Jose Siri

CF Los Angeles Angels

Age 32 R/R 6'2" / 210 lbs MLB K +5%HR +4% Svc 3.331 · Ctrl thru 2029

Overview

MLB40-MANArb-1FA 2030

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	29	INTLGigantes del …	59	.260/.362/.400	1	9	116	—
2024	29	MLBTB	448	.187/.256/.366	18	14	72	0.9
2025	30	AAA/INTL2 orgs	41	.184/.225/.316	1	2	9	—	.100/.100/.150
2025	30	MLBNYM	36	.062/.167/.125	0	2	-10	-0.4
2026	31	AAALAA	140	.288/.355/.504	5	4	75	—	.217/.268/.364
2026	31	MLBLAA	251	.241/.297/.417	10	9	93	0.6
2027PROJ	32	MLBLAA	203	.216/.274/.405	9	14	88	0.7
2028PROJ82% MLB	33	MLBLAA	144	.208/.265/.388	6	7	81	-0.0

Last 3 seasons WAR 1.1 · Next 2 projected WAR 0.6Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2029Service3.331First FA2030

2027Arb-1$0.6M2028Arb-2$0.7M2029Ext$2M

Skills · percentileStatcast 2024-2026

Barrel%90

Speed90

Bat Spd57

xwOBA39

Avg EV34

Form.219/.274/.401 · rolling true talent (60d window) · proj .216/.272/.404

CompsDylan Moore (age 31) · George Lombard (age 31) · Reggie Abercrombie (age 32)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 9188vR 77

AVG/OBP/SLG.216 / .274 / .405

PA203

HR9

SB14

K%33

BB%6

BABIP276

ISO194

MLB%100%

Value2027 · WAR

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

Tools · Recent Form · Splits · ContractCON 30 / POW 60

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT30

xAVG

100.202

POWER60

Barrel%

9014.4

Avg EV

3487.9

Bat Spd

5772.1

EYE40

scouting grade only

SPEED60

Sprint

9030.0

Recent Formrolling true talent ⓘ

K%32%▲31% over 71 PA (60d) · proj 32%

BB%6%·6% over 71 PA (60d) · proj 6%

ISO.182·.167 over 66 AB (60d) · proj .188

HR/BB7.1%·6.8% over 44 BBE (60d) · proj 7.1%

BABIP.280·.317 over 41 BIP (60d) · proj .279

SLASH.219/.274/.401·proj .216/.272/.404

Platoon Splits2024-2025 · 471 PA

vs LHP

vs RHP

Edge

112

359

—

wRC+

◀◀L

wOBA

294

262

◀L

ISO

204

164

◀◀L

BABIP

259

251

◀L

33.9%

38.4%

◀L

BB%

8.9%

7.0%

◀◀L

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

Status Arb-1

MLB Debut 2021

Service 3.331 yrs.days

Team Control Through 2029

First FA Year 2030

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-1	$0.6M	+0.3	$1M	+$0.6M
2028	Arb-2	$0.7M	—	—	—
2029	Ext	beyond projection horizon · no WAR estimate
Totals		$0.6M		$1M	+$0.6M

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)
2013	18	ROK	DSL Reds	—	265	238	72	10	9	5	18	57	5	17	10	303	364	483	847	181	379	22	7	368	44	—	—	—	—	—	—
2014	19	ROK	AZL Reds	—	172	157	39	6	4	2	12	35	2	12	2	248	310	376	686	127	308	20	7	306	34	—	—	—	—	—	—
2015	20	ROK	Billings Mustangs	—	181	176	43	7	9	3	4	65	0	11	2	244	261	438	699	193	370	36	2	300	0	—	—	—	—	—	—
2016	21	A	Dayton Dragons	—	87	83	12	3	0	0	2	34	0	3	2	145	165	181	345	36	240	39	2	154	-42	—	—	—	—	—	—
2016	21	ROK	Billings Mustangs	—	255	241	77	12	8	10	8	66	3	17	4	320	349	560	909	241	404	26	3	390	51	—	—	—	—	—	—
2017	22	A	Dayton Dragons	—	552	498	146	24	11	24	33	130	6	46	12	293	345	530	875	237	349	24	6	371	72	—	—	—	—	—	—
2017	22	INTL	Gigantes del Cibao	—	84	78	25	6	1	2	3	25	1	11	3	321	354	500	854	179	442	30	4	367	134	—	—	—	—	—	—
2018	23	AA	Pensacola Blue Wahoos	—	283	253	58	8	9	12	24	91	3	14	5	229	304	474	778	245	301	32	8	336	70	—	—	—	—	—	—
2018	23	A+	Daytona Tortugas	—	126	119	31	9	2	1	4	32	0	9	1	261	285	395	680	134	341	25	3	292	40	—	—	—	—	—	—
2018	23	INTL	Gigantes del Cibao	—	143	131	36	7	2	3	8	39	3	13	3	275	331	427	758	153	367	27	6	335	113	—	—	—	—	—	—
2019	24	AAA	Louisville Bats	—	112	102	19	4	1	0	9	39	0	5	2	186	252	245	497	59	302	35	8	229	-1	—	—	—	—	—	—
2019	24	AA	Chattanooga Lookouts	—	405	366	92	15	1	11	33	126	1	21	6	251	315	388	703	137	349	31	8	312	48	—	—	—	—	—	—
2019	24	INTL	Gigantes del Cibao	—	125	112	22	4	1	6	10	34	1	4	0	196	268	411	679	214	216	27	8	295	86	—	—	—	—	—	—
2020	25	INTL	Gigantes del Cibao	—	122	110	31	7	0	3	12	34	0	7	3	282	352	427	780	145	384	28	10	349	122	—	—	—	—	—	—
2021	26	MLB	Houston Astros	—	49	46	14	0	1	4	1	17	2	3	1	304	347	609	956	304	400	35	2	413	168	+4	+0	-0	-6	+1	-0.1
2021	26	AAA	Sugar Land Skeeters	—	397	362	115	29	4	16	26	122	5	24	3	318	372	552	924	235	436	31	7	399	102	—	—	—	—	—	—
2021	26	INTL	Dominican Republic	—	109	99	23	3	2	2	8	26	1	6	3	232	294	364	657	131	296	24	7	294	85	—	—	—	—	—	—
2022	27	MLB	Tampa Bay Rays	—	325	301	64	13	2	7	20	108	3	14	2	213	269	339	607	126	305	33	6	273	70	-11	+2	+12	+2	+7	1.1
2022	27	AAA	Sugar Land Space Cowboys	—	78	71	21	3	2	9	6	20	0	2	0	296	351	775	1.125	479	279	26	8	466	131	—	—	—	—	—	—
2022	27	INTL	Gigantes del Cibao	—	85	73	23	6	1	2	9	19	1	9	2	315	393	507	900	192	404	22	11	390	150	—	—	—	—	—	—
2023	28	MLB	Tampa Bay Rays	—	364	338	75	13	2	25	20	130	2	12	3	222	269	494	764	272	269	36	5	327	109	+4	+1	+8	+1	+8	2.4
2023	28	INTL	Gigantes del Cibao	—	52	39	9	0	0	2	11	12	1	5	2	231	412	385	796	154	280	23	21	364	132	—	—	—	—	—	—
2024	29	MLB	Tampa Bay Rays	—	448	402	75	16	1	18	31	170	7	14	7	187	256	366	621	179	261	38	7	274	72	-15	+0	+12	+2	+10	0.9
2024	29	INTL	Gigantes del Cibao	—	59	50	13	4	0	1	7	16	1	9	1	260	362	400	762	140	353	27	12	340	116	—	—	—	—	—	—
2025	30	MLB	New York Mets	—	36	32	2	2	0	0	4	17	0	2	0	62	167	125	292	62	133	47	11	149	-10	-5	+0	-1	+0	+1	-0.4
2025	30	AAA	Syracuse Mets	—	20	20	4	1	0	1	0	10	0	0	0	200	200	400	600	200	333	50	0	259	-14	—	—	—	—	—	—
2025	30	INTL	Gigantes del Cibao	—	21	18	3	1	0	0	2	5	0	2	0	167	250	222	472	56	214	24	10	214	31	—	—	—	—	—	—
2026	31	MLB	Los Angeles Angels	—	251	228	55	10	0	10	15	80	3	9	1	241	297	417	713	175	324	32	6	311	93	-2	+1	+0	+1	+5	0.6
2026	31	AAA	Salt Lake Bees	—	140	125	36	6	3	5	11	37	2	4	0	288	355	504	859	216	369	26	8	371	75	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1473	1347	285	54	6	64	91	522	17	54	14	212	270	403	673	192	287	35	6	295	85	-25	+5	+31	+1	+32	4.5
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2013	18	ROK MLE	DSL Reds	—	265	243	46	6	5	2	13	69	5	17	10	189	245	280	525	91	252	26	5	233	44	—	—	—	—	—	—
2014	19	ROK MLE	AZL Reds	—	172	161	29	4	3	1	8	50	2	12	2	180	228	261	489	81	256	29	5	219	34	—	—	—	—	—	—
2015	20	ROK MLE	Billings Mustangs	—	181	178	26	4	5	2	2	94	0	11	2	146	156	258	414	112	282	52	1	168	0	—	—	—	—	—	—
2016	21	A MLE	Dayton Dragons	—	87	84	8	2	0	0	1	47	0	3	2	95	106	119	225	24	213	54	1	106	-42	—	—	—	—	—	—
2016	21	ROK MLE	Billings Mustangs	—	255	244	50	7	5	6	5	95	3	17	4	205	230	348	579	143	296	37	2	244	51	—	—	—	—	—	—
2017	22	A MLE	Dayton Dragons	—	552	511	117	19	8	16	20	179	6	46	12	229	266	391	658	162	298	32	4	275	72	—	—	—	—	—	—
2018	23	AA MLE	Pensacola Blue Wahoos	—	283	260	48	7	7	10	17	108	3	14	5	185	243	381	624	196	259	38	6	271	70	—	—	—	—	—	—
2018	23	A+ MLE	Daytona Tortugas	—	126	120	24	7	1	1	3	44	0	9	1	200	220	300	520	100	297	35	2	227	40	—	—	—	—	—	—
2019	24	AAA MLE	Louisville Bats	—	112	106	16	3	1	0	5	49	0	5	2	151	189	198	387	47	264	44	4	167	-1	—	—	—	—	—	—
2019	24	AA MLE	Chattanooga Lookouts	—	405	375	73	10	1	8	24	159	1	21	6	195	245	291	536	96	304	39	6	239	48	—	—	—	—	—	—
2021	26	MLB MLE	Houston Astros	—	49	46	14	0	1	4	1	17	2	3	1	304	347	609	956	304	400	35	2	417	168	+4	+0	-0	-6	+1	-0.1
2021	26	AAA MLE	Sugar Land Skeeters	—	397	369	97	25	3	12	19	146	5	24	3	263	308	444	752	182	390	37	5	319	102	—	—	—	—	—	—
2022	27	MLB MLE	Tampa Bay Rays	—	325	301	63	13	2	7	20	108	3	14	2	209	265	336	601	126	305	33	6	272	70	-11	+2	+12	+2	+7	1.1
2022	27	AAA MLE	Sugar Land Space Cowboys	—	78	73	17	2	2	7	4	24	0	2	0	233	273	603	875	370	241	31	5	362	131	—	—	—	—	—	—
2023	28	MLB MLE	Tampa Bay Rays	—	364	338	75	13	2	26	20	130	2	12	3	222	269	503	772	281	269	36	5	330	109	+4	+1	+8	+1	+8	2.4
2024	29	MLB MLE	Tampa Bay Rays	—	448	404	75	16	1	19	31	170	7	14	7	186	256	371	627	186	261	38	7	275	72	-15	+0	+12	+2	+10	0.9
2025	30	MLB MLE	New York Mets	—	36	32	2	2	0	0	4	17	0	2	0	62	167	125	292	62	133	47	11	153	-10	-5	+0	-1	+0	+1	-0.4
2025	30	AAA MLE	Syracuse Mets	—	20	20	2	1	0	0	0	12	0	0	0	100	100	150	250	50	281	60	0	147	-14	—	—	—	—	—	—
2026	31	MLB MLE	Los Angeles Angels	—	251	230	55	10	0	10	13	80	3	9	1	239	289	413	702	174	324	32	5	306	93	-2	+1	+0	+1	+5	0.6
2026	31	AAA MLE	Salt Lake Bees	—	140	129	28	4	3	3	7	44	2	4	0	217	268	364	632	147	302	31	5	279	75	—	—	—	—	—	—
2013	18	ROK MLE	DSL Reds	—	265	243	46	6	5	2	13	69	5	17	10	189	245	280	525	91	254	26	5	233	44	—	—	—	—	—	—
2013	18	ROK RAW	DSL Reds	—	265	238	72	10	9	5	18	57	5	17	10	303	364	483	847	181	379	22	7	368	44	—	—	—	—	—	—
2014	19	ROK MLE	AZL Reds	—	172	161	29	4	3	1	8	50	2	12	2	180	228	261	489	81	255	29	5	219	34	—	—	—	—	—	—
2014	19	ROK RAW	AZL Reds	—	172	157	39	6	4	2	12	35	2	12	2	248	310	376	686	127	308	20	7	306	34	—	—	—	—	—	—
2015	20	ROK MLE	Billings Mustangs	—	181	178	26	4	5	2	2	94	0	11	2	146	156	258	414	112	293	52	1	168	0	—	—	—	—	—	—
2015	20	ROK RAW	Billings Mustangs	—	181	176	43	7	9	3	4	65	0	11	2	244	261	438	699	193	370	36	2	300	0	—	—	—	—	—	—
2016	21	ROK MLE	2 teams	—	342	328	58	9	5	6	6	142	3	20	6	177	199	290	488	113	286	42	2	209	28	—	—	—	—	—	—
2016	21	ROK RAW	2 teams	—	342	324	89	15	8	10	10	100	3	20	6	275	303	463	766	188	366	29	3	330	28	—	—	—	—	—	—
2017	22	A MLE	2 teams	—	636	588	133	21	9	18	24	207	7	57	15	226	265	384	649	158	311	33	4	275	72	—	—	—	—	—	—
2017	22	A RAW	2 teams	—	636	576	171	30	12	26	36	155	7	57	15	297	346	526	872	229	361	24	6	370	72	—	—	—	—	—	—
2018	23	AA MLE	3 teams	—	552	512	99	18	12	15	27	205	6	36	9	193	242	363	605	170	282	37	5	257	60	—	—	—	—	—	—
2018	23	AA RAW	3 teams	—	552	503	125	24	13	16	36	162	6	36	9	249	306	443	750	195	329	29	7	326	60	—	—	—	—	—	—
2019	24	AA MLE	3 teams	—	642	596	110	16	2	10	36	258	2	30	8	185	233	268	502	84	300	40	6	223	37	—	—	—	—	—	—
2019	24	AA RAW	3 teams	—	642	580	133	23	3	17	52	199	2	30	8	229	295	367	662	138	314	31	8	294	37	—	—	—	—	—	—
2020	25	INTL MLE	Gigantes del Cibao	—	122	110	31	7	0	3	12	34	0	7	3	282	352	427	780	145	384	28	10	—	—	—	—	—	—	—	—
2020	25	INTL RAW	Gigantes del Cibao	—	122	110	31	7	0	3	12	34	0	7	3	282	352	427	780	145	384	28	10	349	122	—	—	—	—	—	—
2021	26	AAA MLE	3 teams	—	555	519	137	31	5	19	24	203	8	33	7	264	307	453	760	189	393	37	4	330	109	—	—	—	—	—	—
2021	26	AAA RAW	3 teams	—	555	507	152	32	7	22	35	165	8	33	7	300	354	521	875	221	402	30	6	380	109	—	—	—	—	—	—
2022	27	MLB MLE	3 teams	—	488	451	98	19	5	17	30	160	4	25	4	217	272	395	667	177	293	33	6	290	82	-10	+3	+12	+2	+11	1.8
2022	27	MLB RAW	3 teams	—	488	445	108	22	5	18	35	147	4	25	4	243	303	436	739	193	319	30	7	324	82	-10	+3	+12	+2	+11	1.8
2023	28	MLB MLE	2 teams	—	416	385	85	15	2	29	23	149	3	17	5	221	270	496	766	275	267	36	6	330	109	+5	+1	+8	+1	+9	2.5
2023	28	MLB RAW	2 teams	—	416	377	84	13	2	27	31	142	3	17	5	223	287	483	770	260	270	34	7	332	109	+5	+1	+8	+1	+9	2.5
2024	29	MLB MLE	2 teams	—	507	457	85	19	1	21	35	192	8	23	8	186	256	370	626	184	257	38	7	275	72	-17	+1	+12	+2	+11	1.0
2024	29	MLB RAW	2 teams	—	507	452	88	20	1	19	38	186	8	23	8	195	268	369	637	175	274	37	7	281	72	-17	+1	+12	+2	+11	1.0
2025	30	MLB MLE	3 teams	—	77	70	7	4	0	1	6	40	0	4	0	100	171	200	371	100	200	52	8	151	-12	-10	+1	-1	+0	+2	-0.9
2025	30	MLB RAW	3 teams	—	77	70	9	4	0	1	6	32	0	4	0	129	197	229	426	100	211	42	8	195	-12	-10	+1	-1	+0	+2	-0.9
2026	31	MLB MLE	2 teams	—	391	359	84	15	3	13	20	124	5	13	1	234	284	401	685	167	317	32	5	296	87	-6	+2	+0	+1	+8	0.6
2026	31	MLB RAW	2 teams	—	391	353	91	16	3	15	26	117	5	13	1	258	318	448	765	190	341	30	7	332	87	-6	+2	+0	+1	+8	0.6
2013	18	ROK MLE	DSL Reds	—	265	245	46	6	5	2	13	69	5	17	10	188	245	278	523	90	252	26	5	233	44	—	—	—	—	—	—
2014	19	ROK MLE	AZL Reds	—	172	160	29	4	3	1	8	50	2	12	2	181	228	263	491	81	256	29	5	219	34	—	—	—	—	—	—
2015	20	ROK MLE	Billings Mustangs	—	181	177	26	4	5	2	2	94	0	11	2	147	156	260	415	113	282	52	1	168	0	—	—	—	—	—	—
2016	21	ROK MLE	2 teams	—	342	330	58	9	5	6	6	142	3	20	6	176	199	288	487	112	275	42	2	209	28	—	—	—	—	—	—
2017	22	A MLE	2 teams	—	636	600	133	21	9	18	24	207	7	57	15	222	265	377	642	155	298	33	4	275	72	—	—	—	—	—	—
2018	23	AA MLE	3 teams	—	552	514	99	18	12	15	27	205	6	36	9	193	242	362	604	169	271	37	5	257	60	—	—	—	—	—	—
2019	24	AA MLE	3 teams	—	642	599	110	16	2	10	36	258	2	30	8	184	233	267	501	83	295	40	6	223	37	—	—	—	—	—	—
2021	26	AAA MLE	3 teams	—	555	518	137	31	5	19	24	203	8	33	7	264	307	454	760	189	391	37	4	330	109	—	—	—	—	—	—
2022	27	MLB MLE	3 teams	—	488	451	98	19	5	17	30	160	4	25	4	217	272	395	667	177	292	33	6	290	82	—	—	—	—	—	—
2023	28	MLB MLE	2 teams	—	416	387	85	15	2	29	23	149	3	17	5	220	270	494	764	274	269	36	6	330	109	—	—	—	—	—	—
2024	29	MLB MLE	2 teams	—	507	459	85	19	1	21	35	192	8	23	8	185	256	368	624	183	261	38	7	275	72	—	—	—	—	—	—
2025	30	MLB MLE	3 teams	—	77	71	7	4	0	1	6	40	0	4	0	99	171	197	368	99	186	52	8	151	-12	—	—	—	—	—	—
2026	31	MLB MLE	2 teams	—	391	363	84	15	3	13	20	124	5	13	1	231	284	397	681	165	316	32	5	296	87	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	29	MLB MLE	2 teams	—	507	459	85	19	1	21	35	192	8	23	8	185	256	368	624	183	261	38	7	275	72	—	—	—	—	—	—
2025	30	MLB MLE	3 teams	—	77	71	7	4	0	1	6	40	0	4	0	99	171	197	368	99	186	52	8	151	-12	—	—	—	—	—	—
2026	31	MLB MLE	2 teams	—	391	363	84	15	3	13	20	124	5	13	1	231	284	397	681	165	316	32	5	296	87	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	32	MLB MLE	LAA	100%	313	287	63	11	2	13	19	102	4	22	3	216	274	404	679	188	279	33	6	298	88	-4	+3	+4	+1	+7	0.3
▸ 2027 — real world (MLB)
2027	32	MLB CTX	LAA	100%	203	186	41	7	1	9	12	66	3	14	2	216	274	405	679	189	276	33	6	298	88	-3	+2	+2	+1	+4	0.7
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	33	MLB MLE	LAA	82%	176	161	34	6	1	7	11	58	2	9	1	209	266	387	653	178	271	33	6	288	81	-4	+1	-2	+1	+4	-0.0
2028	33	MLB CTX	LAA	82%	144	132	28	4	1	6	9	48	2	7	1	208	265	388	653	179	270	33	6	288	81	-3	+1	-2	+1	+3	-0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1617	1479	313	58	7	70	100	570	19	61	15	212	270	402	672	191	286	35	6	294	64	-29	+6	+30	+1	+35	4.4
/ 162G	—	A+C		—	650	595	126	23	3	28	40	229	8	25	6	212	271	402	672	190	287	35	6	294	64	-12	+2	+12	+1	+14	1.8
Career	—	MLE		—	5725	5304	1103	201	59	173	289	2051	58	328	83	208	257	366	623	158	298	36	5	262	64	-32	+9	+32	+2	+40	5.1
/ 162G	—	MLE		—	650	602	126	23	7	20	33	233	7	37	9	209	259	370	629	161	300	36	5	262	64	-11	+3	+11	+1	+14	1.8

How the minor-league lines were translated

One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.

2026 AAASalt Lake Bees · 140 PAwOBA .364 → .279 (−85)K% 26.4% → 31.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.43%	÷1.000	×1.200	—	—	31.71%
BB% (unintentional) /PA	7.86%	÷1.000	×0.690	—	×0.962	5.22%
HBP% /PA	1.43%	—	×0.940	—	×0.962	1.29%
Singles /BIP	25.00%	÷1.000	×0.930	×0.950	×0.962	21.25%
Doubles /BIP	6.82%	÷1.000	×0.830	×0.950	×0.962	5.17%
Triples /BIP	3.41%	÷1.000	×0.970	×0.950	×0.962	3.02%
Home runs /BIP	5.68%	÷1.000	×0.700	—	×0.962	3.83%

Factors used: league row International League. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 31 vs a level average of 27.2 → −3.8% on BB/HBP/hit rates (3.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .364 → .279; ISO .216 → .157; BABIP .369 → .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).

2025 AAASyracuse Mets · 20 PAwOBA .250 → .147 (−104)K% 50.0% → 61.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	50.00%	÷0.981	×1.200	—	—	61.17%
BB% (unintentional) /PA	0.00%	÷1.005	×0.690	—	×0.972	0.00%
HBP% /PA	0.00%	—	×0.940	—	×0.972	0.00%
Singles /BIP	20.00%	÷0.975	×0.930	—	×0.972	18.54%
Doubles /BIP	10.00%	÷1.022	×0.830	—	×0.972	7.90%
Triples /BIP	0.00%	÷0.959	×0.970	—	×0.972	0.00%
Home runs /BIP	10.00%	÷1.167	×0.700	—	×0.972	5.83%

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 30 vs a level average of 27.2 → −2.8% on BB/HBP/hit rates (2.8 yr older than average).

Result: wOBA .250 → .147; ISO .200 → .099; BABIP .333 → .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).

2022 AAASugar Land Space Cowboys · 78 PAwOBA .457 → .362 (−96)K% 25.6% → 31.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.64%	÷0.986	×1.200	—	—	31.19%
BB% (unintentional) /PA	7.69%	÷0.953	×0.690	—	×1.003	5.59%
HBP% /PA	0.00%	—	×0.940	—	×1.003	0.00%
Singles /BIP	13.73%	÷0.982	×0.930	×0.950	×1.003	12.38%
Doubles /BIP	5.88%	÷0.952	×0.830	×0.950	×1.003	4.88%
Triples /BIP	3.92%	÷0.900	×0.970	×0.950	×1.003	4.03%
Home runs /BIP	17.65%	÷0.917	×0.700	—	×1.003	13.51%

Factors used: league row International League. Park (home-season share, regressed): HR 83, 1B 96, 2B 90, 3B 80, K 97, BB 91 — 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 ×0.950.

Result: wOBA .457 → .362; ISO .479 → .371; BABIP .279 → .241. 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 AAASugar Land Skeeters · 397 PAwOBA .391 → .319 (−72)K% 30.7% → 36.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.73%	÷1.002	×1.200	—	—	36.81%
BB% (unintentional) /PA	6.55%	÷0.975	×0.690	—	×1.018	4.72%
HBP% /PA	1.26%	—	×0.940	—	×1.018	1.21%
Singles /BIP	27.50%	÷1.023	×0.930	×0.991	×1.018	25.21%
Doubles /BIP	12.08%	÷0.923	×0.830	×0.991	×1.018	10.95%
Triples /BIP	1.67%	÷1.150	×0.920	×0.991	×1.018	1.34%
Home runs /BIP	6.67%	÷0.935	×0.700	—	×1.018	5.08%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 87, 1B 105, 2B 85, 3B 130, K 100, BB 95 — 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 ×0.991.

Result: wOBA .391 → .319; ISO .235 → .181; BABIP .436 → .390. 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 AAChattanooga Lookouts · 405 PAwOBA .306 → .239 (−67)K% 31.1% → 39.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	31.11%	÷0.967	×1.220	—	—	39.25%
BB% (unintentional) /PA	8.15%	÷0.949	×0.680	—	×1.012	5.91%
HBP% /PA	0.25%	—	×0.840	—	×1.012	0.21%
Singles /BIP	27.08%	÷0.974	×0.920	×0.950	×1.012	24.58%
Doubles /BIP	6.25%	÷1.160	×0.910	×0.950	×1.012	4.71%
Triples /BIP	0.42%	÷0.900	×0.880	×0.950	×1.012	0.39%
Home runs /BIP	4.58%	÷0.979	×0.800	—	×1.012	3.79%

Factors used: league row SL. Park (home-season share, regressed): HR 96, 1B 95, 2B 132, 3B 80, K 93, BB 90 — 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 ×0.950.

Result: wOBA .306 → .239; ISO .137 → .102; BABIP .349 → .304. 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 AAALouisville Bats · 112 PAwOBA .220 → .167 (−52)K% 34.8% → 43.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	34.82%	÷0.960	×1.200	—	—	43.51%
BB% (unintentional) /PA	7.14%	÷1.151	×0.690	—	×1.048	4.49%
HBP% /PA	0.00%	—	×0.940	—	×1.048	0.00%
Singles /BIP	22.22%	÷1.018	×0.930	×0.950	×1.048	20.22%
Doubles /BIP	6.35%	÷1.082	×0.830	×0.950	×1.048	4.85%
Triples /BIP	1.59%	÷1.150	×0.970	×0.950	×1.048	1.33%
Home runs /BIP	0.00%	÷0.957	×0.840	—	×1.048	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 91, 1B 104, 2B 116, 3B 130, K 92, BB 130 — applied at half strength. Age: age 24 vs a level average of 27.2 → +4.8% on BB/HBP/hit rates (3.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .220 → .167; ISO .059 → .043; BABIP .302 → .264. 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).

2018 AAPensacola Blue Wahoos · 283 PAwOBA .330 → .271 (−59)K% 32.2% → 38.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	32.16%	÷1.030	×1.220	—	—	38.07%
BB% (unintentional) /PA	8.48%	÷0.967	×0.680	—	×1.027	6.13%
HBP% /PA	1.06%	—	×0.840	—	×1.027	0.91%
Singles /BIP	17.90%	÷1.023	×0.920	×0.950	×1.027	15.70%
Doubles /BIP	4.94%	÷1.039	×0.910	×0.950	×1.027	4.22%
Triples /BIP	5.56%	÷1.006	×0.880	×0.950	×1.027	4.74%
Home runs /BIP	7.41%	÷0.909	×0.800	—	×1.027	6.69%

Factors used: league row SL. Park (home-season share, regressed): HR 82, 1B 105, 2B 108, 3B 101, K 106, BB 93 — applied at half strength. Age: age 23 vs a level average of 24.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .330 → .271; ISO .245 → .207; BABIP .301 → .259. 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).

2018 A+Daytona Tortugas · 126 PAwOBA .289 → .227 (−62)K% 25.4% → 34.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.40%	÷1.035	×1.420	—	—	34.85%
BB% (unintentional) /PA	3.17%	÷0.994	×0.750	—	×0.998	2.39%
HBP% /PA	0.00%	—	×0.930	—	×0.998	0.00%
Singles /BIP	21.84%	÷1.006	×0.920	×0.980	×0.998	19.54%
Doubles /BIP	10.34%	÷1.088	×0.960	×0.980	×0.998	8.93%
Triples /BIP	2.30%	÷1.047	×0.810	×0.980	×0.998	1.74%
Home runs /BIP	1.15%	÷1.058	×0.880	—	×0.998	0.95%

Factors used: league row FSL. Park (home-season share, regressed): HR 112, 1B 101, 2B 118, 3B 109, K 107, BB 99 — 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 ×0.980.

Result: wOBA .289 → .227; ISO .134 → .101; BABIP .341 → .297. 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
#1Jake Marisnicklast yr '23 career totals — 10 seasons, 2,213 PA	3.3	2,213	63	81	227	280	381	+5	+54	8.3	8.1
/162	664	19	24	+1.4	+16.2	2.5	pk7: 8
#2Peter Bourjoslast yr '17 career totals — 8 seasons, 2,241 PA	3.4	2,241	42	66	241	298	382	-0	+38	7.4	7.5
/162	664	12	20	-0.1	+11.3	2.2	pk7: 8
#3Adam Engellast yr '22 career totals — 6 seasons, 1,540 PA	2.3	1,540	30	47	225	280	350	+4	+33	4.1	4.1
/162	664	13	20	+1.8	+14.4	1.8	pk7: 4
#4Ruben Rivera'95-'03 * career totals — 7 seasons, 1,818 PA	2.7	1,818	64	50	206*	292*	376*	-1	+20	4.0	4.0
/162	664	23	18	-0.3	+7.2	1.5	pk7: 4
#5Jacob Brumfield'92-'99 * career totals — 6 seasons, 1,747 PA	2.6	1,747	32	74	244*	305*	386*	-3	+10	3.1	3.1
/162	664	12	28	-1.2	+3.8	1.2	pk7: 3
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	2.6	1,735	75	70	212	267	402	+5	+39	2.8	2.8
/162	664	29	27	+1.8	+15.1	1.1	pk7: 3
#6Rick Bosetti'76-'82 * career totals — 5 seasons, 1,656 PA	2.5	1,656	17	30	243*	286*	358*	+3	+16	0.6	0.6
/162	664	7	12	+1.4	+6.5	0.2	pk7: 1

Career Path Comps

What happened to players with a similar stat profile at this age · Y-axis: wRC+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

		Scouting				At Match Age									Next 3 Yrs									Peak 3 Yrs
Comp	Age	HIT	PWR	SPD	EYE	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR
Jose Siri (OGILVIE)	32	30	60	60	40	214/272/401	186	279	9	14	32%	6%	88	+0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Dylan Moore 2024 · MLB	31	43→49	52→55	55→65	50	217/320/390	173	294	19	29	31%	10%	103	+1.5	206/299/361	155	279	16	32	30%	10%	88	+0.5	189/278/324	136	257	15	36	31%	9%	72	-0.4
✕George Lombard 2007 · MLB	31	44→43	50	59→55	43	222/292/377	155	300	17	25	31%	8%	88	+0.5	222/287/356	134	315	14	23	32%	7%	82	-0.0	210/274/313	104	298	12	32	32%	8%	63	-0.4
✕Reggie Abercrombie 2013 · AAA	32	46→49	51→55	50→60	33	229/288/386	157	328	19	24	35%	4%	90	+0.6	229/281/386	157	323	19	20	34%	4%	86	+0.3	218/258/360	141	306	19	22	34%	3%	71	-0.3
✕Dewayne Wise 2009 · MLB	31	48→40	52→60	59→55	42	244/292/424	180	286	19	25	22%	5%	99	+1.3	237/278/395	158	286	14	20	22%	4%	87	+0.4	238/273/396	158	291	16	27	24%	4%	84	+0.1
✕Drew Stubbs 2017 · MLB	32	46→56	48→50	57→60	46	224/301/365	141	321	16	26	33%	9%	89	+0.5	216/291/331	115	324	12	16	34%	9%	78	-0.3	199/276/290	91	309	9	13	35%	9%	60	-1.0
✕Dairon Blanco 2023 · AAA	30	48→50	46→45	62→70	41	237/290/363	127	308	14	42	27%	6%	84	+0.2	249/310/375	126	320	13	71	25%	6%	95	+0.9	246/312/366	120	313	12	95	24%	6%	91	+0.3
✕Eli White 2024 · MLB	30	43→53	47→50	58→60	46	214/292/345	131	302	16	27	33%	9%	81	-0.1	236/294/374	138	309	16	26	28%	7%	88	+0.5	239/292/380	141	304	16	27	26%	6%	88	+0.2
✕Charlton Jimerson 2010 · AAA	30	42→43	52→55	54→60	30	212/249/373	161	332	21	27	42%	4%	72	-0.7	215/255/368	153	279	18	18	29%	4%	72	-0.7	187/214/361	174	223	20	23	27%	2%	53	-0.6
✕Hiram Bocachica 2007 · MLB	31	48	53→55	54→55	49	247/321/422	174	290	21	21	23%	8%	109	+2.0	235/318/397	162	267	19	19	19%	9%	103	+1.6	203/292/360	156	229	17	21	20%	9%	84	+0.1
✕Keon Broxton 2021 · MLB	31	41→51	47→55	53→60	38	196/265/324	128	336	15	25	44%	8%	67	-1.1	188/262/304	116	366	14	17	48%	8%	61	-1.5	132/213/215	83	277	12	20	53%	8%	22	-2.2
✕Chase d'Arnaud 2019 · MLB	32	46→50	46→45	56→60	45	228/288/361	133	290	14	23	26%	7%	83	+0.1	198/263/321	123	283	14	16	33%	7%	65	-1.2	148/216/240	92	221	11	15	37%	6%	28	-2.4
✕Wynton Bernard 2023 · MLB	32	49→59	46→45	62→60	44	242/286/382	140	287	13	30	21%	5%	86	+0.3	236/282/346	110	292	9	33	22%	6%	77	-0.3	231/279/323	91	291	7	39	22%	5%	66	-0.8
✕Justin Leone 2009 · AAA	32	39	49→50	52→55	50	205/285/355	150	258	17	18	27%	10%	81	-0.1	191/261/317	126	270	13	13	32%	8%	63	-1.3	124/191/212	89	184	9	6	37%	7%	13	-2.0
✕Mark Little 2006 · MLB	34	42	51→55	52→55	40	219/289/380	161	284	19	19	30%	6%	89	+0.5	226/308/346	120	311	11	15	29%	7%	88	+0.5	221/318/307	86	323	4	13	29%	6%	80	-0.1
✕Tim Locastro 2024 · MLB	32	40→50	45	56→60	40	201/281/322	122	255	12	24	25%	5%	73	-0.6	222/301/340	118	272	11	29	22%	6%	84	+0.2	219/299/327	108	266	9	38	20%	5%	78	-0.1
✕Adam Engel 2022 · MLB	30	47→48	51→50	55→60	42	238/301/405	167	296	19	20	26%	6%	99	+1.2	216/280/342	126	303	12	24	31%	7%	76	-0.4	198/264/306	108	292	9	29	33%	7%	60	-0.8
✕Matt Carson 2011 · MLB	30	43→50	54→60	54→50	41	231/278/411	180	274	22	18	25%	5%	91	+0.7	231/277/392	161	290	19	13	27%	5%	86	+0.3	226/272/371	145	288	16	11	27%	5%	76	-0.3
✕Alexis Gomez 2011 · AAA	32	55→59	49→50	60→55	48	273/321/418	145	312	17	34	18%	7%	108	+1.9	253/302/386	133	297	13	21	19%	6%	93	+0.8	248/288/374	126	286	7	13	16%	4%	84	+0.0
●Adolis García 2023 · MLB	30	47→49	56→60	53→50	40	245/293/442	197	308	24	19	29%	6%	104	+1.6	235/297/433	198	288	26	13	27%	7%	104	+1.6	227/292/419	192	273	26	11	27%	7%	99	+1.2
✕Will Venable 2014 · MLB	31	52→55	53→55	61→60	45	262/312/449	187	310	19	26	22%	6%	112	+2.2	234/292/362	128	293	13	18	24%	7%	84	+0.2	215/277/310	95	275	9	16	24%	7%	66	-0.7

Jose Siri

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps