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Originally Posted by Macho0978
But there seems to be a bit of a disconnect between his goals for and against vs shots scoring chances high danger scoring chances and expected goals for %. His numbers don’t look as bad as the results do
Also, the Stars player boring hockey. Klingberg could excel under Sutter and the checking style game. I could see a Tanev scenario here where the numbers said he’s declining but the numbers were wrong
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This is the model in a nutshell if you are curious. Maybe, but is it worth over paying to find out? Im not so sure we should take chances on a possible anchor contract.
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Game Score is a linear weight model with the weights for each stat within it being derived according to the frequency of goals occurring from them and are as such:
Goals: 0.75
Primary Assists: 0.7
Secondary Assists: 0.55
Shots: 0.075
Blocks: 0.05
Penalty Differential: 0.15
Faceoff Differential: 0.01
5-on-5 Corsi Differential: 0.05
5-on-5 Goal Differential: 0.15
It uses data from each player’s last three seasons, with each component weighted by recency and regressed to the mean individually. That means that the weight for each prior season is different for goals than it is for shots or blocks (and different for forwards and defencemen), as is the regression factor. On top of that, there’s an age adjustment (using methods outlined here) performed at the start of each year that slowly lessens until the end of the season, as well as a small usage adjustment that factors in a player’s teammates and competition based on 5-on-5 Game Score.
From there, each player has a projection for each component going forward and that’s plugged into the Game Score formula to get a projected Game Score going forward. That’s then transformed into a wins above replacement rate (with replacement level being the 372nd forward and 186th defenceman) to create Game Score Value Added, or GSVA.
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