Ronald Torreyes

PosSS

B/TR/R

Born1992-09-02

Age (2027)34

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2022

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2019	26	AAAWSH	330	.256/.293/.406	11	2	62	—	.224/.253/.353
2019	26	MLBMIN	17	.188/.235/.188	0	1	24	0.4
2021	28	AAAPHI	36	.276/.417/.414	0	0	94	—	.258/.361/.387
2021	28	MLBPHI	344	.242/.287/.346	7	2	71	0.2
2022	29	AAAPHI	38	.171/.237/.200	0	0	-1	—	.167/.211/.194
2023	30	No MLB games played
2024	31	No MLB games played
2025	32	No MLB games played
2026	33	No MLB games played

Last 3 seasons WAR 0.5

Contract

No contract data on file.

Skills · percentileStatcast 2019-2021

Speed37

Barrel%10

xwOBA10

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)
2010	17	A	Dayton Dragons	—	25	25	6	2	1	0	0	3	0	0	0	240	240	400	640	160	273	12	0	276	39	—	—	—	—	—	—
2010	17	ROK	AZL Reds	—	374	324	123	27	11	5	24	16	19	25	17	380	452	577	1.029	198	384	4	6	444	122	—	—	—	—	—	—
2011	18	A	Dayton Dragons	—	306	278	99	9	5	3	14	19	6	12	7	356	399	457	856	101	374	6	5	373	123	—	—	—	—	—	—
2012	19	A+	Daytona Cubs	—	474	421	111	23	5	6	32	29	10	13	4	264	330	385	715	121	268	6	7	315	80	—	—	—	—	—	—
2013	20	AA	Corpus Christi Hooks	—	427	375	101	19	6	2	28	29	7	5	1	269	332	368	700	99	284	7	7	304	75	—	—	—	—	—	—
2014	21	AAA	Oklahoma City RedHawks	—	519	460	137	20	5	2	25	26	10	12	9	298	347	376	724	78	310	5	5	313	84	—	—	—	—	—	—
2015	22	AAA	Oklahoma City Dodgers	—	125	119	29	3	1	0	3	13	1	0	1	244	268	286	554	42	271	10	2	247	36	—	—	—	—	—	—
2015	22	AA	Tulsa Drillers	—	328	299	80	15	2	4	24	25	2	5	3	268	326	371	697	104	279	8	7	312	78	—	—	—	—	—	—
2016	23	MLB	New York Yankees	—	169	155	40	7	4	1	10	20	1	2	1	258	305	374	680	116	289	12	6	299	88	-2	+0	-0	+1	+4	0.2
2017	24	MLB	New York Yankees	—	336	315	92	15	1	3	11	43	1	2	0	292	318	375	693	83	326	13	3	302	90	-4	+0	+4	+1	+7	1.0
2018	25	MLB	New York Yankees	—	102	100	28	7	1	0	2	16	0	0	0	280	294	370	664	90	333	16	2	295	86	-2	+0	-2	+1	+2	-0.1
2018	25	AAA	Scranton/Wilkes-Barre RailRiders	—	106	97	24	3	0	0	7	11	1	0	0	247	305	278	583	31	276	10	7	269	42	—	—	—	—	—	—
2018	25	A+	Tampa Tarpons	—	15	14	4	0	0	0	0	0	0	0	0	286	286	286	571		267	0	0	241	48	—	—	—	—	—	—
2019	26	MLB	Minnesota Twins	—	17	16	3	0	0	0	0	3	1	1	0	188	235	188	423		231	18	0	203	24	-2	+0	+1	+4	+0	0.4
2019	26	AAA	Rochester Red Wings	—	330	308	79	11	1	11	12	33	4	2	1	256	293	406	699	149	253	10	4	305	62	—	—	—	—	—	—
2021	28	MLB	Philadelphia Phillies	—	344	318	77	10	1	7	19	41	1	2	1	242	287	346	633	104	258	12	6	280	71	-12	+0	+5	+1	+7	0.2
2021	28	AAA	Lehigh Valley IronPigs	—	36	29	8	4	0	0	6	6	1	0	0	276	417	414	830	138	348	17	17	380	94	—	—	—	—	—	—
2022	29	AAA	Lehigh Valley IronPigs	—	38	35	6	1	0	0	3	2	0	0	0	171	237	200	437	29	182	5	8	208	-1	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	968	904	240	39	7	11	42	123	4	7	2	265	301	361	661	95	295	13	4	291	83	-19	+1	+8	+8	+21	1.8
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2010	17	A MLE	Dayton Dragons	—	25	25	6	2	1	0	0	4	0	0	0	240	240	400	640	160	247	16	0	226	39	—	—	—	—	—	—
2010	17	ROK MLE	AZL Reds	—	374	335	103	21	8	4	13	23	19	25	17	307	368	454	822	146	306	6	3	349	122	—	—	—	—	—	—
2011	18	A MLE	Dayton Dragons	—	306	283	99	8	4	2	9	26	6	12	7	350	383	428	810	78	369	8	3	350	123	—	—	—	—	—	—
2012	19	A+ MLE	Daytona Cubs	—	474	429	108	21	4	5	24	39	10	13	4	252	307	354	661	103	257	8	5	287	80	—	—	—	—	—	—
2013	20	AA MLE	Corpus Christi Hooks	—	427	385	100	17	7	2	18	35	7	5	1	260	305	356	661	96	266	8	4	279	75	—	—	—	—	—	—
2014	21	AAA MLE	Oklahoma City RedHawks	—	519	466	134	19	4	2	19	34	10	12	9	288	329	358	688	71	290	7	4	292	84	—	—	—	—	—	—
2015	22	AAA MLE	Oklahoma City Dodgers	—	125	120	27	3	1	0	2	17	1	0	1	225	244	267	511	42	255	14	2	222	36	—	—	—	—	—	—
2015	22	AA MLE	Tulsa Drillers	—	328	305	78	13	2	3	18	31	2	5	3	256	302	341	643	85	272	9	5	284	78	—	—	—	—	—	—
2016	23	MLB MLE	New York Yankees	—	169	156	40	7	4	1	10	20	1	2	1	256	305	372	677	115	289	12	6	299	88	-2	+0	-0	+1	+4	0.2
2017	24	MLB MLE	New York Yankees	—	336	315	92	15	1	3	11	43	1	2	0	292	318	375	693	83	326	13	3	302	90	-4	+0	+4	+1	+7	1.0
2018	25	MLB MLE	New York Yankees	—	102	100	28	7	1	0	2	16	0	0	0	280	294	370	664	90	333	16	2	296	86	-2	+0	-2	+1	+2	-0.1
2018	25	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	106	99	22	3	0	0	5	13	1	0	0	222	267	253	519	30	249	12	5	231	42	—	—	—	—	—	—
2018	25	A+ MLE	Tampa Tarpons	—	15	14	4	0	0	0	0	0	0	0	0	286	286	286	571		238	0	0	239	48	—	—	—	—	—	—
2019	26	MLB MLE	Minnesota Twins	—	17	16	3	0	0	0	0	3	1	1	0	188	235	188	423		231	18	0	203	24	-2	+0	+1	+4	+0	0.4
2019	26	AAA MLE	Rochester Red Wings	—	330	312	70	8	1	10	8	40	4	2	1	224	253	353	606	128	220	12	2	260	62	—	—	—	—	—	—
2021	28	MLB MLE	Philadelphia Phillies	—	344	320	77	10	1	7	17	41	1	2	1	241	281	344	625	103	258	12	5	273	71	-12	+0	+5	+1	+7	0.2
2021	28	AAA MLE	Lehigh Valley IronPigs	—	36	31	8	4	0	0	4	7	1	0	0	258	361	387	748	129	305	19	11	307	94	—	—	—	—	—	—
2022	29	AAA MLE	Lehigh Valley IronPigs	—	38	36	6	1	0	0	2	2	0	0	0	167	211	194	405	28	160	5	5	167	-1	—	—	—	—	—	—
2010	17	ROK MLE	2 teams	—	399	360	108	22	9	4	13	27	19	25	17	300	357	444	802	144	312	7	3	341	117	—	—	—	—	—	—
2010	17	ROK RAW	2 teams	—	399	349	129	29	12	5	24	19	19	25	17	370	439	564	1.003	195	377	5	6	433	117	—	—	—	—	—	—
2011	18	A MLE	Dayton Dragons	—	306	283	99	8	4	2	9	26	6	12	7	350	383	428	810	78	379	8	3	350	123	—	—	—	—	—	—
2011	18	A RAW	Dayton Dragons	—	306	278	99	9	5	3	14	19	6	12	7	356	399	457	856	101	374	6	5	373	123	—	—	—	—	—	—
2012	19	A+ MLE	Daytona Cubs	—	474	429	108	21	4	5	24	39	10	13	4	252	307	354	661	103	263	8	5	287	80	—	—	—	—	—	—
2012	19	A+ RAW	Daytona Cubs	—	474	421	111	23	5	6	32	29	10	13	4	264	330	385	715	121	268	6	7	315	80	—	—	—	—	—	—
2013	20	AA MLE	Corpus Christi Hooks	—	427	385	100	17	7	2	18	35	7	5	1	260	305	356	661	96	278	8	4	279	75	—	—	—	—	—	—
2013	20	AA RAW	Corpus Christi Hooks	—	427	375	101	19	6	2	28	29	7	5	1	269	332	368	700	99	284	7	7	304	75	—	—	—	—	—	—
2014	21	AAA MLE	Oklahoma City RedHawks	—	519	466	134	19	4	2	19	34	10	12	9	288	329	358	688	71	305	7	4	292	84	—	—	—	—	—	—
2014	21	AAA RAW	Oklahoma City RedHawks	—	519	460	137	20	5	2	25	26	10	12	9	298	347	376	724	78	310	5	5	313	84	—	—	—	—	—	—
2015	22	AA MLE	2 teams	—	453	425	106	16	3	3	20	48	3	5	4	249	288	322	610	73	273	11	4	267	67	—	—	—	—	—	—
2015	22	AA RAW	2 teams	—	453	418	109	18	3	4	27	38	3	5	4	261	310	347	657	86	277	8	6	294	67	—	—	—	—	—	—
2016	23	MLB MLE	New York Yankees	—	169	156	40	7	4	1	10	20	1	2	1	256	305	372	677	115	287	12	6	299	88	-2	+0	-0	+1	+4	0.2
2016	23	MLB RAW	New York Yankees	—	169	155	40	7	4	1	10	20	1	2	1	258	305	374	680	116	289	12	6	299	88	-2	+0	-0	+1	+4	0.2
2017	24	MLB MLE	New York Yankees	—	336	315	92	15	1	3	11	43	1	2	0	292	318	375	693	83	326	13	3	302	90	-4	+0	+4	+1	+7	1.0
2017	24	MLB RAW	New York Yankees	—	336	315	92	15	1	3	11	43	1	2	0	292	318	375	693	83	326	13	3	302	90	-4	+0	+4	+1	+7	1.0
2018	25	AAA MLE	3 teams	—	223	213	54	10	1	0	7	29	1	0	0	254	281	310	590	56	290	13	3	261	63	—	—	—	—	—	—
2018	25	AAA RAW	3 teams	—	223	211	56	10	1	0	9	27	1	0	0	265	299	322	621	57	301	12	4	279	63	—	—	—	—	—	—
2019	26	AAA MLE	2 teams	—	347	328	73	8	1	10	8	43	5	3	1	223	252	345	597	122	225	12	2	257	60	—	—	—	—	—	—
2019	26	AAA RAW	2 teams	—	347	324	82	11	1	11	12	36	5	3	1	253	290	395	685	142	252	10	3	300	60	—	—	—	—	—	—
2021	28	MLB MLE	2 teams	—	380	351	84	14	1	7	21	48	2	2	1	239	286	345	631	105	259	13	6	277	73	-12	+0	+5	+1	+8	0.2
2021	28	MLB RAW	2 teams	—	380	347	85	14	1	7	25	47	2	2	1	245	299	352	651	107	265	12	7	290	73	-12	+0	+5	+1	+8	0.2
2022	29	AAA MLE	Lehigh Valley IronPigs	—	38	36	6	1	0	0	2	2	0	0	0	167	211	194	405	28	176	5	5	167	-1	—	—	—	—	—	—
2022	29	AAA RAW	Lehigh Valley IronPigs	—	38	35	6	1	0	0	3	2	0	0	0	171	237	200	437	29	182	5	8	208	-1	—	—	—	—	—	—
2010	17	ROK MLE	2 teams	—	399	364	108	22	9	4	13	27	19	25	17	297	357	440	797	143	302	7	3	341	117	—	—	—	—	—	—
2011	18	A MLE	Dayton Dragons	—	306	288	99	8	4	2	9	26	6	12	7	344	383	420	803	76	369	8	3	350	123	—	—	—	—	—	—
2012	19	A+ MLE	Daytona Cubs	—	474	437	108	21	4	5	24	39	10	13	4	247	307	348	655	101	257	8	5	287	80	—	—	—	—	—	—
2013	20	AA MLE	Corpus Christi Hooks	—	427	399	100	17	7	2	18	35	7	5	1	251	305	343	648	93	266	8	4	279	75	—	—	—	—	—	—
2014	21	AAA MLE	Oklahoma City RedHawks	—	519	485	134	19	4	2	19	34	10	12	9	276	329	344	674	68	290	7	4	292	84	—	—	—	—	—	—
2015	22	AA MLE	2 teams	—	453	427	106	16	3	3	20	48	3	5	4	248	288	321	609	73	267	11	4	267	67	—	—	—	—	—	—
2016	23	MLB MLE	New York Yankees	—	169	156	40	7	4	1	10	20	1	2	1	256	305	372	677	115	289	12	6	299	88	—	—	—	—	—	—
2017	24	MLB MLE	New York Yankees	—	336	321	92	15	1	3	11	43	1	2	0	287	318	368	686	81	326	13	3	302	90	—	—	—	—	—	—
2018	25	AAA MLE	3 teams	—	223	213	54	10	1	0	7	29	1	0	0	254	281	310	590	56	287	13	3	261	63	—	—	—	—	—	—
2019	26	AAA MLE	2 teams	—	347	331	73	8	1	10	8	43	5	3	1	221	252	341	594	121	221	12	2	257	60	—	—	—	—	—	—
2021	28	MLB MLE	2 teams	—	380	354	84	14	1	7	21	48	2	2	1	237	286	342	628	105	263	13	6	277	73	—	—	—	—	—	—
2022	29	AAA MLE	Lehigh Valley IronPigs	—	38	36	6	1	0	0	2	2	0	0	0	167	211	194	405	28	160	5	5	167	-1	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	968	904	240	39	7	11	42	123	4	7	2	265	301	361	661	95	295	13	4	291	83	-19	+1	+8	+8	+21	1.8
/ 162G	—	A+C		—	650	607	161	26	5	7	28	83	3	5	1	265	300	359	660	94	296	13	4	291	83	-13	+0	+5	+5	+14	1.2
Career	—	MLE		—	4071	3747	1004	158	39	39	162	394	65	81	45	268	310	362	672	94	288	10	4	290	83	-19	+1	+8	+8	+21	1.8
/ 162G	—	MLE		—	650	598	160	25	6	6	26	63	10	13	7	268	309	360	668	92	288	10	4	290	83	-13	+0	+5	+5	+14	1.2

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.

2022 AAALehigh Valley IronPigs · 38 PAwOBA .203 → .167 (−36)K% 5.3% → 6.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	5.26%	÷0.970	×1.200	—	—	6.51%
BB% (unintentional) /PA	7.89%	÷1.067	×0.690	—	×0.972	4.96%
HBP% /PA	0.00%	—	×0.940	—	×0.972	0.00%
Singles /BIP	15.15%	÷1.007	×0.930	—	×0.972	13.60%
Doubles /BIP	3.03%	÷1.018	×0.830	—	×0.972	2.40%
Triples /BIP	0.00%	÷0.900	×0.970	—	×0.972	0.00%
Home runs /BIP	0.00%	÷1.039	×0.700	—	×0.972	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 108, 1B 101, 2B 104, 3B 80, K 94, BB 113 — 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 .203 → .167; ISO .029 → .023; BABIP .182 → .160. 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 AAALehigh Valley IronPigs · 36 PAwOBA .371 → .307 (−64)K% 16.7% → 20.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.67%	÷0.992	×1.200	—	—	20.17%
BB% (unintentional) /PA	16.67%	÷1.061	×0.690	—	×0.982	10.64%
HBP% /PA	2.78%	—	×0.940	—	×0.982	2.56%
Singles /BIP	17.39%	÷1.016	×0.930	—	×0.982	15.63%
Doubles /BIP	17.39%	÷0.952	×0.830	—	×0.982	14.89%
Triples /BIP	0.00%	÷1.150	×0.920	—	×0.982	0.00%
Home runs /BIP	0.00%	÷0.957	×0.700	—	×0.982	0.00%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 91, 1B 103, 2B 90, 3B 130, K 98, BB 112 — 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 .371 → .307; ISO .138 → .123; BABIP .348 → .305. 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 AAARochester Red Wings · 330 PAwOBA .301 → .260 (−41)K% 10.0% → 12.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.00%	÷0.999	×1.200	—	—	12.01%
BB% (unintentional) /PA	3.64%	÷1.095	×0.690	—	×1.003	2.30%
HBP% /PA	1.21%	—	×0.940	—	×1.003	1.14%
Singles /BIP	20.36%	÷0.982	×0.930	×0.950	×1.003	18.38%
Doubles /BIP	4.00%	÷1.063	×0.830	×0.950	×1.003	2.98%
Triples /BIP	0.36%	÷1.150	×0.970	×0.950	×1.003	0.29%
Home runs /BIP	4.00%	÷0.958	×0.840	—	×1.003	3.52%

Factors used: league row IL. Park (home-season share, regressed): HR 92, 1B 96, 2B 113, 3B 130, K 100, BB 119 — 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 .301 → .260; ISO .149 → .128; BABIP .253 → .220. 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 AAAScranton/Wilkes-Barre RailRiders · 106 PAwOBA .264 → .231 (−34)K% 10.4% → 12.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.38%	÷1.002	×1.200	—	—	12.43%
BB% (unintentional) /PA	6.60%	÷1.034	×0.690	—	×1.018	4.48%
HBP% /PA	0.94%	—	×0.940	—	×1.018	0.90%
Singles /BIP	24.42%	÷1.032	×0.930	×0.996	×1.018	22.31%
Doubles /BIP	3.49%	÷1.004	×0.830	×0.996	×1.018	2.92%
Triples /BIP	0.00%	÷1.130	×0.970	×0.996	×1.018	0.00%
Home runs /BIP	0.00%	÷1.046	×0.840	—	×1.018	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 109, 1B 106, 2B 101, 3B 126, K 100, BB 107 — 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 ×0.996.

Result: wOBA .264 → .231; ISO .031 → .026; BABIP .276 → .249. 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 A+Tampa Tarpons · 15 PAwOBA .251 → .239 (−12)K% 0.0% → 0.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	0.00%	÷1.004	×1.420	—	—	0.00%
BB% (unintentional) /PA	0.00%	÷1.015	×0.750	—	×0.968	0.00%
HBP% /PA	0.00%	—	×0.930	—	×0.968	0.00%
Singles /BIP	28.57%	÷1.003	×0.920	—	×0.968	25.38%
Doubles /BIP	0.00%	÷0.891	×0.960	—	×0.968	0.00%
Triples /BIP	0.00%	÷0.983	×0.810	—	×0.968	0.00%
Home runs /BIP	0.00%	÷1.205	×0.880	—	×0.968	0.00%

Factors used: league row FSL. Park (home-season share, regressed): HR 141, 1B 101, 2B 78, 3B 97, K 101, BB 103 — applied at half strength. Age: age 26 vs a level average of 22.8 → −3.2% on BB/HBP/hit rates (3.2 yr older than average).

Result: wOBA .251 → .239; ISO .000 → .000; BABIP .267 → .238. 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 AATulsa Drillers · 328 PAwOBA .306 → .284 (−22)K% 7.6% → 9.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	7.62%	÷0.989	×1.220	—	—	9.40%
BB% (unintentional) /PA	7.32%	÷0.976	×0.700	—	×1.027	5.39%
HBP% /PA	0.61%	—	×0.870	—	×1.027	0.54%
Singles /BIP	21.53%	÷0.938	×0.920	×0.998	×1.027	21.65%
Doubles /BIP	5.47%	÷1.006	×0.840	×0.998	×1.027	4.69%
Triples /BIP	0.73%	÷0.900	×0.940	×0.998	×1.027	0.78%
Home runs /BIP	1.46%	÷1.039	×0.800	—	×1.027	1.15%

Factors used: league row TL. Park (home-season share, regressed): HR 108, 1B 88, 2B 101, 3B 80, K 98, BB 95 — 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 ×0.998.

Result: wOBA .306 → .284; ISO .104 → .090; BABIP .279 → .272. 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 AAAOklahoma City Dodgers · 125 PAwOBA .243 → .222 (−20)K% 10.4% → 13.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.40%	÷0.984	×1.290	—	—	13.63%
BB% (unintentional) /PA	2.40%	÷1.095	×0.710	—	×1.050	1.63%
HBP% /PA	0.80%	—	×0.980	—	×1.050	0.82%
Singles /BIP	23.58%	÷1.028	×0.900	×1.030	×1.050	22.33%
Doubles /BIP	2.83%	÷0.965	×0.810	×1.030	×1.050	2.57%
Triples /BIP	0.94%	÷0.941	×0.810	×1.030	×1.050	0.88%
Home runs /BIP	0.00%	÷0.866	×0.780	—	×1.050	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 73, 1B 106, 2B 93, 3B 88, K 97, BB 119 — 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 ×1.030.

Result: wOBA .243 → .222; ISO .042 → .038; BABIP .271 → .255. 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).

2014 AAAOklahoma City RedHawks · 519 PAwOBA .306 → .292 (−14)K% 5.0% → 6.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	5.01%	÷0.994	×1.290	—	—	6.50%
BB% (unintentional) /PA	4.82%	÷0.977	×0.710	—	×1.050	3.68%
HBP% /PA	1.93%	—	×0.980	—	×1.050	1.98%
Singles /BIP	25.35%	÷1.018	×0.900	×1.019	×1.050	23.98%
Doubles /BIP	4.61%	÷0.935	×0.810	×1.019	×1.050	4.27%
Triples /BIP	1.15%	÷1.150	×0.810	×1.019	×1.050	0.87%
Home runs /BIP	0.46%	÷1.042	×0.780	—	×1.050	0.36%

Factors used: league row PCL. Park (home-season share, regressed): HR 108, 1B 104, 2B 87, 3B 130, K 99, BB 95 — 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 ×1.019.

Result: wOBA .306 → .292; ISO .078 → .070; BABIP .310 → .290. 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).