Thoughts on Hockey Analytics

It seems every time a new hockey person gets hired these days they will get asked “do you believe in hockey analytics?” It started with Trevor Linden in Vancouver. Then Brendan Shanahan in Toronto. And today Brad Treliving in Calgary. Nichols on hockey has a good rundown on both Treliving’s and Burke’s response to the question today so go give it a read. As we all know, Brian Burke is an analytics skeptic to say the least. A popular Brian Burke quote is the following: “Let’s get the record straight on that too. The first analytics systems I see that’ll

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Can last years statistics predict this years playoff teams?

As of last night games all 16 playoff teams have been determined. Before I get into any playoff predictions, lets take a look at how last seasons 5v5 close statistics do at predicting who would make the playoffs this season. The above table shows last years 5v5close GF% and CF% and the teams in red are this years playoff teams. There were 15 teams with a CF% above 50% last year, 9 of them made the playoffs this year while 6 missed. Of the remaining 15 teams that had sub 50% CF% last year, 7 of them made the playoffs

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Stats on stats.hockeyanalysis.com

The past few weeks while I have been shifting my website from one web host to another in an attempt to fight off the DDoS attacks I started thinking about how big my stats.hockeyanalysis.com database actually is. I was thinking about it because of how long it takes to upload the data to a new web host and how long it takes to set up the database again. So, how many data points do I have in my database?  A lot. A data point is any single piece of data like the Leafs 2008-09 CF% or Jarome Iginla’s 2007-13 (6yr)

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Two Graphs and 665 words that will convince you on Shooting %

Last week Tyler Dellow had a post titled “Two Graphs and 480 Words That Will Convince You On Corsi%” in which, you can say, I was less than convinced (read the comments). This post is my rebuttal that will attempt to convince you on the importance of Sh% in player evaluation. The problem with shooting percentage is that it suffers from small sample size issues. Over small sample sizes it often gets dominated by randomness (I prefer the term randomness to luck) but the question I have always had is, if we remove randomness from the equation, how important of

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