Adjusted stats - how valuable?
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09-23-2012, 06:20 AM
Join Date: Aug 2009
Location: Ho Chi Minh City
Originally Posted by
Accurate? Fair is a better word, I would suggest. There's no accuracy involved.
You can say it with a good degree on confidence. The lower the average goals per game, the greater value each goal has in terms of winning games, which of course is the point of scoring goals in the first place. The number of goals required to add a win for an average team is easily calculated.
You'll need some more work to develop this idea. Have you considered whether forwards and defencemen should be analyzed separately? Have you considered the effect of ice time (should even out over a large enough number of players, but you never know)?
Again, the only accurate thing was what actually happened. I can't see how you can call any adjustment accurate. The adjustment is not to make the numbers more "accurate", just more comparable, or perhaps more meaningful.
Since goals were easier to come by in 2010/11, arguably Perry's 50 goals were worth less than Malkin's, since Malkin's did more to help his team win.
That's why I said it works well for the great majority of players. Outliers do not fall within the great majority.
You keep saying that, and I still don't know what you mean. Since we're not dealing with true values, I don't see how accuracy is an issue.
However, again, comparing goals in one season, where it takes 5.00 goals to earn a win for your team to another season where it takes 4.00 goals to win a game is certainly valid. The easier goals are to come by, the less value they have in winning games.
Almost five goals difference is almost nothing. If you assign a large degree of confidence to a 53-goal player being better than a 48-goal player, you're making too fine a distinction.
I can certainly see how from your perspective, your method is more accurate. That does not mean that using means is
, it just means it's
somewhat less accurate
Inflated by what amount? Is it large enough that mean-based analysis is completely usless? I doubt it.
A human resources study that I've referred to has demonstrated that means have an error several magnitudes above a method that looks at the influence of outliers. One of the groups they studied was hockey players. Goals by RWs IIRC.
I think the fact that a small percentage of players are responsible for so much of the output falls in line with the conclusions of the HR study I've referenced. It says nothing at all about methods that don't use or rely on means or bell curving.
I think breaking things down by position, TOI, etc is premature at this point. I am slowly collecting data to compare seasons and see if my idea has value in comparing players across seasons and eras. Also I was just looking at goals so IMHO all skaters must be accounted for.
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