Again, the coefficient values are not the same and vary quite a bit. I also ran the regression using only teams that had the DH (yes, sometimes the NL gets to use the DH-I mean AL teams only from 1973-2004). Here are those results:
Then I went back to all teams and put it SB and CS per game. Here are the results:
I know, in some cases things don't make sense. We see some negative values for SBs and positive values for CSs. I mentioned this last week. But I just wanted people to get a chance to look at this.
Then I did the SB/CS regression for DH teams only. Here are the results:
Again, judge for yourself if the differences are meaningful.
Now there could be collinearity between the IVs. I discussed this a little last week. I did not run any test yet for it this time. If I do, I will update this story. I ran a regression with some different variables to avoid or lessen this problem. Each lineup slot had 3 variables: walk percentage, hit percentage and extra-base percentage. For walks, hits, and extra-bases, the denominator was plate appearances (PAs). This is a little different than comparing OBP and SLG since OBP has PAs as the denominator and SLG has ABs. Also, by using extra-bases, it is a little like isolated power. SLG is not always as good measure of power because a guy who hits a single drives up his SLG. Isolated power is SLG - AVG, or extra-bases divided by ABs. Of course, here, I am using PAs. H1 is the hit% of the leadoff man, W1 is the walk% of the leadoff man, XB1 is the extra-base% of the leadoff man, etc. Here are the coefficient estimates:
Then I added SB and CS in. Here are those results:
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