Anecdotes and validating statistical models

I often get criticized by others in the hockey analytics community, particularly on twitter, when I through out a piece of data that runs counter to conventional analytical thinking and raise a question as to whether it means something or not. Sometimes I do it because I believe in what I am saying but other times I do it because I think we should constantly be challenging and testing current conventional wisdom. That is how we learn new things. We make observations, we ask questions about their relevance, we investigate and we either toss out the new idea or we

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Is possession hockey providing diminishing returns?

Ian Cooper sent me a link to an article he recently wrote how hockey analytics has driven the importance of puck possession hockey which in turn can change the dynamics of hockey analytics. In his article he showed that in recent years there has been a smaller spread in team CF% talent which he believes is due to a higher percentage of teams focusing on puck possession hockey. That’s more consistent with a league in which teams are all deploying tactics in order to optimize their SAT% and pummeling a small number of holdouts who either don’t accept analytics orthodoxy or simply aren’t

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Correcting a post on shot quality and save percentage revisited, again

It is beginning to become a regular occurrence but someone over at Hockey Graphs has attempted to debunk a theory/stat/opinion of mine and once again failed in their procedure for doing so. This time Garret Hohl tried to debunk Sv% RelTM as a useful statistic by looking at the persistence and predictability of Sv% RelTM over time despite the fact that just a month ago I suggested that evaluation of the past and predicting the future are two different questions. The reason for this is due to the fact that lack of persistence might be due to players changing teams or changing roles. What

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Evaluating Player Evaluation Metrics and Expected Goal Models

  Think about the perfect scenario where we have an infinite sample size. A scenario where every player plays an infinite amount of ice time with and against every other player. In fact, every 6-player combination of 3F-2D-1G plays against every other 6-player combination an infinite amount of ice time. Players start an infinite number of times in the offensive zone, defensive zone and neutral zone and they play an infinite amount of time in all score scenarios. Under this scenario there is no need to make considerations for sample size, quality of teammates, quality of competition, zone starts, score

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