David Hensley

RF Jaguares de Nayarit

Age 31 R/R 6'6" / 219 lbs INTL HR -8% Svc 5.000 · Ctrl thru 2027

Overview

INTLArb-3FA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2023	27	AAAHOU	293	.220/.368/.356	6	9	76	—	.205/.306/.319
2023	27	MLBHOU	94	.119/.213/.167	1	1	12	-0.7
2024	28	AAA/INTL2 orgs	434	.243/.367/.376	7	20	80	—	.199/.282/.308
2024	28	MLBMIA	58	.212/.293/.288	1	1	73	-0.8
2025	29	AAA/INTL2 orgs	147	.185/.299/.282	1	1	54	—	.080/.193/.160
2026	30	No MLB games played
2027PROJMLE	31	MLBDET	200	.229/.315/.357	4	5	92	0.1
2028PROJ22% MLB	32	MLBDET	24	.220/.306/.338	0	0	87	-0.1

Last 3 seasons WAR -1.4 · Next 2 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service5.000First FA2028

2027Arb-3$0.6M

Skills · percentileStatcast 2022-2024

Speed52

Avg EV43

Bat Spd43

Barrel%15

xwOBA10

CompsGarrett Stubbs (age 31) · Andy Burns (age 31) · John Andreoli (age 31)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 124 proj PA

wRC+†92

AVG/OBP/SLG.227 / .313 / .354

PA124

HR3

K%29

BB%10

ISO128

MLB%0%

Value2027 · WAR

trajectory · projected WAR by year

Tools · ContractPOW 40

Toolsscout grade · Statcast %ile · 2022-2024

CONTACT—

xAVG

100.182

POWER40

Barrel%

153.8

Avg EV

4388.6

Bat Spd

4370.6

EYE72

scouting grade only

SPEED56

Sprint

5227.6

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

Status Arb-3

MLB Debut 2022

Service 5.000 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-3	$0.6M	—	—	—
Totals		$0.0M		$0.0M	+$0.0M

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)
2018	22	A	Quad Cities River Bandits	—	268	234	49	11	2	4	31	79	0	2	6	209	302	325	627	115	294	29	12	285	37	—	—	—	—	—	—
2019	23	A+	Fayetteville Woodpeckers	—	111	98	32	11	0	0	11	23	0	0	2	327	394	439	833	112	416	21	10	368	69	—	—	—	—	—	—
2019	23	A	Quad Cities River Bandits	—	318	290	69	11	3	6	25	72	0	11	4	238	298	359	657	121	293	23	8	293	34	—	—	—	—	—	—
2021	25	AA	Corpus Christi Hooks	—	445	396	116	25	3	9	46	104	2	11	3	293	369	439	809	146	377	23	10	361	88	—	—	—	—	—	—
2021	25	INTL	Cangrejeros de Santurce	—	65	58	20	2	0	0	6	15	1	1	0	345	415	379	795	34	465	23	9	366	134	—	—	—	—	—	—
2022	26	MLB	Houston Astros	—	34	29	10	2	1	1	5	6	0	0	0	345	441	586	1.027	241	409	18	15	447	186	+3	+0	-1	+5	+1	0.9
2022	26	AAA	Sugar Land Space Cowboys	—	464	379	113	30	4	10	80	103	2	20	7	298	423	478	901	179	383	22	17	400	124	—	—	—	—	—	—
2023	27	MLB	Houston Astros	—	94	84	10	1	0	1	10	35	0	1	0	119	213	167	379	48	188	37	11	187	12	-10	+0	-0	+1	+2	-0.7
2023	27	AAA	Sugar Land Space Cowboys	—	293	236	52	10	2	6	54	82	1	9	3	220	368	356	724	136	307	28	18	334	76	—	—	—	—	—	—
2024	28	MLB	Miami Marlins	—	58	52	11	1	0	1	6	17	0	1	0	212	293	288	582	77	294	29	10	271	73	-2	+0	-2	-5	+1	-0.8
2024	28	AAA	Sugar Land Space Cowboys	—	358	303	71	20	1	7	54	89	1	17	2	234	352	376	728	142	309	25	15	333	68	—	—	—	—	—	—
2024	28	INTL	Tigres del Licey	—	76	59	17	5	0	0	16	22	0	3	1	288	440	373	813	85	447	29	21	374	139	—	—	—	—	—	—
2025	29	AAA	Toledo Mud Hens	—	58	47	4	1	0	1	9	26	1	0	0	85	246	170	416	85	150	45	16	210	-5	—	—	—	—	—	—
2025	29	INTL	Jaguares de Nayarit	—	89	77	19	4	2	0	10	24	0	1	2	247	333	351	684	104	345	27	11	305	92	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	186	165	31	4	1	3	21	58	0	2	0	188	280	279	558	91	269	31	11	261	62	-8	+0	-3	+1	+4	-0.6
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2018	22	A MLE	Quad Cities River Bandits	—	268	243	42	8	2	3	22	110	0	2	6	173	242	259	501	86	288	41	8	223	37	—	—	—	—	—	—
2019	23	A+ MLE	Fayetteville Woodpeckers	—	111	102	25	8	0	0	7	33	0	0	2	245	294	324	617	78	341	30	6	270	69	—	—	—	—	—	—
2019	23	A MLE	Quad Cities River Bandits	—	318	299	55	7	2	5	16	97	0	11	4	184	225	271	496	87	246	31	5	218	34	—	—	—	—	—	—
2021	25	AA MLE	Corpus Christi Hooks	—	445	411	105	22	2	6	31	132	2	11	3	255	311	363	673	107	360	30	7	298	88	—	—	—	—	—	—
2022	26	MLB MLE	Houston Astros	—	34	29	10	2	1	1	5	6	0	0	0	345	441	586	1.027	241	409	18	15	443	186	+3	+0	-1	+5	+1	0.9
2022	26	AAA MLE	Sugar Land Space Cowboys	—	464	400	111	28	5	8	59	125	2	20	7	278	373	432	806	155	377	27	13	351	124	—	—	—	—	—	—
2023	27	MLB MLE	Houston Astros	—	94	84	10	1	0	1	10	35	0	1	0	119	213	167	379	48	188	37	11	187	12	-10	+0	-0	+1	+2	-0.7
2023	27	AAA MLE	Sugar Land Space Cowboys	—	293	254	52	10	2	5	36	98	1	9	3	205	306	319	625	114	303	33	12	280	76	—	—	—	—	—	—
2024	28	MLB MLE	Miami Marlins	—	58	52	11	1	0	1	6	17	0	1	0	212	293	288	582	77	294	29	10	277	73	-2	+0	-2	-5	+1	-0.8
2024	28	AAA MLE	Sugar Land Space Cowboys	—	358	321	64	18	1	5	36	106	1	17	2	199	282	308	591	109	285	30	10	269	68	—	—	—	—	—	—
2025	29	AAA MLE	Toledo Mud Hens	—	58	50	4	1	0	1	6	29	1	0	0	80	193	160	353	80	133	50	10	161	-5	—	—	—	—	—	—
2018	22	A MLE	Quad Cities River Bandits	—	268	243	42	8	2	3	22	110	0	2	6	173	242	259	501	86	295	41	8	223	37	—	—	—	—	—	—
2018	22	A RAW	Quad Cities River Bandits	—	268	234	49	11	2	4	31	79	0	2	6	209	302	325	627	115	294	29	12	285	37	—	—	—	—	—	—
2019	23	A MLE	2 teams	—	429	401	80	15	2	5	23	130	0	11	6	200	243	284	527	85	277	30	5	231	43	—	—	—	—	—	—
2019	23	A RAW	2 teams	—	429	388	101	22	3	6	36	95	0	11	6	260	323	379	702	119	325	22	8	312	43	—	—	—	—	—	—
2021	25	AA MLE	2 teams	—	510	471	120	25	3	7	35	151	3	12	3	255	310	365	676	110	360	30	7	298	88	—	—	—	—	—	—
2021	25	AA RAW	2 teams	—	510	454	136	27	3	9	52	119	3	12	3	300	375	432	807	132	388	23	10	362	88	—	—	—	—	—	—
2022	26	AAA MLE	2 teams	—	498	429	121	30	6	9	64	131	2	20	7	282	378	443	821	161	384	26	13	357	128	—	—	—	—	—	—
2022	26	AAA RAW	2 teams	—	498	408	123	32	5	11	85	109	2	20	7	301	424	485	910	184	385	22	17	403	128	—	—	—	—	—	—
2023	27	AAA MLE	2 teams	—	387	338	62	11	2	6	46	133	1	10	3	183	283	281	564	98	279	34	12	257	60	—	—	—	—	—	—
2023	27	AAA RAW	2 teams	—	387	320	62	11	2	7	64	117	1	10	3	194	330	306	636	113	278	30	17	298	60	—	—	—	—	—	—
2024	28	AAA MLE	3 teams	—	492	440	91	23	1	8	50	146	1	21	3	207	289	318	607	111	289	30	10	270	69	—	—	—	—	—	—
2024	28	AAA RAW	3 teams	—	492	414	99	26	1	8	76	128	1	21	3	239	358	365	723	126	326	26	15	332	69	—	—	—	—	—	—
2025	29	INTL MLE	2 teams	—	147	127	9	2	0	2	16	74	1	1	2	71	181	134	314	63	132	50	11	161	-5	—	—	—	—	—	—
2025	29	INTL RAW	2 teams	—	147	124	23	5	2	1	19	50	1	1	2	185	299	282	581	97	293	34	13	267	-5	—	—	—	—	—	—
2018	22	A MLE	Quad Cities River Bandits	—	268	244	42	8	2	3	22	110	0	2	6	172	242	258	500	86	288	41	8	223	37	—	—	—	—	—	—
2019	23	A MLE	2 teams	—	429	403	80	15	2	5	23	130	0	11	6	199	243	283	526	84	271	30	5	231	43	—	—	—	—	—	—
2021	25	AA MLE	2 teams	—	510	467	120	25	3	7	35	151	3	12	3	257	310	368	679	111	360	30	7	298	88	—	—	—	—	—	—
2022	26	AAA MLE	2 teams	—	498	429	121	30	6	9	64	131	2	20	7	282	378	443	821	161	379	26	13	357	128	—	—	—	—	—	—
2023	27	AAA MLE	2 teams	—	387	337	62	11	2	6	46	133	1	10	3	184	283	282	565	98	275	34	12	257	60	—	—	—	—	—	—
2024	28	AAA MLE	3 teams	—	492	438	91	23	1	8	50	146	1	21	3	208	289	320	609	112	286	30	10	270	69	—	—	—	—	—	—
2025	29	INTL MLE	2 teams	—	147	129	9	2	0	2	16	74	1	1	2	70	181	132	312	62	133	50	11	161	-5	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	28	AAA MLE	3 teams	—	492	438	91	23	1	8	50	146	1	21	3	208	289	320	609	112	286	30	10	270	69	—	—	—	—	—	—
2025	29	INTL MLE	2 teams	—	147	129	9	2	0	2	16	74	1	1	2	70	181	132	312	62	133	50	11	161	-5	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	31	MLB MLE	DET	0%	200	176	41	9	1	4	21	59	1	5	1	229	315	357	672	128	316	30	10	304	92	-2	+1	-1	-2	+4	0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	32	MLB MLE	DET	22%	112	99	22	5	0	2	11	33	1	2	1	224	309	346	656	122	310	29	10	297	87	-2	+0	-4	-1	+2	-0.4
2028	32	MLB CTX	DET	22%	24	22	4	1	0	0	2	7	0	0	0	220	306	338	644	118	305	29	8	292	87	-0	+0	-1	-0	+1	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	210	187	35	5	1	3	23	65	0	2	0	187	276	273	549	86	269	31	11	264	72	-9	+0	-4	+1	+5	-0.7
/ 162G	—	A+C		—	650	579	107	15	3	9	71	201	0	6	0	185	274	268	542	83	266	31	11	264	72	-27	+1	-13	+4	+14	-2.1
Career	—	MLE		—	2967	2657	572	124	16	45	280	945	10	82	32	215	293	325	617	110	313	32	9	275	72	-11	+1	-8	-1	+9	-1.0
/ 162G	—	MLE		—	650	582	126	27	4	10	61	207	2	18	7	216	293	328	621	112	314	32	9	275	72	-17	+1	-12	-2	+14	-1.6

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.

2025 AAAToledo Mud Hens · 58 PAwOBA .206 → .161 (−45)K% 44.8% → 50.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	44.83%	÷1.073	×1.200	—	—	50.14%
BB% (unintentional) /PA	15.52%	÷0.988	×0.690	—	×0.982	10.64%
HBP% /PA	1.72%	—	×0.940	—	×0.982	1.59%
Singles /BIP	9.52%	÷0.993	×0.930	—	×0.982	8.76%
Doubles /BIP	4.76%	÷0.953	×0.830	—	×0.982	4.07%
Triples /BIP	0.00%	÷0.905	×0.970	—	×0.982	0.00%
Home runs /BIP	4.76%	÷0.872	×0.700	—	×0.982	3.75%

Factors used: league row International League. Park (home-season share, regressed): HR 74, 1B 99, 2B 91, 3B 81, K 115, BB 98 — applied at half strength. Age: age 29 vs a level average of 27.2 → −1.8% on BB/HBP/hit rates (1.8 yr older than average).

Result: wOBA .206 → .161; ISO .085 → .071; BABIP .150 → .133. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2024 AAASugar Land Space Cowboys · 358 PAwOBA .325 → .269 (−56)K% 24.9% → 29.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.86%	÷1.006	×1.200	—	—	29.67%
BB% (unintentional) /PA	15.08%	÷1.022	×0.690	—	×0.992	10.11%
HBP% /PA	0.28%	—	×0.940	—	×0.992	0.26%
Singles /BIP	20.09%	÷1.035	×0.930	×1.050	×0.992	18.80%
Doubles /BIP	9.35%	÷0.953	×0.830	×1.050	×0.992	8.48%
Triples /BIP	0.47%	÷0.900	×0.970	×1.050	×0.992	0.52%
Home runs /BIP	3.27%	÷0.903	×0.700	—	×0.992	2.51%

Factors used: league row International League. Park (home-season share, regressed): HR 81, 1B 107, 2B 91, 3B 80, K 101, BB 104 — applied at half strength. Age: age 28 vs a level average of 27.2 → −0.8% on BB/HBP/hit rates (0.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .325 → .269; ISO .142 → .121; BABIP .309 → .285. 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 AAASugar Land Space Cowboys · 293 PAwOBA .328 → .280 (−48)K% 28.0% → 33.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.99%	÷1.000	×1.200	—	—	33.57%
BB% (unintentional) /PA	18.43%	÷1.028	×0.690	—	×1.003	12.41%
HBP% /PA	0.34%	—	×0.940	—	×1.003	0.32%
Singles /BIP	22.08%	÷0.981	×0.930	×1.050	×1.003	22.05%
Doubles /BIP	6.49%	÷0.882	×0.830	×1.050	×1.003	6.44%
Triples /BIP	1.30%	÷1.056	×0.970	×1.050	×1.003	1.26%
Home runs /BIP	3.90%	÷0.896	×0.700	—	×1.003	3.05%

Factors used: league row International League. Park (home-season share, regressed): HR 79, 1B 96, 2B 76, 3B 111, K 100, 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .328 → .280; ISO .136 → .121; BABIP .307 → .303. 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 · 464 PAwOBA .393 → .351 (−42)K% 22.2% → 27.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.20%	÷0.986	×1.200	—	—	27.01%
BB% (unintentional) /PA	17.24%	÷0.953	×0.690	—	×1.018	12.71%
HBP% /PA	0.43%	—	×0.940	—	×1.018	0.41%
Singles /BIP	25.00%	÷0.982	×0.930	×1.050	×1.018	25.30%
Doubles /BIP	10.87%	÷0.952	×0.830	×1.050	×1.018	10.13%
Triples /BIP	1.45%	÷0.900	×0.970	×1.050	×1.018	1.67%
Home runs /BIP	3.62%	÷0.917	×0.700	—	×1.018	2.82%

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 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 ×1.050.

Result: wOBA .393 → .351; ISO .179 → .161; BABIP .383 → .377. 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 AACorpus Christi Hooks · 445 PAwOBA .351 → .298 (−53)K% 23.4% → 29.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.37%	÷0.959	×1.220	—	—	29.74%
BB% (unintentional) /PA	9.89%	÷0.990	×0.690	—	×0.998	6.88%
HBP% /PA	0.45%	—	×0.850	—	×0.998	0.38%
Singles /BIP	27.05%	÷1.002	×0.940	×1.050	×0.998	26.60%
Doubles /BIP	8.56%	÷0.987	×0.870	×1.050	×0.998	7.91%
Triples /BIP	1.03%	÷1.150	×0.920	×1.050	×0.998	0.86%
Home runs /BIP	3.08%	÷1.074	×0.780	—	×0.998	2.23%

Factors used: level-wide AA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 115, 1B 100, 2B 97, 3B 130, K 92, BB 98 — applied at half strength. Age: age 25 vs a level average of 24.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .351 → .298; ISO .146 → .116; BABIP .377 → .360. 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 AQuad Cities River Bandits · 318 PAwOBA .287 → .218 (−69)K% 22.6% → 30.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.64%	÷1.006	×1.360	—	—	30.60%
BB% (unintentional) /PA	7.55%	÷1.010	×0.690	—	×0.990	5.10%
HBP% /PA	0.00%	—	×0.780	—	×0.990	0.00%
Singles /BIP	22.48%	÷0.979	×0.920	×0.950	×0.990	19.86%
Doubles /BIP	5.05%	÷1.128	×0.830	×0.950	×0.990	3.49%
Triples /BIP	1.38%	÷1.150	×0.910	×0.950	×0.990	1.02%
Home runs /BIP	2.75%	÷0.964	×0.800	—	×0.990	2.26%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 93, 1B 96, 2B 126, 3B 130, K 101, BB 102 — applied at half strength. Age: age 23 vs a level average of 22.0 → −1.0% on BB/HBP/hit rates (1.0 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .287 → .218; ISO .121 → .087; BABIP .293 → .246. 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+Fayetteville Woodpeckers · 111 PAwOBA .365 → .270 (−95)K% 20.7% → 29.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.72%	÷0.983	×1.420	—	—	29.92%
BB% (unintentional) /PA	9.91%	÷1.000	×0.630	—	×0.998	6.23%
HBP% /PA	0.00%	—	×0.860	—	×0.998	0.00%
Singles /BIP	28.00%	÷1.029	×0.940	×0.950	×0.998	24.24%
Doubles /BIP	14.67%	÷1.068	×0.830	×0.950	×0.998	10.81%
Triples /BIP	0.00%	÷1.150	×0.800	×0.950	×0.998	0.00%
Home runs /BIP	0.00%	÷0.969	×0.900	—	×0.998	0.00%

Factors used: league row CAR. Park (home-season share, regressed): HR 94, 1B 106, 2B 114, 3B 130, K 97, BB 100 — 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 .365 → .270; ISO .112 → .078; BABIP .416 → .341. 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 AQuad Cities River Bandits · 268 PAwOBA .280 → .223 (−56)K% 29.5% → 41.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	29.48%	÷0.976	×1.360	—	—	41.10%
BB% (unintentional) /PA	11.57%	÷0.968	×0.690	—	—	8.25%
HBP% /PA	0.00%	—	×0.780	—	—	0.00%
Singles /BIP	20.65%	÷0.939	×0.920	×1.050	—	21.23%
Doubles /BIP	7.10%	÷1.012	×0.830	×1.050	—	6.11%
Triples /BIP	1.29%	÷0.973	×0.910	×1.050	—	1.27%
Home runs /BIP	2.58%	÷0.973	×0.800	—	—	2.12%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 95, 1B 88, 2B 102, 3B 95, K 95, BB 94 — applied at half strength. Age: age 22 vs a level average of 22.0 → +0.0% on BB/HBP/hit rates (0.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .280 → .223; ISO .115 → .087; BABIP .294 → .288. 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
#1Sam Fuld'07-'15 * career totals — 6 seasons, 1,535 PA	2.3	1,535	12	67	230*	314*	336*	-10	+29	3.7	4.0
/162	664	5	29	-4.3	+12.7	1.6	pk7: 4
#2Eric Young Jr.last yr '18 career totals — 9 seasons, 1,925 PA	2.9	1,925	13	161	245	312	332	-11	-8	1.2	1.6
/162	664	4	56	-3.9	-2.7	0.4	pk7: 2
#3Jake Cavelast yr '24 career totals — 7 seasons, 1,564 PA	2.4	1,564	45	13	236	292	400	-11	-6	1.3	1.3
/162	664	19	6	-4.5	-2.5	0.6	pk7: 1
#4James Mouton'94-'01 * career totals — 8 seasons, 1,795 PA	2.7	1,795	18	109	235*	314*	329*	-11	-0	0.7	1.0
/162	664	7	40	-4.2	-0.1	0.3	pk7: 1
#5Jimmy Stewart'63-'73 * career totals — 8 seasons, 1,602 PA	2.4	1,602	8	38	235*	309*	329*	-1	+2	-0.2	0.5
/162	664	3	16	-0.4	+0.7	-0.1	pk7: 1
#6Dave McCarty'93-'05 * career totals — 9 seasons, 1,647 PA	2.5	1,647	36	9	233*	295*	365*	-26	+16	-1.1	0.5
/162	664	15	4	-10.5	+6.6	-0.4	pk7: 2
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 3 projected seasons	0.5	300	5	6	192	277	285	-3	-3	-0.8	-0.8
/162	664	11	12	-6.9	-7.1	-1.8	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
David Hensley (OGILVIE)	31	—	40	56	72	227/313/354	127	316	3	3	29%	10%	92	+0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Garrett Stubbs 2024 · MLB	31	47	45	54→50	51	229/307/352	123	286	12	11	24%	9%	88	+0.4	218/290/318	100	282	10	12	25%	8%	74	-0.5	204/276/286	82	265	9	12	25%	7%	61	-0.5
✕Andy Burns 2022 · MLB	31	43→53	47→50	51→55	51	217/297/356	140	273	15	15	25%	10%	86	+0.3	203/274/313	110	283	11	12	30%	9%	68	-1.0	174/245/259	85	244	9	8	31%	8%	42	-1.6
✕John Andreoli 2021 · MLB	31	44→54	44→45	54→60	48	211/297/330	119	311	11	15	33%	10%	80	-0.2	178/273/307	129	305	15	17	42%	11%	66	-1.1	137/244/257	120	233	15	21	44%	12%	43	-1.4
✕Cole Gillespie 2015 · MLB	31	49→57	46→50	50	50	243/308/376	133	288	14	12	21%	8%	94	+0.9	239/293/338	99	290	7	12	19%	7%	78	-0.3	236/286/317	82	289	3	11	19%	6%	71	-0.4
✕Eric Campbell 2018 · MLB	31	48→56	43→45	49→50	52	234/318/344	110	287	10	12	21%	9%	91	+0.6	233/314/359	126	284	12	10	21%	9%	93	+0.8	228/314/352	124	275	12	9	21%	10%	90	+0.4
✕David Bote 2024 · MLB	31	43→50	47→50	49→45	44	215/285/352	137	279	14	9	27%	7%	80	-0.1	228/291/375	147	283	15	8	24%	7%	88	+0.4	231/286/393	162	270	16	0	20%	6%	88	+0.1
✕Chris Owings 2023 · MLB	31	38→48	45→50	50→55	44	196/263/321	125	267	13	12	31%	8%	65	-1.2	199/271/320	121	287	14	11	33%	8%	68	-1.0	187/264/301	114	271	13	11	34%	8%	58	-1.0
✕Chad Huffman 2016 · AAA	31	47→52	48→50	50→45	48	237/307/381	145	297	16	9	25%	8%	95	+1.0	224/301/380	156	272	16	8	23%	8%	93	+0.8	214/294/368	154	261	17	5	24%	8%	85	+0.1
✕Jayson Nix 2014 · MLB	31	46→51	43→55	53→55	45	223/290/333	109	294	10	18	27%	7%	78	-0.3	196/247/285	89	257	8	10	26%	6%	50	-2.3	163/204/230	67	212	6	4	26%	4%	19	-1.9
✕Matt Reynolds 2022 · AAA	31	47→57	42→45	47→50	47	223/295/332	109	311	9	9	30%	9%	79	-0.2	221/287/344	123	313	11	9	30%	8%	79	-0.2	213/281/347	134	298	13	9	31%	8%	76	-0.3
✕Hernán Pérez 2022 · MLB	31	47→57	48→50	52→55	43	238/285/377	138	300	16	15	26%	6%	86	+0.3	218/264/334	116	278	13	20	26%	5%	68	-1.0	201/245/310	110	254	13	20	26%	5%	54	-1.0
✕Steve Tolleson 2014 · MLB	30	48→53	42→45	49→50	49	231/298/334	103	289	9	15	22%	8%	80	-0.1	226/293/333	107	293	9	15	24%	8%	78	-0.3	232/293/334	102	299	8	18	24%	7%	77	-0.2
✕Jonathan Davis 2022 · MLB	30	40→50	44→45	52→55	48	198/301/313	115	267	11	19	28%	9%	79	-0.2	220/302/329	109	302	9	22	28%	9%	82	-0.0	216/296/320	104	303	8	22	29%	8%	75	-0.2
✕Mitch Maier 2013 · MLB	31	48→56	44→50	52→50	52	233/310/352	118	296	11	9	24%	10%	89	+0.5	228/298/350	122	308	13	9	28%	9%	84	+0.1	259/340/362	102	329	10	11	22%	11%	97	+0.3
✕Gorkys Hernández 2019 · MLB	31	50→60	46→45	47→55	46	247/302/376	129	302	13	14	23%	7%	91	+0.7	206/274/339	133	282	15	16	31%	8%	73	-0.6	172/247/289	117	244	13	19	34%	8%	51	-2.1
✕Tyler Saladino 2019 · MLB	30	45→47	43→45	51→55	46	222/286/329	107	283	11	16	25%	8%	75	-0.5	217/287/377	160	280	19	14	29%	8%	87	+0.4	194/268/371	176	242	23	14	30%	8%	76	-0.3
✕Jon Berti 2022 · MLB	32	50→60	45	53→60	56	241/337/365	124	305	12	22	23%	11%	103	+1.5	258/329/370	112	324	10	33	21%	9%	100	+1.3	268/335/372	103	335	9	39	21%	8%	103	+0.8
✕Ryan Roberts 2011 · MLB	30	47→52	45→50	52→55	51	230/299/358	127	277	12	16	21%	9%	86	+0.3	229/301/369	140	267	16	15	20%	9%	90	+0.6	227/300/361	134	261	16	13	19%	9%	88	+0.4
✕Pokey Reese 2004 · MLB	31	49→54	41→45	55	49	237/296/333	96	283	8	20	19%	7%	79	-0.2	227/282/330	103	281	10	14	22%	7%	73	-0.6	214/261/294	79	270	7	13	22%	6%	57	-0.8
✕Matt Szczur 2019 · MLB	30	48→58	44→45	46→55	54	231/314/353	122	284	10	8	22%	10%	91	+0.7	225/287/374	149	276	16	7	24%	8%	86	+0.3	194/244/348	154	230	19	0	25%	6%	63	-0.3

David Hensley

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps