How does performance as of Dec. 1 relate to making the playoffs?

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Every year right around December 1, NHL analysts and fans alike start thinking a little more seriously about playoff chances. Although in many ways this is an arbitrary point in time, particularly when linking it to US Thanksgiving, there’s also some logic to it as well.

By the end of November, we are two months in and most teams have played 20-25 games, or a quarter of the season. And from an analytics perspective, that’s about the point when you can start making use of most of the early season data.

So while most of the traditional playoff discussion at this time of the year tends to focus on points or even where teams are in the standings, let’s take a look at how early-season shot-based metrics relate to whether a team ultimately makes the playoffs.

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2016-17 Hockey Graphs Top 50 Players

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Welcome to the second annual Hockey Graphs Top 50 Players in the NHL list.

The main reason I put this together last year (you can view that here) was as a basis for comparison against the other, more famous, top 50 players lists. The annual list is a season preview staple for TSN and THN and the rankings are usually slightly controversial. Both lists are created via a poll of various people inside hockey, who are generally very smart people, but who are also prone to old-school thinking with value sometimes being shaped by recency bias, reputation and a winning pedigree.

This list is a bit of the opposite as it comes from mostly outsiders, people who study and analyze the game in the public sphere. That’s not to say these are necessarily smarter people, they just approach the game from a different angle based mostly on underlying trends and numbers over more traditional stats and what is immediately seen on the ice.

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NHL Draft Probability Tool

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SUNRISE, FL – JUNE 27: the Boston Bruins during the 2015 NHL Draft at BB&T Center on June 27, 2015 in Sunrise, Florida. (Photo by Dave Sandford/NHLI via Getty Images)

The annual NHL draft has become a great source of entertainment for fans. Since teams make player selections based on a combination of game theory and data, the draft is also a fertile ground for analysts as well. Game theory specifically is the foundation for the Draft Probability Tool that will be presented in this piece. It will help you explore how teams should approach the draft strategically: if you’re interested in a specific player, do you need to trade up or down to get him? How much should you be giving up or asking for? How far should you trade up or down to still get the player you value highly? This tool helps answer those questions.

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xSV% is a better predictor of goaltending performance than existing models

This piece is co-authored between DTMAboutHeart and asmean.

Analysis of goaltending performance in hockey has traditionally relied on save percentage (Sv%). Recent efforts have improved on this statistic, such as adjusting for shot location and accounting for goals saved above average (GSAA). The common denominator of all these recent developments has been the use of completed shots on goal to analyze and predict goaltender performance.

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