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[QUOTE="Cusefan95, post: 4911699, member: 173"]
I don’t think how you view this is accurate - although I don’t know for sure since I don’t know the algorithm.

Margin of victory shouldn’t be a linear correlation, it’s probably some form of power graph.  The “value difference” between winning by 1 vs 2 pts is much greater than winning by 8 vs 9 points.  A significant amount of the issue with a team taking their foot off the gas doesn’t really matter as a result.  But there’s always going to be potential for some weird potential outliers.

Plus I think he used margin of victory to simplify the explanation - which actually isn’t helpful.  The whole point of this analysis is on offensive and defensive efficiency, so that’s what would most likely be used to calculate “luck”.   Those should both be impacted less than pure margin of victory by a strategy of running the clock out at the end of a game.

As an aside, when hockey analytics were initially taking off, a lot of people mocked the measure of “puck luck”.  Then the Kings (#8 seed) and Devils (#6 seed) made the 2012 Stanley Cup Finals as the two worst “puck luck” teams - then everyone thought it was some magic bullet measure (which it isn’t).  It might be better if luck was called something else like potential variance, although nobody would know what that meant and it’s not really accurate either.  The whole issue here is that most people don’t understand statistical analysis, and efforts to simply enough to explain it generally just confuse the situation for the average person.  I know enough to know I don’t know enough to know if how luck is calculated here has any predictive value, and I also know that investigating it to figure that out isn’t a valuable way for me to spend my time.
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