Curt Casali

PosC

B/TR/R

Born1988-11-09

Age (2027)38

No MLB projection yet. Career stats below are historical.

Overview

MLBLAST SEASON 2024

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2022	33	MLBSEA	176	.203/.322/.331	5	0	91	0.6
2023	34	MLBCIN	96	.175/.290/.200	0	0	44	-0.1
2024	35	AAACHC	88	.362/.494/.551	2	0	136	—	.297/.402/.419
2024	35	MLBSF	125	.194/.293/.250	1	0	61	-0.2
2025	36	No MLB games played
2026	37	No MLB games played

Last 3 seasons WAR 0.4

Contract

No contract data on file.

Skills · percentileStatcast 2022-2024

xwOBA28

Barrel%13

Avg EV10

Speed10

Bat Spd10

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. Catcher framing: only 2027 Statcast framing is modeled (Baseball Savant server-caches the leaderboard to the current season); prior-year framing is unmodeled — projections for established framers may run 1-3 WAR low.

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)
2011	22	A	West Michigan Whitecaps	—	92	75	17	7	0	2	13	9	1	0	0	227	348	400	748	173	231	10	14	328	73	—	—	—	—	—	—
2012	23	A+	Lakeland Flying Tigers	—	179	160	40	13	0	1	11	28	6	0	0	250	322	350	672	100	298	16	6	304	55	—	—	—	—	—	—
2012	23	A	West Michigan Whitecaps	—	206	170	49	12	0	8	27	18	6	2	1	288	404	500	904	212	283	9	13	396	110	—	—	—	—	—	—
2013	24	AA	Montgomery Biscuits	—	145	120	46	11	0	5	21	18	3	0	0	383	486	600	1.086	217	418	12	14	473	145	—	—	—	—	—	—
2013	24	A+	Charlotte Stone Crabs	—	184	165	44	6	1	5	18	31	1	1	0	267	342	406	748	139	302	17	10	337	73	—	—	—	—	—	—
2014	25	MLB	Tampa Bay Rays	—	84	72	12	3	0	0	8	23	2	0	0	167	268	208	477	42	245	27	10	227	39	-6	+0	+2	+6	+2	0.4
2014	25	AAA	Durham Bulls	—	183	156	37	10	0	3	22	50	2	0	0	237	339	359	698	122	324	27	12	315	66	—	—	—	—	—	—
2014	25	AA	Montgomery Biscuits	—	96	70	22	5	0	1	23	16	3	0	0	314	500	429	929	114	396	17	24	430	138	—	—	—	—	—	—
2015	26	MLB	Tampa Bay Rays	—	113	101	24	6	0	10	8	34	2	0	0	238	306	594	900	356	241	30	7	379	146	+6	+0	+2	+4	+2	1.6
2015	26	AAA	Durham Bulls	—	132	112	23	4	0	4	17	29	3	1	0	205	326	348	674	143	241	22	13	311	50	—	—	—	—	—	—
2016	27	MLB	Tampa Bay Rays	—	256	226	42	10	0	8	25	82	2	0	0	186	273	336	609	150	250	32	10	274	71	-9	+0	+11	+6	+6	1.4
2016	27	AAA	Durham Bulls	—	81	63	16	1	0	2	15	12	2	0	0	254	412	365	778	111	280	15	19	360	78	—	—	—	—	—	—
2017	28	AAA	Durham Bulls	—	343	300	79	10	0	5	37	65	4	0	0	263	352	347	699	83	320	19	11	320	61	—	—	—	—	—	—
2018	29	MLB	Cincinnati Reds	—	156	140	41	10	0	4	12	32	2	0	2	293	357	450	807	157	352	21	8	355	120	+4	-1	-5	+5	+3	0.6
2018	29	AAA	Durham Bulls	—	104	95	26	5	0	4	7	19	1	0	0	274	330	453	783	179	301	18	7	344	76	—	—	—	—	—	—
2019	30	MLB	Cincinnati Reds	—	236	207	52	9	0	8	25	59	1	0	0	251	335	411	745	159	308	25	11	331	103	+1	+0	+5	+4	+5	1.6
2019	30	AAA	Louisville Bats	—	15	14	3	0	0	1	1	3	0	0	0	214	267	429	695	214	200	20	7	306	46	—	—	—	—	—	—
2020	31	MLB	Cincinnati Reds	—	93	76	17	3	0	6	14	29	3	2	0	224	366	500	866	276	268	31	15	382	136	+4	+0	+1	+2	+2	0.9
2021	32	MLB	San Francisco Giants	—	231	200	42	11	1	5	26	66	4	0	0	210	313	350	663	140	287	29	11	302	86	-4	+0	+2	+4	+5	0.8
2022	33	MLB	Seattle Mariners	—	176	148	30	4	0	5	24	50	2	0	0	203	322	331	653	128	263	28	14	300	91	-2	+0	+0	+4	+4	0.6
2022	33	AAA	Tacoma Rainiers	—	24	20	4	1	0	0	3	10	1	0	0	200	333	250	583	50	400	42	12	284	32	—	—	—	—	—	—
2023	34	MLB	Cincinnati Reds	—	96	80	14	2	0	0	11	23	2	0	0	175	290	200	490	25	246	24	11	235	44	-6	+0	+2	+2	+2	-0.1
2023	34	AAA	Louisville Bats	—	24	23	6	1	0	0	0	7	1	0	0	261	292	304	596	43	375	29	0	273	31	—	—	—	—	—	—
2024	35	MLB	San Francisco Giants	—	125	108	21	3	0	1	13	22	2	0	0	194	293	250	543	56	235	18	10	255	61	-6	+0	-2	+4	+3	-0.2
2024	35	AAA	Iowa Cubs	—	88	69	25	7	0	2	15	16	3	0	0	362	494	551	1.045	188	442	18	17	458	136	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1566	1358	295	61	1	47	166	420	22	2	2	217	312	367	680	150	276	27	11	305	93	-14	-0	+18	+41	+34	8.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2011	22	A MLE	West Michigan Whitecaps	—	92	80	17	7	0	2	8	13	1	0	0	212	292	375	667	163	208	14	9	276	73	—	—	—	—	—	—
2012	23	A+ MLE	Lakeland Flying Tigers	—	179	163	34	12	0	1	8	40	6	0	0	209	271	301	572	92	266	22	4	250	55	—	—	—	—	—	—
2012	23	A MLE	West Michigan Whitecaps	—	206	180	46	11	0	8	17	25	6	2	1	256	340	450	790	194	249	12	8	331	110	—	—	—	—	—	—
2013	24	AA MLE	Montgomery Biscuits	—	145	128	41	10	0	4	13	22	3	0	0	320	396	492	888	172	356	15	9	382	145	—	—	—	—	—	—
2013	24	A+ MLE	Charlotte Stone Crabs	—	184	170	37	5	1	4	13	46	1	1	0	218	277	329	607	112	282	25	7	276	73	—	—	—	—	—	—
2014	25	MLB MLE	Tampa Bay Rays	—	84	72	12	3	0	0	8	23	2	0	0	167	268	208	477	42	245	27	10	226	39	-6	+0	+2	+6	+2	0.4
2014	25	AAA MLE	Durham Bulls	—	183	162	34	8	0	3	16	56	2	0	0	210	289	315	604	105	289	31	9	266	66	—	—	—	—	—	—
2014	25	AA MLE	Montgomery Biscuits	—	96	77	23	5	0	1	16	19	3	0	0	299	438	403	840	104	380	20	17	372	138	—	—	—	—	—	—
2015	26	MLB MLE	Tampa Bay Rays	—	113	101	24	6	0	10	8	34	2	0	0	238	306	594	900	356	241	30	7	384	146	+6	+0	+2	+4	+2	1.6
2015	26	AAA MLE	Durham Bulls	—	132	119	20	3	0	3	10	34	3	1	0	168	250	269	519	101	209	26	8	242	50	—	—	—	—	—	—
2016	27	MLB MLE	Tampa Bay Rays	—	256	227	42	10	0	8	24	82	2	0	0	185	269	335	604	150	250	32	9	272	71	-9	+0	+11	+6	+6	1.4
2016	27	AAA MLE	Durham Bulls	—	81	69	15	1	0	2	9	14	2	0	0	217	325	319	644	101	237	17	11	284	78	—	—	—	—	—	—
2017	28	AAA MLE	Durham Bulls	—	343	313	70	8	0	4	24	76	4	0	0	224	287	288	575	64	278	22	7	259	61	—	—	—	—	—	—
2018	29	MLB MLE	Cincinnati Reds	—	156	141	41	10	0	4	11	32	2	0	2	291	351	447	797	156	352	21	7	346	120	+4	-1	-5	+5	+3	0.6
2018	29	AAA MLE	Durham Bulls	—	104	97	22	4	0	3	5	22	1	0	0	227	272	361	633	134	258	21	5	281	76	—	—	—	—	—	—
2019	30	MLB MLE	Cincinnati Reds	—	236	208	51	9	0	7	24	59	1	0	0	245	326	389	716	144	308	25	10	321	103	+1	+0	+5	+4	+5	1.6
2019	30	AAA MLE	Louisville Bats	—	15	14	3	0	0	1	1	4	0	0	0	214	267	429	695	214	173	27	7	236	46	—	—	—	—	—	—
2020	31	MLB MLE	Cincinnati Reds	—	93	76	17	3	0	6	14	29	3	2	0	224	366	500	866	276	268	31	15	370	136	+4	+0	+1	+2	+2	0.9
2021	32	MLB MLE	San Francisco Giants	—	231	204	42	11	1	5	22	66	4	0	0	206	296	343	639	137	287	29	10	295	86	-4	+0	+2	+4	+5	0.8
2022	33	MLB MLE	Seattle Mariners	—	176	148	30	4	0	5	24	50	2	0	0	203	322	331	653	128	263	28	14	302	91	-2	+0	+0	+4	+4	0.6
2022	33	AAA MLE	Tacoma Rainiers	—	24	21	3	1	0	0	2	12	1	0	0	143	250	190	440	48	352	50	8	216	32	—	—	—	—	—	—
2023	34	MLB MLE	Cincinnati Reds	—	96	80	14	2	0	0	11	23	2	0	0	175	290	200	490	25	246	24	11	233	44	-6	+0	+2	+2	+2	-0.1
2023	34	AAA MLE	Louisville Bats	—	24	23	5	1	0	0	0	8	1	0	0	217	250	261	511	43	326	33	0	214	31	—	—	—	—	—	—
2024	35	MLB MLE	San Francisco Giants	—	125	108	21	3	0	1	13	22	2	0	0	194	293	250	543	56	235	18	10	258	61	-6	+0	-2	+4	+3	-0.2
2024	35	AAA MLE	Iowa Cubs	—	88	74	22	6	0	1	10	19	3	0	0	297	402	419	821	122	375	22	11	369	136	—	—	—	—	—	—
2011	22	A MLE	West Michigan Whitecaps	—	92	80	17	7	0	2	8	13	1	0	0	212	292	375	667	163	227	14	9	276	73	—	—	—	—	—	—
2011	22	A RAW	West Michigan Whitecaps	—	92	75	17	7	0	2	13	9	1	0	0	227	348	400	748	173	231	10	14	328	73	—	—	—	—	—	—
2012	23	A MLE	2 teams	—	385	343	80	23	0	8	25	65	12	2	1	233	308	370	678	137	266	17	6	293	85	—	—	—	—	—	—
2012	23	A RAW	2 teams	—	385	330	89	25	0	9	38	46	12	2	1	270	366	427	793	158	290	12	10	353	85	—	—	—	—	—	—
2013	24	A+ MLE	2 teams	—	329	297	79	15	1	8	27	69	4	1	0	266	335	404	739	138	321	21	8	323	105	—	—	—	—	—	—
2013	24	A+ RAW	2 teams	—	329	285	90	17	1	10	39	49	4	1	0	316	405	488	893	172	352	15	12	397	105	—	—	—	—	—	—
2014	25	AAA MLE	3 teams	—	363	310	68	16	0	3	41	98	7	0	0	219	324	300	624	81	308	27	11	285	79	—	—	—	—	—	—
2014	25	AAA RAW	3 teams	—	363	298	71	18	0	4	53	89	7	0	0	238	366	339	705	101	324	25	15	325	79	—	—	—	—	—	—
2015	26	AAA MLE	2 teams	—	245	220	45	9	0	14	18	68	5	1	0	205	280	436	716	232	223	28	7	308	94	—	—	—	—	—	—
2015	26	AAA RAW	2 teams	—	245	213	47	10	0	14	25	63	5	1	0	221	317	465	782	244	241	26	10	342	94	—	—	—	—	—	—
2016	27	MLB MLE	2 teams	—	337	296	57	11	0	10	33	96	4	0	0	193	282	331	613	139	246	28	10	275	72	-11	+0	+11	+6	+7	1.3
2016	27	MLB RAW	2 teams	—	337	289	58	11	0	10	40	94	4	0	0	201	306	343	649	142	258	28	12	295	72	-11	+0	+11	+6	+7	1.3
2017	28	AAA MLE	Durham Bulls	—	343	313	70	8	0	4	24	76	4	0	0	224	287	288	575	64	282	22	7	259	61	—	—	—	—	—	—
2017	28	AAA RAW	Durham Bulls	—	343	300	79	10	0	5	37	65	4	0	0	263	352	347	699	83	320	19	11	320	61	—	—	—	—	—	—
2018	29	MLB MLE	2 teams	—	260	238	63	14	0	7	16	54	3	0	2	265	319	412	731	147	313	21	6	320	103	+1	-1	-5	+5	+6	0.6
2018	29	MLB RAW	2 teams	—	260	235	67	15	0	8	19	51	3	0	2	285	346	451	797	166	331	20	7	351	103	+1	-1	-5	+5	+6	0.6
2019	30	MLB MLE	2 teams	—	251	222	54	9	0	8	25	63	1	0	0	243	323	392	714	149	299	25	10	316	100	-0	+0	+5	+4	+5	1.5
2019	30	MLB RAW	2 teams	—	251	221	55	9	0	9	26	62	1	0	0	249	331	412	742	163	301	25	10	329	100	-0	+0	+5	+4	+5	1.5
2020	31	MLB MLE	Cincinnati Reds	—	93	76	17	3	0	6	14	29	3	2	0	224	366	500	866	276	268	31	15	370	136	+4	+0	+1	+2	+2	0.9
2020	31	MLB RAW	Cincinnati Reds	—	93	76	17	3	0	6	14	29	3	2	0	224	366	500	866	276	268	31	15	382	136	+4	+0	+1	+2	+2	0.9
2021	32	MLB MLE	San Francisco Giants	—	231	204	42	11	1	5	22	66	4	0	0	206	296	343	639	137	278	29	10	295	86	-4	+0	+2	+4	+5	0.8
2021	32	MLB RAW	San Francisco Giants	—	231	200	42	11	1	5	26	66	4	0	0	210	313	350	663	140	287	29	11	302	86	-4	+0	+2	+4	+5	0.8
2022	33	MLB MLE	2 teams	—	200	169	34	5	0	5	26	62	3	0	0	201	318	320	638	118	279	31	13	292	84	-4	+0	+0	+4	+4	0.5
2022	33	MLB RAW	2 teams	—	200	168	34	5	0	5	27	60	3	0	0	202	323	321	645	119	276	30	14	298	84	-4	+0	+0	+4	+4	0.5
2023	34	MLB MLE	2 teams	—	120	103	19	3	0	0	11	31	3	0	0	184	282	214	496	29	264	26	9	229	41	-8	+0	+2	+2	+3	-0.2
2023	34	MLB RAW	2 teams	—	120	103	20	3	0	0	11	30	3	0	0	194	291	223	514	29	274	25	9	243	41	-8	+0	+2	+2	+3	-0.2
2024	35	MLB MLE	2 teams	—	213	182	43	9	0	2	23	41	5	0	0	236	338	319	657	82	293	19	11	304	92	-2	+0	-2	+4	+5	0.4
2024	35	MLB RAW	2 teams	—	213	177	46	10	0	3	28	38	5	0	0	260	376	367	743	107	314	18	13	339	92	-2	+0	-2	+4	+5	0.4
2011	22	A MLE	West Michigan Whitecaps	—	92	83	17	7	0	2	8	13	1	0	0	205	292	361	654	157	208	14	9	276	73	—	—	—	—	—	—
2012	23	A MLE	2 teams	—	385	345	80	23	0	8	25	65	12	2	1	232	308	368	676	136	257	17	6	293	85	—	—	—	—	—	—
2013	24	A+ MLE	2 teams	—	329	295	79	15	1	8	27	69	4	1	0	268	335	407	742	139	315	21	8	323	105	—	—	—	—	—	—
2014	25	AAA MLE	3 teams	—	363	312	68	16	0	3	41	98	7	0	0	218	324	298	622	80	303	27	11	285	79	—	—	—	—	—	—
2015	26	AAA MLE	2 teams	—	245	220	45	9	0	14	18	68	5	1	0	205	280	436	716	232	224	28	7	308	94	—	—	—	—	—	—
2016	27	MLB MLE	2 teams	—	337	297	57	11	0	10	33	96	4	0	0	192	282	330	612	138	247	28	10	275	72	—	—	—	—	—	—
2017	28	AAA MLE	Durham Bulls	—	343	312	70	8	0	4	24	76	4	0	0	224	287	288	576	64	278	22	7	259	61	—	—	—	—	—	—
2018	29	MLB MLE	2 teams	—	260	239	63	14	0	7	16	54	3	0	2	264	319	410	729	146	315	21	6	320	103	—	—	—	—	—	—
2019	30	MLB MLE	2 teams	—	251	223	54	9	0	8	25	63	1	0	0	242	323	390	713	148	300	25	10	316	100	—	—	—	—	—	—
2020	31	MLB MLE	Cincinnati Reds	—	93	76	17	3	0	6	14	29	3	2	0	224	366	500	866	276	268	31	15	370	136	—	—	—	—	—	—
2021	32	MLB MLE	San Francisco Giants	—	231	203	42	11	1	5	22	66	4	0	0	207	296	345	640	138	287	29	10	295	86	—	—	—	—	—	—
2022	33	MLB MLE	2 teams	—	200	169	34	5	0	5	26	62	3	0	0	201	318	320	638	118	274	31	13	292	84	—	—	—	—	—	—
2023	34	MLB MLE	2 teams	—	120	105	19	3	0	0	11	31	3	0	0	181	282	210	492	29	262	26	9	229	41	—	—	—	—	—	—
2024	35	MLB MLE	2 teams	—	213	183	43	9	0	2	23	41	5	0	0	235	338	317	655	82	293	19	11	304	92	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	35	MLB MLE	2 teams	—	213	183	43	9	0	2	23	41	5	0	0	235	338	317	655	82	293	19	11	304	92	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1566	1358	295	61	1	47	166	420	22	2	2	217	312	367	680	150	276	27	11	305	86	-14	-0	+18	+41	+34	8.1
/ 162G	—	A+C		—	650	564	122	25	0	20	69	174	9	1	1	216	312	367	679	151	273	27	11	305	86	-6	-0	+8	+17	+14	3.4
Career	—	MLE		—	3462	3053	688	143	2	82	313	831	59	6	3	225	309	354	664	129	281	24	9	295	86	-14	-0	+18	+41	+34	8.1
/ 162G	—	MLE		—	650	573	129	27	0	15	59	156	11	1	1	225	309	351	660	126	281	24	9	295	86	-6	-0	+8	+17	+14	3.4

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.

2024 AAAIowa Cubs · 88 PAwOBA .452 → .369 (−83)K% 18.2% → 21.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.18%	÷0.998	×1.200	—	—	21.87%
BB% (unintentional) /PA	17.05%	÷0.949	×0.690	—	×0.940	11.65%
HBP% /PA	3.41%	—	×0.940	—	×0.940	3.01%
Singles /BIP	30.19%	÷0.994	×0.930	—	×0.940	26.56%
Doubles /BIP	13.21%	÷0.962	×0.830	—	×0.940	10.72%
Triples /BIP	0.00%	÷1.000	×0.970	—	×0.940	0.00%
Home runs /BIP	3.77%	÷1.079	×0.700	—	×0.940	2.30%

Factors used: league row International League. Park (home-season share, regressed): HR 116, 1B 99, 2B 92, 3B 100, K 100, BB 90 — applied at half strength. Age: age 36 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (8.8 yr older than average).

Result: wOBA .452 → .369; ISO .188 → .143; BABIP .442 → .375. 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 AAALouisville Bats · 24 PAwOBA .265 → .214 (−51)K% 29.2% → 34.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	29.17%	÷1.004	×1.200	—	—	34.85%
BB% (unintentional) /PA	0.00%	÷0.993	×0.690	—	×0.940	0.00%
HBP% /PA	4.17%	—	×0.940	—	×0.940	3.68%
Singles /BIP	31.25%	÷0.998	×0.930	—	×0.940	27.37%
Doubles /BIP	6.25%	÷0.938	×0.830	—	×0.940	5.20%
Triples /BIP	0.00%	÷1.042	×0.970	—	×0.940	0.00%
Home runs /BIP	0.00%	÷1.054	×0.700	—	×0.940	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 111, 1B 100, 2B 88, 3B 108, K 101, BB 99 — applied at half strength. Age: age 35 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (7.8 yr older than average).

Result: wOBA .265 → .214; ISO .043 → .033; BABIP .375 → .326. 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 AAATacoma Rainiers · 24 PAwOBA .278 → .216 (−62)K% 41.7% → 49.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	41.67%	÷1.020	×1.200	—	—	49.04%
BB% (unintentional) /PA	12.50%	÷1.048	×0.690	—	×0.940	7.74%
HBP% /PA	4.17%	—	×0.940	—	×0.940	3.68%
Singles /BIP	30.00%	÷1.013	×0.930	—	×0.940	25.88%
Doubles /BIP	10.00%	÷0.839	×0.830	—	×0.940	9.30%
Triples /BIP	0.00%	÷0.902	×0.970	—	×0.940	0.00%
Home runs /BIP	0.00%	÷1.144	×0.700	—	×0.940	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 129, 1B 103, 2B 68, 3B 80, K 104, BB 110 — applied at half strength. Age: age 34 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (6.8 yr older than average).

Result: wOBA .278 → .216; ISO .050 → .044; BABIP .400 → .352. 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 AAALouisville Bats · 15 PAwOBA .297 → .236 (−61)K% 20.0% → 25.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.00%	÷0.960	×1.200	—	—	24.99%
BB% (unintentional) /PA	6.67%	÷1.151	×0.690	—	×0.962	3.85%
HBP% /PA	0.00%	—	×0.940	—	×0.962	0.00%
Singles /BIP	18.18%	÷1.018	×0.930	—	×0.962	15.99%
Doubles /BIP	0.00%	÷1.082	×0.830	—	×0.962	0.00%
Triples /BIP	0.00%	÷1.150	×0.970	—	×0.962	0.00%
Home runs /BIP	9.09%	÷0.957	×0.840	—	×0.962	7.67%

Factors used: league row IL. Park (home-season share, regressed): HR 91, 1B 104, 2B 116, 3B 130, K 92, BB 130 — 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 .297 → .236; ISO .214 → .176; BABIP .200 → .173. 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 AAADurham Bulls · 104 PAwOBA .337 → .281 (−57)K% 18.3% → 21.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.27%	÷1.032	×1.200	—	—	21.24%
BB% (unintentional) /PA	6.73%	÷0.986	×0.690	—	×0.972	4.58%
HBP% /PA	0.96%	—	×0.940	—	×0.972	0.88%
Singles /BIP	22.37%	÷1.052	×0.930	×1.038	×0.972	19.95%
Doubles /BIP	6.58%	÷1.091	×0.830	×1.038	×0.972	5.05%
Triples /BIP	0.00%	÷0.993	×0.970	×1.038	×0.972	0.00%
Home runs /BIP	5.26%	÷0.970	×0.840	—	×0.972	4.43%

Factors used: league row IL. Park (home-season share, regressed): HR 94, 1B 110, 2B 118, 3B 99, K 106, BB 97 — 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 ×1.038.

Result: wOBA .337 → .281; ISO .179 → .147; BABIP .301 → .258. 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 AAADurham Bulls · 343 PAwOBA .311 → .259 (−52)K% 19.0% → 22.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.95%	÷1.027	×1.200	—	—	22.14%
BB% (unintentional) /PA	10.20%	÷0.993	×0.690	—	×0.982	6.97%
HBP% /PA	1.17%	—	×0.940	—	×0.982	1.08%
Singles /BIP	27.23%	÷1.025	×0.930	×0.991	×0.982	24.04%
Doubles /BIP	4.26%	÷1.008	×0.830	×0.991	×0.982	3.41%
Triples /BIP	0.00%	÷1.022	×0.970	×0.991	×0.982	0.00%
Home runs /BIP	2.13%	÷1.049	×0.840	—	×0.982	1.67%

Factors used: league row IL. Park (home-season share, regressed): HR 110, 1B 105, 2B 102, 3B 104, K 105, BB 99 — 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 ×0.991.

Result: wOBA .311 → .259; ISO .083 → .067; BABIP .320 → .278. 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 AAADurham Bulls · 81 PAwOBA .356 → .284 (−73)K% 14.8% → 17.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.81%	÷0.994	×1.200	—	—	17.89%
BB% (unintentional) /PA	18.52%	÷1.082	×0.690	—	×0.992	11.71%
HBP% /PA	2.47%	—	×0.940	—	×0.992	2.30%
Singles /BIP	25.49%	÷1.010	×0.930	×0.950	×0.992	22.11%
Doubles /BIP	1.96%	÷1.093	×0.830	×0.950	×0.992	1.40%
Triples /BIP	0.00%	÷0.900	×0.970	×0.950	×0.992	0.00%
Home runs /BIP	3.92%	÷1.167	×0.840	—	×0.992	2.80%

Factors used: league row IL. Park (home-season share, regressed): HR 133, 1B 102, 2B 119, 3B 80, K 99, BB 116 — 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 ×0.950.

Result: wOBA .356 → .284; ISO .111 → .086; BABIP .280 → .237. 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 AAADurham Bulls · 132 PAwOBA .304 → .242 (−62)K% 22.0% → 25.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.97%	÷1.025	×1.200	—	—	25.72%
BB% (unintentional) /PA	12.88%	÷1.148	×0.690	—	×1.003	7.76%
HBP% /PA	2.27%	—	×0.940	—	×1.003	2.14%
Singles /BIP	18.07%	÷1.025	×0.930	×0.992	×1.003	16.32%
Doubles /BIP	4.82%	÷1.062	×0.830	×0.992	×1.003	3.75%
Triples /BIP	0.00%	÷0.900	×0.970	×0.992	×1.003	0.00%
Home runs /BIP	4.82%	÷1.039	×0.840	—	×1.003	3.91%

Factors used: league row IL. Park (home-season share, regressed): HR 108, 1B 105, 2B 112, 3B 80, K 105, BB 130 — 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 ×0.992.

Result: wOBA .304 → .242; ISO .143 → .117; BABIP .241 → .209. 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).