Quote:
Originally Posted by fantasyhockeygeek
Z-score describes how a datapoint compares to a population of datapoint, so of course Staal comes out with a negative z-score when you compare him to a population of 14 centres! By definition, a z-score of zero is exactly average within a population... so since Staal likely isn't top-7 within that group of 14 players, he's going to be negative. When you calculate z-scores, you need to compare to a larger population, and in my view the most reasonable player population to compare to is the "owned" players at a given position in a league.
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Yep, should be compared to all owned players. Typically it takes about 5-7 iterations (re-sorting by z-score totals using a pool of 500 skaters, for instance, until the top 210 players out those 500, stay in the same order when you sort them) to find the theoretical top 210 players that should be owned.
Z-scores challenge the thought that certain categories matter more than others, or that it's acceptable to be weak in categories like PIM or Hits because "hey, it's not a negative value, so it can't hurt my team". It's a lot more obvious when a goalie has a bad GAA or SV% because you think "damn, he's killing me!" In reality, Kessel is "killing you" in Hits and PIM by having such a low total.
That said, there are also caveats that certain stats are more predictable and should have more value placed on them. +/- is not nearly as predictable as G, A, Hits, Blocks, or PIM. In fact I did a little experiment recently. Dobber's projections unfortunately only offer grades of A, B, C, or D for players to gauge predict their +/-. Guideline's are given such as A = +5 to +15, B = 0 to +5, etc. Last season, the group of players that were in group D - that is to say, the worst of the worst - ended up with a better average +/- than the players in group C. So even with a large group of players where you'd assume the outliers would cancel each other out, the error in projection was extremely large. This tells me one thing: do not place much emphasis on +/- when summing up z-scores. I didn't do the same test for goals or assists, but I can almost guarantee that the group of players projected for 65-80 points scored a lot more than the group of players projected for 50-65 points. Same goes for PIM, PPP, Hits, etc. My way to deal with this is to cut the z-score total for +/- in half. So every other stat is weighted twice as much as +/-. It woudl probably be a good idea to get an ideal weighting for each category based on predictability, but I'm not a mathematician.
Nonetheless, the fact remains that players with huge negative values in certain categories deserve to be docked severely for those shortcomings. Nobody has an issue with this when docking Chris Neil for his lack of goals or PPP. So why is it such an issue for Kessel and PIM, Hits, or +/-? His value should take a huge hit, and the fact that it doesn't is precisely because of faulty logic.
