State of the League

 

Look at that graph.  Look at those 60% transparent baseballs in the background.  Man (and Justine), that is a goddamn fine looking graph.  So colorful.  So easy to compare.  So actually conclusion suggesting.  Isn't it amazing how, after Oksana went to sleep before the Jacuzzi in weeks 6 and 7, the quantitative categories go down and the ERA and WHIP rise?  And then fell in tandem with the rising other categories?
I feel sadness that the league was in such a slump in those weeks 6 and 7.  I feel happiness that moves were made and the league is now as potent as it evar was.  I feel pressure that the league is doing its best lately.  I feel worried about how this week 15, where there will be a full week plus 4 post all star break days, will affect my statistical correlations.  But then I look at that graph again and I feel happy.

Materials and Methods:

Team totals were tabulated and the averages of each category for the entire season was calculated.  To calculate the individual weekly totals, a more complicated moving average was required to smooth out some of the noise in the data.  Thus, for the meat of the weeks, the team averages were calculated by multiplying the team's performance in that given week by 4, the preceding and next weeks by 2, and the weeks surrounding that 3-week period by 1, and then dividing that by 10.  For the first and last weeks, the same calculation was used except using 1-tail rather than 2 in the weekly tabulations.  To construct the graph above, all data needed to be scaled so that it could be accurately compared (40HR can't be compared to 0.300 average in the same units).  Thus, a variance-based approach was used where the weekly floating average was subtracted from the total average, and then divided by the total variation (the difference between the maximum weekly average and the minimum) to give values that range from 0.3704 (AVG in week 14) to -0.3198 (K/9 in week 7).