## A couple ideas on SV% variation (response to holiday park)

Let me start by saying that the idea of variation in SV% IS an interesting topic to explore. Holiday park has started this, so let's keep it going.

I'm going to have a quick stab at "Evaluating Goaltenders Using Variation in Save Percentage" (park's title) by looking at two goaltenders from 2012-2013: Antti Niemi and Jonathan Quick.

In collecting the data and trying some shit out, I think there's four basic tests we can consider to get a grasp of the "consistency" of a goalie. (Assuming that crap exists.)

1) Difference between aggregate season SV% and game-to-game mean SV%. The greater the difference, the more inconsistency.
2) Standard deviation of game-to-game SV%. Same as #1.
3) Size of slope of trend line of game-to-game SV%. Same #1. This is likely most problematic as linear R^2 will vary. High R^2 will suggest linear/equal distribution(s) of SV%(s). Note this works only if you order the SV% numbers.
4) Eyeball test looking at chart of game-to-game SV%. The greater the range of values, the more inconsistency. Nobody likes this option, right? :)

I think #2 is what makes the most sense, but for the sake of argument, I listed all four that I thought worth exploring. Some caveats re: sample size apply, but I will try to interpret and qualify properly below.

 Goalie 2012-2013 G agg SV% gtg mean SV% gtg SV% stdev lineslope abs R^2 Niemi-reg 43 0.924 0.922 0.049 0.0037 0.915 Quick-reg 36 0.902 0.883 0.109 0.0072 0.511 Niemi-poff 11 0.930 0.929 0.032 0.0095 0.958 Quick-poff 18 0.934 0.929 0.056 0.0095 0.816

Shine on you crazy Table. Numbers are all-situation aggregates.

1) Regular season first. Numbers suggest we've got one pretty darn consistent goaltender (Niemi) and one not so much (Quick). These tests are evidence for the claim that: Niemi was more consistent than Quick. In addition, he was more consistent in sustaining a higher SV%. I think that's the key for evaluating goaltenders. It's not just the SV%, it's keeping a high one with minimal game-to-game variation. I think holiday park could have said this more clearly (and I'm on your side!).

2) Playoffs second. Sample size caveat applies here, but EVEN SO, Niemi was more consistent in playoffs and maintained an even higher SV%. Dang. But Quick though, cut his standard deviation in half, maintained a higher aggregate SV% than Niemi, and closed the gap by half in the game-to-game mean SV%. Line slope test was even. WTF, you guys. (I know, sample size.)

Variation seems to matter when evaluating goaltending talent in two ways. The first is possessing a high SV% and the second is minimizing the variation around that SV%. Niemi is more consistent than Quick by the tests suggested here (even so, though by a smaller margin, in the playoffs).

While I'm thinking about Snark's suggestion for generating n-game samples, calculating their SDs, and comparing to equal samples, I will probably do this for all goaltenders 2012-2013. It wasn't too tough to scrape. Think I need to grab other stuff? Is this bullshit or what?

This item was created by a member of this blog's community and is not necessarily endorsed by Fear The Fin.

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