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Post by alantech on Oct 29, 2014 17:17:50 GMT -5
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Post by n00b on Oct 29, 2014 21:38:19 GMT -5
Hmmm...
I think the main issue is that your version of VORP isn't a cumulative statistic. Somebody that rarely gets set but hits for a high percentage doesn't ADD VALUE at a high rate. Swanegan is a perfect example. How your statistic is currently calculated says that she has 16 kills in 8 matches, and by doing that, she added more value than any other middle in the conference. Obviously that isn't true.
Baseball WAR and basketball Win Shares are all counting stats. That is, the more shots a player takes, the more Win Shares they'll get (assuming they make them). Similarly, a baseball player that hits .300 over the course of a season will have a higher WAR than a baseball player that hits .400 for a month then misses the remainder of the season.
Now after you calculate that counting stat, they often average it out (Win Shares/Game for basketball, something like RC24 for baseball), but it has to be totalled first.
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Post by alantech on Oct 29, 2014 22:23:16 GMT -5
Good points. Thanks!
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Post by VivaLaVolley on Oct 30, 2014 11:39:58 GMT -5
I would love to see it for the BIG WEST!
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Post by mikegarrison on Oct 30, 2014 15:26:27 GMT -5
I didn't know "win shares" (which was invented for baseball) had been translated into a basketball metric.
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Post by n00b on Oct 30, 2014 15:35:23 GMT -5
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Post by joetrinsey on Nov 1, 2014 0:59:19 GMT -5
The commenter on your site already mentioned this, but this is just hitting percentage expressed in a different way.
Swanegan's hitting efficiency is 0.433. Your average value for an MB is 0.274.
(0.433 - 0.274)*100 = 15.9, the value you calculated for her. Of course, this is still valuable, because hitting efficiency is a powerful statistic. However, what you have presented is still purely a rate stat, and subject to the same flaws that any rate stat has: the inability to account for usage.
If you want to go further with this stat, my advice to you would be something like:
(Efficiency - Average ) * Total Attempts.
To use the example of Haley Eckerman, she's hitting 0.272 on 1142 swings. (In total matches, I don't feel like adding up only conference)
(0.272 - 0.197 ) * 1142 = 88.65
So we might think that Haley Eckerman has gotten about 88 more kills than an average outside would so far this year.
Compare that to say... Mia Swanegan who's hitting 0.328 on 67 swings. Even if she was hitting 0.433 for the total (Again, going quickly to not have to add up conference-only stats), she might be:
(0.433 - 0.274) * 67 = =10.65
So clearly, Eckerman has produced significantly more value than Swanegan, which I don't think is a surprising conclusion to anybody. Hope that's helpful?
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Post by joetrinsey on Nov 1, 2014 1:02:39 GMT -5
Also, a side note: we've used a WAR-like framework as one of our primary statistical tools for the National Team for the past couple years. With DataVolley you can add a lot beyond the typical box score.
A few college assistants have volunteered with us and learned some of the framework, but I don't think any have quite introduced it on a full scale as part of their analysis.
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