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July 28, 2008
Z-Scores out of Whack
Upon sifting through my data this afternoon (and thinking about it yesterday), I noticed that the mean values of some of my z-score tables was not 0. I went through some of my calculation scripts and noticed that my primary calculation was not picking up the sample mean correctly. I had to adjust & recalculate and now the population mean jives correctly. I'm going to go through and adjust my past few blog entries to reflect this.
A couple important things to note when calculating the z-score yourself:
- The z-score is meant to normalize data (i.e. distribute the data normally, that is, within the standard normal distribution)
- The mean of all your z-scores should be zero
- The standard deviation of all your z-scores should be 1
Why do I think the z-score is particularly valuable in this situation? We can normalize the game-by-game performance of players. Furthermore, we can normalize it to a single player-against-team metric (see my recent post about Kitna). From this, we can load in the 2008 schedules, de-normalize and see who might have a good season.
Posted by haydenth at July 28, 2008 07:45 PM