The Z Files: Pitcher Streaming -- A Cautionary Tale

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Updated on July 13, 2022 6:41PM EST

The best lineups to stream against were presented in the most recent Weekly Pitching Rankings. They were listed by handedness, with each team's year-to-date K%, BB%, HR% and wOBA included.

The implication is if you want strikeouts, stream against lineups with a high K%. If you need run prevention, pick on offenses with a low wOBA. If your pitcher is wild, use him against teams with a low BB% or if he's homer-prone, deploy against clubs with the lowest HR%.

Seems intuitive, no?

Unfortunately, I broke one of the cardinal rules of analysis. For that I apologize. As someone with an advanced science degree, doing so was even more egregious.

You see, I have no evidence that how a team has performed to date reflects current expectations. If the tables had been data from the last "X" weeks, the same would be true. I don't know the proper sample to use to gauge current expectations. Maybe it exists, and I'm just not aware. However, since this information would be the Holy Grail of daily fantasy, DFS and betting, I have to think if it were truly known, the research and data would be publicly accessible.

Making matters worse is, I posted the tables (and provided advice) knowing I can't validate its efficacy. The fact everyone does the same does not make it right.

The problem is, there has to be a reason why the proper time frame isn't public knowledge. At one extreme, everyone just assumes year-to-date stats are

The best lineups to stream against were presented in the most recent Weekly Pitching Rankings. They were listed by handedness, with each team's year-to-date K%, BB%, HR% and wOBA included.

Seems intuitive, no?

Unfortunately, I broke one of the cardinal rules of analysis. For that I apologize. As someone with an advanced science degree, doing so was even more egregious.

Making matters worse is, I posted the tables (and provided advice) knowing I can't validate its efficacy. The fact everyone does the same does not make it right.

The problem is, there has to be a reason why the proper time frame isn't public knowledge. At one extreme, everyone just assumes year-to-date stats are the best predictor and doesn't dig deeper. At the other, there is no correct answer.

My gut sense is the answer is somewhere in between. There may not be a perfect sample size, but there is likely a range in which the probability is highest. This has long been on my Toddy-do list, but something else has always taken greater priority. Unfortunately, this is more than an All-Star break project, so once again I'm planning on addressing it in the offseason.

The best I can do now is demonstrate why year-to-date metrics could be misleading. What follows is a team by team breakdown of plate appearances, wOBA, K%, BB%, HR% and BABIP against left-handed and right-handed pitching. The data is pulled through July 11. At that time, there was an average of 87 games played per team. Choosing to break the data into 29-game segments (one-third of 87 games) is arbitrary but serves to show the noise within the sample, and the perils of making unsubstantiated assumptions.

Period 1: April 7 - May 9
Period 2: May 10 - June 10
Period 3: June 11 - July 11

PA versus RHP

	Team	1	2	3	Full	StDev
1	Angels	811	766	703	2280	54.249
2	Astros	716	822	707	2245	63.956
3	Athletics	771	746	696	2213	38.188
4	Blue Jays	893	861	883	2637	16.371
5	Atlanta	770	793	836	2399	33.501
6	Brewers	804	783	781	2368	12.741
7	Cardinals	842	914	921	2677	43.730
8	Cubs	669	930	789	2388	130.641
9	D-backs	828	815	691	2334	75.624
10	Dodgers	671	918	729	2318	129.160
11	Giants	845	798	689	2332	80.027
12	Guardians	790	683	801	2274	65.184
13	Mariners	786	816	803	2405	15.044
14	Marlins	832	797	893	2522	48.583
15	Mets	861	749	616	2226	122.650
16	Nationals	767	799	657	2223	74.485
17	Orioles	736	753	754	2243	10.116
18	Padres	795	787	721	2303	40.612
19	Phillies	760	778	788	2326	14.189
20	Pirates	737	676	670	2083	37.072
21	Rangers	647	781	841	2269	99.324
22	Rays	846	731	838	2415	64.211
23	Red Sox	834	917	762	2513	77.565
24	Reds	726	766	793	2285	33.710
25	Rockies	758	836	624	2218	107.226
26	Royals	721	842	783	2346	60.506
27	Tigers	722	774	819	2315	48.542
28	Twins	653	935	830	2418	142.524
29	White Sox	812	831	949	2592	74.223
30	Yankees	736	797	793	2326	34.122

PA versus LHP

		1	2	3	Full	StDev
1	Angels	337	314	272	923	32.960
2	Astros	349	276	311	936	36.510
3	Athletics	260	370	295	925	56.199
4	Blue Jays	201	187	268	656	43.294
5	Atlanta	330	315	274	919	28.989
6	Brewers	297	346	255	898	45.545
7	Cardinals	208	280	208	696	41.569
8	Cubs	356	224	324	904	68.857
9	D-backs	262	303	337	902	37.554
10	Dodgers	337	294	300	931	23.288
11	Giants	245	295	359	899	57.143
12	Guardians	318	242	335	895	49.521
13	Mariners	339	276	263	878	40.649
14	Marlins	256	233	157	646	51.811
15	Mets	279	409	393	1081	70.890
16	Nationals	359	330	378	1067	24.173
17	Orioles	353	376	288	1017	45.640
18	Padres	330	316	414	1060	53.003
19	Phillies	315	342	298	955	22.189
20	Pirates	295	320	457	1072	87.214
21	Rangers	347	326	195	868	82.367
22	Rays	272	276	238	786	20.881
23	Red Sox	237	277	330	844	46.651
24	Reds	313	311	255	879	32.924
25	Rockies	325	287	469	1081	96.007
26	Royals	227	335	307	869	56.048
27	Tigers	282	231	279	792	28.618
28	Twins	401	266	239	906	86.793
29	White Sox	203	234	203	640	17.898
30	Yankees	305	355	276	936	39.962

Standard deviation is included to illustrate "games" may not be the best measure. Perhaps plate appearances is better. As can be witnessed via the standard deviation, the number of plate appearances within the game sample can vary by a lot.

The conundrum is, the proper sample is likely a balance between one large enough to flesh out biases, but short enough so the composition of the lineup hasn't changed enough to affect the team results. Complicating matters is teams accrue fewer plate appearances facing southpaws, so by the time a lineup achieves the requisite number of plate appearances against lefties, the lineup may be significantly different. That said, we're dealing with probabilities, not absolutes, so it will likely be the sample against LHP simply isn't as reliable as it is against RHP.

wOBA versus RHP

	Team	1	2	3	Full	StDev
1	Angels	0.318	0.304	0.280	0.302	0.019
2	Astros	0.298	0.330	0.351	0.326	0.027
3	Athletics	0.248	0.264	0.259	0.257	0.008
4	Blue Jays	0.299	0.342	0.336	0.326	0.023
5	Atlanta	0.299	0.308	0.350	0.320	0.027
6	Brewers	0.311	0.315	0.337	0.321	0.014
7	Cardinals	0.285	0.322	0.311	0.306	0.019
8	Cubs	0.296	0.321	0.317	0.312	0.013
9	D-backs	0.287	0.317	0.291	0.299	0.016
10	Dodgers	0.320	0.335	0.342	0.333	0.011
11	Giants	0.308	0.319	0.297	0.309	0.011
12	Guardians	0.332	0.294	0.314	0.314	0.019
13	Mariners	0.303	0.323	0.289	0.305	0.017
14	Marlins	0.306	0.351	0.276	0.310	0.038
15	Mets	0.329	0.326	0.296	0.319	0.018
16	Nationals	0.308	0.308	0.297	0.304	0.006
17	Orioles	0.304	0.284	0.304	0.297	0.012
18	Padres	0.287	0.292	0.315	0.298	0.015
19	Phillies	0.316	0.317	0.296	0.310	0.012
20	Pirates	0.289	0.278	0.306	0.291	0.014
21	Rangers	0.254	0.301	0.313	0.292	0.031
22	Rays	0.304	0.269	0.311	0.295	0.023
23	Red Sox	0.268	0.346	0.318	0.312	0.040
24	Reds	0.279	0.309	0.294	0.294	0.015
25	Rockies	0.303	0.303	0.293	0.300	0.006
26	Royals	0.263	0.316	0.302	0.295	0.027
27	Tigers	0.250	0.261	0.274	0.262	0.012
28	Twins	0.302	0.340	0.335	0.328	0.021
29	White Sox	0.262	0.279	0.323	0.290	0.031
30	Yankees	0.305	0.344	0.342	0.331	0.022

wOBA versus LHP

	Team	1	2	3	Full	StDev
1	Angels	0.323	0.284	0.269	0.294	0.028
2	Astros	0.288	0.330	0.347	0.320	0.030
3	Athletics	0.275	0.285	0.284	0.282	0.006
4	Blue Jays	0.299	0.359	0.307	0.319	0.033
5	Atlanta	0.310	0.387	0.317	0.338	0.043
6	Brewers	0.293	0.274	0.349	0.301	0.039
7	Cardinals	0.356	0.295	0.342	0.327	0.032
8	Cubs	0.298	0.346	0.310	0.314	0.025
9	D-backs	0.256	0.298	0.323	0.295	0.034
10	Dodgers	0.285	0.354	0.318	0.317	0.035
11	Giants	0.299	0.341	0.307	0.316	0.022
12	Guardians	0.275	0.282	0.252	0.268	0.016
13	Mariners	0.292	0.319	0.333	0.313	0.021
14	Marlins	0.281	0.243	0.306	0.273	0.032
15	Mets	0.281	0.326	0.310	0.309	0.023
16	Nationals	0.284	0.324	0.288	0.298	0.022
17	Orioles	0.259	0.307	0.318	0.294	0.031
18	Padres	0.309	0.334	0.283	0.306	0.026
19	Phillies	0.315	0.337	0.338	0.330	0.013
20	Pirates	0.304	0.272	0.281	0.285	0.017
21	Rangers	0.308	0.333	0.375	0.332	0.034
22	Rays	0.325	0.286	0.320	0.310	0.021
23	Red Sox	0.275	0.373	0.358	0.339	0.053
24	Reds	0.265	0.353	0.334	0.316	0.046
25	Rockies	0.356	0.310	0.347	0.340	0.024
26	Royals	0.276	0.308	0.341	0.311	0.033
27	Tigers	0.297	0.271	0.341	0.305	0.035
28	Twins	0.321	0.301	0.301	0.310	0.012
29	White Sox	0.334	0.379	0.306	0.342	0.037
30	Yankees	0.331	0.302	0.361	0.329	0.030

It's a crude measure, but the average standard deviation versus RHP (.019) is less than versus LHP (.028). This makes sense since there is more noise within a smaller sample.

Let's cherry-pick some teams with misleading results. For the first two periods, the Angels and Atlanta were pretty close in wOBA versus RHP. However, for the third period, the Angels were one of the best teams against which to stream right-handers, while Atlanta was one of the worst. After the first period, the Red Sox appeared meek facing southpaws, but they crushed them over the next 58 games.

My takeaway is rest-of-season expectations could be more important that actual team performance, given there is a relationship between the two as expectations are seasoned with what's been done. Further, and this is obvious but impossible to foresee without a crystal ball, judgements should be made on a game-by-game basis, fueled by that day's starting lineup.

Even so, the goal is probability, so we can still determine the optimal sample to decide if a pitcher should be streamed in a two-start week, even if we don't know the Tuesday and Sunday lineups he'll be facing.

Let's finish the story with the tables for the other metrics. BABIP is included to display luck is also a factor, not to mention a driving force for wOBA.

K% versus RHP

	Team	1	2	3	Full	StDev
1	Angels	25.0%	25.7%	30.2%	26.8%	2.8%
2	Astros	22.8%	19.1%	19.1%	20.3%	2.1%
3	Athletics	26.2%	22.4%	22.3%	23.7%	2.2%
4	Blue Jays	22.5%	19.9%	21.1%	21.2%	1.3%
5	Atlanta	25.1%	27.1%	22.7%	24.9%	2.2%
6	Brewers	25.2%	22.3%	23.0%	23.6%	1.5%
7	Cardinals	19.8%	19.6%	22.5%	20.7%	1.6%
8	Cubs	24.8%	21.7%	22.8%	22.9%	1.6%
9	D-backs	26.1%	23.9%	18.4%	23.1%	4.0%
10	Dodgers	20.9%	22.3%	22.4%	21.9%	0.8%
11	Giants	21.5%	23.1%	24.1%	22.8%	1.3%
12	Guardians	18.9%	15.7%	17.9%	17.5%	1.6%
13	Mariners	21.5%	22.8%	23.2%	22.5%	0.9%
14	Marlins	21.9%	21.8%	23.5%	22.4%	1.0%
15	Mets	19.0%	19.5%	20.3%	19.5%	0.7%
16	Nationals	21.6%	19.1%	18.6%	19.8%	1.6%
17	Orioles	22.7%	22.6%	24.1%	23.1%	0.8%
18	Padres	22.4%	22.5%	21.4%	22.1%	0.6%
19	Phillies	21.8%	23.3%	21.3%	22.1%	1.0%
20	Pirates	26.1%	24.3%	25.8%	25.4%	1.0%
21	Rangers	22.6%	24.5%	22.5%	23.2%	1.1%
22	Rays	25.9%	23.7%	24.6%	24.8%	1.1%
23	Red Sox	21.6%	19.7%	20.3%	20.5%	1.0%
24	Reds	26.3%	20.8%	25.2%	24.1%	2.9%
25	Rockies	21.6%	21.5%	21.3%	21.5%	0.2%
26	Royals	19.7%	22.3%	21.7%	21.3%	1.4%
27	Tigers	25.2%	24.4%	22.6%	24.0%	1.3%
28	Twins	23.6%	22.6%	21.4%	22.5%	1.1%
29	White Sox	19.5%	19.6%	21.1%	20.1%	0.9%
30	Yankees	21.6%	20.5%	21.4%	21.2%	0.6%

K% versus LHP

	Team	1	2	3	Full	StDev
1	Angels	23.7%	23.9%	27.2%	24.8%	2.0%
2	Astros	21.2%	13.8%	20.6%	18.8%	4.1%
3	Athletics	28.1%	19.7%	20.0%	22.2%	4.8%
4	Blue Jays	24.4%	15.0%	17.2%	18.8%	4.9%
5	Atlanta	25.8%	22.9%	21.9%	23.6%	2.0%
6	Brewers	23.9%	24.9%	20.8%	23.4%	2.1%
7	Cardinals	19.7%	18.6%	23.1%	20.3%	2.3%
8	Cubs	22.5%	22.8%	25.3%	23.6%	1.5%
9	D-backs	22.1%	27.4%	19.9%	23.1%	3.9%
10	Dodgers	22.3%	18.7%	26.0%	22.3%	3.7%
11	Giants	21.2%	23.1%	25.1%	23.4%	2.0%
12	Guardians	22.0%	16.1%	23.9%	21.1%	4.1%
13	Mariners	21.2%	24.3%	24.0%	23.0%	1.7%
14	Marlins	29.7%	28.8%	22.9%	27.7%	3.7%
15	Mets	24.0%	17.4%	20.4%	20.2%	3.3%
16	Nationals	16.7%	17.6%	19.8%	18.1%	1.6%
17	Orioles	28.6%	23.1%	25.0%	25.6%	2.8%
18	Padres	22.4%	18.7%	22.2%	21.2%	2.1%
19	Phillies	26.0%	23.7%	16.8%	22.3%	4.8%
20	Pirates	20.7%	28.4%	27.8%	26.0%	4.3%
21	Rangers	21.0%	21.5%	24.6%	22.0%	2.0%
22	Rays	18.8%	16.3%	25.6%	20.0%	4.8%
23	Red Sox	21.9%	22.0%	21.8%	21.9%	0.1%
24	Reds	26.8%	19.0%	23.9%	23.2%	3.9%
25	Rockies	20.3%	17.8%	17.7%	18.5%	1.5%
26	Royals	18.5%	17.9%	16.9%	17.7%	0.8%
27	Tigers	24.8%	19.9%	20.4%	21.8%	2.7%
28	Twins	23.4%	15.8%	17.2%	19.5%	4.0%
29	White Sox	21.7%	20.5%	25.1%	22.3%	2.4%
30	Yankees	24.9%	22.0%	25.0%	23.8%	1.7%

There is more variance than I expected with strikeouts. As such, one of the ancillary projects will be determining if the trends within team strikeouts are due to the ups and downs of individual players, or the in and out of players within the lineup. That is, how is K% affected by lineup composition?

HR% versus RHP

	Team	1	2	3	Full	StDev
1	Angels	3.8%	3.3%	3.6%	3.6%	0.3%
2	Astros	3.5%	3.4%	5.1%	4.0%	1.0%
3	Athletics	1.8%	1.6%	3.0%	2.1%	0.8%
4	Blue Jays	3.4%	3.7%	3.5%	3.5%	0.2%
5	Atlanta	3.4%	3.4%	5.7%	4.2%	1.3%
6	Brewers	3.2%	4.0%	4.5%	3.9%	0.7%
7	Cardinals	1.7%	3.3%	3.4%	2.8%	1.0%
8	Cubs	1.5%	3.1%	2.5%	2.5%	0.8%
9	D-backs	3.0%	3.9%	2.7%	3.3%	0.6%
10	Dodgers	2.8%	3.5%	4.1%	3.5%	0.7%
11	Giants	2.7%	3.3%	2.6%	2.9%	0.4%
12	Guardians	2.4%	2.6%	2.0%	2.3%	0.3%
13	Mariners	2.8%	2.9%	3.0%	2.9%	0.1%
14	Marlins	2.5%	3.9%	2.7%	3.0%	0.8%
15	Mets	2.3%	2.7%	3.2%	2.7%	0.5%
16	Nationals	2.2%	2.6%	1.5%	2.2%	0.6%
17	Orioles	1.9%	3.6%	2.7%	2.7%	0.9%
18	Padres	1.4%	1.9%	2.9%	2.0%	0.8%
19	Phillies	3.2%	4.0%	3.6%	3.6%	0.4%
20	Pirates	1.9%	2.5%	4.5%	2.9%	1.4%
21	Rangers	2.0%	3.8%	3.2%	3.1%	0.9%
22	Rays	2.6%	3.3%	1.9%	2.6%	0.7%
23	Red Sox	1.7%	2.7%	2.8%	2.4%	0.6%
24	Reds	2.5%	2.7%	2.0%	2.4%	0.4%
25	Rockies	3.0%	2.2%	2.4%	2.5%	0.4%
26	Royals	1.7%	2.5%	2.3%	2.2%	0.4%
27	Tigers	1.2%	2.1%	2.0%	1.8%	0.5%
28	Twins	2.6%	4.0%	3.9%	3.6%	0.8%
29	White Sox	2.2%	1.6%	1.9%	1.9%	0.3%
30	Yankees	3.0%	4.6%	5.3%	4.3%	1.2%

HR% versus LHP

	Team	1	2	3	Full	StDev
1	Angels	2.7%	2.5%	1.8%	2.4%	0.5%
2	Astros	3.2%	4.0%	4.2%	3.7%	0.5%
3	Athletics	2.3%	1.4%	2.4%	1.9%	0.6%
4	Blue Jays	2.0%	3.2%	3.4%	2.9%	0.8%
5	Atlanta	3.0%	4.4%	3.3%	3.6%	0.7%
6	Brewers	3.7%	2.0%	3.5%	3.0%	0.9%
7	Cardinals	4.3%	1.1%	2.9%	2.6%	1.6%
8	Cubs	2.8%	4.0%	2.8%	3.1%	0.7%
9	D-backs	2.7%	2.3%	3.0%	2.7%	0.4%
10	Dodgers	2.1%	4.1%	3.0%	3.0%	1.0%
11	Giants	3.3%	4.1%	3.3%	3.6%	0.5%
12	Guardians	2.2%	0.8%	1.2%	1.5%	0.7%
13	Mariners	2.7%	2.9%	2.3%	2.6%	0.3%
14	Marlins	2.0%	2.6%	1.9%	2.2%	0.4%
15	Mets	1.8%	2.4%	2.8%	2.4%	0.5%
16	Nationals	0.8%	1.5%	3.2%	1.9%	1.2%
17	Orioles	1.1%	3.2%	3.5%	2.6%	1.3%
18	Padres	4.2%	1.6%	1.7%	2.5%	1.5%
19	Phillies	2.5%	4.1%	2.7%	3.1%	0.9%
20	Pirates	2.7%	2.8%	3.9%	3.3%	0.7%
21	Rangers	3.2%	5.8%	6.2%	4.8%	1.6%
22	Rays	2.6%	1.4%	2.9%	2.3%	0.8%
23	Red Sox	0.8%	4.7%	3.0%	3.0%	2.0%
24	Reds	1.9%	3.5%	3.1%	2.8%	0.8%
25	Rockies	1.5%	2.4%	2.8%	2.3%	0.7%
26	Royals	0.4%	2.7%	3.6%	2.4%	1.7%
27	Tigers	0.7%	1.3%	2.2%	1.4%	0.8%
28	Twins	3.2%	1.9%	2.9%	2.8%	0.7%
29	White Sox	3.4%	4.3%	1.5%	3.1%	1.4%
30	Yankees	4.9%	3.9%	5.8%	4.8%	1.0%

I don't use HR% as much as wOBA and K% when identifying pitchers to stream, but there are occasions when the hurler in question's main crutch is homers, so there are scenarios in which using an iffy guy against a powerless lineup is a sage play.

BB% versus RHP

	Team	1	2	3	Full	StDev
1	Angels	9.6%	6.1%	7.3%	7.7%	1.8%
2	Astros	9.5%	8.9%	10.5%	9.6%	0.8%
3	Athletics	6.6%	7.4%	5.0%	6.4%	1.2%
4	Blue Jays	6.7%	9.1%	7.6%	7.8%	1.2%
5	Atlanta	8.2%	5.9%	7.3%	7.1%	1.2%
6	Brewers	9.0%	8.4%	9.7%	9.0%	0.7%
7	Cardinals	8.7%	7.7%	7.4%	7.9%	0.7%
8	Cubs	10.3%	9.9%	8.0%	9.4%	1.2%
9	D-backs	11.1%	8.8%	9.7%	9.9%	1.2%
10	Dodgers	11.5%	9.9%	8.6%	10.0%	1.5%
11	Giants	9.8%	9.4%	11.5%	10.2%	1.1%
12	Guardians	7.6%	8.9%	7.0%	7.8%	1.0%
13	Mariners	9.3%	8.6%	8.7%	8.9%	0.4%
14	Marlins	8.8%	8.3%	6.0%	7.7%	1.5%
15	Mets	8.9%	6.7%	5.8%	7.3%	1.6%
16	Nationals	7.2%	7.6%	9.7%	8.1%	1.3%
17	Orioles	7.9%	6.9%	6.6%	7.1%	0.7%
18	Padres	11.1%	6.9%	9.4%	9.1%	2.1%
19	Phillies	7.8%	8.0%	7.5%	7.7%	0.3%
20	Pirates	8.4%	9.8%	8.2%	8.8%	0.9%
21	Rangers	7.1%	6.4%	8.2%	7.3%	0.9%
22	Rays	8.3%	7.3%	8.7%	8.1%	0.7%
23	Red Sox	5.8%	8.4%	7.9%	7.4%	1.4%
24	Reds	7.9%	9.1%	5.2%	7.4%	2.0%
25	Rockies	8.3%	7.5%	7.7%	7.8%	0.4%
26	Royals	7.9%	7.5%	8.9%	8.1%	0.7%
27	Tigers	8.0%	4.9%	7.0%	6.6%	1.6%
28	Twins	9.2%	9.0%	8.2%	8.8%	0.5%
29	White Sox	5.7%	6.1%	6.2%	6.0%	0.3%
30	Yankees	10.1%	10.7%	10.8%	10.5%	0.4%

BB% versus LHP

	Team	1	2	3	Full	StDev
1	Angels	10.7%	8.6%	9.6%	9.6%	1.1%
2	Astros	10.6%	9.8%	8.7%	9.7%	1.0%
3	Athletics	8.1%	9.2%	7.1%	8.2%	1.1%
4	Blue Jays	10.0%	12.8%	4.9%	8.7%	4.0%
5	Atlanta	10.6%	9.5%	8.0%	9.5%	1.3%
6	Brewers	9.1%	9.0%	11.0%	9.6%	1.1%
7	Cardinals	9.1%	9.3%	8.2%	8.9%	0.6%
8	Cubs	7.0%	9.8%	6.5%	7.5%	1.8%
9	D-backs	8.4%	8.9%	8.0%	8.4%	0.5%
10	Dodgers	10.1%	10.5%	9.3%	10.0%	0.6%
11	Giants	9.8%	8.5%	9.2%	9.1%	0.7%
12	Guardians	10.1%	5.4%	7.2%	7.7%	2.4%
13	Mariners	11.8%	10.5%	11.4%	11.3%	0.7%
14	Marlins	9.4%	6.4%	5.1%	7.3%	2.2%
15	Mets	8.6%	9.5%	9.4%	9.3%	0.5%
16	Nationals	9.7%	8.2%	8.7%	8.9%	0.8%
17	Orioles	9.3%	7.2%	8.0%	8.2%	1.1%
18	Padres	10.6%	10.4%	7.0%	9.2%	2.0%
19	Phillies	8.3%	9.9%	12.4%	10.2%	2.1%
20	Pirates	8.5%	6.6%	6.3%	7.0%	1.2%
21	Rangers	9.8%	6.1%	9.2%	8.3%	2.0%
22	Rays	9.2%	7.6%	6.7%	7.9%	1.3%
23	Red Sox	7.2%	9.4%	10.6%	9.2%	1.7%
24	Reds	7.7%	8.0%	8.2%	8.0%	0.3%
25	Rockies	6.5%	8.0%	7.9%	7.5%	0.8%
26	Royals	6.6%	9.3%	9.1%	8.5%	1.5%
27	Tigers	9.2%	4.8%	6.8%	7.1%	2.2%
28	Twins	9.5%	7.9%	8.4%	8.7%	0.8%
29	White Sox	9.4%	6.8%	6.4%	7.5%	1.6%
30	Yankees	7.9%	9.3%	10.9%	9.3%	1.5%

Like HR%, I don't use a team's BB% a lot, but there are pitchers whose main issue is control, so knowing the impatient lineups can help.

BABIP versus RHP

Team	1	2	3	Full	StDev
Angels	0.285	0.305	0.278	0.290	0.014
Astros	0.257	0.289	0.267	0.272	0.016
Athletics	0.255	0.261	0.236	0.251	0.013
Blue Jays	0.277	0.299	0.320	0.299	0.022
Atlanta	0.273	0.314	0.289	0.292	0.021
Brewers	0.291	0.271	0.288	0.283	0.011
Cardinals	0.276	0.300	0.286	0.288	0.012
Cubs	0.308	0.291	0.315	0.304	0.012
D-backs	0.243	0.276	0.249	0.256	0.018
Dodgers	0.285	0.303	0.307	0.299	0.012
Giants	0.293	0.284	0.258	0.280	0.018
Guardians	0.320	0.251	0.306	0.294	0.036
Mariners	0.279	0.306	0.254	0.280	0.026
Marlins	0.287	0.329	0.269	0.293	0.031
Mets	0.318	0.319	0.262	0.303	0.033
Nationals	0.317	0.286	0.281	0.295	0.020
Orioles	0.309	0.239	0.291	0.279	0.036
Padres	0.275	0.307	0.289	0.291	0.016
Phillies	0.298	0.289	0.266	0.284	0.017
Pirates	0.310	0.254	0.250	0.273	0.034
Rangers	0.252	0.286	0.303	0.282	0.026
Rays	0.309	0.231	0.329	0.292	0.052
Red Sox	0.274	0.331	0.305	0.304	0.029
Reds	0.266	0.294	0.314	0.292	0.024
Rockies	0.274	0.316	0.277	0.291	0.023
Royals	0.256	0.313	0.301	0.291	0.030
Tigers	0.262	0.269	0.282	0.271	0.010
Twins	0.290	0.312	0.302	0.302	0.011
White Sox	0.247	0.288	0.345	0.296	0.049
Yankees	0.277	0.285	0.256	0.273	0.015

BABIP versus LHP

	Team	1	2	3	Full	StDev
1	Angels	0.322	0.285	0.265	0.293	0.029
2	Astros	0.232	0.254	0.299	0.261	0.034
3	Athletics	0.272	0.277	0.264	0.271	0.007
4	Blue Jays	0.296	0.313	0.272	0.290	0.021
5	Atlanta	0.283	0.352	0.294	0.310	0.037
6	Brewers	0.247	0.269	0.290	0.268	0.022
7	Cardinals	0.301	0.301	0.326	0.308	0.014
8	Cubs	0.280	0.307	0.302	0.294	0.014
9	D-backs	0.220	0.313	0.310	0.284	0.053
10	Dodgers	0.266	0.308	0.319	0.296	0.028
11	Giants	0.244	0.304	0.286	0.280	0.031
12	Guardians	0.251	0.301	0.257	0.268	0.027
13	Mariners	0.239	0.304	0.329	0.286	0.046
14	Marlins	0.293	0.259	0.320	0.288	0.031
15	Mets	0.274	0.301	0.278	0.286	0.015
16	Nationals	0.283	0.343	0.243	0.289	0.050
17	Orioles	0.285	0.293	0.296	0.291	0.006
18	Padres	0.246	0.338	0.289	0.292	0.046
19	Phillies	0.323	0.286	0.294	0.301	0.019
20	Pirates	0.289	0.277	0.261	0.274	0.014
21	Rangers	0.271	0.264	0.310	0.277	0.025
22	Rays	0.305	0.291	0.336	0.308	0.023
23	Red Sox	0.287	0.335	0.354	0.328	0.035
24	Reds	0.278	0.316	0.333	0.308	0.028
25	Rockies	0.389	0.282	0.331	0.336	0.054
26	Royals	0.287	0.277	0.284	0.282	0.005
27	Tigers	0.350	0.292	0.359	0.335	0.036
28	Twins	0.293	0.290	0.259	0.283	0.019
29	White Sox	0.305	0.365	0.373	0.349	0.037
30	Yankees	0.277	0.263	0.288	0.275	0.013

Out of curiosity, I wanted to determine which metric correlates best with wOBA. Here are the results:

RHP Correlation to wOBA

	Stat	1	2	3	Full
1	K%	-0.25	-0.27	-0.27	-0.34
2	HR%	0.57	0.60	0.60	0.70
3	BB%	0.43	0.55	0.42	0.56
4	BABIP	0.72	0.68	0.41	0.50

LHP Correlation to wOBA

	Stat	1	2	3	Full
1	K%	-0.29	-0.25	-0.20	-0.32
2	HR%	0.51	0.67	0.62	0.55
3	BB%	0.02	0.47	0.46	0.28
4	BABIP	0.55	0.67	0.55	0.54

I'm not exactly sure how to apply this yet, but if I figured if I was curious, you may be as well.

I don't want to give the impression using data of this nature is a waste of time without "proof". That said, I do think it needs to presented without an implied level of certainty. This hobby is based on deciding what is most likely to happen, and this is just another example. Shoot, if we all KNEW what would happen, I'd still be making peptides.

However, there must be a sample size that yields the best answer; we just don't know what it is (yet).