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08-23-2011, 12:40 PM
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Join Date: Mar 2006
Location: Regina, SK
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I've studied correlations between ES icetime and ESGF+ESGA and they don't necessarily correspond very well, perhaps especially regarding forwards. For example, during 2002-03, I guy like Kowalchuk (who had a reputation as an offensive minded player) had about 1.5 times more ESGF+ESGA played than the average player.
So here we thus have our first bias. ESGF=60 and ESGA=50, will give higher "ice time" than ESGF=50 and ESGA=40, even if real ice time is the same. ?
I'm surprised CYM didn't mention/ask this, but... did you mean he had about 1.5 times the "average" player? or the average of his own team? there are only so many minutes to go around, and I find it unlikely that he would be that far off of his own team's average. If you compare him to another team, sure, his icetime figures would look wonky. but that's not what a model that uses GF & GA to calculate icetime does.

Also, Kovalchuk is about the most extreme example of a "high risk, high reward" type player. Watching the guy play it is clear he is going to cause both more goals for and more goals against while on the ice. If there was ever a player who would be an outlier whose GF/GA figures might cause an estimation model to lie, it would be him. With that said, that's no reason to throw out such a model.

If I was asked to rank the following seasonal ES stats for players, without paying any attention at all to context, I would rank them as follow (with a tie for 2nd best):

72-50 +22 1.440 112 161.28
60-40 +20 1.500 100 150
40-20 +20 2.000 60 120
45-30 +15 1.500 75 112.5
7- 4 + 3 1.750 11 19.25
3- 1 + 2 3.000 4 12
GD=GF-GA (goal difference). GS=GF+GA (goal sum).

1. The guy with a GF/GA of 3.000 looks far too good compared to the others.
2. The lower numbers, the more extreme GF/GA. (It's a bit like pts per game. The fewer games played, the more extreme points per game.)

That's why I generally think one should be careful with using GF/GA.
I have an even more compelling reason to throw out the bottom player - any calculation done on him would be based on an obscenely low number of game situations. It's a poor sample size and is practically meaningless. Of course, if it got further in the season and he was 40-13, then we'd have something to talk about, and whether he was outperforming the 72-50 player would be a worthy question to ask.

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