Davis Schneider

LF Buffalo Bisons

Age 28 R/R 5'8" / 190 lbs AAA Svc 2.797S2 · Ctrl thru 2030

Overview

AAA40-MANArb-1FA 2031

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	25	MLBTOR	454	.191/.285/.343	13	6	77	-0.6
2025	26	AAATOR	160	.226/.352/.391	4	3	64	—	.179/.277/.300
2025	26	MLBTOR	227	.234/.363/.436	11	3	128	0.7
2026	27	AAATOR	218	.220/.456/.460	10	4	105	—	.179/.358/.351
2026	27	MLBTOR	156	.145/.312/.315	5	1	83	-0.3
2027PROJ45% MLB	28	MLBTOR	107	.200/.330/.379	4	2	103	0.3
2028PROJ53% MLB	29	MLBTOR	161	.197/.327/.371	6	2	100	0.2
2029PROJ58% MLB	30	MLBTOR	172	.193/.323/.361	6	1	97	0.1

Last 3 seasons WAR -0.3 · Next 3 projected WAR 0.5Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2030Service2.797First FA2031Super-2

2027Arb-1$0.9M2028Arb-2$1M2029Arb-3$1M2030Ext$1M

Skills · percentileStatcast 2024-2026

Barrel%78

Bat Spd55

Avg EV48

xwOBA43

Speed37

CompsJabari Blash (age 28) · Drew Ellis (age 28) · Kyle Lewis (age 28)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 104103vR 97

AVG/OBP/SLG.200 / .330 / .379

PA107

HR4

K%30

BB%15

BABIP256

ISO170

MLB%45%

Value2027 · WAR

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

Tools · Splits · ContractCON 35 / POW 60

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT35

xAVG

100.186

POWER60

Barrel%

7812.3

Avg EV

4889.0

Bat Spd

5571.8

EYE60

scouting grade only

SPEED50

Sprint

3726.9

Platoon Splits2024-2026 · 731 PA

vs LHP

vs RHP

Edge

289

442

—

wRC+

102

▶▶R

wOBA

282

318

▶R

ISO

125

190

▶▶R

BABIP

263

261

—

31.8%

29.0%

▶R

BB%

13.1%

12.4%

◀L

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

Status Pre-Arb SUPER-2

MLB Debut 2023

Service 2.797 yrs.days

Team Control Through 2030

First FA Year 2031

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-1	$0.9M	+0.3	$1M	+$0.2M
2028	Arb-2	$1M	+0.2	$0.7M	+$0.0M (cut)
2029	Arb-3	$1M	+0.1	$0.3M	+$0.0M (cut)
2030	Ext	beyond projection horizon · no WAR estimate
Totals		$0.9M		$2M	+$0.2M

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)
2017	18	ROK	GCL Blue Jays	—	210	168	40	12	1	4	36	36	2	3	1	238	379	393	771	155	273	17	17	346	55	—	—	—	—	—	—
2018	19	ROK	Bluefield Blue Jays	—	161	133	31	8	1	3	22	47	3	4	4	233	354	376	730	143	329	29	14	328	36	—	—	—	—	—	—
2021	22	A+	Vancouver Canadians	—	179	147	34	7	1	9	26	59	2	0	1	231	354	476	830	245	305	33	15	359	74	—	—	—	—	—	—
2022	23	AAA	Buffalo Bisons	—	75	60	14	4	0	2	14	20	1	1	1	233	387	400	787	167	316	27	19	361	88	—	—	—	—	—	—
2022	23	AA	New Hampshire Fisher Cats	—	190	166	47	8	3	6	22	46	1	10	0	283	370	476	846	193	357	24	12	373	95	—	—	—	—	—	—
2022	23	A+	Vancouver Canadians	—	189	157	36	10	1	8	29	50	2	6	1	229	356	459	815	229	280	26	15	361	63	—	—	—	—	—	—
2023	24	MLB	Toronto Blue Jays	—	141	116	32	12	1	8	21	43	4	1	0	276	404	603	1.008	328	369	30	15	434	180	+13	+0	+2	+2	+3	2.1
2023	24	AAA	Buffalo Bisons	—	392	309	85	21	1	21	72	86	6	9	3	275	421	553	975	278	309	22	18	421	117	—	—	—	—	—	—
2024	25	MLB	Toronto Blue Jays	—	454	397	76	19	1	13	47	144	5	6	0	191	285	343	628	151	257	32	10	283	77	-12	+1	-0	-5	+10	-0.6
2025	26	MLB	Toronto Blue Jays	—	227	188	44	5	0	11	36	60	2	3	1	234	363	436	799	202	280	26	16	358	128	+8	+0	-2	-4	+5	0.7
2025	26	AAA	Buffalo Bisons	—	160	133	30	6	2	4	24	46	2	3	1	226	352	391	743	165	310	29	15	336	64	—	—	—	—	—	—
2026	27	MLB	Toronto Blue Jays	—	156	124	18	6	0	5	29	51	1	1	0	145	312	315	626	169	188	33	19	291	83	-3	+0	+0	-4	+3	-0.3
2026	27	AAA	Buffalo Bisons	—	218	150	33	6	0	10	57	49	8	4	3	220	456	460	916	240	245	22	26	411	105	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	978	825	170	42	2	37	133	298	12	11	1	206	325	396	721	190	268	30	14	323	105	+6	+2	+1	-11	+21	1.9
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2017	18	ROK MLE	GCL Blue Jays	—	210	182	32	9	1	3	22	52	2	3	1	176	272	286	558	110	208	25	10	250	55	—	—	—	—	—	—
2018	19	ROK MLE	Bluefield Blue Jays	—	161	141	22	5	1	2	14	67	3	4	4	156	247	248	495	92	252	42	9	222	36	—	—	—	—	—	—
2021	22	A+ MLE	Vancouver Canadians	—	179	153	26	5	1	7	20	80	2	0	1	170	274	353	627	183	264	45	11	277	74	—	—	—	—	—	—
2022	23	AAA MLE	Buffalo Bisons	—	75	64	14	4	0	2	10	24	1	1	1	219	333	375	708	156	304	32	13	298	88	—	—	—	—	—	—
2022	23	AA MLE	New Hampshire Fisher Cats	—	190	171	42	6	3	5	17	55	1	10	0	246	317	404	721	158	327	29	9	309	95	—	—	—	—	—	—
2022	23	A+ MLE	Vancouver Canadians	—	189	166	28	6	1	7	20	67	2	6	1	169	266	343	609	175	223	35	11	262	63	—	—	—	—	—	—
2023	24	MLB MLE	Toronto Blue Jays	—	141	116	32	12	1	8	21	43	4	1	0	276	404	603	1.008	328	369	30	15	434	180	+13	+0	+2	+2	+3	2.1
2023	24	AAA MLE	Buffalo Bisons	—	392	328	74	17	1	17	53	106	6	9	3	226	344	439	783	213	265	27	14	341	117	—	—	—	—	—	—
2024	25	MLB MLE	Toronto Blue Jays	—	454	397	76	19	1	13	47	144	5	6	0	191	285	343	628	151	257	32	10	283	77	-12	+1	-0	-5	+10	-0.6
2025	26	MLB MLE	Toronto Blue Jays	—	227	188	44	5	0	11	36	60	2	3	1	234	363	436	799	202	280	26	16	357	128	+8	+0	-2	-4	+5	0.7
2025	26	AAA MLE	Buffalo Bisons	—	160	140	25	4	2	3	17	56	2	3	1	179	277	300	577	121	264	35	11	263	64	—	—	—	—	—	—
2026	27	MLB MLE	Toronto Blue Jays	—	156	124	18	6	0	5	29	51	1	1	0	145	312	315	626	169	188	33	19	291	83	-3	+0	+0	-4	+3	-0.3
2026	27	AAA MLE	Buffalo Bisons	—	218	168	30	5	0	8	39	59	8	4	3	179	358	351	709	173	205	27	18	324	105	—	—	—	—	—	—
2017	18	ROK MLE	GCL Blue Jays	—	210	182	32	9	1	3	22	52	2	3	1	176	272	286	558	110	221	25	10	250	55	—	—	—	—	—	—
2017	18	ROK RAW	GCL Blue Jays	—	210	168	40	12	1	4	36	36	2	3	1	238	379	393	771	155	273	17	17	346	55	—	—	—	—	—	—
2018	19	ROK MLE	Bluefield Blue Jays	—	161	141	22	5	1	2	14	67	3	4	4	156	247	248	495	92	270	42	9	222	36	—	—	—	—	—	—
2018	19	ROK RAW	Bluefield Blue Jays	—	161	133	31	8	1	3	22	47	3	4	4	233	354	376	730	143	329	29	14	328	36	—	—	—	—	—	—
2021	22	A+ MLE	Vancouver Canadians	—	179	153	26	5	1	7	20	80	2	0	1	170	274	353	627	183	275	45	11	277	74	—	—	—	—	—	—
2021	22	A+ RAW	Vancouver Canadians	—	179	147	34	7	1	9	26	59	2	0	1	231	354	476	830	245	305	33	15	359	74	—	—	—	—	—	—
2022	23	AA MLE	3 teams	—	454	401	83	16	4	13	47	146	4	17	2	207	296	364	661	157	287	32	10	288	81	—	—	—	—	—	—
2022	23	AA RAW	3 teams	—	454	383	97	22	4	16	65	116	4	17	2	253	367	457	824	204	320	26	14	366	81	—	—	—	—	—	—
2023	24	AAA MLE	2 teams	—	533	444	106	29	2	25	74	149	10	10	3	239	360	482	842	243	295	28	14	366	134	—	—	—	—	—	—
2023	24	AAA RAW	2 teams	—	533	425	117	33	2	29	93	129	10	10	3	275	417	567	984	292	324	24	17	424	134	—	—	—	—	—	—
2024	25	MLB MLE	Toronto Blue Jays	—	454	397	76	19	1	13	47	144	5	6	0	191	285	343	628	151	257	32	10	283	77	-12	+1	-0	-5	+10	-0.6
2024	25	MLB RAW	Toronto Blue Jays	—	454	397	76	19	1	13	47	144	5	6	0	191	285	343	628	151	257	32	10	283	77	-12	+1	-0	-5	+10	-0.6
2025	26	MLB MLE	2 teams	—	387	328	69	9	2	14	53	116	4	6	2	210	327	378	705	168	275	30	14	318	102	+1	+0	-2	-4	+8	0.4
2025	26	MLB RAW	2 teams	—	387	321	74	11	2	15	60	106	4	6	2	231	358	417	776	187	292	27	16	349	102	+1	+0	-2	-4	+8	0.4
2026	27	AAA MLE	2 teams	—	374	292	48	11	0	13	68	110	9	5	3	164	339	336	674	171	202	29	18	310	96	—	—	—	—	—	—
2026	27	AAA RAW	2 teams	—	374	274	51	12	0	15	86	100	9	5	3	186	396	394	790	208	221	27	23	361	96	—	—	—	—	—	—
2017	18	ROK MLE	GCL Blue Jays	—	210	184	32	9	1	3	22	52	2	3	1	174	272	283	554	109	208	25	10	250	55	—	—	—	—	—	—
2018	19	ROK MLE	Bluefield Blue Jays	—	161	143	22	5	1	2	14	67	3	4	4	154	247	245	492	91	252	42	9	222	36	—	—	—	—	—	—
2021	22	A+ MLE	Vancouver Canadians	—	179	155	26	5	1	7	20	80	2	0	1	168	274	348	623	181	264	45	11	277	74	—	—	—	—	—	—
2022	23	AA MLE	3 teams	—	454	400	83	16	4	13	47	146	4	17	2	207	296	365	661	158	280	32	10	288	81	—	—	—	—	—	—
2023	24	AAA MLE	2 teams	—	533	444	106	29	2	25	74	149	10	10	3	239	360	482	842	243	293	28	14	366	134	—	—	—	—	—	—
2024	25	MLB MLE	Toronto Blue Jays	—	454	399	76	19	1	13	47	144	5	6	0	190	285	341	626	150	257	32	10	283	77	—	—	—	—	—	—
2025	26	MLB MLE	2 teams	—	387	327	69	9	2	14	53	116	4	6	2	211	327	379	706	168	273	30	14	318	102	—	—	—	—	—	—
2026	27	AAA MLE	2 teams	—	374	294	48	11	0	13	68	110	9	5	3	163	339	333	672	170	198	29	18	310	96	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	25	MLB MLE	Toronto Blue Jays	—	454	399	76	19	1	13	47	144	5	6	0	190	285	341	626	150	257	32	10	283	77	—	—	—	—	—	—
2025	26	MLB MLE	2 teams	—	387	327	69	9	2	14	53	116	4	6	2	211	327	379	706	168	273	30	14	318	102	—	—	—	—	—	—
2026	27	AAA MLE	2 teams	—	374	294	48	11	0	13	68	110	9	5	3	163	339	333	672	170	198	29	18	310	96	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	28	MLB MLE	TOR	45%	412	343	68	13	1	15	60	122	6	6	2	200	330	378	708	178	255	30	15	321	103	+2	+0	+2	-4	+9	0.6
▸ 2027 — real world (MLB)
2027	28	MLB CTX	TOR	45%	107	88	17	3	0	4	16	32	2	2	0	200	330	379	709	178	256	30	15	321	103	+0	+0	+1	-1	+2	0.3
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	29	MLB MLE	TOR	53%	303	251	50	10	1	11	44	90	5	3	1	197	327	371	697	174	253	30	15	317	100	+0	+0	+0	-3	+7	0.4
2029	30	MLB MLE	TOR	58%	297	248	48	9	1	10	43	90	4	2	1	193	322	361	683	168	249	30	14	311	97	-1	+0	-1	-3	+6	0.1
2028	29	MLB CTX	TOR	53%	161	135	26	5	0	6	23	48	2	2	1	197	327	371	698	174	254	30	14	317	100	+0	+0	+0	-2	+3	0.2
2029	30	MLB CTX	TOR	58%	172	142	27	5	0	6	25	52	3	1	0	193	323	361	684	168	250	30	15	312	97	-1	+0	-0	-2	+4	0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1311	1102	223	52	2	49	181	398	17	14	2	202	324	387	710	184	262	30	14	321	93	+5	+2	+0	-15	+28	2.2
/ 162G	—	A+C		—	650	546	110	26	1	24	90	197	8	7	1	201	322	385	707	183	261	30	14	321	93	+3	+1	+0	-7	+14	1.1
Career	—	MLE		—	3590	3034	600	130	15	120	467	1114	52	59	19	198	315	369	684	171	262	31	13	305	93	+6	+2	+1	-20	+39	2.9
/ 162G	—	MLE		—	650	549	110	24	3	22	85	202	9	11	3	200	317	375	692	175	266	31	13	305	93	+2	+1	+0	-7	+14	1.0

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 AAABuffalo Bisons · 218 PAwOBA .407 → .324 (−84)K% 22.5% → 27.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.48%	÷1.000	×1.200	—	—	26.97%
BB% (unintentional) /PA	26.15%	÷1.000	×0.690	—	×1.003	18.10%
HBP% /PA	3.67%	—	×0.940	—	×1.003	3.46%
Singles /BIP	16.83%	÷1.000	×0.930	×0.950	×1.003	14.92%
Doubles /BIP	5.94%	÷1.000	×0.830	×0.950	×1.003	4.70%
Triples /BIP	0.00%	÷1.000	×0.970	×0.950	×1.003	0.00%
Home runs /BIP	9.90%	÷1.000	×0.700	—	×1.003	6.95%

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 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 .407 → .324; ISO .240 → .191; BABIP .245 → .205. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2025 AAABuffalo Bisons · 160 PAwOBA .330 → .263 (−67)K% 28.7% → 34.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.75%	÷0.988	×1.200	—	—	34.92%
BB% (unintentional) /PA	15.00%	÷0.984	×0.690	—	×1.018	10.70%
HBP% /PA	1.25%	—	×0.940	—	×1.018	1.20%
Singles /BIP	20.69%	÷1.007	×0.930	×0.950	×1.018	18.48%
Doubles /BIP	6.90%	÷1.098	×0.830	×0.950	×1.018	5.04%
Triples /BIP	2.30%	÷0.986	×0.970	×0.950	×1.018	2.19%
Home runs /BIP	4.60%	÷0.847	×0.700	—	×1.018	3.87%

Factors used: league row International League. Park (home-season share, regressed): HR 69, 1B 101, 2B 120, 3B 97, K 98, BB 97 — 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 ×0.950.

Result: wOBA .330 → .263; ISO .165 → .135; BABIP .310 → .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).

2023 AAABuffalo Bisons · 392 PAwOBA .415 → .341 (−74)K% 21.9% → 27.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.94%	÷0.973	×1.200	—	—	27.06%
BB% (unintentional) /PA	18.37%	÷0.984	×0.690	—	×1.048	13.50%
HBP% /PA	1.53%	—	×0.940	—	×1.048	1.51%
Singles /BIP	18.83%	÷1.018	×0.930	×0.950	×1.048	17.13%
Doubles /BIP	9.42%	÷1.033	×0.830	×0.950	×1.048	7.54%
Triples /BIP	0.45%	÷1.150	×0.970	×0.950	×1.048	0.38%
Home runs /BIP	9.42%	÷0.916	×0.700	—	×1.048	7.54%

Factors used: league row International League. Park (home-season share, regressed): HR 83, 1B 104, 2B 107, 3B 130, K 95, BB 97 — 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 .415 → .341; ISO .278 → .227; BABIP .309 → .265. 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 AANew Hampshire Fisher Cats · 190 PAwOBA .365 → .309 (−56)K% 24.2% → 29.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.21%	÷1.012	×1.220	—	—	29.18%
BB% (unintentional) /PA	11.58%	÷0.911	×0.700	—	×1.027	9.14%
HBP% /PA	0.53%	—	×0.850	—	×1.027	0.46%
Singles /BIP	25.00%	÷0.991	×0.970	×0.950	×1.027	23.88%
Doubles /BIP	6.67%	÷1.067	×0.860	×0.950	×1.027	5.24%
Triples /BIP	2.50%	÷0.900	×0.950	×0.950	×1.027	2.57%
Home runs /BIP	5.00%	÷1.027	×0.780	—	×1.027	3.90%

Factors used: league row EL. Park (home-season share, regressed): HR 105, 1B 98, 2B 113, 3B 80, K 102, BB 82 — 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 .365 → .309; ISO .193 → .155; BABIP .357 → .327. 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 A+Vancouver Canadians · 189 PAwOBA .354 → .262 (−92)K% 26.5% → 35.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.46%	÷1.003	×1.350	—	—	35.60%
BB% (unintentional) /PA	15.34%	÷1.037	×0.710	—	×0.998	10.49%
HBP% /PA	1.06%	—	×0.810	—	×0.998	0.86%
Singles /BIP	15.89%	÷0.950	×0.910	×0.950	×0.998	14.42%
Doubles /BIP	9.35%	÷1.254	×0.830	×0.950	×0.998	5.86%
Triples /BIP	0.93%	÷0.900	×0.820	×0.950	×0.998	0.81%
Home runs /BIP	7.48%	÷0.952	×0.830	—	×0.998	6.51%

Factors used: level-wide A+ factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 90, 1B 90, 2B 151, 3B 80, K 101, BB 107 — 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 ×0.950.

Result: wOBA .354 → .262; ISO .229 → .172; BABIP .280 → .223. 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 · 75 PAwOBA .352 → .298 (−54)K% 26.7% → 31.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.67%	÷1.018	×1.200	—	—	31.44%
BB% (unintentional) /PA	18.67%	÷1.032	×0.690	—	×1.050	13.10%
HBP% /PA	1.33%	—	×0.940	—	×1.050	1.32%
Singles /BIP	20.00%	÷0.960	×0.930	—	×1.050	20.34%
Doubles /BIP	10.00%	÷0.984	×0.830	—	×1.050	8.86%
Triples /BIP	0.00%	÷1.149	×0.970	—	×1.050	0.00%
Home runs /BIP	5.00%	÷0.951	×0.700	—	×1.050	3.86%

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 23 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (4.2 yr younger than average).

Result: wOBA .352 → .298; ISO .167 → .138; BABIP .316 → .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).

2021 A+Vancouver Canadians · 179 PAwOBA .356 → .277 (−79)K% 33.0% → 44.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	32.96%	÷0.991	×1.350	—	—	44.90%
BB% (unintentional) /PA	14.53%	÷0.944	×0.710	—	×1.012	11.06%
HBP% /PA	1.12%	—	×0.810	—	×1.012	0.92%
Singles /BIP	19.32%	÷0.974	×0.910	×0.950	×1.012	17.35%
Doubles /BIP	7.95%	÷0.938	×0.830	×0.950	×1.012	6.77%
Triples /BIP	1.14%	÷1.049	×0.820	×0.950	×1.012	0.85%
Home runs /BIP	10.23%	÷0.909	×0.830	—	×1.012	9.45%

Factors used: level-wide A+ factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 82, 1B 95, 2B 88, 3B 110, K 98, BB 89 — applied at half strength. Age: age 22 vs a level average of 22.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .356 → .277; ISO .245 → .193; BABIP .305 → .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 ROKBluefield Blue Jays · 161 PAwOBA .322 → .222 (−100)K% 29.2% → 41.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	29.19%	÷1.000	×1.420	—	—	41.45%
BB% (unintentional) /PA	13.04%	÷1.000	×0.640	—	×1.008	8.41%
HBP% /PA	1.86%	—	×0.740	—	×1.008	1.39%
Singles /BIP	22.09%	÷1.000	×0.840	×0.950	×1.008	17.76%
Doubles /BIP	9.30%	÷1.000	×0.740	×0.950	×1.008	6.59%
Triples /BIP	1.16%	÷1.000	×0.740	×0.950	×1.008	0.82%
Home runs /BIP	3.49%	÷1.000	×0.800	—	×1.008	2.81%

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 19 vs a level average of 19.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .322 → .222; ISO .143 → .098; BABIP .329 → .252. 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
#1Joe Lahoud'68-'78 * career totals — 10 seasons, 2,261 PA	3.4	2,261	65	20	227*	339*	418*	-30	-1	5.3	6.0
/162	664	19	6	-8.7	-0.3	1.6	pk7: 7
#2Gabe Grosslast yr '10 career totals — 7 seasons, 1,682 PA	2.5	1,682	40	22	239	330	385	-14	+11	5.1	5.1
/162	664	16	9	-5.7	+4.4	2.0	pk7: 5
#3Daniel Vogelbachlast yr '24 career totals — 7 seasons, 1,913 PA	2.9	1,913	81	0	220	342	411	-29	-16	4.4	4.4
/162	664	28	0	-10.2	-5.6	1.5	pk7: 4
#4Ted Savage'62-'71 * career totals — 8 seasons, 1,613 PA	2.4	1,613	34	49	233*	335*	390*	-13	+0	3.4	3.8
/162	664	14	20	-5.5	+0.1	1.4	pk7: 4
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	2.1	1,417	53	15	204	322	390	-15	-0	3.0	3.0
/162	664	25	7	-7.1	-0.2	1.4	pk7: 3
#5Dan Johnson'05-'15 * career totals — 5 seasons, 1,625 PA	2.4	1,625	57	1	226*	330*	401*	-30	-3	2.2	2.8
/162	664	23	0	-12.2	-1.2	0.9	pk7: 3
#6Norm Miller'65-'74 * career totals — 6 seasons, 1,561 PA	2.4	1,561	24	16	238*	325*	391*	-14	-3	2.4	2.7
/162	664	10	7	-6.1	-1.3	1.0	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
Davis Schneider (OGILVIE)	28	35	60	50	60	198/327/374	176	255	9	3	30%	15%	103	+0.6	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Jabari Blash 2017 · MLB	28	39→41	55→60	46→50	46	207/302/394	187	288	24	7	35%	10%	97	+1.1	215/316/411	196	319	25	8	37%	11%	106	+1.8	205/313/411	206	301	27	7	38%	12%	102	+1.1
✕Drew Ellis 2024 · MLB	28	36→38	51→55	46→40	50	195/285/358	163	247	18	6	29%	10%	82	+0.0	197/281/341	144	252	18	6	28%	9%	77	-0.3	166/258/293	127	202	19	3	28%	10%	55	-0.6
✕Kyle Lewis 2023 · MLB	28	42→48	54→55	49→40	50	225/307/394	170	280	24	7	29%	10%	99	+1.2	251/317/419	168	321	22	5	27%	8%	107	+1.9	273/336/441	168	351	22	0	27%	8%	116	+1.5
✕David Villar 2024 · MLB	27	42→44	56→60	46→40	47	223/308/415	192	286	25	5	30%	9%	104	+1.6	219/296/353	134	293	15	5	29%	9%	84	+0.2	211/289/324	113	284	13	2	29%	9%	74	-0.4
✕David Bote 2021 · MLB	28	46→50	54→50	48→45	50	236/321/414	178	295	22	9	27%	10%	108	+1.9	217/291/360	143	276	16	7	26%	8%	84	+0.2	218/284/358	140	283	14	8	27%	7%	80	-0.1
✕DJ Stewart 2022 · MLB	28	42→49	54→60	42→50	56	219/324/399	180	269	22	4	27%	12%	106	+1.8	220/322/398	178	276	23	6	28%	11%	105	+1.7	205/316/378	174	254	24	6	28%	11%	98	+0.6
✕Clint Frazier 2022 · MLB	27	45→49	51→55	48→50	53	227/321/393	167	293	19	7	28%	11%	103	+1.6	196/285/311	115	294	12	11	34%	10%	72	-0.7	174/262/271	97	269	10	12	36%	9%	52	-1.2
✕Casper Wells 2013 · MLB	28	45→44	55→60	48→50	47	232/306/425	193	286	21	8	27%	8%	105	+1.7	205/273/323	118	285	12	7	30%	8%	69	-0.9	126/186/148	22	188	0	0	30%	7%	-4	-1.1
✕Sean Bouchard 2024 · MLB	28	46→48	54→55	53→50	51	236/322/422	187	304	21	14	28%	11%	110	+2.1	212/300/358	146	304	15	15	32%	10%	87	+0.4	191/284/326	134	282	13	15	34%	10%	72	-0.4
✕Shelley Duncan 2009 · MLB	29	40→44	57→60	46→45	48	223/291/416	194	255	26	7	25%	8%	97	+1.1	226/296/414	188	261	24	4	24%	8%	99	+1.2	223/294/408	186	254	24	2	23%	8%	96	+0.8
✕David Cook 2009 · AAA	28	45→49	52→55	48→50	51	230/310/399	169	288	19	11	26%	10%	100	+1.3	219/290/372	153	276	17	9	26%	8%	87	+0.4	204/275/346	143	260	16	8	27%	8%	73	-0.5
✕Joe Mather 2010 · MLB	28	40→44	54→60	50	46	216/281/394	178	236	22	12	21%	6%	89	+0.5	216/267/334	118	270	11	10	24%	6%	69	-0.9	205/255/310	105	257	10	8	24%	6%	59	-0.7
✕Yoshi Tsutsugo 2021 · MLB	29	43→41	56→50	48→30	55	228/324/420	192	275	24	5	26%	12%	110	+2.1	219/305/372	153	279	19	3	27%	11%	93	+0.8	209/299/349	140	271	17	1	28%	11%	85	+0.1
✕Aristides Aquino 2022 · MLB	28	40→41	62→65	48→50	47	224/304/447	222	276	31	9	31%	9%	109	+2.0	216/283/388	172	314	21	8	36%	8%	88	+0.5	198/256/367	169	293	22	6	39%	6%	73	-0.4
✕Jerry Sands 2016 · MLB	28	44→46	50→60	42→45	49	228/300/385	156	278	18	3	25%	9%	93	+0.8	232/293/378	146	289	16	4	24%	8%	88	+0.5	226/286/373	147	283	16	3	25%	7%	82	+0.0
✕Jake Fraley 2023 · MLB	28	47	53→55	51→55	55	241/338/410	168	298	22	15	26%	12%	113	+2.3	253/327/404	151	299	17	23	20%	9%	107	+1.9	254/325/394	139	298	15	27	19%	9%	104	+0.9
✕Mike Wilson 2011 · AAA	28	40→50	54→55	50	45	215/291/387	173	274	23	12	30%	8%	91	+0.7	229/296/384	155	306	19	8	30%	8%	92	+0.7	227/293/374	147	307	17	4	30%	7%	85	+0.1
✕Wyatt Mathisen 2022 · MLB	28	38→48	50	47→40	46	198/297/349	151	264	18	4	31%	9%	86	+0.3	199/279/334	135	289	15	7	34%	8%	75	-0.5	127/211/245	118	190	15	0	41%	8%	31	-0.8
✕Kody Clemens 2024 · MLB	28	39→43	53→60	50→45	45	211/271/385	174	257	21	9	27%	7%	82	+0.0	224/280/416	192	262	24	9	24%	6%	93	+0.8	225/282/430	205	254	26	9	23%	6%	97	+0.9
●David Ross 2005 · MLB	28	41	54→60	48→45	45	218/296/396	178	281	23	4	31%	8%	95	+1.0	223/291/417	194	265	25	3	26%	8%	98	+1.2	269/361/462	194	343	20	0	25%	12%	134	+1.0

Davis Schneider

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps