Lonnie Chisenhall

Pos3B

B/TL/R

Born1988-10-04

Age (2027)38

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2019

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2017	28	AAA/AACLE	45	.279/.295/.395	1	1	60	—	.278/.297/.393
2017	28	MLBCleveland Ind…	270	.288/.364/.521	12	2	139	1.6
2018	29	MLBCleveland Ind…	95	.321/.394/.452	1	1	136	0.3
2019	30	AAAPIT	24	.208/.208/.250	0	0	-7	—	.167/.167/.208
2020	31	No MLB games played
2021	32	No MLB games played
2022	33	No MLB games played
2023	34	No MLB games played
2024	35	No MLB games played
2025	36	No MLB games played
2026	37	No MLB games played

Last 3 seasons WAR 1.9

Contract

No contract data on file.

Skills · percentileStatcast 2016-2018

xwOBA53

Speed30

Barrel%28

Avg EV10

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)
2009	20	AA	Akron Aeros	—	101	93	17	5	1	4	7	16	0	1	0	183	240	387	627	204	176	16	7	273	40	—	—	—	—	—	—
2009	20	A+	Kinston Indians	—	432	388	107	26	2	18	37	80	5	2	1	276	347	492	839	216	306	19	9	368	90	—	—	—	—	—	—
2010	21	AA	Akron Aeros	—	524	460	128	22	3	17	46	77	10	3	0	278	357	450	807	172	297	15	9	354	103	—	—	—	—	—	—
2011	22	MLB	Cleveland Indians	—	223	212	54	13	0	7	8	49	1	1	0	255	285	415	700	160	299	22	4	306	91	-3	+0	+3	+2	+5	0.7
2011	22	AAA	Columbus Clippers	—	292	255	68	15	3	7	28	47	7	0	1	267	355	431	787	165	300	16	10	350	80	—	—	—	—	—	—
2012	23	MLB	Cleveland Indians	—	151	142	38	6	1	5	8	27	1	2	1	268	311	430	741	162	300	18	5	328	109	+2	+0	-3	+1	+3	0.3
2012	23	AAA	Columbus Clippers	—	126	118	37	12	0	4	4	22	2	0	0	314	347	517	864	203	351	17	3	373	95	—	—	—	—	—	—
2013	24	MLB	Cleveland Indians	—	308	289	65	17	0	11	16	56	2	1	0	225	270	398	668	173	243	18	5	295	85	-6	+0	+3	+2	+7	0.6
2013	24	AAA	Columbus Clippers	—	125	105	41	8	2	6	12	24	4	2	0	390	471	676	1.147	286	443	19	10	479	178	—	—	—	—	—	—
2014	25	MLB	Cleveland Indians	—	533	478	134	29	1	13	39	99	8	3	1	280	344	427	771	146	328	19	7	340	113	+8	+0	-11	+2	+12	1.1
2015	26	MLB	Cleveland Indians	—	362	333	82	19	1	7	23	69	1	4	1	246	297	372	669	126	288	19	6	296	82	-8	+0	+7	+2	+8	1.0
2015	26	AAA	Columbus Clippers	—	171	157	44	13	0	3	11	35	1	1	0	280	331	420	752	140	342	20	6	331	61	—	—	—	—	—	—
2016	27	MLB	Cleveland Indians	—	418	385	110	25	5	8	23	70	3	6	0	286	331	439	770	153	328	17	6	335	112	+6	+1	-4	-5	+9	0.8
2016	27	AA	Akron RubberDucks	—	18	15	2	1	0	0	2	2	0	0	0	133	235	200	435	67	143	11	11	199	5	—	—	—	—	—	—
2017	28	MLB	Cleveland Indians	—	270	236	68	17	1	12	25	55	3	2	2	288	364	521	885	233	326	20	9	379	139	+13	-0	+1	-3	+6	1.6
2017	28	AAA	Columbus Clippers	—	28	27	10	2	0	1	0	6	0	1	0	370	370	556	926	185	429	21	0	392	116	—	—	—	—	—	—
2017	28	AA	Akron RubberDucks	—	17	16	2	0	0	0	1	4	0	0	0	125	176	125	301		167	24	6	148	-33	—	—	—	—	—	—
2018	29	MLB	Cleveland Indians	—	95	84	27	6	1	1	8	12	2	1	0	321	394	452	846	131	366	13	8	375	136	+4	+0	-2	-1	+2	0.3
2018	29	AAA	Columbus Clippers	—	23	19	5	2	0	1	4	5	0	0	0	263	391	526	918	263	308	22	17	402	98	—	—	—	—	—	—
2019	30	AAA	Indianapolis Indians	—	24	24	5	1	0	0	0	8	0	0	0	208	208	250	458	42	312	33	0	204	-7	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	2360	2159	578	132	10	64	150	437	21	20	5	268	321	427	748	159	307	19	6	329	109	+24	+2	-7	-1	+51	7.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2009	20	AA MLE	Akron Aeros	—	101	96	15	4	1	3	4	19	0	1	0	156	190	312	502	156	163	19	4	228	40	—	—	—	—	—	—
2009	20	A+ MLE	Kinston Indians	—	432	402	95	21	2	16	23	114	5	2	1	236	286	418	704	182	287	26	5	301	90	—	—	—	—	—	—
2010	21	AA MLE	Akron Aeros	—	524	474	126	20	3	15	32	96	10	3	0	266	326	416	741	150	291	18	6	320	103	—	—	—	—	—	—
2011	22	MLB MLE	Cleveland Indians	—	223	213	54	13	0	7	7	49	1	1	0	254	281	413	694	160	299	22	3	302	91	-3	+0	+3	+2	+5	0.7
2011	22	AAA MLE	Columbus Clippers	—	292	265	60	13	3	4	18	59	7	0	1	226	293	343	636	117	271	20	6	287	80	—	—	—	—	—	—
2012	23	MLB MLE	Cleveland Indians	—	151	142	38	6	1	5	8	27	1	2	1	268	311	430	741	162	300	18	5	329	109	+2	+0	-3	+1	+3	0.3
2012	23	AAA MLE	Columbus Clippers	—	126	120	32	10	0	3	2	27	2	0	0	267	290	425	715	158	309	21	2	308	95	—	—	—	—	—	—
2013	24	MLB MLE	Cleveland Indians	—	308	289	65	17	0	11	16	56	2	1	0	225	270	398	668	173	243	18	5	294	85	-6	+0	+3	+2	+7	0.6
2013	24	AAA MLE	Columbus Clippers	—	125	108	38	7	2	5	9	28	4	2	0	352	421	593	1.014	241	404	22	7	432	178	—	—	—	—	—	—
2014	25	MLB MLE	Cleveland Indians	—	533	482	134	29	1	13	36	99	8	3	1	278	338	423	762	145	328	19	7	335	113	+8	+0	-11	+2	+12	1.1
2015	26	MLB MLE	Cleveland Indians	—	362	336	82	19	1	7	20	69	1	4	1	244	289	369	658	125	288	19	6	290	82	-8	+0	+7	+2	+8	1.0
2015	26	AAA MLE	Columbus Clippers	—	171	162	37	10	0	2	6	42	1	1	0	228	260	327	588	99	289	25	4	259	61	—	—	—	—	—	—
2016	27	MLB MLE	Cleveland Indians	—	418	387	111	25	6	8	21	70	3	6	0	287	328	444	773	158	328	17	5	334	112	+6	+1	-4	-5	+9	0.8
2016	27	AA MLE	Akron RubberDucks	—	18	16	2	1	0	0	1	2	0	0	0	125	176	188	364	62	125	11	6	175	5	—	—	—	—	—	—
2017	28	MLB MLE	Cleveland Indians	—	270	238	68	17	1	12	23	55	3	2	2	286	356	517	873	231	326	20	9	374	139	+13	-0	+1	-3	+6	1.6
2017	28	AAA MLE	Columbus Clippers	—	28	27	10	2	0	1	0	7	0	1	0	370	370	556	926	185	392	25	0	339	116	—	—	—	—	—	—
2017	28	AA MLE	Akron RubberDucks	—	17	16	2	0	0	0	1	5	0	0	0	125	176	125	301		158	29	6	120	-33	—	—	—	—	—	—
2018	29	MLB MLE	Cleveland Indians	—	95	85	27	6	1	1	7	12	2	1	0	318	383	447	830	129	366	13	7	369	136	+4	+0	-2	-1	+2	0.3
2018	29	AAA MLE	Columbus Clippers	—	23	20	5	2	0	1	3	6	0	0	0	250	348	500	848	250	267	26	13	313	98	—	—	—	—	—	—
2019	30	AAA MLE	Indianapolis Indians	—	24	24	4	1	0	0	0	9	0	0	0	167	167	208	375	42	273	38	0	158	-7	—	—	—	—	—	—
2009	20	A+ MLE	2 teams	—	533	497	111	26	3	19	28	133	5	3	1	223	272	402	674	179	265	25	5	287	80	—	—	—	—	—	—
2009	20	A+ RAW	2 teams	—	533	481	124	31	3	22	44	96	5	3	1	258	326	472	798	214	279	18	8	350	80	—	—	—	—	—	—
2010	21	AA MLE	Akron Aeros	—	524	474	126	20	3	15	32	96	10	3	0	266	326	416	741	150	299	18	6	320	103	—	—	—	—	—	—
2010	21	AA RAW	Akron Aeros	—	524	460	128	22	3	17	46	77	10	3	0	278	357	450	807	172	297	15	9	354	103	—	—	—	—	—	—
2011	22	AAA MLE	2 teams	—	515	478	113	25	3	11	25	108	8	1	1	236	286	370	656	134	282	21	5	293	85	—	—	—	—	—	—
2011	22	AAA RAW	2 teams	—	515	467	122	28	3	14	36	96	8	1	1	261	325	424	749	163	300	19	7	331	85	—	—	—	—	—	—
2012	23	MLB MLE	2 teams	—	277	262	70	16	1	8	10	54	3	2	1	267	302	427	729	160	307	19	4	320	102	+1	+0	-3	+1	+6	0.5
2012	23	MLB RAW	2 teams	—	277	260	75	18	1	9	12	49	3	2	1	288	327	469	797	181	324	18	4	349	102	+1	+0	-3	+1	+6	0.5
2013	24	MLB MLE	2 teams	—	433	397	103	24	2	16	25	84	6	3	0	259	313	451	764	191	289	19	6	334	112	+6	+1	+3	+2	+9	2.1
2013	24	MLB RAW	2 teams	—	433	394	106	25	2	17	28	80	6	3	0	269	327	472	799	203	296	18	6	348	112	+6	+1	+3	+2	+9	2.1
2014	25	MLB MLE	Cleveland Indians	—	533	482	134	29	1	13	36	99	8	3	1	278	338	423	762	145	324	19	7	335	113	+8	+0	-11	+2	+12	1.1
2014	25	MLB RAW	Cleveland Indians	—	533	478	134	29	1	13	39	99	8	3	1	280	344	427	771	146	328	19	7	340	113	+8	+0	-11	+2	+12	1.1
2015	26	MLB MLE	2 teams	—	533	498	119	29	1	9	26	111	2	5	1	239	279	355	635	116	288	21	5	280	76	-16	+1	+7	+2	+12	0.6
2015	26	MLB RAW	2 teams	—	533	490	126	32	1	10	34	104	2	5	1	257	308	388	696	131	305	20	6	307	76	-16	+1	+7	+2	+12	0.6
2016	27	MLB MLE	2 teams	—	436	403	113	26	6	8	22	72	3	6	0	280	322	434	757	154	320	17	5	328	108	+4	+1	-4	-5	+9	0.6
2016	27	MLB RAW	2 teams	—	436	400	112	26	5	8	25	72	3	6	0	280	327	430	757	150	320	17	6	330	108	+4	+1	-4	-5	+9	0.6
2017	28	MLB MLE	3 teams	—	315	281	78	18	1	13	24	67	3	3	2	278	341	488	828	210	317	21	8	357	128	+10	-0	+1	-3	+7	1.5
2017	28	MLB RAW	3 teams	—	315	279	80	19	1	13	26	65	3	3	2	287	354	502	856	215	327	21	8	368	128	+10	-0	+1	-3	+7	1.5
2018	29	MLB MLE	2 teams	—	118	105	32	8	1	2	10	18	2	1	0	305	376	457	833	152	353	15	8	358	129	+4	+0	-2	-1	+3	0.4
2018	29	MLB RAW	2 teams	—	118	103	32	8	1	2	12	17	2	1	0	311	393	466	859	155	357	14	10	380	129	+4	+0	-2	-1	+3	0.4
2019	30	AAA MLE	Indianapolis Indians	—	24	24	4	1	0	0	0	9	0	0	0	167	167	208	375	42	267	38	0	158	-7	—	—	—	—	—	—
2019	30	AAA RAW	Indianapolis Indians	—	24	24	5	1	0	0	0	8	0	0	0	208	208	250	458	42	312	33	0	204	-7	—	—	—	—	—	—
2009	20	A+ MLE	2 teams	—	533	495	111	26	3	19	28	133	5	3	1	224	272	404	676	180	264	25	5	287	80	—	—	—	—	—	—
2010	21	AA MLE	Akron Aeros	—	524	477	126	20	3	15	32	96	10	3	0	264	326	413	739	149	291	18	6	320	103	—	—	—	—	—	—
2011	22	AAA MLE	2 teams	—	515	477	113	25	3	11	25	108	8	1	1	237	286	371	657	134	283	21	5	293	85	—	—	—	—	—	—
2012	23	MLB MLE	2 teams	—	277	262	70	16	1	8	10	54	3	2	1	267	302	427	729	160	304	19	4	320	102	—	—	—	—	—	—
2013	24	MLB MLE	2 teams	—	433	399	103	24	2	16	25	84	6	3	0	258	313	449	762	190	290	19	6	334	112	—	—	—	—	—	—
2014	25	MLB MLE	Cleveland Indians	—	533	484	134	29	1	13	36	99	8	3	1	277	338	421	760	145	328	19	7	335	113	—	—	—	—	—	—
2015	26	MLB MLE	2 teams	—	533	500	119	29	1	9	26	111	2	5	1	238	279	354	633	116	289	21	5	280	76	—	—	—	—	—	—
2016	27	MLB MLE	2 teams	—	436	408	113	26	6	8	22	72	3	6	0	277	322	429	751	152	320	17	5	328	108	—	—	—	—	—	—
2017	28	MLB MLE	3 teams	—	315	285	78	18	1	13	24	67	3	3	2	274	341	481	822	207	322	21	8	357	128	—	—	—	—	—	—
2018	29	MLB MLE	2 teams	—	118	105	32	8	1	2	10	18	2	1	0	305	376	457	833	152	347	15	8	358	129	—	—	—	—	—	—
2019	30	AAA MLE	Indianapolis Indians	—	24	24	4	1	0	0	0	9	0	0	0	167	167	208	375	42	273	38	0	158	-7	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2360	2159	578	132	10	64	150	437	21	20	5	268	321	427	748	159	307	19	6	329	99	+24	+2	-7	-1	+51	7.1
/ 162G	—	A+C		—	650	595	159	36	3	18	41	120	6	6	1	267	321	429	749	161	306	18	6	329	99	+7	+1	-2	-0	+14	1.9
Career	—	MLE		—	4241	3901	1003	222	22	114	238	851	50	30	7	257	308	413	721	156	299	20	6	315	99	+24	+2	-7	-1	+51	7.1
/ 162G	—	MLE		—	650	598	153	34	3	17	36	130	8	5	1	256	307	408	715	152	298	20	6	315	99	+7	+1	-2	-0	+14	1.9

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.

2019 AAAIndianapolis Indians · 24 PAwOBA .199 → .158 (−41)K% 33.3% → 39.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	33.33%	÷1.013	×1.200	—	—	39.49%
BB% (unintentional) /PA	0.00%	÷1.010	×0.690	—	×0.962	0.00%
HBP% /PA	0.00%	—	×0.940	—	×0.962	0.00%
Singles /BIP	25.00%	÷1.026	×0.930	—	×0.962	21.81%
Doubles /BIP	6.25%	÷0.901	×0.830	—	×0.962	5.54%
Triples /BIP	0.00%	÷1.150	×0.970	—	×0.962	0.00%
Home runs /BIP	0.00%	÷0.953	×0.840	—	×0.962	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 91, 1B 105, 2B 80, 3B 130, K 103, BB 102 — 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 .199 → .158; ISO .042 → .034; BABIP .312 → .273. 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 AAAColumbus Clippers · 23 PAwOBA .392 → .313 (−79)K% 21.7% → 25.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.74%	÷1.017	×1.200	—	—	25.66%
BB% (unintentional) /PA	17.39%	÷0.972	×0.690	—	×0.972	12.00%
HBP% /PA	0.00%	—	×0.940	—	×0.972	0.00%
Singles /BIP	14.29%	÷0.974	×0.930	—	×0.972	13.26%
Doubles /BIP	14.29%	÷0.958	×0.830	—	×0.972	12.02%
Triples /BIP	0.00%	÷0.900	×0.970	—	×0.972	0.00%
Home runs /BIP	7.14%	÷1.135	×0.840	—	×0.972	5.14%

Factors used: league row IL. Park (home-season share, regressed): HR 127, 1B 95, 2B 92, 3B 80, K 103, BB 94 — applied at half strength. Age: age 30 vs a level average of 27.2 → −2.8% on BB/HBP/hit rates (2.8 yr older than average).

Result: wOBA .392 → .313; ISO .263 → .207; BABIP .308 → .267. 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 AAAColumbus Clippers · 28 PAwOBA .395 → .339 (−55)K% 21.4% → 26.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.43%	÷0.989	×1.200	—	—	26.00%
BB% (unintentional) /PA	0.00%	÷1.089	×0.690	—	×0.982	0.00%
HBP% /PA	0.00%	—	×0.940	—	×0.982	0.00%
Singles /BIP	33.33%	÷0.945	×0.930	—	×0.982	32.20%
Doubles /BIP	9.52%	÷1.018	×0.830	—	×0.982	7.63%
Triples /BIP	0.00%	÷0.900	×0.970	—	×0.982	0.00%
Home runs /BIP	4.76%	÷1.231	×0.840	—	×0.982	3.19%

Factors used: league row IL. Park (home-season share, regressed): HR 146, 1B 89, 2B 104, 3B 80, K 98, BB 118 — 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 .395 → .339; ISO .185 → .132; BABIP .429 → .392. 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 AAAkron RubberDucks · 17 PAwOBA .144 → .120 (−24)K% 23.5% → 29.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.53%	÷0.990	×1.220	—	—	28.99%
BB% (unintentional) /PA	5.88%	÷1.052	×0.700	—	×0.958	3.75%
HBP% /PA	0.00%	—	×0.850	—	×0.958	0.00%
Singles /BIP	16.67%	÷0.978	×0.970	—	×0.958	15.84%
Doubles /BIP	0.00%	÷1.072	×0.860	—	×0.958	0.00%
Triples /BIP	0.00%	÷1.150	×0.950	—	×0.958	0.00%
Home runs /BIP	0.00%	÷1.008	×0.780	—	×0.958	0.00%

Factors used: league row EL. Park (home-season share, regressed): HR 102, 1B 96, 2B 114, 3B 130, K 98, BB 110 — applied at half strength. Age: age 29 vs a level average of 24.8 → −4.2% on BB/HBP/hit rates (4.2 yr older than average).

Result: wOBA .144 → .120; ISO .000 → .000; BABIP .167 → .158. 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 AAAkron RubberDucks · 18 PAwOBA .206 → .175 (−31)K% 11.1% → 13.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.11%	÷0.997	×1.220	—	—	13.59%
BB% (unintentional) /PA	11.11%	÷0.950	×0.700	—	×0.968	7.93%
HBP% /PA	0.00%	—	×0.850	—	×0.968	0.00%
Singles /BIP	7.69%	÷1.014	×0.970	—	×0.968	7.13%
Doubles /BIP	7.69%	÷1.015	×0.860	—	×0.968	6.31%
Triples /BIP	0.00%	÷1.150	×0.950	—	×0.968	0.00%
Home runs /BIP	0.00%	÷0.949	×0.780	—	×0.968	0.00%

Factors used: league row EL. Park (home-season share, regressed): HR 90, 1B 103, 2B 103, 3B 130, K 99, BB 90 — applied at half strength. Age: age 28 vs a level average of 24.8 → −3.2% on BB/HBP/hit rates (3.2 yr older than average).

Result: wOBA .206 → .175; ISO .067 → .059; BABIP .143 → .125. 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).

2015 AAAColumbus Clippers · 171 PAwOBA .322 → .259 (−63)K% 20.5% → 24.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.47%	÷1.009	×1.200	—	—	24.33%
BB% (unintentional) /PA	5.85%	÷1.068	×0.690	—	×1.003	3.79%
HBP% /PA	0.58%	—	×0.940	—	×1.003	0.55%
Singles /BIP	22.95%	÷1.005	×0.930	×0.955	×1.003	20.35%
Doubles /BIP	10.66%	÷1.019	×0.830	×0.955	×1.003	8.31%
Triples /BIP	0.00%	÷0.900	×0.970	×0.955	×1.003	0.00%
Home runs /BIP	2.46%	÷1.217	×0.840	—	×1.003	1.70%

Factors used: league row IL. Park (home-season share, regressed): HR 143, 1B 101, 2B 104, 3B 80, K 102, BB 114 — 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 ×0.955.

Result: wOBA .322 → .259; ISO .140 → .104; BABIP .342 → .289. 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).

2013 AAAColumbus Clippers · 125 PAwOBA .482 → .432 (−50)K% 19.2% → 22.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.20%	÷1.013	×1.200	—	—	22.74%
BB% (unintentional) /PA	9.60%	÷0.986	×0.690	—	×1.033	6.94%
HBP% /PA	3.20%	—	×0.940	—	×1.033	3.11%
Singles /BIP	30.86%	÷0.980	×0.930	×0.950	×1.033	28.73%
Doubles /BIP	9.88%	÷0.933	×0.830	×0.950	×1.033	8.62%
Triples /BIP	2.47%	÷0.900	×0.970	×0.950	×1.033	2.61%
Home runs /BIP	7.41%	÷1.111	×0.840	—	×1.033	5.79%

Factors used: league row IL. Park (home-season share, regressed): HR 122, 1B 96, 2B 87, 3B 80, K 103, BB 97 — applied at half strength. Age: age 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .482 → .432; ISO .286 → .250; BABIP .443 → .404. 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).

2012 AAAColumbus Clippers · 126 PAwOBA .365 → .308 (−57)K% 17.5% → 21.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.46%	÷0.974	×1.200	—	—	21.50%
BB% (unintentional) /PA	2.38%	÷0.998	×0.690	—	×1.048	1.72%
HBP% /PA	1.59%	—	×0.940	—	×1.048	1.56%
Singles /BIP	21.88%	÷1.002	×0.930	×0.950	×1.048	20.21%
Doubles /BIP	12.50%	÷0.999	×0.830	×0.950	×1.048	10.34%
Triples /BIP	0.00%	÷1.101	×0.970	×0.950	×1.048	0.00%
Home runs /BIP	4.17%	÷1.178	×0.840	—	×1.048	3.11%

Factors used: league row IL. Park (home-season share, regressed): HR 136, 1B 100, 2B 100, 3B 120, K 95, BB 100 — 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 .365 → .308; ISO .203 → .158; BABIP .351 → .309. 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).