Bo Bichette

3B New York Mets

Age 29 R/R 5'11" / 190 lbs MLB H -5% Svc 7.366 · Ctrl thru 2028

Overview

MLB40-MANExtFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	26	MLBTOR	336	.225/.278/.322	4	5	68	0.1
2025	27	MLBTOR	628	.311/.358/.483	18	4	135	4.0
2026	28	MLBNYM	696	.260/.315/.390	18	2	103	2.1
2027PROJ	29	MLBNYM	614	.272/.325/.409	15	3	112	2.6
2028PROJ	30	MLBNYM	614	.268/.320/.400	15	1	108	2.1
2029PROJ	31	MLBNYM	614	.263/.315/.390	14	1	104	1.7

Last 3 seasons WAR 6.2 · Next 3 projected WAR 6.4Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2028Service7.366First FA2028Options1NTC

2027Ext$42M2028Ext$42M

Skills · percentileStatcast 2024-2026

xwOBA71

Avg EV63

Barrel%37

Bat Spd30

Speed22

Form.274/.335/.416 · rolling true talent (45d window) · proj .280/.330/.421

CompsStarlin Castro (age 29) · Ronny Paulino (age 29) · T.J. Rivera (age 29)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 115112vR 101

AVG/OBP/SLG.272 / .325 / .409

PA614

HR15

K%18

BB%7

BABIP309

ISO135

MLB%100%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit option yr━ post-control-$76M ctrl surplus

Tools · Recent Form · Splits · ContractCON 60 / POW 45

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT60

xAVG

850.279

POWER45

Barrel%

376.6

Avg EV

6390.0

Bat Spd

3069.2

EYE35

scouting grade only

SPEED40

Sprint

2226.1

Recent Formrolling true talent ⓘ

K%19%▼20% over 65 PA (45d) · proj 18%

BB%8%▲10% over 124 PA (60d) · proj 7%

ISO.142·.143 over 112 AB (60d) · proj .141

HR/BB3.9%·4.5% over 89 BBE (60d) · proj 3.4%

BABIP.316·.282 over 85 BIP (60d) · proj .319

SLASH.274/.335/.416·proj .280/.330/.421

Platoon Splits2024-2026 · 1079 PA

vs LHP

vs RHP

Edge

233

846

—

wRC+

103

105

—

wOBA

320

324

—

ISO

179

127

◀◀L

BABIP

272

328

▶▶R

13.3%

17.7%

◀◀L

BB%

4.3%

6.1%

▶▶R

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

Status FA

MLB Debut 2019

Service 7.366 yrs.days

Team Control Through 2028

First FA Year 2028

NTCOPT

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$42M	+2.5	$20M	-$22M
2028	Ext	$42M	+2.1	$16M	-$22M
Totals		$84M		$36M	-$44M

Options · projected decision
2029	PLAYER OPT	$42.0M / $5.0M buyout	EXERCISE

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	GCL Blue Jays	—	91	82	35	9	2	4	6	17	0	3	0	427	466	732	1.198	305	484	19	7	499	134	—	—	—	—	—	—
2017	19	A+	Dunedin Blue Jays	—	182	164	53	9	1	4	14	26	2	10	4	323	383	463	847	140	360	14	8	374	101	—	—	—	—	—	—
2017	19	A	Lansing Lugnuts	—	317	284	109	32	3	10	28	55	5	12	3	384	448	623	1.071	239	452	17	9	466	135	—	—	—	—	—	—
2018	20	AA	New Hampshire Fisher Cats	—	595	539	154	43	7	11	48	101	2	32	11	286	346	453	799	167	331	17	8	350	101	—	—	—	—	—	—
2019	21	MLB	Toronto Blue Jays	—	212	196	61	18	0	11	14	50	1	4	4	311	360	571	932	260	368	24	7	403	159	+15	-1	-3	+5	+5	2.1
2019	21	AAA	Buffalo Bisons	—	244	222	61	16	2	8	19	48	1	15	5	275	335	473	808	198	317	20	8	353	95	—	—	—	—	—	—
2019	21	A+	Dunedin Blue Jays	—	16	11	6	2	0	0	5	3	0	1	0	545	688	727	1.415	182	750	19	31	605	232	—	—	—	—	—	—
2020	22	MLB	Toronto Blue Jays	—	128	123	37	9	1	5	5	27	0	4	1	301	328	512	840	211	352	21	4	367	130	+5	+0	+2	+1	+3	1.1
2021	23	MLB	Toronto Blue Jays	—	690	640	191	30	1	29	40	137	6	25	1	298	345	484	830	186	339	20	6	364	132	+26	+5	-0	+7	+15	5.4
2022	24	MLB	Toronto Blue Jays	—	697	652	189	43	1	24	41	155	2	13	8	290	334	469	803	179	347	22	6	353	125	+21	-1	-1	+7	+15	4.2
2023	25	MLB	Toronto Blue Jays	—	601	571	175	30	3	20	27	115	2	5	3	306	340	475	815	168	355	19	4	359	128	+20	-0	+1	+6	+13	4.1
2024	26	MLB	Toronto Blue Jays	—	336	311	70	16	1	4	20	64	3	5	1	225	278	322	600	96	269	19	6	271	68	-13	+1	+2	+4	+7	0.1
2025	27	MLB	Toronto Blue Jays	—	628	582	181	44	1	18	40	91	3	4	3	311	358	483	841	172	342	14	6	370	135	+26	-0	-7	+7	+14	4.0
2026	28	MLB	New York Mets	—	696	638	166	25	2	18	49	127	2	2	2	260	315	390	705	130	296	18	7	313	103	+2	-0	+1	+2	+15	2.1
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	3988	3713	1070	215	10	129	236	766	19	62	23	288	334	456	790	168	332	19	6	348	122	+102	+3	-5	+41	+86	23.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2016	18	ROK MLE	GCL Blue Jays	—	91	84	25	6	1	3	4	24	0	3	0	298	330	500	830	202	367	26	4	366	134	—	—	—	—	—	—
2017	19	A+ MLE	Dunedin Blue Jays	—	182	170	48	9	1	3	8	37	2	10	4	282	322	400	722	118	336	20	4	317	101	—	—	—	—	—	—
2017	19	A MLE	Lansing Lugnuts	—	317	293	91	24	2	9	19	78	5	12	3	311	363	498	861	188	397	25	6	368	135	—	—	—	—	—	—
2018	20	AA MLE	New Hampshire Fisher Cats	—	595	551	149	39	6	10	36	119	2	32	11	270	317	417	735	147	322	20	6	317	101	—	—	—	—	—	—
2019	21	MLB MLE	Toronto Blue Jays	—	212	196	61	18	0	11	14	50	1	4	4	311	360	571	932	260	368	24	7	403	159	+15	-1	-3	+5	+5	2.1
2019	21	AAA MLE	Buffalo Bisons	—	244	227	56	14	2	7	14	60	1	15	5	247	293	419	712	172	304	25	6	308	95	—	—	—	—	—	—
2019	21	A+ MLE	Dunedin Blue Jays	—	16	12	6	2	0	0	4	4	0	1	0	500	625	667	1.292	167	708	25	25	511	232	—	—	—	—	—	—
2020	22	MLB MLE	Toronto Blue Jays	—	128	124	37	9	1	5	4	27	0	4	1	298	320	508	828	210	352	21	3	361	130	+5	+0	+2	+1	+3	1.1
2021	23	MLB MLE	Toronto Blue Jays	—	690	640	190	30	1	29	40	137	6	25	1	297	344	483	827	186	339	20	6	364	132	+26	+5	-0	+7	+15	5.4
2022	24	MLB MLE	Toronto Blue Jays	—	697	652	188	43	1	24	41	155	2	13	8	288	332	468	800	179	347	22	6	353	125	+21	-1	-1	+7	+15	4.2
2023	25	MLB MLE	Toronto Blue Jays	—	601	571	174	30	3	20	27	115	2	5	3	305	338	473	811	168	355	19	4	358	128	+20	-0	+1	+6	+13	4.1
2024	26	MLB MLE	Toronto Blue Jays	—	336	312	70	16	1	4	19	64	3	5	1	224	275	321	596	96	269	19	6	268	68	-13	+1	+2	+4	+7	0.1
2025	27	MLB MLE	Toronto Blue Jays	—	628	584	180	44	1	18	38	91	3	4	3	308	354	479	833	171	342	14	6	367	135	+26	-0	-7	+7	+14	4.0
2026	28	MLB MLE	New York Mets	—	696	638	171	27	2	18	49	127	2	2	2	268	322	401	723	133	296	18	7	320	103	+2	-0	+1	+2	+15	2.1
2016	18	ROK MLE	GCL Blue Jays	—	91	84	25	6	1	3	4	24	0	3	0	298	330	500	830	202	367	26	4	366	134	—	—	—	—	—	—
2016	18	ROK RAW	GCL Blue Jays	—	91	82	35	9	2	4	6	17	0	3	0	427	466	732	1.198	305	484	19	7	499	134	—	—	—	—	—	—
2017	19	A MLE	2 teams	—	499	463	139	33	3	12	27	115	7	22	7	300	348	462	810	162	376	23	5	349	123	—	—	—	—	—	—
2017	19	A RAW	2 teams	—	499	448	162	41	4	14	42	81	7	22	7	362	425	565	989	203	417	16	8	433	123	—	—	—	—	—	—
2018	20	AA MLE	New Hampshire Fisher Cats	—	595	551	149	39	6	10	36	119	2	32	11	270	317	417	735	147	326	20	6	317	101	—	—	—	—	—	—
2018	20	AA RAW	New Hampshire Fisher Cats	—	595	539	154	43	7	11	48	101	2	32	11	286	346	453	799	167	331	17	8	350	101	—	—	—	—	—	—
2019	21	AAA MLE	3 teams	—	472	435	122	34	2	18	32	114	2	20	9	280	333	492	825	211	341	24	7	357	128	—	—	—	—	—	—
2019	21	AAA RAW	3 teams	—	472	429	128	36	2	19	38	101	2	20	9	298	358	524	883	226	350	21	8	384	128	—	—	—	—	—	—
2020	22	MLB MLE	Toronto Blue Jays	—	128	124	37	9	1	5	4	27	0	4	1	298	320	508	828	210	348	21	3	361	130	+5	+0	+2	+1	+3	1.1
2020	22	MLB RAW	Toronto Blue Jays	—	128	123	37	9	1	5	5	27	0	4	1	301	328	512	840	211	352	21	4	367	130	+5	+0	+2	+1	+3	1.1
2021	23	MLB MLE	Toronto Blue Jays	—	690	640	190	30	1	29	40	137	6	25	1	297	344	483	827	186	337	20	6	364	132	+26	+5	-0	+7	+15	5.4
2021	23	MLB RAW	Toronto Blue Jays	—	690	640	191	30	1	29	40	137	6	25	1	298	345	484	830	186	339	20	6	364	132	+26	+5	-0	+7	+15	5.4
2022	24	MLB MLE	Toronto Blue Jays	—	697	652	188	43	1	24	41	155	2	13	8	288	332	468	800	179	345	22	6	353	125	+21	-1	-1	+7	+15	4.2
2022	24	MLB RAW	Toronto Blue Jays	—	697	652	189	43	1	24	41	155	2	13	8	290	334	469	803	179	347	22	6	353	125	+21	-1	-1	+7	+15	4.2
2023	25	MLB MLE	Toronto Blue Jays	—	601	571	174	30	3	20	27	115	2	5	3	305	338	473	811	168	352	19	4	358	128	+20	-0	+1	+6	+13	4.1
2023	25	MLB RAW	Toronto Blue Jays	—	601	571	175	30	3	20	27	115	2	5	3	306	340	475	815	168	355	19	4	359	128	+20	-0	+1	+6	+13	4.1
2024	26	MLB MLE	Toronto Blue Jays	—	336	312	70	16	1	4	19	64	3	5	1	224	275	321	596	96	268	19	6	268	68	-13	+1	+2	+4	+7	0.1
2024	26	MLB RAW	Toronto Blue Jays	—	336	311	70	16	1	4	20	64	3	5	1	225	278	322	600	96	269	19	6	271	68	-13	+1	+2	+4	+7	0.1
2025	27	MLB MLE	Toronto Blue Jays	—	628	584	180	44	1	18	38	91	3	4	3	308	354	479	833	171	339	14	6	367	135	+26	-0	-7	+7	+14	4.0
2025	27	MLB RAW	Toronto Blue Jays	—	628	582	181	44	1	18	40	91	3	4	3	311	358	483	841	172	342	14	6	370	135	+26	-0	-7	+7	+14	4.0
2026	28	MLB MLE	New York Mets	—	696	638	171	27	2	18	49	127	2	2	2	268	322	401	723	133	306	18	7	320	103	+2	-0	+1	+2	+15	2.1
2026	28	MLB RAW	New York Mets	—	696	638	166	25	2	18	49	127	2	2	2	260	315	390	705	130	296	18	7	313	103	+2	-0	+1	+2	+15	2.1
2016	18	ROK MLE	GCL Blue Jays	—	91	87	25	6	1	3	4	24	0	3	0	287	330	483	812	195	367	26	4	366	134	—	—	—	—	—	—
2017	19	A MLE	2 teams	—	499	462	139	33	3	12	27	115	7	22	7	301	348	463	811	162	375	23	5	349	123	—	—	—	—	—	—
2018	20	AA MLE	New Hampshire Fisher Cats	—	595	552	149	39	6	10	36	119	2	32	11	270	317	417	734	147	322	20	6	317	101	—	—	—	—	—	—
2019	21	AAA MLE	3 teams	—	472	435	122	34	2	18	32	114	2	20	9	280	333	492	825	211	346	24	7	357	128	—	—	—	—	—	—
2020	22	MLB MLE	Toronto Blue Jays	—	128	123	37	9	1	5	4	27	0	4	1	301	320	512	833	211	352	21	3	361	130	—	—	—	—	—	—
2021	23	MLB MLE	Toronto Blue Jays	—	690	639	190	30	1	29	40	137	6	25	1	297	344	484	828	186	339	20	6	364	132	—	—	—	—	—	—
2022	24	MLB MLE	Toronto Blue Jays	—	697	649	188	43	1	24	41	155	2	13	8	290	332	470	802	180	347	22	6	353	125	—	—	—	—	—	—
2023	25	MLB MLE	Toronto Blue Jays	—	601	567	174	30	3	20	27	115	2	5	3	307	338	476	815	169	355	19	4	358	128	—	—	—	—	—	—
2024	26	MLB MLE	Toronto Blue Jays	—	336	311	70	16	1	4	19	64	3	5	1	225	275	322	597	96	269	19	6	268	68	—	—	—	—	—	—
2025	27	MLB MLE	Toronto Blue Jays	—	628	582	180	44	1	18	38	91	3	4	3	309	354	481	835	172	342	14	6	367	135	—	—	—	—	—	—
2026	28	MLB MLE	New York Mets	—	696	640	171	27	2	18	49	127	2	2	2	267	322	400	722	133	296	18	7	320	103	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	26	MLB MLE	Toronto Blue Jays	—	336	311	70	16	1	4	19	64	3	5	1	225	275	322	597	96	269	19	6	268	68	—	—	—	—	—	—
2025	27	MLB MLE	Toronto Blue Jays	—	628	582	180	44	1	18	38	91	3	4	3	309	354	481	835	172	342	14	6	367	135	—	—	—	—	—	—
2026	28	MLB MLE	New York Mets	—	696	640	171	27	2	18	49	127	2	2	2	267	322	400	722	133	296	18	7	320	103	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	29	MLB MLE	NYM	100%	616	567	159	29	2	16	42	108	2	3	1	280	332	421	753	141	319	18	7	334	112	+9	+0	+1	+2	+13	2.5
▸ 2027 — real world (MLB)
2027	29	MLB CTX	NYM	100%	614	565	153	27	2	15	42	108	2	3	1	272	325	409	734	138	309	18	7	326	112	+9	+0	+1	+2	+13	2.6
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	30	MLB MLE	NYM	100%	614	566	156	29	2	15	41	110	2	1	1	276	327	412	739	136	316	18	7	328	108	+6	-0	-1	+2	+13	2.1
2029	31	MLB MLE	NYM	100%	614	566	154	28	2	14	41	112	2	1	0	271	322	401	724	130	313	18	7	321	104	+3	+0	-1	+2	+13	1.7
2030	32	MLB MLE	NYM	100%	614	567	150	27	1	13	40	115	2	1	0	265	315	388	703	123	309	19	7	313	98	-2	+0	-2	+2	+13	1.2
2031	33	MLB MLE	NYM	100%	521	482	124	22	1	10	33	100	1	1	0	258	307	371	678	113	303	19	6	302	91	-6	+0	-3	+2	+11	0.5
2032	34	MLB MLE	NYM	100%	462	429	107	18	1	8	29	92	1	0	0	248	296	351	647	103	296	20	6	289	82	-10	+0	-4	+2	+10	-0.2
2028	30	MLB CTX	NYM	100%	614	566	152	27	2	15	41	110	2	1	1	268	320	400	720	133	306	18	7	320	108	+6	-0	-1	+2	+13	2.1
2029	31	MLB CTX	NYM	100%	614	566	149	26	2	14	41	112	2	1	0	263	315	390	705	127	303	18	7	314	104	+3	+0	-1	+2	+13	1.7
2030	32	MLB CTX	NYM	100%	614	567	145	25	1	13	40	115	2	1	0	257	308	377	685	119	299	19	7	305	98	-2	+0	-2	+2	+13	1.2
2031	33	MLB CTX	NYM	100%	521	482	120	20	1	10	33	100	1	1	0	250	300	360	660	110	294	19	6	295	91	-6	+0	-3	+2	+11	0.5
2032	34	MLB CTX	NYM	100%	462	429	104	17	1	8	29	92	1	0	0	241	289	341	630	100	286	20	6	283	82	-10	+0	-4	+2	+10	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	6813	6323	1740	330	17	189	420	1295	27	66	24	275	323	422	745	147	318	19	6	330	111	+94	+4	-16	+51	+148	28.5
/ 162G	—	A+C		—	650	603	166	31	2	18	40	124	3	6	2	275	324	423	746	148	319	19	6	330	111	+9	+0	-2	+5	+14	2.7
Career	—	MLE		—	8872	8229	2294	464	31	237	543	1725	39	142	48	279	326	429	756	150	326	19	6	333	111	+102	+4	-15	+53	+161	31.1
/ 162G	—	MLE		—	650	603	167	34	2	17	40	126	3	10	4	277	326	425	750	148	323	19	6	333	111	+9	+0	-1	+5	+14	2.7

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.

2019 AAABuffalo Bisons · 244 PAwOBA .345 → .308 (−37)K% 19.7% → 24.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.67%	÷0.968	×1.200	—	—	24.38%
BB% (unintentional) /PA	7.79%	÷0.953	×0.690	—	×1.050	5.92%
HBP% /PA	0.41%	—	×0.940	—	×1.050	0.40%
Singles /BIP	20.11%	÷1.011	×0.930	×1.008	×1.050	19.58%
Doubles /BIP	9.20%	÷0.954	×0.830	×1.008	×1.050	8.47%
Triples /BIP	1.15%	÷0.909	×0.970	×1.008	×1.050	1.30%
Home runs /BIP	4.60%	÷1.000	×0.840	—	×1.050	4.06%

Factors used: league row IL. Park (home-season share, regressed): HR 100, 1B 102, 2B 91, 3B 82, K 94, BB 91 — applied at half strength. Age: age 21 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (6.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.008.

Result: wOBA .345 → .308; ISO .198 → .177; BABIP .317 → .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 A+Dunedin Blue Jays · 16 PAwOBA .591 → .511 (−80)K% 18.8% → 27.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.75%	÷0.966	×1.420	—	—	27.56%
BB% (unintentional) /PA	31.25%	÷0.993	×0.750	—	×1.027	24.24%
HBP% /PA	0.00%	—	×0.930	—	×1.027	0.00%
Singles /BIP	50.00%	÷1.029	×0.920	—	×1.027	45.92%
Doubles /BIP	25.00%	÷0.992	×0.960	—	×1.027	24.84%
Triples /BIP	0.00%	÷1.150	×0.810	—	×1.027	0.00%
Home runs /BIP	0.00%	÷1.194	×0.880	—	×1.027	0.00%

Factors used: league row FSL. Park (home-season share, regressed): HR 139, 1B 106, 2B 98, 3B 130, K 93, BB 99 — 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).

Result: wOBA .591 → .511; ISO .182 → .174; BABIP .750 → .708. 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 AANew Hampshire Fisher Cats · 595 PAwOBA .343 → .317 (−26)K% 17.0% → 20.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.97%	÷1.033	×1.220	—	—	20.04%
BB% (unintentional) /PA	7.90%	÷0.961	×0.700	—	×1.050	6.04%
HBP% /PA	0.34%	—	×0.850	—	×1.050	0.30%
Singles /BIP	21.23%	÷0.995	×0.970	×0.990	×1.050	21.51%
Doubles /BIP	9.82%	÷0.980	×0.860	×0.990	×1.050	8.95%
Triples /BIP	1.60%	÷1.086	×0.950	×0.990	×1.050	1.45%
Home runs /BIP	2.51%	÷0.945	×0.780	—	×1.050	2.18%

Factors used: league row EL. Park (home-season share, regressed): HR 89, 1B 99, 2B 96, 3B 117, K 107, BB 92 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.990.

Result: wOBA .343 → .317; ISO .167 → .149; BABIP .331 → .322. 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).

2017 ALansing Lugnuts · 317 PAwOBA .454 → .368 (−86)K% 17.4% → 24.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.35%	÷0.960	×1.360	—	—	24.58%
BB% (unintentional) /PA	8.83%	÷1.055	×0.690	—	×1.045	6.04%
HBP% /PA	1.58%	—	×0.780	—	×1.045	1.29%
Singles /BIP	27.95%	÷0.988	×0.920	×0.952	×1.045	25.89%
Doubles /BIP	13.97%	÷1.033	×0.830	×0.952	×1.045	11.17%
Triples /BIP	1.31%	÷1.150	×0.910	×0.952	×1.045	1.03%
Home runs /BIP	4.37%	÷0.894	×0.800	—	×1.045	4.09%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 79, 1B 98, 2B 107, 3B 130, K 92, BB 111 — applied at half strength. Age: age 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.952.

Result: wOBA .454 → .368; ISO .239 → .194; BABIP .452 → .397. 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).

2017 A+Dunedin Blue Jays · 182 PAwOBA .364 → .317 (−47)K% 14.3% → 20.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.29%	÷1.007	×1.420	—	—	20.15%
BB% (unintentional) /PA	6.59%	÷1.118	×0.750	—	×1.050	4.65%
HBP% /PA	1.10%	—	×0.930	—	×1.050	1.07%
Singles /BIP	28.26%	÷1.002	×0.920	×0.961	×1.050	26.18%
Doubles /BIP	6.52%	÷0.940	×0.960	×0.961	×1.050	6.72%
Triples /BIP	0.72%	÷1.150	×0.810	×0.961	×1.050	0.51%
Home runs /BIP	2.90%	÷1.265	×0.880	—	×1.050	2.12%

Factors used: league row FSL. Park (home-season share, regressed): HR 153, 1B 100, 2B 88, 3B 130, K 101, BB 124 — applied at half strength. Age: age 19 vs a level average of 22.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.961.

Result: wOBA .364 → .317; ISO .140 → .116; BABIP .360 → .336. 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).

2016 ROKGCL Blue Jays · 91 PAwOBA .501 → .366 (−136)K% 18.7% → 26.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.68%	÷1.000	×1.440	—	—	26.90%
BB% (unintentional) /PA	6.59%	÷1.000	×0.620	—	×1.022	4.18%
HBP% /PA	0.00%	—	×0.720	—	×1.022	0.00%
Singles /BIP	30.77%	÷1.000	×0.820	×0.957	×1.022	24.69%
Doubles /BIP	13.85%	÷1.000	×0.720	×0.957	×1.022	9.76%
Triples /BIP	3.08%	÷1.000	×0.720	×0.957	×1.022	2.17%
Home runs /BIP	6.15%	÷1.000	×0.780	—	×1.022	4.91%

Factors used: level-wide ROK 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 18 vs a level average of 19.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.957.

Result: wOBA .501 → .366; ISO .305 → .220; BABIP .484 → .367. 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
#1Jim Fregosi'61-'78 * career totals — 16 seasons, 7,402 PA	11.1	7,402	151	76	272*	344*	438*	+46	+2	43.0	38.7
/162	664	14	7	+4.1	+0.2	3.9	pk7: 34
#2Jay Bell'86-'03 * career totals — 17 seasons, 8,525 PA	12.8	8,525	195	91	257*	334*	419*	+73	+9	39.1	36.0
/162	664	15	7	+5.7	+0.7	3.0	pk7: 33
#3Asdrúbal Cabreralast yr '21 career totals — 15 seasons, 7,401 PA	11.1	7,401	195	91	266	329	423	+58	+11	38.2	32.2
/162	664	17	8	+5.2	+1.0	3.4	pk7: 26
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 14 projected seasons	11.2	7,427	205	70	280	324	429	+43	+11	34.8	30.6
/162	664	18	6	+3.9	+1.0	3.1	pk7: 26
#4Travis Fryman'90-'02 * career totals — 13 seasons, 7,217 PA	10.9	7,217	223	72	264*	325*	440*	+35	+13	32.2	29.6
/162	664	21	7	+3.2	+1.2	3.0	pk7: 27
#5Aaron Hilllast yr '17 career totals — 13 seasons, 6,217 PA	9.4	6,217	162	74	266	323	417	+22	+25	27.7	26.1
/162	664	17	8	+2.4	+2.6	3.0	pk7: 25
#6Pablo Sandovallast yr '21 career totals — 13 seasons, 5,045 PA	7.6	5,045	153	12	278	330	444	+11	+1	24.9	24.6
/162	664	20	2	+1.4	+0.1	3.3	pk7: 24

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
Bo Bichette (OGILVIE)	29	60	45	40	35	278/330/417	140	319	16	3	18%	7%	112	+2.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
●Starlin Castro 2019 · MLB	29	57→63	48→50	45→50	46	283/325/422	140	331	15	5	19%	6%	111	+2.1	275/315/425	150	316	16	4	18%	6%	107	+1.9	276/314/421	145	313	15	1	17%	5%	107	+1.5
✕Ronny Paulino 2010 · MLB	29	51→61	48→50	42→40	50	254/310/397	143	293	15	4	19%	8%	99	+1.3	254/298/360	106	297	9	3	17%	6%	86	+0.3	252/294/346	94	300	8	0	18%	6%	79	-0.1
✕T.J. Rivera 2018 · MLB	29	57→66	45	44→45	43	277/314/400	123	312	12	4	16%	4%	101	+1.4	244/289/367	123	293	12	8	20%	5%	84	+0.2	217/256/330	113	265	12	2	23%	4%	63	-0.7
✕Ramón Urías 2023 · MLB	29	49→59	50	43→50	47	250/314/405	155	303	19	4	24%	7%	103	+1.6	249/312/391	142	305	16	5	23%	7%	99	+1.2	246/310/381	135	302	15	4	22%	7%	97	+0.7
✕Brendan Harris 2010 · MLB	29	54→58	43→50	40→45	49	261/318/383	121	308	10	3	18%	7%	99	+1.2	216/272/319	103	254	9	3	18%	6%	67	-1.1	219/298/331	111	254	10	1	17%	9%	79	-0.1
✕Harold Ramírez 2024 · MLB	29	59→65	46→50	42→50	44	290/334/425	135	334	14	7	17%	5%	115	+2.4	259/302/362	103	319	10	11	21%	5%	88	+0.4	251/283/305	54	323	3	12	22%	3%	65	-0.7
✕Chris Stynes 2002 · MLB	29	59→66	48→50	43→45	49	290/337/435	145	318	15	8	14%	6%	118	+2.6	253/317/393	140	281	13	5	15%	8%	101	+1.4	238/309/372	133	265	11	3	14%	8%	94	+0.4
✕Andy Ibáñez 2022 · MLB	29	52→56	51→50	45	48	261/313/426	166	288	18	5	17%	6%	107	+1.9	244/298/384	140	283	14	7	18%	7%	92	+0.7	247/306/390	143	290	15	7	20%	7%	96	+0.6
✕Kevin Plawecki 2020 · MLB	29	47→57	47→45	41→30	49	233/307/374	141	273	14	3	20%	8%	94	+0.9	252/318/371	119	295	11	5	18%	7%	97	+1.1	238/300/320	82	288	6	0	19%	7%	76	-0.1
●Adam Frazier 2021 · MLB	29	52→62	47→50	39→50	50	257/315/401	144	279	14	5	14%	7%	102	+1.5	266/326/378	112	296	8	10	13%	7%	101	+1.4	262/323/369	107	291	7	11	12%	7%	98	+1.1
✕J.R. House 2009 · MLB	29	51→59	47→50	36→30	49	255/304/392	138	275	15	3	14%	6%	96	+1.0	221/262/320	99	246	10	3	15%	5%	63	-1.3	205/240/283	77	229	8	0	14%	4%	43	-1.9
✕Orlando Arcia 2024 · MLB	29	49→59	51→50	45→55	49	252/312/410	158	285	20	4	20%	8%	103	+1.6	227/277/360	133	265	16	4	21%	6%	79	-0.2	214/260/336	123	248	15	3	21%	6%	67	-0.7
●Casey McGehee 2012 · MLB	29	51→61	49→55	35→40	49	254/307/405	151	281	17	2	17%	7%	100	+1.3	246/308/368	122	286	12	4	18%	8%	92	+0.7	255/320/349	94	302	7	3	17%	9%	92	+0.6
●Mark Ellis 2006 · MLB	29	58→63	48→50	43→50	55	284/349/434	149	305	14	4	12%	8%	122	+2.9	262/329/410	148	286	15	8	14%	8%	109	+2.0	250/321/394	145	272	15	10	14%	8%	104	+1.5
●Saul Soto 2007 · AAA	28	52→60	49→55	38→45	48	262/314/409	147	290	16	4	16%	6%	103	+1.6	261/313/426	165	291	20	4	18%	6%	107	+1.9	270/323/439	169	299	21	2	17%	7%	112	+1.5
✕Chris Johnson 2014 · MLB	29	58→65	48→55	46→45	42	286/324/431	145	353	15	4	23%	5%	112	+2.2	263/298/377	114	345	12	5	26%	5%	90	+0.6	242/278/362	120	337	13	2	31%	4%	79	-0.1
●Jhonny Peralta 2011 · MLB	29	51→61	48→55	43→40	50	255/315/402	147	293	15	2	19%	8%	102	+1.5	271/326/431	160	311	17	2	18%	8%	113	+2.3	275/337/435	160	317	18	2	19%	8%	119	+2.6
✕Trevor Plouffe 2015 · MLB	29	50→54	50→60	43→45	50	252/316/415	163	290	17	3	20%	8%	106	+1.8	244/304/409	165	283	19	3	20%	8%	100	+1.3	234/295/395	162	270	20	2	21%	7%	94	+0.7
●Gio Urshela 2020 · MLB	28	55→61	49→55	43→40	44	274/315/429	155	309	17	3	18%	5%	109	+2.0	277/325/440	163	323	18	4	20%	6%	115	+2.4	275/326/424	149	324	16	2	20%	7%	112	+1.4
●Lourdes Gurriel Jr. 2023 · MLB	29	57→61	48→60	38→45	47	280/328/430	150	322	15	4	18%	6%	114	+2.3	263/310/431	168	291	21	7	17%	6%	108	+1.9	255/303/429	174	274	23	8	17%	5%	106	+1.6

Bo Bichette

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps