Wednesday, November 14, 2007

Team Run Production in 2007

Statistics such as runs created and OPS (on base percentage plus slugging percentage) are good for summarizing the offensive performance of a player. However, they don’t tell us much about a player's specific batting skills. How to best break down offense into statistics that describe skills is always under debate and there is no one best way to do it. The combination of statistics most commonly used by analysts is batting average (BA), on base percentage (OBP) and slugging average (SLG). These are the statistics I typically use too but the combination does have some problems.

First, BA, OBP and SLG are highly correlated. For the more statistically inclined, a look at individual seasons of players in the American League between 2002 and 2006 shows that the correlations range from .56 to .68 with the highest correlation between BA and OBP. In short, this says that the three stats are measuring similar things. Logically, consider that batting average is essentially a subset of both OBP and SLG and thus the three of them are closely related.

Another problem (and this is related to the first issue described above) is that neither OBP nor SLG measures a pure skill. OBP combines the ability to get hits with the ability to draw walks. These are two very different skills which can be loosely defined as making contact (hits) and having a good eye (walks). Similarly, slugging combines the ability to get hits with the ability to get extra base hits. Again, these are two different skills – making contact and hitting for power.

BA can be subtracted from SLG to give us isolated power (ISO), a purer measure of slugging ability than SLG. Similarly, BA can be “subtracted” from OBP to give us extra on base percentage (EOBP). Because BA and OBP have different denominators (at bats and plate appearances respectively), it is best not to use the equation OBP-BA. Instead, we subtract hits from times reached based in the numerator and use plate appearances as the denominator. That is, EOBP=(BB+HBP)/PA. So we now have BA, ISO and EOBP. The correlations between these three statistics range from .01 to .45 with the highest correlation between ISO and EOBP. These correlations are much lower that those between BA, OBP and SLG. This is because BA, ISO and EOBP are more independent of one another than BA, OBP and SLG.

Furthermore, using AL team data from 2001 to 2005, I found that BA, ISO and EOBP explain 92% of the variation in team runs scored. I also found that BA, OBP and SLG explain 92% of the variation in runs scored. So the two sets of statistics have the same very strong explanatory power but the former trio is appealing because it more purely measures three separate skills.

Finally, BA in isolation, explains 58% of the variation in runs, ISO explains 56% and EOBP explains 42%. So neither of the three statistics explains a great deal by itself. All three must be used together to explain runs scored.

I have not included base running in run production because the only readily available statistic is stolen bases which is not highly correlated with runs scored. I will talk more about base running statistics later in the off-season. Even without it though, we are explaining most of what we need to know about runs scored as that 92% figure is very high.

The table below presents the BA, ISO and EOBP for all American League teams in 2007. From the tables, we can see that the Tigers finished 2nd in runs scored despite ranking 13th in EOBP. This is because they were able to overcome their lack of walks by hitting for average and power. They were second in the league in both categories. Finishing .287 in batting average again will be difficult so it's likely they will have to improve their walk rate in 2008 if they are going to remain near the top of the league in runs scored.


Table 1: American League Team Run Production in 2007

Team

Runs

Runs Rank

BA

BA Rank

ISO

ISO Rank

EOBP

EOBP Rank

NYA

968

1

.290

1

.174

1

.110

3

DET

887

2

.287

2

.171

2

.084

13

BOS

867

3

.279

5

.165

4

.118

1

LAA

822

4

.284

4

.133

12

.089

10

TEX

816

5

.263

10

.163

5

.091

9

CLE

811

6

.268

7

.159

7

.106

4

SEA

794

7

.287

3

.138

11

.073

14

TB

782

8

.268

8

.165

3

.096

6

BAL

756

9

.272

6

.141

10

.088

11

TOR

753

10

.259

12

.160

6

.094

7

OAK

741

11

.256

13

.151

9

.112

2

MIN

718

12

.264

9

.127

13

.091

8

KC

706

13

.261

11

.126

14

.085

12

CHA

693

14

.246

14

.158

8

.096

5

Ave

794

14

.270

14

.152

8

.095

5

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