Danny Jansen

C Texas Rangers

Age 32 R/R 6'2" / 240 lbs MLB HR +15%BB +5% Svc 8.291 · Ctrl thru 2027

Overview

MLB40-MANExtFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	29	MLBBOS	324	.205/.312/.349	9	0	85	0.7
2025	30	MLBMIL	337	.215/.323/.399	14	0	105	1.7
2026	31	MLBTEX	227	.203/.296/.381	8	1	84	0.6
2027PROJ	32	MLBTEX	199	.206/.305/.372	7	1	90	0.4
2028PROJ	33	MLBTEX	157	.198/.297/.354	5	1	83	-0.2

Last 3 seasons WAR 3.0 · Next 2 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service8.291First FA2028Options4

2027Ext$7M

Skills · percentileStatcast 2024-2026

Bat Spd44

Barrel%43

xwOBA33

Speed33

Avg EV26

Form.223/.309/.390 ▲ rolling true talent (60d window) · proj .204/.302/.363

CompsElias Díaz (age 32) · Miguel Ojeda (age 31) · Carlos Pérez (age 33)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 9390vR 81

AVG/OBP/SLG.206 / .305 / .372

PA199

HR7

K%23

BB%11

BABIP235

ISO163

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Recent Form · Splits · ContractCON 40 / POW 45

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT40

xAVG

100.195

POWER45

Barrel%

437.3

Avg EV

2687.3

Bat Spd

4470.7

EYE60

scouting grade only

SPEED40

Sprint

3326.7

Recent Formrolling true talent ⓘ

K%18%▲▲13% over 68 PA (60d) · proj 23%

BB%9%▼7% over 68 PA (60d) · proj 10%

ISO.167·.190 over 58 AB (60d) · proj .159

HR/BB5.4%·6.1% over 49 BBE (60d) · proj 5.0%

BABIP.238·.283 over 46 BIP (60d) · proj .236

SLASH.223/.309/.390▲proj .204/.302/.363

Platoon Splits2024-2026 · 708 PA

vs LHP

vs RHP

Edge

213

495

—

wRC+

109

◀◀L

wOBA

330

297

◀L

ISO

163

162

—

BABIP

264

235

◀L

25.8%

21.6%

▶▶R

BB%

17.8%

9.5%

◀◀L

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

Status FA

MLB Debut 2018

Service 8.291 yrs.days

Team Control Through 2027

First FA Year 2028

OPT

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$7M	+0.4	$2M	-$6M
Totals		$7M		$2M	-$6M

Options · projected decision
2028	MUTUAL OPT	$7.2M / $0.0M buyout	DECLINE
2029	MUTUAL OPT	$8.0M / $2.2M buyout	DECLINE
2030	MUTUAL OPT	$12.0M / $0.0M buyout	DECLINE
2031	MUTUAL OPT	$7.2M / $0.0M buyout	DECLINE

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. Catcher framing: only 2027 Statcast framing is modeled (Baseball Savant server-caches the leaderboard to the current season); prior-year framing is unmodeled — projections for established framers may run 1-3 WAR low.

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	GCL Blue Jays	—	140	114	28	4	0	0	21	10	2	0	0	246	372	281	653	35	262	7	15	307	51	—	—	—	—	—	—
2014	19	ROK	Bluefield Blue Jays	—	146	124	35	10	0	5	16	17	6	2	1	282	390	484	874	202	294	12	11	390	78	—	—	—	—	—	—
2015	20	A	Lansing Lugnuts	—	184	160	33	8	0	4	19	22	3	2	0	206	302	331	633	125	213	12	10	288	35	—	—	—	—	—	—
2015	20	ROK	GCL Blue Jays	—	23	21	5	1	0	1	2	5	0	0	0	238	304	429	733	190	267	22	9	325	34	—	—	—	—	—	—
2016	21	A+	Dunedin Blue Jays	—	217	188	41	7	0	1	22	40	5	7	1	218	316	271	588	53	268	18	10	276	33	—	—	—	—	—	—
2016	21	INTL	Mesa Solar Sox	—	82	71	20	0	2	0	9	10	1	0	0	282	370	338	708	56	323	12	11	324	105	—	—	—	—	—	—
2017	22	AAA	Buffalo Bisons	—	78	67	22	4	1	3	11	7	0	0	0	328	423	552	975	224	333	9	14	427	150	—	—	—	—	—	—
2017	22	AA	New Hampshire Fisher Cats	—	210	179	52	15	1	2	22	19	5	1	0	291	383	419	802	128	311	9	10	356	104	—	—	—	—	—	—
2017	22	A+	Dunedin Blue Jays	—	136	122	45	6	0	5	8	14	4	0	0	369	425	541	966	172	385	10	6	422	134	—	—	—	—	—	—
2018	23	MLB	Toronto Blue Jays	—	95	81	20	6	0	3	9	17	4	0	0	247	351	432	783	185	274	18	9	349	122	+2	+0	+3	+8	+2	1.6
2018	23	AAA	Buffalo Bisons	—	360	298	82	21	1	12	44	49	14	5	1	275	393	473	866	198	292	14	12	383	112	—	—	—	—	—	—
2019	24	MLB	Toronto Blue Jays	—	384	347	72	12	1	13	31	79	4	0	1	207	280	360	640	153	230	21	8	287	79	-10	-0	+21	+7	+8	2.7
2020	25	MLB	Toronto Blue Jays	—	147	120	22	3	0	6	21	31	2	0	0	183	315	358	673	175	190	21	14	301	90	-2	+0	+3	+3	+3	0.7
2021	26	MLB	Toronto Blue Jays	—	205	184	41	13	0	11	17	44	3	0	0	223	299	473	772	250	233	21	8	337	114	+3	+0	+7	+4	+4	2.0
2021	26	AAA	Buffalo Bisons	—	26	21	5	0	0	1	4	3	0	0	0	238	360	381	741	143	222	12	15	327	68	—	—	—	—	—	—
2022	27	MLB	Toronto Blue Jays	—	248	215	56	10	0	15	25	44	3	1	0	260	346	516	862	256	255	18	10	370	134	+10	+0	+6	+5	+5	2.7
2022	27	AAA	Buffalo Bisons	—	18	17	5	1	0	1	1	6	0	0	0	294	333	529	863	235	400	33	6	377	82	—	—	—	—	—	—
2023	28	MLB	Toronto Blue Jays	—	301	268	61	15	0	17	23	62	10	0	0	228	312	474	786	246	233	21	8	346	119	+7	+0	+6	+5	+7	2.5
2024	29	MLB	Boston Red Sox	—	324	278	57	13	0	9	40	61	3	0	0	205	312	349	660	144	227	19	12	300	85	-6	+0	+0	+6	+7	0.7
2025	30	MLB	Milwaukee Brewers	—	337	288	62	11	0	14	42	86	4	0	0	215	323	399	723	184	253	26	12	323	105	+2	+0	+1	+6	+7	1.7
2026	31	MLB	Texas Rangers	—	227	197	40	9	1	8	18	55	8	1	1	203	296	381	677	178	239	24	8	300	84	-4	-0	+1	+4	+5	0.6
2026	31	AAA	Round Rock Express	—	17	15	5	0	0	0	2	2	0	0	0	333	412	333	745		385	12	12	348	82	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	2268	1978	431	92	2	96	226	479	41	2	2	218	311	412	723	194	237	21	10	321	103	+8	-0	+48	+48	+49	15.7
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2013	18	ROK MLE	GCL Blue Jays	—	140	122	25	3	0	0	13	14	2	0	0	205	292	230	521	25	219	10	9	244	51	—	—	—	—	—	—
2014	19	ROK MLE	Bluefield Blue Jays	—	146	130	27	7	0	4	10	24	6	2	1	208	295	354	648	146	226	16	7	284	78	—	—	—	—	—	—
2015	20	A MLE	Lansing Lugnuts	—	184	166	26	5	0	3	13	31	3	2	0	157	231	241	472	84	172	17	7	220	35	—	—	—	—	—	—
2015	20	ROK MLE	GCL Blue Jays	—	23	22	4	1	0	1	1	7	0	0	0	182	217	364	581	182	208	30	4	219	34	—	—	—	—	—	—
2016	21	A+ MLE	Dunedin Blue Jays	—	217	194	33	6	0	1	16	59	5	7	1	170	251	216	468	46	232	27	7	217	33	—	—	—	—	—	—
2017	22	AAA MLE	Buffalo Bisons	—	78	71	22	4	1	3	7	9	0	0	0	310	372	521	893	211	325	12	9	390	150	—	—	—	—	—	—
2017	22	AA MLE	New Hampshire Fisher Cats	—	210	186	51	14	1	1	15	23	5	1	0	274	345	376	721	102	295	11	7	322	104	—	—	—	—	—	—
2017	22	A+ MLE	Dunedin Blue Jays	—	136	125	41	6	0	3	5	20	4	0	0	328	373	448	821	120	366	15	4	366	134	—	—	—	—	—	—
2018	23	MLB MLE	Toronto Blue Jays	—	95	81	20	6	0	3	9	17	4	0	0	247	351	432	783	185	274	18	9	348	122	+2	+0	+3	+8	+2	1.6
2018	23	AAA MLE	Buffalo Bisons	—	360	309	77	18	1	10	33	59	14	5	1	249	348	411	759	162	270	16	9	333	112	—	—	—	—	—	—
2019	24	MLB MLE	Toronto Blue Jays	—	384	348	72	12	1	13	30	79	4	0	1	207	277	359	637	152	230	21	8	285	79	-10	-0	+21	+7	+8	2.7
2020	25	MLB MLE	Toronto Blue Jays	—	147	120	22	3	0	6	21	31	2	0	0	183	315	358	673	175	190	21	14	301	90	-2	+0	+3	+3	+3	0.7
2021	26	MLB MLE	Toronto Blue Jays	—	205	184	41	13	0	11	17	44	3	0	0	223	299	473	772	250	233	21	8	337	114	+3	+0	+7	+4	+4	2.0
2021	26	AAA MLE	Buffalo Bisons	—	26	22	5	0	0	1	3	4	0	0	0	227	320	364	684	136	194	15	12	268	68	—	—	—	—	—	—
2022	27	MLB MLE	Toronto Blue Jays	—	248	216	56	10	0	15	24	44	3	1	0	259	342	514	855	255	255	18	10	367	134	+10	+0	+6	+5	+5	2.7
2022	27	AAA MLE	Buffalo Bisons	—	18	17	5	1	0	1	1	7	0	0	0	294	333	529	863	235	366	39	6	290	82	—	—	—	—	—	—
2023	28	MLB MLE	Toronto Blue Jays	—	301	269	61	15	0	17	22	62	10	0	0	227	309	472	781	245	233	21	7	344	119	+7	+0	+6	+5	+7	2.5
2024	29	MLB MLE	Boston Red Sox	—	324	278	55	12	0	9	40	61	3	0	0	198	305	338	643	140	227	19	12	294	85	-6	+0	+0	+6	+7	0.7
2025	30	MLB MLE	Milwaukee Brewers	—	337	288	62	12	0	13	42	86	4	0	0	215	323	392	716	177	253	26	12	323	105	+2	+0	+1	+6	+7	1.7
2026	31	MLB MLE	Texas Rangers	—	227	198	39	9	1	7	17	55	8	1	1	197	287	359	646	162	239	24	7	292	84	-4	-0	+1	+4	+5	0.6
2026	31	AAA MLE	Round Rock Express	—	17	16	5	0	0	0	1	2	0	0	0	312	353	312	665		344	12	6	290	82	—	—	—	—	—	—
2013	18	ROK MLE	GCL Blue Jays	—	140	122	25	3	0	0	13	14	2	0	0	205	292	230	521	25	225	10	9	244	51	—	—	—	—	—	—
2013	18	ROK RAW	GCL Blue Jays	—	140	114	28	4	0	0	21	10	2	0	0	246	372	281	653	35	262	7	15	307	51	—	—	—	—	—	—
2014	19	ROK MLE	Bluefield Blue Jays	—	146	130	27	7	0	4	10	24	6	2	1	208	295	354	648	146	225	16	7	284	78	—	—	—	—	—	—
2014	19	ROK RAW	Bluefield Blue Jays	—	146	124	35	10	0	5	16	17	6	2	1	282	390	484	874	202	294	12	11	390	78	—	—	—	—	—	—
2015	20	A MLE	2 teams	—	207	187	30	6	0	4	15	38	3	2	0	160	234	257	491	96	177	18	7	220	35	—	—	—	—	—	—
2015	20	A RAW	2 teams	—	207	181	38	9	0	5	21	27	3	2	0	210	302	343	645	133	219	13	10	292	35	—	—	—	—	—	—
2016	21	A+ MLE	2 teams	—	299	268	45	8	0	1	22	82	6	7	1	168	247	209	456	41	234	27	7	217	33	—	—	—	—	—	—
2016	21	A+ RAW	2 teams	—	299	259	61	7	2	1	31	50	6	7	1	236	331	290	621	54	284	17	10	289	33	—	—	—	—	—	—
2017	22	AA MLE	3 teams	—	424	382	115	24	2	8	27	52	9	1	0	301	361	437	798	136	328	12	6	349	122	—	—	—	—	—	—
2017	22	AA RAW	3 teams	—	424	368	119	25	2	10	41	40	9	1	0	323	404	484	888	160	339	9	10	390	122	—	—	—	—	—	—
2018	23	AAA MLE	2 teams	—	455	390	97	24	1	13	42	76	18	5	1	249	349	415	764	167	275	17	9	336	114	—	—	—	—	—	—
2018	23	AAA RAW	2 teams	—	455	379	102	27	1	15	53	66	18	5	1	269	384	464	849	195	288	15	12	376	114	—	—	—	—	—	—
2019	24	MLB MLE	Toronto Blue Jays	—	384	348	72	12	1	13	30	79	4	0	1	207	277	359	637	152	230	21	8	285	79	-10	-0	+21	+7	+8	2.7
2019	24	MLB RAW	Toronto Blue Jays	—	384	347	72	12	1	13	31	79	4	0	1	207	280	360	640	153	230	21	8	287	79	-10	-0	+21	+7	+8	2.7
2020	25	MLB MLE	Toronto Blue Jays	—	147	120	22	3	0	6	21	31	2	0	0	183	315	358	673	175	190	21	14	301	90	-2	+0	+3	+3	+3	0.7
2020	25	MLB RAW	Toronto Blue Jays	—	147	120	22	3	0	6	21	31	2	0	0	183	315	358	673	175	190	21	14	301	90	-2	+0	+3	+3	+3	0.7
2021	26	MLB MLE	2 teams	—	231	206	46	13	0	12	20	48	3	0	0	223	301	461	762	238	231	21	9	329	109	+2	+0	+7	+4	+5	1.9
2021	26	MLB RAW	2 teams	—	231	205	46	13	0	12	21	47	3	0	0	224	306	463	769	239	231	20	9	336	109	+2	+0	+7	+4	+5	1.9
2022	27	MLB MLE	2 teams	—	266	233	61	11	0	16	25	51	3	1	0	262	341	515	856	253	263	19	9	362	131	+10	+0	+6	+5	+6	2.7
2022	27	MLB RAW	2 teams	—	266	232	61	11	0	16	26	50	3	1	0	263	345	517	862	254	263	19	10	370	131	+10	+0	+6	+5	+6	2.7
2023	28	MLB MLE	Toronto Blue Jays	—	301	269	61	15	0	17	22	62	10	0	0	227	309	472	781	245	232	21	7	344	119	+7	+0	+6	+5	+7	2.5
2023	28	MLB RAW	Toronto Blue Jays	—	301	268	61	15	0	17	23	62	10	0	0	228	312	474	786	246	233	21	8	346	119	+7	+0	+6	+5	+7	2.5
2024	29	MLB MLE	Boston Red Sox	—	324	278	55	12	0	9	40	61	3	0	0	198	305	338	643	140	218	19	12	294	85	-6	+0	+0	+6	+7	0.7
2024	29	MLB RAW	Boston Red Sox	—	324	278	57	13	0	9	40	61	3	0	0	205	312	349	660	144	227	19	12	300	85	-6	+0	+0	+6	+7	0.7
2025	30	MLB MLE	Milwaukee Brewers	—	337	288	62	12	0	13	42	86	4	0	0	215	323	392	716	177	257	26	12	323	105	+2	+0	+1	+6	+7	1.7
2025	30	MLB RAW	Milwaukee Brewers	—	337	288	62	11	0	14	42	86	4	0	0	215	323	399	723	184	253	26	12	323	105	+2	+0	+1	+6	+7	1.7
2026	31	MLB MLE	2 teams	—	244	214	43	9	1	7	18	57	8	1	1	201	287	350	638	150	240	23	7	292	84	-5	-0	+1	+4	+5	0.6
2026	31	MLB RAW	2 teams	—	244	212	45	9	1	8	20	57	8	1	1	212	304	377	682	165	252	23	8	304	84	-5	-0	+1	+4	+5	0.6
2013	18	ROK MLE	GCL Blue Jays	—	140	124	25	3	0	0	13	14	2	0	0	202	292	226	518	24	219	10	9	244	51	—	—	—	—	—	—
2014	19	ROK MLE	Bluefield Blue Jays	—	146	129	27	7	0	4	10	24	6	2	1	209	295	357	651	147	226	16	7	284	78	—	—	—	—	—	—
2015	20	A MLE	2 teams	—	207	187	30	6	0	4	15	38	3	2	0	160	234	257	491	96	176	18	7	220	35	—	—	—	—	—	—
2016	21	A+ MLE	2 teams	—	299	269	45	8	0	1	22	82	6	7	1	167	247	208	455	41	232	27	7	217	33	—	—	—	—	—	—
2017	22	AA MLE	3 teams	—	424	385	115	24	2	8	27	52	9	1	0	299	361	434	795	135	323	12	6	349	122	—	—	—	—	—	—
2018	23	AAA MLE	2 teams	—	455	392	97	24	1	13	42	76	18	5	1	247	349	413	762	166	271	17	9	336	114	—	—	—	—	—	—
2019	24	MLB MLE	Toronto Blue Jays	—	384	347	72	12	1	13	30	79	4	0	1	207	277	360	638	153	230	21	8	285	79	—	—	—	—	—	—
2020	25	MLB MLE	Toronto Blue Jays	—	147	123	22	3	0	6	21	31	2	0	0	179	315	350	664	171	190	21	14	301	90	—	—	—	—	—	—
2021	26	MLB MLE	2 teams	—	231	206	46	13	0	12	20	48	3	0	0	223	301	461	762	238	228	21	9	329	109	—	—	—	—	—	—
2022	27	MLB MLE	2 teams	—	266	236	61	11	0	16	25	51	3	1	0	258	341	508	849	250	262	19	9	362	131	—	—	—	—	—	—
2023	28	MLB MLE	Toronto Blue Jays	—	301	266	61	15	0	17	22	62	10	0	0	229	309	477	786	248	233	21	7	344	119	—	—	—	—	—	—
2024	29	MLB MLE	Boston Red Sox	—	324	278	55	12	0	9	40	61	3	0	0	198	305	338	643	140	227	19	12	294	85	—	—	—	—	—	—
2025	30	MLB MLE	Milwaukee Brewers	—	337	288	62	12	0	13	42	86	4	0	0	215	323	392	716	177	253	26	12	323	105	—	—	—	—	—	—
2026	31	MLB MLE	2 teams	—	244	216	43	9	1	7	18	57	8	1	1	199	287	347	635	148	246	23	7	292	84	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	29	MLB MLE	Boston Red Sox	—	324	278	55	12	0	9	40	61	3	0	0	198	305	338	643	140	227	19	12	294	85	—	—	—	—	—	—
2025	30	MLB MLE	Milwaukee Brewers	—	337	288	62	12	0	13	42	86	4	0	0	215	323	392	716	177	253	26	12	323	105	—	—	—	—	—	—
2026	31	MLB MLE	2 teams	—	244	216	43	9	1	7	18	57	8	1	1	199	287	347	635	148	246	23	7	292	84	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	32	MLB MLE	TEX	100%	308	267	55	11	1	10	32	70	6	2	1	205	304	363	667	159	236	23	10	301	90	-4	+0	-3	+6	+7	0.4
▸ 2027 — real world (MLB)
2027	32	MLB CTX	TEX	100%	199	172	35	7	0	7	21	45	4	1	0	206	305	372	677	166	235	23	11	305	90	-2	+0	-2	+4	+4	0.4
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	33	MLB MLE	TEX	100%	157	137	27	5	0	5	16	37	3	1	0	197	295	345	641	149	229	24	10	291	83	-3	+0	-6	+3	+3	-0.2
2028	33	MLB CTX	TEX	100%	157	137	27	5	0	5	16	37	3	1	0	198	297	354	650	155	228	24	10	294	83	-3	+0	-6	+3	+3	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2425	2115	458	97	2	101	242	516	44	3	2	217	310	408	717	191	236	21	10	319	92	+5	-0	+43	+51	+53	15.4
/ 162G	—	A+C		—	650	567	123	26	1	27	65	138	12	1	1	217	311	409	720	192	236	21	10	319	92	+1	-0	+11	+14	+14	4.1
Career	—	MLE		—	4261	3744	822	171	5	134	384	843	88	21	5	220	307	375	682	156	246	20	9	304	92	+3	+0	+41	+54	+57	15.8
/ 162G	—	MLE		—	650	571	125	26	1	20	59	129	13	3	1	219	306	373	679	154	246	20	9	304	92	+1	+0	+10	+13	+14	3.9

How the minor-league lines were translated

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

2026 AAARound Rock Express · 17 PAwOBA .340 → .290 (−50)K% 11.8% → 14.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.76%	÷1.000	×1.200	—	—	14.12%
BB% (unintentional) /PA	11.76%	÷1.000	×0.690	—	×0.962	7.81%
HBP% /PA	0.00%	—	×0.940	—	×0.962	0.00%
Singles /BIP	38.46%	÷1.000	×0.930	—	×0.962	34.41%
Doubles /BIP	0.00%	÷1.000	×0.830	—	×0.962	0.00%
Triples /BIP	0.00%	÷1.000	×0.970	—	×0.962	0.00%
Home runs /BIP	0.00%	÷1.000	×0.700	—	×0.962	0.00%

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).

Result: wOBA .340 → .290; ISO .000 → .000; BABIP .385 → .344. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2022 AAABuffalo Bisons · 18 PAwOBA .365 → .290 (−76)K% 33.3% → 39.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	33.33%	÷1.018	×1.200	—	—	39.30%
BB% (unintentional) /PA	5.56%	÷1.032	×0.690	—	×1.003	3.72%
HBP% /PA	0.00%	—	×0.940	—	×1.003	0.00%
Singles /BIP	27.27%	÷0.960	×0.930	—	×1.003	26.50%
Doubles /BIP	9.09%	÷0.984	×0.830	—	×1.003	7.69%
Triples /BIP	0.00%	÷1.149	×0.970	—	×1.003	0.00%
Home runs /BIP	9.09%	÷0.951	×0.700	—	×1.003	6.71%

Factors used: league row International League. Park (home-season share, regressed): HR 90, 1B 92, 2B 97, 3B 130, K 104, BB 106 — applied at half strength. Age: age 27 vs a level average of 27.2 → +0.3% on BB/HBP/hit rates (0.2 yr younger than average).

Result: wOBA .365 → .290; ISO .235 → .168; BABIP .400 → .366. 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 AAABuffalo Bisons · 26 PAwOBA .331 → .268 (−63)K% 11.5% → 14.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.54%	÷0.965	×1.200	—	—	14.34%
BB% (unintentional) /PA	15.38%	÷1.024	×0.690	—	×1.018	10.55%
HBP% /PA	0.00%	—	×0.940	—	×1.018	0.00%
Singles /BIP	22.22%	÷1.071	×0.930	—	×1.018	19.65%
Doubles /BIP	0.00%	÷0.962	×0.830	—	×1.018	0.00%
Triples /BIP	0.00%	÷1.150	×0.920	—	×1.018	0.00%
Home runs /BIP	5.56%	÷1.081	×0.700	—	×1.018	3.66%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 116, 1B 114, 2B 92, 3B 130, K 93, BB 105 — 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).

Result: wOBA .331 → .268; ISO .143 → .102; BABIP .222 → .194. 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 AAABuffalo Bisons · 360 PAwOBA .376 → .333 (−43)K% 13.6% → 16.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.61%	÷0.993	×1.200	—	—	16.45%
BB% (unintentional) /PA	11.94%	÷0.954	×0.690	—	×1.050	9.07%
HBP% /PA	3.89%	—	×0.940	—	×1.050	3.84%
Singles /BIP	19.28%	÷0.970	×0.930	×0.964	×1.050	18.72%
Doubles /BIP	8.43%	÷0.987	×0.830	×0.964	×1.050	7.18%
Triples /BIP	0.40%	÷1.150	×0.970	×0.964	×1.050	0.34%
Home runs /BIP	4.82%	÷1.080	×0.840	—	×1.050	3.94%

Factors used: league row IL. Park (home-season share, regressed): HR 116, 1B 94, 2B 97, 3B 130, K 99, BB 91 — applied at half strength. Age: age 23 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (4.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.964.

Result: wOBA .376 → .333; ISO .198 → .168; BABIP .292 → .270. 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 AANew Hampshire Fisher Cats · 210 PAwOBA .349 → .322 (−27)K% 9.0% → 11.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	9.05%	÷1.007	×1.220	—	—	10.97%
BB% (unintentional) /PA	9.52%	÷0.995	×0.700	—	×1.042	6.99%
HBP% /PA	2.38%	—	×0.850	—	×1.042	2.11%
Singles /BIP	21.25%	÷1.024	×0.970	×0.998	×1.042	20.93%
Doubles /BIP	9.38%	÷1.024	×0.860	×0.998	×1.042	8.19%
Triples /BIP	0.62%	÷0.900	×0.950	×0.998	×1.042	0.69%
Home runs /BIP	1.25%	÷1.165	×0.780	—	×1.042	0.87%

Factors used: league row EL. Park (home-season share, regressed): HR 133, 1B 105, 2B 105, 3B 80, K 101, BB 99 — applied at half strength. Age: age 22 vs a level average of 24.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.998.

Result: wOBA .349 → .322; ISO .128 → .114; BABIP .311 → .295. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2017 A+Dunedin Blue Jays · 136 PAwOBA .413 → .366 (−47)K% 10.3% → 14.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.29%	÷1.007	×1.420	—	—	14.52%
BB% (unintentional) /PA	5.88%	÷1.118	×0.750	—	×1.012	3.99%
HBP% /PA	2.94%	—	×0.930	—	×1.012	2.77%
Singles /BIP	31.48%	÷1.002	×0.920	×1.022	×1.012	29.91%
Doubles /BIP	5.56%	÷0.940	×0.960	×1.022	×1.012	5.87%
Triples /BIP	0.00%	÷1.150	×0.810	×1.022	×1.012	0.00%
Home runs /BIP	4.63%	÷1.265	×0.880	—	×1.012	3.26%

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 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 ×1.022.

Result: wOBA .413 → .366; ISO .172 → .137; BABIP .385 → .366. 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 AAABuffalo Bisons · 78 PAwOBA .413 → .390 (−22)K% 9.0% → 11.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	8.97%	÷0.950	×1.200	—	—	11.33%
BB% (unintentional) /PA	12.82%	÷1.027	×0.690	—	×1.050	9.04%
HBP% /PA	0.00%	—	×0.940	—	×1.050	0.00%
Singles /BIP	23.33%	÷1.021	×0.930	×1.022	×1.050	22.82%
Doubles /BIP	6.67%	÷0.940	×0.830	×1.022	×1.050	6.32%
Triples /BIP	1.67%	÷0.961	×0.970	×1.022	×1.050	1.81%
Home runs /BIP	5.00%	÷0.903	×0.840	—	×1.050	4.89%

Factors used: league row IL. Park (home-season share, regressed): HR 80, 1B 104, 2B 88, 3B 92, K 90, BB 106 — applied at half strength. Age: age 22 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (5.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.022.

Result: wOBA .413 → .390; ISO .224 → .228; BABIP .333 → .325. 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 A+Dunedin Blue Jays · 217 PAwOBA .272 → .217 (−55)K% 18.4% → 27.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.43%	÷0.955	×1.420	—	—	27.42%
BB% (unintentional) /PA	10.14%	÷1.038	×0.750	—	×1.027	7.53%
HBP% /PA	2.30%	—	×0.930	—	×1.027	2.20%
Singles /BIP	22.30%	÷1.042	×0.920	×0.950	×1.027	19.20%
Doubles /BIP	4.73%	÷1.064	×0.960	×0.950	×1.027	4.16%
Triples /BIP	0.00%	÷1.150	×0.810	×0.950	×1.027	0.00%
Home runs /BIP	0.68%	÷0.912	×0.880	—	×1.027	0.67%

Factors used: league row FSL. Park (home-season share, regressed): HR 82, 1B 108, 2B 113, 3B 130, K 91, BB 108 — 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 ×0.950.

Result: wOBA .272 → .217; ISO .053 → .045; BABIP .268 → .232. 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
#1Jason Castrolast yr '22 career totals — 12 seasons, 3,381 PA	5.1	3,381	97	6	227	312	387	+60	+77	22.5	21.6
/162	664	19	1	+11.9	+15.1	4.4	pk7: 21
#2Steve Yeager'72-'86 * career totals — 15 seasons, 4,014 PA	6.0	4,014	102	14	223*	294*	383*	+72	+0	12.3	11.6
/162	664	17	2	+11.9	+0.0	2.0	pk7: 11
#3Kelly Shoppachlast yr '13 career totals — 8 seasons, 1,839 PA	2.8	1,839	70	1	225	314	417	+33	+14	11.3	11.5
/162	664	25	0	+11.9	+5.0	4.1	pk7: 12
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 11 projected seasons	4.0	2,624	107	4	216	306	405	+47	+59	12.2	11.2
/162	664	27	1	+11.9	+15.0	3.1	pk7: 10
#4Jason LaRue'99-'10 * career totals — 12 seasons, 3,103 PA	4.7	3,103	96	14	223*	304*	385*	+54	+0	9.6	9.7
/162	664	21	3	+11.5	+0.1	2.1	pk7: 10
#5Elrod Hendricks'68-'79 * career totals — 9 seasons, 2,155 PA	3.2	2,155	62	1	224*	308*	401*	+37	-0	8.7	8.7
/162	664	19	0	+11.4	-0.1	2.7	pk7: 9
#6Curt Casalilast yr '24 career totals — 10 seasons, 1,566 PA	2.4	1,566	47	2	217	311	367	+28	+19	7.8	7.9
/162	664	20	1	+11.9	+7.9	3.3	pk7: 8

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
Danny Jansen (OGILVIE)	32	40	45	40	60	203/301/360	157	236	6	1	23%	10%	90	+0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Elias Díaz 2023 · MLB	32	44→54	50	42→45	48	227/286/381	154	256	18	2	20%	7%	87	+0.4	245/298/378	133	297	14	2	22%	7%	91	+0.6	245/298/371	126	300	14	1	22%	6%	90	+0.4
✕Miguel Ojeda 2006 · MLB	31	41→45	49→45	41→45	50	212/285/353	141	242	18	5	21%	8%	80	-0.1	228/291/343	115	269	11	6	19%	7%	80	-0.2	237/302/363	127	268	13	7	17%	8%	87	+0.2
✕Carlos Pérez 2024 · MLB	33	38→48	53→55	46→45	46	209/273/378	169	228	23	2	21%	7%	82	+0.0	209/273/380	171	232	21	3	21%	7%	82	+0.0	196/260/370	174	213	22	1	21%	7%	73	-0.4
✕Taylor Motter 2022 · MLB	32	42→49	52→50	47→55	51	220/299/386	166	266	19	4	25%	10%	93	+0.8	208/277/361	153	266	18	8	28%	9%	80	-0.2	185/254/326	141	236	18	8	29%	8%	61	-0.8
✕Michael McKenry 2017 · MLB	32	45→47	48→55	44→40	54	221/316/371	150	289	15	7	27%	11%	97	+1.1	201/287/318	117	283	11	6	30%	10%	74	-0.6	159/252/243	84	230	7	0	31%	10%	42	-1.3
●Robinson Chirinos 2016 · MLB	32	43→46	52→60	44→50	49	225/298/392	166	260	20	3	22%	8%	95	+0.9	234/328/442	208	282	26	4	26%	10%	118	+2.6	229/342/435	206	294	26	2	29%	11%	120	+1.8
✕John Mayberry Jr. 2015 · MLB	31	44→48	51→55	44→50	48	227/295/393	167	269	18	5	23%	8%	93	+0.8	214/281/366	152	263	16	7	25%	8%	82	-0.0	161/216/284	123	202	11	4	26%	6%	38	-0.8
✕Dustin Garneau 2021 · MLB	33	40→38	49→50	45	46	208/290/361	153	270	17	5	29%	8%	85	+0.2	192/269/357	165	248	20	6	31%	7%	76	-0.4	145/226/306	160	173	21	1	31%	7%	48	-0.8
✕Anthony Recker 2015 · MLB	31	41→48	52→50	42→45	42	216/275/381	165	287	21	5	32%	7%	84	+0.1	204/276/349	145	275	17	5	31%	8%	76	-0.4	193/262/327	134	259	15	2	30%	7%	64	-0.6
✕Scott Seabol 2007 · MLB	32	44→42	53→55	38→40	45	229/284/401	173	270	20	3	24%	7%	91	+0.7	234/288/421	187	269	23	7	22%	7%	97	+1.1	228/281/424	196	253	25	5	21%	6%	95	+0.9
✕John Buck 2013 · MLB	33	44→53	52→60	42→30	50	228/303/392	164	271	20	2	24%	9%	97	+1.1	226/293/363	137	276	17	4	24%	7%	86	+0.3	224/284/345	121	273	17	2	24%	6%	79	-0.1
✕Alex Gonzalez 2005 · MLB	32	45→50	51→55	41→45	46	230/285/395	165	266	18	5	21%	7%	90	+0.6	239/292/376	137	285	14	6	21%	7%	88	+0.4	265/318/403	138	312	14	3	19%	7%	105	+1.1
✕Bryan Holaday 2020 · MLB	32	46	45	38→40	48	230/289/352	123	258	13	4	17%	6%	82	-0.0	222/283/363	141	267	15	7	23%	7%	82	-0.0	186/238/360	174	219	21	4	27%	5%	67	-0.3
✕Brian O'Keefe 2024 · MLB	31	39→42	50	41→40	43	205/263/360	156	263	18	4	29%	7%	74	-0.5	196/254/337	141	249	17	5	28%	7%	65	-1.2	174/231/302	128	216	17	3	28%	7%	46	-0.9
✕Kelly Stinnett 2001 · MLB	31	44	49→50	42→40	46	227/290/369	142	262	18	4	21%	6%	86	+0.3	239/307/398	159	296	19	6	25%	8%	99	+1.3	236/306/391	155	302	17	5	26%	7%	98	+0.3
✕Iker Franco 2013 · AAA	32	46→47	46→50	40	48	231/289/355	124	269	15	3	21%	8%	82	+0.0	223/279/316	93	271	10	3	21%	7%	69	-0.9	234/287/315	81	287	9	1	21%	7%	69	-0.3
✕Curt Casali 2020 · MLB	31	49	48→50	40→30	48	244/309/380	137	296	16	3	23%	8%	95	+1.0	230/320/392	162	298	19	5	28%	10%	103	+1.5	207/312/292	85	276	8	0	25%	11%	77	-0.1
✕Corky Miller 2008 · MLB	32	41	50	48→40	48	210/293/357	147	228	18	7	18%	7%	86	+0.3	213/286/335	122	245	13	5	19%	7%	77	-0.3	211/280/323	112	244	12	0	18%	7%	71	-0.3
✕Brook Fordyce 2002 · MLB	32	48	49→50	40→30	47	244/296/394	151	269	16	4	17%	6%	94	+0.9	241/293/354	113	271	11	5	15%	6%	82	+0.0	243/291/332	89	274	8	3	14%	5%	77	-0.1
✕Said Gutierrez 2013 · AAA	33	45	48→50	43→40	45	231/284/367	136	269	16	6	22%	6%	83	+0.1	222/268/332	110	254	12	6	18%	5%	68	-1.0	217/252/285	67	260	9	0	20%	3%	50	-0.8

Danny Jansen

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps