using z scores to compare and average player values from different fantasy hockey analyses? I'm VERY bad at math - but am trying to find the right statistical technique to use to build a cheat sheet for my fantasy hockey draft. Here's my proposed approach - but I'm hoping for feedback to make sure this is legitimate:
1)I have purchased player value projections for the 2018/2019 season from two different sources, both of which use a "secret sauce" to generate a player "value score" based on the specific settings of my league. 
2) However, each source uses a totally different scale for their scores. Since I assume each source has it's own strengths and weaknesses, I want to try to average the two value scores for any given player. 
3) I've started by using the Standardize function in excel to generate a z-score value for each player, from each source.
4)Can I now simply average the two z-scores for each player to get an "average value score" for the player, given my two sources? Or am I approaching this the wrong way?
Again, sorry for my innumeracy - hoping the great minds here can help me figure this out. Thanks all, 
 A: Welcome to CV! No apologies necessary—I don't think you're as bad at math as you say you are.
I think this is a good approach. What I would do is z-score (standardize) each of the modeled scores you downloaded. Then, I would average these two together. Lastly, I would rank the players from highest value to lowest. This gives you a sorting of the best to worst players (according to an average of both scoring systems you downloaded).
This is better than percentile/rank, in my opinion, because you have more information on the differences between "tiers" of players. Imagine there are 5 elite fantasy players in the league and then a huge drop-off to the next 20, then another drop-off. The average of two standardized variables will show the drop-off, while the ranking will hide it.
You can do a simple average, which weights the scores equally. Let's say, for some reason, you think that one source is twice as good as the other source. You could then do a weighted average, where the one source is weighted twice as much. But if I were you, I would do exactly as you proposed: z-score the two variables, then average them together.
I'm a huge basketball fan, and I really enjoyed the book Basketball on Paper by Dean Oliver. In the third chapter of that book, he talks at length about how useful z-scores can be to compare across different scales. In his context, he is talking about how we can compare a player in the 60s to a player in the 90s. He suggests z-scoring within that given year to see how good a player was relative to an average player at the time in which they were playing.
