Triples /BIP	0.65%	÷1.000	×0.850	×1.023	×1.027	0.58%
Home runs /BIP	1.62%	÷1.000	×0.800	—	×1.027	1.33%

Factors used: league row Midwest League. 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 22.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.023.

Result: wOBA .330 → .289; ISO .085 → .072; BABIP .342 → .324. 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 ARancho Cucamonga Quakes · 330 PAwOBA .323 → .271 (−52)K% 15.5% → 21.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.45%	÷0.987	×1.360	—	—	21.29%
BB% (unintentional) /PA	19.09%	÷0.981	×0.690	—	×1.030	13.83%
HBP% /PA	1.52%	—	×0.780	—	×1.030	1.22%
Singles /BIP	20.87%	÷1.004	×0.920	×1.018	×1.030	20.06%
Doubles /BIP	3.88%	÷1.054	×0.830	×1.018	×1.030	3.21%
Triples /BIP	1.46%	÷1.150	×0.910	×1.018	×1.030	1.21%
Home runs /BIP	1.46%	÷1.055	×0.800	—	×1.030	1.14%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 111, 1B 101, 2B 111, 3B 130, K 97, BB 96 — 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 ×1.018.

Result: wOBA .323 → .271; ISO .089 → .074; BABIP .262 → .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).

2025 AATulsa Drillers · 53 PAwOBA .241 → .212 (−28)K% 24.5% → 30.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.53%	÷0.984	×1.220	—	—	30.42%
BB% (unintentional) /PA	13.21%	÷1.061	×0.700	—	×1.050	9.15%
HBP% /PA	0.00%	—	×0.870	—	×1.050	0.00%
Singles /BIP	28.12%	÷0.968	×0.920	—	×1.050	28.07%
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 .241 → .212; ISO .000 → .000; BABIP .281 → .281. 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 · 22 PAwOBA .183 → .147 (−35)K% 18.2% → 23.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.18%	÷0.980	×1.270	—	—	23.56%
BB% (unintentional) /PA	4.55%	÷1.023	×0.710	—	×1.042	3.29%
HBP% /PA	0.00%	—	×0.790	—	×1.042	0.00%
Singles /BIP	11.76%	÷1.000	×0.920	—	×1.042	11.28%
Doubles /BIP	0.00%	÷0.927	×0.810	—	×1.042	0.00%
Triples /BIP	5.88%	÷1.150	×0.850	—	×1.042	4.53%
Home runs /BIP	0.00%	÷0.992	×0.800	—	×1.042	0.00%

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).

Result: wOBA .183 → .147; ISO .095 → .069; BABIP .176 → .158. 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 ROKACL Dodgers · 169 PAwOBA .349 → .266 (−83)K% 17.2% → 25.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.16%	÷0.984	×1.440	—	—	25.11%
BB% (unintentional) /PA	17.75%	÷1.070	×0.620	—	×1.008	10.37%
HBP% /PA	3.55%	—	×0.720	—	×1.008	2.58%
Singles /BIP	27.27%	÷1.011	×0.820	×1.049	×1.008	23.37%
Doubles /BIP	3.03%	÷1.010	×0.720	×1.049	×1.008	2.28%
Triples /BIP	3.03%	÷0.967	×0.720	×1.049	×1.008	2.38%
Home runs /BIP	0.00%	÷0.942	×0.780	—	×1.008	0.00%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 88, 1B 102, 2B 102, 3B 93, K 97, BB 114 — 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 ×1.049.

Result: wOBA .349 → .266; ISO .070 → .058; BABIP .317 → .268. 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 · 90 PAwOBA .245 → .200 (−46)K% 24.4% → 34.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.44%	÷0.964	×1.360	—	—	34.48%
BB% (unintentional) /PA	13.33%	÷0.943	×0.690	—	×1.045	10.20%
HBP% /PA	0.00%	—	×0.780	—	×1.045	0.00%
Singles /BIP	25.45%	÷1.072	×0.920	×1.041	×1.045	23.76%
Doubles /BIP	1.82%	÷0.973	×0.830	×1.041	×1.045	1.69%
Triples /BIP	0.00%	÷0.973	×0.910	×1.041	×1.045	0.00%
Home runs /BIP	0.00%	÷1.072	×0.800	—	×1.045	0.00%

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 ×1.041.

Result: wOBA .245 → .200; ISO .013 → .011; BABIP .268 → .249. 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 DSLDSL LAD Mega · 184 PAwOBA .315 → .201 (−114)K% 13.0% → 16.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.04%	÷0.978	×1.220	—	—	16.28%
BB% (unintentional) /PA	9.78%	÷1.050	×0.700	—	×1.008	6.57%
HBP% /PA	0.54%	—	×0.700	—	×1.008	0.38%
Singles /BIP	19.57%	÷0.998	×0.680	×0.950	×1.008	12.77%
Doubles /BIP	8.70%	÷0.985	×0.600	×0.950	×1.008	5.07%
Triples /BIP	1.45%	÷0.937	×0.600	×0.950	×1.008	0.89%
Home runs /BIP	0.72%	÷1.325	×0.470	—	×1.008	0.26%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 165, 1B 100, 2B 97, 3B 87, K 96, BB 110 — 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 ×0.950.

Result: wOBA .315 → .201; ISO .117 → .066; BABIP .293 → .184. 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 Mega · 202 PAwOBA .331 → .236 (−94)K% 15.8% → 19.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.84%	÷0.973	×1.220	—	—	19.87%
BB% (unintentional) /PA	11.39%	÷1.059	×0.700	—	×1.022	7.70%
HBP% /PA	1.49%	—	×0.700	—	×1.022	1.06%
Singles /BIP	32.86%	÷0.977	×0.680	×1.026	×1.022	23.99%
Doubles /BIP	2.86%	÷1.045	×0.600	×1.026	×1.022	1.72%
Triples /BIP	0.00%	÷1.150	×0.600	×1.026	×1.022	0.00%
Home runs /BIP	0.71%	÷0.975	×0.470	—	×1.022	0.35%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 95, 1B 95, 2B 109, 3B 130, K 95, BB 112 — 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 ×1.026.

Result: wOBA .331 → .236; ISO .041 → .023; BABIP .350 → .251. 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
#1Bobby 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
#2Cliff 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
#3Jose Uribe'84-'93 * career totals — 9 seasons, 3,369 PA	5.1	3,369	19	74	240*	300*	338*	+36	+27	7.8	7.7
/162	664	4	15	+7.1	+5.3	1.5	pk7: 8
#4Kevin Stocker'93-'00 * career totals — 8 seasons, 3,197 PA	4.8	3,197	23	45	241*	324*	337*	+34	+8	6.4	6.5
/162	664	5	9	+7.1	+1.8	1.3	pk7: 7
#5Gene Michael'66-'75 * career totals — 9 seasons, 3,095 PA	4.7	3,095	15	22	233*	291*	316*	+32	+27	4.6	5.8
/162	664	3	5	+6.8	+5.8	1.0	pk7: 7
#6Ronny Cedenolast yr '13 career totals — 9 seasons, 2,783 PA	4.2	2,783	40	39	246	289	354	+28	+19	5.5	5.6
/162	664	10	9	+6.7	+4.5	1.3	pk7: 6
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 5 projected seasons	3.5	2,308	38	30	225	307	325	+25	+15	3.7	3.6
/162	664	11	9	+7.1	+4.3	1.1	pk7: 3

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
Eduardo Guerrero (OGILVIE)	22	40	25	45	60	211/298/276	64	275	2	4	22%	10%	68	-0.3	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Jeremy Arocho 2021 · A	22	48→44	36→30	48→60	47	224/284/295	71	288	3	10	22%	7%	65	-1.2	228/321/282	54	318	2	26	25%	12%	78	-0.3	221/328/267	46	302	1	34	24%	13%	75	-0.3
✕Noe Becerra 2009 · AAA	22	43	37→30	44→40	48	206/272/275	69	267	5	7	24%	8%	57	-1.8	233/292/318	85	284	7	7	19%	7%	74	-0.5	291/342/352	61	329	2	0	12%	6%	99	+0.4
✕Juan Mosquera 2009 · A	21	41	33→30	46→55	54	187/287/229	41	257	1	14	25%	11%	54	-2.0	199/263/256	57	258	2	9	22%	7%	49	-2.4	181/239/208	28	219	0	9	16%	7%	26	-1.0
✕Yonathan Mendoza 2015 · A	21	46	35→30	46→45	50	216/280/274	58	267	2	8	19%	8%	59	-1.6	244/296/307	63	293	3	6	17%	7%	72	-0.7	255/305/308	53	303	3	5	16%	6%	75	-0.3
✕Elih Marrero 2019 · A	22	45	36→40	49→55	47	212/276/279	66	277	3	5	23%	8%	59	-1.6	212/271/292	80	283	5	9	25%	7%	60	-1.6	210/266/317	107	293	8	22	29%	6%	61	-0.4
✕Riley Unroe 2018 · AA	22	41→47	37→45	47→55	45	195/265/266	71	282	5	12	31%	8%	53	-2.1	212/278/300	88	296	7	12	29%	8%	65	-1.2	218/301/329	112	292	11	26	27%	10%	78	-0.1
✕Josh Johnson 2008 · A	22	47→50	36→45	45→50	54	221/304/291	70	284	3	9	22%	10%	73	-0.6	230/312/308	78	298	4	10	22%	10%	80	-0.2	247/316/346	99	293	8	16	17%	9%	86	+0.2
✕Miguel Arrendell 2010 · A	22	41	37→30	48→50	58	193/299/261	68	248	4	11	22%	12%	65	-1.2	210/275/291	81	274	6	9	24%	8%	62	-1.4	209/267/286	77	266	6	10	23%	7%	55	-0.8
✕Dalfis Ortiz 2013 · A	21	44	35→40	43→55	52	203/285/265	61	276	2	10	25%	10%	60	-1.6	200/265/273	73	242	2	14	17%	8%	53	-2.1	210/273/300	89	245	1	18	14%	8%	63	-0.5
✕Manuel Bobadilla 2007 · AAA	23	43	39→40	47→45	48	207/263/289	82	242	7	9	18%	6%	57	-1.8	224/296/330	106	283	11	6	23%	8%	79	-0.2	238/312/336	99	295	9	4	21%	8%	84	+0.1
✕Carlos Alvarez 2008 · A	22	44	36→40	49→45	49	203/282/268	65	263	2	8	22%	8%	60	-1.6	209/292/288	79	245	4	8	15%	9%	68	-1.0	198/293/274	77	226	3	9	13%	10%	64	-0.5
✕Alfredo Angarita 2019 · A	22	44	35→30	47→55	45	207/270/266	59	285	2	12	27%	8%	54	-2.0	199/264/264	65	289	3	9	30%	7%	51	-2.2	130/215/146	16	199	0	7	31%	9%	7	-1.4
✕Kier Meredith 2022 · A	22	42	36→30	51→60	45	197/266/263	67	278	4	12	29%	8%	53	-2.1	208/305/278	70	291	4	26	27%	9%	72	-0.7	223/339/272	49	296	2	35	22%	11%	80	-0.0
✕Oliver Nunez 2017 · A	22	45	35→30	49→50	57	206/288/267	60	245	2	12	16%	10%	61	-1.5	216/266/288	72	283	4	13	24%	6%	57	-1.8	215/258/281	66	284	5	16	25%	5%	50	-0.9
✕Frainyer Chavez 2022 · A	23	44→47	35→40	46→50	47	206/279/262	56	290	2	11	28%	8%	57	-1.8	208/270/278	70	287	5	13	27%	7%	57	-1.8	223/291/306	84	291	8	18	25%	8%	69	-0.7
✕Cesar Diaz 2015 · A	22	51	38→40	47→50	53	237/306/318	81	270	5	12	14%	8%	80	-0.2	225/294/314	89	265	5	19	16%	8%	74	-0.5	223/294/319	96	258	5	28	15%	9%	72	-0.2
✕Taylor Krick 2011 · A	23	43	39→30	48→40	50	207/292/287	80	272	6	7	25%	9%	68	-1.0	226/310/289	63	311	3	5	26%	8%	76	-0.4	233/322/283	50	324	2	2	25%	8%	76	-0.2
✕Angelo Amendolare 2016 · AAA	23	47	37→30	44→50	51	220/294/294	73	264	4	7	18%	8%	70	-0.8	227/298/297	70	305	3	9	25%	8%	72	-0.7	237/314/279	43	327	0	10	25%	8%	70	-0.3
✕Mack Chambers 2022 · A	22	42	37→40	45→50	44	199/258/274	76	267	4	7	26%	7%	51	-2.2	213/275/311	98	279	8	11	25%	7%	66	-1.1	206/273/300	95	263	9	13	24%	8%	61	-0.8
✕Deivi Estrada 2022 · A	21	43	36→30	46→50	47	200/276/265	66	284	3	8	29%	9%	57	-1.8	184/240/252	68	328	3	8	42%	6%	40	-3.1	144/185/202	58	313	3	4	52%	4%	4	-1.2

Eduardo Guerrero

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps