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03-14-2013, 09:55 PM
Two by two...
Join Date: Aug 2006
Location: Long Island
Do some of you guys really not understand how biased stats can be in small sample sizes? Obviously he hasn't played well so far this year but that doesn't mean he does not have the ability to do so. Do you honestly think replacing Gaborik with a different player is going to improve the offense? That's essentially impossible given that there are very few better goal scorers than him and certainly none that we would be able to trade him for.
Guess what. Last year from 12/26 to 2/21 he was 6-12-18 in 25 games. in 09/10 from 12/26-3/7 he was 9-11-20 in 25 games. And these were years where he was 40G and PPG.
Last year from 11/27 to 1/21 Nash was 9-6-15 in 25 games.
As you see I can pick and choose small samples where players don't produce as well. And the point of the game is to produce - not how you do it. You can play as well as possible if you don't contribute to scoring it doesn't get you anything.
Originally Posted by
Our point exactly. You think we liked him before. We didn't. Hes always been soft. I dont care if he scores 50 goals a season. He scores them when its safe to score them. He doesnt have the game nor does he have the ability to raise his level, ever. He will never be a go-to player when any team needs him.
I've said this before in this thread regarding data like this. Provide proof that Gaborik scores goals when they are not needed (say the what % of his goals occur when up by 2 or down by at least 3) and see how that compares to other top scorers in the league. Without this you are just randomly speculating and making comments to try and fit what you want the player to seem like. I guarantee he is not going to be significantly different than other players of his caliber in this category and any difference is merely going to be a statistical outlier. It's like arguing clutch in baseball - it's nothing that actually exists (by existing i mean being a skill..obviously one player can happen to perform better in clutch situations since it's just making a small sample smaller and allowing for more variance). For more info on this sort of thing read The Book by Tom Tango.
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