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03-19-2013, 01:16 PM
  #19
hairylikebear
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Join Date: Apr 2009
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Quote:
Originally Posted by GuineaPig View Post
The issue here is sample size. Save percentage itself is heavily dependent on luck over the course of a season, and it becomes even more important if you reduce the sample (both in the type of shots, and number of games). It's interesting to look at, but pretty meaningless as it stands.
As far as SV% is concerned, all goals against will be counted, "lucky" or otherwise. Shots from the scoring chance pentagon will be included, regardless of luck. The only situation in which there will be a difference involving luck is when a "lucky" shot from outside of the scoring chance area goes in (ie a softy, which counts as a GA but not a scoring chance) or when the goalie makes a "lucky" save on a shot that comes from outside the SC area. The idea behind the pentagon is that any shot from outside the pentagon is relatively harmless, and therefore no save from there can be a "lucky" one. Unless there is a deflection, but those count as scoring chances.

It does reduce the sample size a bit, but at least the dependent variable is kept the same so it minimizes that effect as much as possible.

Quote:
Originally Posted by Micklebot View Post
By his methodology,

Bishop .8359
Lehner .8787

The problem as I see it is that the SCA is an average for the whole team, not just the starters, so if one goalie gets sheltered games, the team buckles down on chances allowed for their back-up or for any reason some games skew the averages, the numbers won't be entirely accurate for the goalie specific stats.
That's not true. I did it that way because I'm missing data and also because I'm lazy. If I had scoring chance data for every game (or even a timestamp for every scoring chance), it would then be possible to determine who was on the ice for them, including the goalie. After that the math is pretty simple.

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