Greg Bird

Pos1B

B/TL/R

Born1992-11-09

Age (2027)34

No MLB projection yet. Career stats below are historical.

Overview

INTLLAST SEASON 2024

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2022	29	AAAScranton/Wilk…	240	.218/.326/.354	6	2	42	—	.174/.247/.271
2023	30	INTLMelbourne Aces	161	.277/.354/.539	11	2	145	—
2024	31	INTLMelbourne Aces	166	.309/.415/.496	5	1	158	—

Contract

No contract data on file.

Skills · percentileStatcast 2017-2019

Barrel%59

xwOBA48

Avg EV41

Speed10

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)
2012	19	ROK	GCL Yankees	—	62	49	14	2	1	0	11	13	1	0	0	286	426	367	794	82	378	21	18	364	63	—	—	—	—	—	—
2013	20	A	Charleston RiverDogs	—	573	458	132	36	3	20	107	132	6	1	1	288	429	511	940	223	364	23	19	415	110	—	—	—	—	—	—
2014	21	AA	Trenton Thunder	—	116	95	24	8	0	7	18	27	2	0	0	253	383	558	941	305	274	23	16	405	117	—	—	—	—	—	—
2014	21	A+	Tampa Yankees	—	325	274	76	22	1	7	45	70	1	1	0	277	381	442	823	164	342	22	14	364	84	—	—	—	—	—	—
2014	21	INTL	Scottsdale Scorpions	—	115	99	31	6	0	6	13	23	1	1	1	313	398	556	954	242	347	20	11	410	164	—	—	—	—	—	—
2015	22	MLB	New York Yankees	—	178	157	41	9	0	11	19	53	1	0	0	261	345	529	873	268	319	30	11	379	138	+8	+0	-3	-10	+4	-0.0
2015	22	AAA	Scranton/Wilkes-Barre RailRiders	—	150	136	41	7	1	6	11	27	1	0	0	301	358	500	858	199	333	18	7	373	109	—	—	—	—	—	—
2015	22	AA	Trenton Thunder	—	212	182	47	16	0	6	24	30	5	1	1	258	360	445	805	187	279	14	11	359	83	—	—	—	—	—	—
2016	23	INTL	Scottsdale Scorpions	—	78	65	14	4	1	1	12	17	1	1	0	215	346	354	700	138	277	22	15	323	105	—	—	—	—	—	—
2017	24	MLB	New York Yankees	—	170	147	28	7	0	9	19	42	2	0	0	190	292	422	713	231	194	25	11	314	94	-1	+0	-3	-4	+4	-0.5
2017	24	AAA	Scranton/Wilkes-Barre RailRiders	—	59	47	14	4	0	3	11	9	0	0	0	298	431	574	1.006	277	306	15	19	430	128	—	—	—	—	—	—
2017	24	A+	Tampa Yankees	—	22	17	6	2	0	0	5	1	0	0	0	353	500	471	971	118	375	5	23	440	135	—	—	—	—	—	—
2018	25	MLB	New York Yankees	—	311	272	54	16	1	11	30	78	5	0	0	199	290	386	676	188	230	25	10	300	85	-6	+0	-2	-6	+7	-0.7
2018	25	AAA	Scranton/Wilkes-Barre RailRiders	—	18	16	4	0	0	2	2	7	0	0	0	250	333	625	958	375	286	39	11	409	90	—	—	—	—	—	—
2018	25	AA	Trenton Thunder	—	20	15	2	0	0	1	5	2	0	0	0	133	350	333	683	200	83	10	25	324	56	—	—	—	—	—	—
2019	26	MLB	New York Yankees	—	41	35	6	0	0	1	6	16	0	0	0	171	293	257	550	86	278	39	15	263	62	-2	+0	-0	-1	+1	-0.3
2019	26	INTL	Gigantes del Cibao	—	30	24	3	0	0	0	6	9	0	0	0	125	300	125	425		200	30	20	230	42	—	—	—	—	—	—
2021	28	AAA	Albuquerque Isotopes	—	461	393	105	21	1	27	58	106	4	0	1	267	367	532	899	265	293	23	13	388	68	—	—	—	—	—	—
2022	29	AAA	Scranton/Wilkes-Barre RailRiders	—	240	206	45	8	1	6	31	61	2	2	0	218	326	354	681	136	279	25	13	311	42	—	—	—	—	—	—
2023	30	INTL	Melbourne Aces	—	161	141	39	4	0	11	15	22	2	2	1	277	354	539	893	262	252	14	9	383	145	—	—	—	—	—	—
2024	31	INTL	Melbourne Aces	—	166	139	43	11	0	5	20	24	5	1	0	309	415	496	911	187	339	14	12	401	158	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	700	611	129	32	1	32	74	189	8	0	0	211	304	424	728	213	244	27	11	321	103	+3	+0	-8	-22	+15	-1.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2012	19	ROK MLE	GCL Yankees	—	62	53	11	1	1	0	7	19	1	0	0	208	311	264	576	57	301	31	11	261	63	—	—	—	—	—	—
2013	20	A MLE	Charleston RiverDogs	—	573	493	116	30	3	17	72	174	6	1	1	235	340	412	752	176	322	30	13	331	110	—	—	—	—	—	—
2014	21	AA MLE	Trenton Thunder	—	116	100	22	7	0	6	13	33	2	0	0	220	322	470	792	250	249	28	11	341	117	—	—	—	—	—	—
2014	21	A+ MLE	Tampa Yankees	—	325	286	63	19	1	6	32	105	1	1	0	220	300	357	657	136	302	32	10	292	84	—	—	—	—	—	—
2015	22	MLB MLE	New York Yankees	—	178	157	40	9	0	10	19	53	1	0	0	255	339	503	842	248	319	30	11	372	138	+8	+0	-3	-10	+4	-0.0
2015	22	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	150	140	38	6	1	6	7	33	1	0	0	271	311	457	768	186	305	22	5	330	109	—	—	—	—	—	—
2015	22	AA MLE	Trenton Thunder	—	212	191	42	14	0	4	15	39	5	1	1	220	294	356	650	136	255	18	7	291	83	—	—	—	—	—	—
2017	24	MLB MLE	New York Yankees	—	170	147	27	7	0	8	19	42	2	0	0	184	286	395	680	211	194	25	11	307	94	-1	+0	-3	-4	+4	-0.5
2017	24	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	59	51	13	4	0	2	7	11	0	0	0	255	345	451	796	196	284	19	12	358	128	—	—	—	—	—	—
2017	24	A+ MLE	Tampa Yankees	—	22	18	6	2	0	0	4	1	0	0	0	333	455	444	899	111	328	5	18	368	135	—	—	—	—	—	—
2018	25	MLB MLE	New York Yankees	—	311	273	53	16	1	10	29	78	5	0	0	194	283	370	653	176	230	25	9	294	85	-6	+0	-2	-6	+7	-0.7
2018	25	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	18	17	3	0	0	1	1	8	0	0	0	176	222	353	575	176	249	44	6	301	90	—	—	—	—	—	—
2018	25	AA MLE	Trenton Thunder	—	20	16	2	0	0	1	4	2	0	0	0	125	300	312	613	188	82	10	20	251	56	—	—	—	—	—	—
2019	26	MLB MLE	New York Yankees	—	41	35	6	0	0	1	6	16	0	0	0	171	293	257	550	86	278	39	15	260	62	-2	+0	-0	-1	+1	-0.3
2021	28	AAA MLE	Albuquerque Isotopes	—	461	413	79	17	1	16	38	133	4	0	1	191	266	354	619	162	225	29	8	268	68	—	—	—	—	—	—
2022	29	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	240	218	38	7	1	4	19	73	2	2	0	174	247	271	518	96	233	30	8	231	42	—	—	—	—	—	—
2012	19	ROK MLE	GCL Yankees	—	62	53	11	1	1	0	7	19	1	0	0	208	311	264	576	57	314	31	11	261	63	—	—	—	—	—	—
2012	19	ROK RAW	GCL Yankees	—	62	49	14	2	1	0	11	13	1	0	0	286	426	367	794	82	378	21	18	364	63	—	—	—	—	—	—
2013	20	A MLE	Charleston RiverDogs	—	573	493	116	30	3	17	72	174	6	1	1	235	340	412	752	176	326	30	13	331	110	—	—	—	—	—	—
2013	20	A RAW	Charleston RiverDogs	—	573	458	132	36	3	20	107	132	6	1	1	288	429	511	940	223	364	23	19	415	110	—	—	—	—	—	—
2014	21	A+ MLE	3 teams	—	556	486	106	32	1	16	58	174	4	2	1	218	307	387	693	169	296	31	10	305	92	—	—	—	—	—	—
2014	21	A+ RAW	3 teams	—	556	468	131	36	1	20	76	120	4	2	1	280	385	489	874	209	330	22	14	382	92	—	—	—	—	—	—
2015	22	AA MLE	3 teams	—	540	487	121	29	1	21	42	124	7	1	1	248	317	441	759	193	289	23	8	328	108	—	—	—	—	—	—
2015	22	AA RAW	3 teams	—	540	475	129	32	1	23	54	110	7	1	1	272	354	488	843	217	306	20	10	369	108	—	—	—	—	—	—
2016	23	INTL MLE	Scottsdale Scorpions	—	78	65	14	4	1	1	12	17	1	1	0	215	346	354	700	138	277	22	15	—	—	—	—	—	—	—	—
2016	23	INTL RAW	Scottsdale Scorpions	—	78	65	14	4	1	1	12	17	1	1	0	215	346	354	700	138	277	22	15	323	105	—	—	—	—	—	—
2017	24	MLB MLE	3 teams	—	251	216	47	13	0	11	30	54	2	0	0	218	319	431	749	213	234	22	12	324	106	+2	+0	-3	-4	+5	0.0
2017	24	MLB RAW	3 teams	—	251	211	48	13	0	12	35	52	2	0	0	227	343	460	802	232	240	21	14	352	106	+2	+0	-3	-4	+5	0.0
2018	25	MLB MLE	3 teams	—	349	306	59	16	1	13	34	89	5	0	0	193	284	379	663	186	221	26	10	291	83	-7	+0	-2	-6	+8	-0.8
2018	25	MLB RAW	3 teams	—	349	303	60	16	1	14	37	87	5	0	0	198	296	396	692	198	223	25	11	307	83	-7	+0	-2	-6	+8	-0.8
2019	26	MLB MLE	2 teams	—	71	61	11	0	0	2	10	28	0	0	0	180	296	279	574	98	290	39	14	260	62	-3	+0	-0	-1	+2	-0.3
2019	26	MLB RAW	2 teams	—	71	59	9	0	0	1	12	25	0	0	0	153	296	203	499	51	242	35	17	249	62	-3	+0	-0	-1	+2	-0.3
2021	28	AAA MLE	Albuquerque Isotopes	—	461	413	79	17	1	16	38	133	4	0	1	191	266	354	619	162	233	29	8	268	68	—	—	—	—	—	—
2021	28	AAA RAW	Albuquerque Isotopes	—	461	393	105	21	1	27	58	106	4	0	1	267	367	532	899	265	293	23	13	388	68	—	—	—	—	—	—
2022	29	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	240	218	38	7	1	4	19	73	2	2	0	174	247	271	518	96	239	30	8	231	42	—	—	—	—	—	—
2022	29	AAA RAW	Scranton/Wilkes-Barre RailRiders	—	240	206	45	8	1	6	31	61	2	2	0	218	326	354	681	136	279	25	13	311	42	—	—	—	—	—	—
2023	30	INTL MLE	Melbourne Aces	—	161	141	39	4	0	11	15	22	2	2	1	277	354	539	893	262	252	14	9	—	—	—	—	—	—	—	—
2023	30	INTL RAW	Melbourne Aces	—	161	141	39	4	0	11	15	22	2	2	1	277	354	539	893	262	252	14	9	383	145	—	—	—	—	—	—
2024	31	INTL MLE	Melbourne Aces	—	166	139	43	11	0	5	20	24	5	1	0	309	415	496	911	187	339	14	12	—	—	—	—	—	—	—	—
2024	31	INTL RAW	Melbourne Aces	—	166	139	43	11	0	5	20	24	5	1	0	309	415	496	911	187	339	14	12	401	158	—	—	—	—	—	—
2012	19	ROK MLE	GCL Yankees	—	62	54	11	1	1	0	7	19	1	0	0	204	311	259	571	56	301	31	11	261	63	—	—	—	—	—	—
2013	20	A MLE	Charleston RiverDogs	—	573	490	116	30	3	17	72	174	6	1	1	237	340	414	754	178	322	30	13	331	110	—	—	—	—	—	—
2014	21	A+ MLE	3 teams	—	556	489	106	32	1	16	58	174	4	2	1	217	307	384	691	168	288	31	10	305	92	—	—	—	—	—	—
2015	22	AA MLE	3 teams	—	540	486	121	29	1	21	42	124	7	1	1	249	317	442	760	193	290	23	8	328	108	—	—	—	—	—	—
2017	24	MLB MLE	3 teams	—	251	217	47	13	0	11	30	54	2	0	0	217	319	429	747	212	227	22	12	324	106	—	—	—	—	—	—
2018	25	MLB MLE	3 teams	—	349	307	59	16	1	13	34	89	5	0	0	192	284	378	662	186	222	26	10	291	83	—	—	—	—	—	—
2019	26	MLB MLE	2 teams	—	71	61	11	0	0	2	10	28	0	0	0	180	296	279	574	98	278	39	14	260	62	—	—	—	—	—	—
2021	28	AAA MLE	Albuquerque Isotopes	—	461	416	79	17	1	16	38	133	4	0	1	190	266	351	617	161	225	29	8	268	68	—	—	—	—	—	—
2022	29	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	240	217	38	7	1	4	19	73	2	2	0	175	247	272	519	97	233	30	8	231	42	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	700	611	129	32	1	32	74	189	8	0	0	211	304	424	728	213	244	27	11	321	66	+3	+0	-8	-22	+15	-1.1
/ 162G	—	A+C		—	650	567	120	30	1	30	69	176	7	0	0	212	304	427	731	215	245	27	11	321	66	+3	+0	-7	-20	+14	-1.1
Career	—	MLE		—	3508	3078	684	164	10	117	357	931	39	10	5	222	311	396	707	174	275	27	10	266	66	+3	+0	-8	-22	+15	-1.1
/ 162G	—	MLE		—	650	570	127	30	2	22	66	173	7	2	1	223	311	398	709	175	276	27	10	266	66	+3	+0	-7	-20	+14	-1.1

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 AAAScranton/Wilkes-Barre RailRiders · 240 PAwOBA .303 → .231 (−72)K% 25.4% → 30.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.42%	÷1.001	×1.200	—	—	30.46%
BB% (unintentional) /PA	12.50%	÷1.066	×0.690	—	×0.972	7.87%
HBP% /PA	0.83%	—	×0.940	—	×0.972	0.76%
Singles /BIP	20.69%	÷1.047	×0.930	×0.993	×0.972	17.73%
Doubles /BIP	5.52%	÷0.988	×0.830	×0.993	×0.972	4.47%
Triples /BIP	0.69%	÷1.000	×0.970	×0.993	×0.972	0.65%
Home runs /BIP	4.14%	÷1.006	×0.700	—	×0.972	2.80%

Factors used: league row International League. Park (home-season share, regressed): HR 101, 1B 109, 2B 98, 3B 100, K 100, 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.993.

Result: wOBA .303 → .231; ISO .136 → .100; BABIP .279 → .233. 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 AAAAlbuquerque Isotopes · 461 PAwOBA .382 → .268 (−114)K% 23.0% → 28.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.99%	÷0.958	×1.200	—	—	28.80%
BB% (unintentional) /PA	12.58%	÷1.032	×0.690	—	×0.982	8.26%
HBP% /PA	0.87%	—	×0.940	—	×0.982	0.80%
Singles /BIP	19.51%	÷1.110	×0.930	×0.971	×0.982	15.59%
Doubles /BIP	7.32%	÷0.988	×0.830	×0.971	×0.982	5.86%
Triples /BIP	0.35%	÷1.150	×0.920	×0.971	×0.982	0.27%
Home runs /BIP	9.41%	÷1.172	×0.700	—	×0.982	5.52%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 134, 1B 122, 2B 98, 3B 130, K 92, BB 106 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.971.

Result: wOBA .382 → .268; ISO .265 → .167; BABIP .293 → .225. 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 AATrenton Thunder · 20 PAwOBA .317 → .251 (−66)K% 10.0% → 12.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.00%	÷1.002	×1.220	—	—	12.17%
BB% (unintentional) /PA	25.00%	÷0.972	×0.700	—	×0.988	17.79%
HBP% /PA	0.00%	—	×0.850	—	×0.988	0.00%
Singles /BIP	7.69%	÷0.954	×0.970	—	×0.988	7.73%
Doubles /BIP	0.00%	÷1.042	×0.860	—	×0.988	0.00%
Triples /BIP	0.00%	÷0.944	×0.950	—	×0.988	0.00%
Home runs /BIP	7.69%	÷1.034	×0.780	—	×0.988	5.74%

Factors used: league row EL. Park (home-season share, regressed): HR 107, 1B 91, 2B 108, 3B 89, K 100, BB 94 — applied at half strength. Age: age 26 vs a level average of 24.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average).

Result: wOBA .317 → .251; ISO .200 → .161; BABIP .083 → .082. 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 · 18 PAwOBA .397 → .301 (−96)K% 38.9% → 46.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	38.89%	÷1.002	×1.200	—	—	46.59%
BB% (unintentional) /PA	11.11%	÷1.034	×0.690	—	×1.018	7.55%
HBP% /PA	0.00%	—	×0.940	—	×1.018	0.00%
Singles /BIP	22.22%	÷1.032	×0.930	—	×1.018	20.39%
Doubles /BIP	0.00%	÷1.004	×0.830	—	×1.018	0.00%
Triples /BIP	0.00%	÷1.130	×0.970	—	×1.018	0.00%
Home runs /BIP	22.22%	÷1.046	×0.840	—	×1.018	18.17%

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).

Result: wOBA .397 → .301; ISO .375 → .281; BABIP .286 → .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).

2017 AAAScranton/Wilkes-Barre RailRiders · 59 PAwOBA .427 → .358 (−68)K% 15.3% → 18.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.25%	÷0.995	×1.200	—	—	18.40%
BB% (unintentional) /PA	18.64%	÷1.105	×0.690	—	×1.033	12.03%
HBP% /PA	0.00%	—	×0.940	—	×1.033	0.00%
Singles /BIP	18.42%	÷0.980	×0.930	—	×1.033	18.06%
Doubles /BIP	10.53%	÷0.951	×0.830	—	×1.033	9.49%
Triples /BIP	0.00%	÷1.150	×0.970	—	×1.033	0.00%
Home runs /BIP	7.89%	÷1.247	×0.840	—	×1.033	5.50%

Factors used: league row IL. Park (home-season share, regressed): HR 149, 1B 96, 2B 90, 3B 130, K 99, BB 121 — 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).

Result: wOBA .427 → .358; ISO .277 → .227; BABIP .306 → .284. 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+Tampa Yankees · 22 PAwOBA .430 → .368 (−62)K% 4.5% → 6.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	4.55%	÷0.949	×1.420	—	—	6.80%
BB% (unintentional) /PA	22.73%	÷1.007	×0.750	—	×0.978	16.56%
HBP% /PA	0.00%	—	×0.930	—	×0.978	0.00%
Singles /BIP	25.00%	÷1.071	×0.920	—	×0.978	21.00%
Doubles /BIP	12.50%	÷0.995	×0.960	—	×0.978	11.80%
Triples /BIP	0.00%	÷1.031	×0.810	—	×0.978	0.00%
Home runs /BIP	0.00%	÷0.949	×0.880	—	×0.978	0.00%

Factors used: league row FSL. Park (home-season share, regressed): HR 90, 1B 114, 2B 99, 3B 106, K 90, BB 101 — applied at half strength. Age: age 25 vs a level average of 22.8 → −2.2% on BB/HBP/hit rates (2.2 yr older than average).

Result: wOBA .430 → .368; ISO .118 → .117; BABIP .375 → .328. 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 AATrenton Thunder · 212 PAwOBA .350 → .291 (−59)K% 14.2% → 18.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.15%	÷0.950	×1.220	—	—	18.17%
BB% (unintentional) /PA	10.85%	÷1.067	×0.700	—	×1.027	7.31%
HBP% /PA	2.36%	—	×0.850	—	×1.027	2.06%
Singles /BIP	16.45%	÷0.977	×0.970	×0.950	×1.027	15.93%
Doubles /BIP	10.53%	÷0.978	×0.860	×0.950	×1.027	9.03%
Triples /BIP	0.00%	÷1.150	×0.950	×0.950	×1.027	0.00%
Home runs /BIP	3.95%	÷1.153	×0.780	—	×1.027	2.74%

Factors used: league row EL. Park (home-season share, regressed): HR 131, 1B 95, 2B 96, 3B 130, K 90, BB 114 — 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 .350 → .291; ISO .187 → .146; BABIP .279 → .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).

2015 AAAScranton/Wilkes-Barre RailRiders · 150 PAwOBA .367 → .330 (−37)K% 18.0% → 21.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.00%	÷0.991	×1.200	—	—	21.80%
BB% (unintentional) /PA	7.33%	÷1.139	×0.690	—	×1.050	4.66%
HBP% /PA	0.67%	—	×0.940	—	×1.050	0.66%
Singles /BIP	24.77%	÷1.011	×0.930	×0.950	×1.050	22.73%
Doubles /BIP	6.42%	÷0.903	×0.830	×0.950	×1.050	5.89%
Triples /BIP	0.92%	÷1.150	×0.970	×0.950	×1.050	0.77%
Home runs /BIP	5.50%	÷0.878	×0.840	—	×1.050	5.53%

Factors used: league row IL. Park (home-season share, regressed): HR 76, 1B 102, 2B 81, 3B 130, K 98, BB 128 — 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 ×0.950.

Result: wOBA .367 → .330; ISO .199 → .193; BABIP .333 → .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).

Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .