2016-17 Hockey Graphs Top 50 Players

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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Just How Important is Quality of Competition? Very. Also, not much. It’s All Relative.

*This post is co-authored by DTMAboutHeart and Ryan Stimson*

Recently, the topic of Quality of Competition has been at the forefront of Hockey Twitter. This post hopes to articulate some of the nuance associated with Quality of Competition, as well as Quality of Teammate, metrics and how impactful they are. To do that, we will revisit methods outlined here by Eric Tulsky, namely splitting the competition and teammate quality by position and measuring the impact of each split. Ryan recently wrote about this at the NCAA level, but it has not been looked at with much rigor at the NHL level.

Both Quality of Competition and Quality of Teammates matter. They also don’t matter. It depends on the position and metric you’re looking at. All TOI data is 5v5 and from Corsica. Ryan had the game files of who was on the ice during each 5v5 shot from Micah Blake McCurdy, so that data was used as well. Also, thanks to Muneeb for feedback during this process. Thanks to all!

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Behind The Numbers: On the World Cup and Team Canada’s domination

Team Canada won the cup. Team Canada went undefeated. They were the favourites going in, and they came out the winner. Not only did they win, but they went about it in dominant fashion. They rarely trailed and they controlled nearly every facet of the game.

It wouldn’t be surprising for many to hear that the team also dominated in the shots column… but they were not the most effective team in every aspect, which raises some interesting questions.

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#1MinuteTactics – Studying The World Cup Of Hockey

When you bring the best players and coaches together, entertaining things happen. Not only that, but many of the tactical habits employed by elite hockey team are actually not so hard to grasp.

Here are five teaching points brought to us by The World Cup Of Hockey 2016, broken down and served up in just over one minute apiece:

1) Transition Play: Team North America’s Neutral Zone Mastery

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Tactalytics: Defending the Pass


At the 2nd Annual Hockey Analytics Conference at the Rochester Institute of Technology, Matt Cane and I presented on new ways of measuring and evaluating defensive play. We used the passing data from my project to take a look. I believe Matt will write up his half of the presentation, so this post will focus on my half of the presentation. You can access our slides and view our presentation here. I will go into greater detail in this post since I am without time constraints. All of the data we used can be accessed here. Everything in this post deals with 5v5 play.

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#RITHAC Slides, Video, & Recap

On Saturday, September 10th, the 2nd Hockey Analytics Conference at the Rochester Institute of Technology was held. It was a huge success and this post has the slides for each presenter, as well as video for most of the day. We had some technical problems early on, but most of the event was recorded. There is also footage of the #RITHAC Cup that was held immediately following the conference (stick tap to Conor Tompkins for Periscoping the event).

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Why Deterrents Are Irrelevant

Hits. Long-forgotten when it comes to hockey analytics and for good reason. It’s been established in many places, even on this site by Garret Hohl, that how often you hit your opponent carries little worth when it comes to predicting goals. Sure, there will always be a play here or there that works out, but by and large hits are noise. Yet, that doesn’t stop teams from shelling out big money for players that can score and hit, despite all evidence to the contrary that the latter is noise. So, why bring it up? Well, someone retweeted this into my timeline Wednesday night and I couldn’t get it out of my head.

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Behind the Numbers: Why statistic-folks are sometimes assholes, UNjustifiably

Every once-in-a-while I will rant on the concepts and ideas behind what numbers suggest in a series called Behind the Numbers, as a tip of the hat to the website that brought me into hockey analytics: Behind the Net.

Here we go. Here is part two, to what really should have been part one in hindsight prior to this piece, which would have saved me some of the backlash on Twitter, as the point was frequently misunderstood. (And while we’re dealing with hindsight, the title was part of the misunderstanding as well.)

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Behind the Numbers: Why statistic-folks are sometimes assholes, justifiably

Every once-in-a-while I will rant on the concepts and ideas behind what numbers suggest in a series called Behind the Numbers, as a tip of the hat to the website that brought me into hockey analytics: Behind the Net.

It does not take long for Hockey Twitter to complete one full rotation on its typical life-cycle of subjects. The same debates come up on shot quality, grit and leadership, eye-test versus numbers, and how statistics should be used in player evaluation again and again.

These debates often come to an impasse. Sometimes they even deviate into ad hominem and red herrings. There are parties guilty on both sides, as one would (and should) expect there to be “assholes” in every demographic.

But why is the prerogative for being nice always on the “stats guys”? Why are the “analytics guys” the only ones needing to change their ways to make things better? Why is it that only one side is discussed to be less cordial than the other?

Why does this hypocrisy exist?

I have a theory on this.

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