Year: 2016

Predicting Shot Differentials for NCAA Players

Ryan Stimson Uncategorized Leave a comment

While there has been an increase in the type of data that’s available to us on prospects, we are still lacking across all developmental leagues. More importantly, and this is particularly true for the NCAA, player-level data still eludes us, even when there is team-level data present. To get at the context with which a player performs and the factors governing his or her environment, we are left with estimates of things like ice time and quality of competition/teammates.

While this hasn’t stopped us from making advances to enhance traditional scouting and prospect analysis, having player-level shot metrics would be a wonderful piece of data to have when evaluating their performance. This article will look at a method to predict those numbers.

Special thanks to DTMAboutHeart and Matt Cane for their feedback and guidance at certain steps in this process.

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League Wide Report for Weeks 1-4

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As a person who learns best by looking at visual representations of data, I have a couple of statistics that I check on a regular basis to hep me calibrate my interpretation of what’s happening around the NHL. I’m going to start sharing them in a regular series that I hope will give a quick overview of how teams are performing around the league. The goal is for this to be a high level view of the basic trends for all 30 teams that will draw attention to specific areas that might need to be explored further. The charts in this article are up to date through last night’s games. All data is via corsica.hockey.

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Behind the Numbers: Why Plus/Minus is the worst statistic in hockey and should be abolished

Garret Hohl Behind the Numbers 11 Comments
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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.

Hockey’s plus/minus may be the worst statistic in hockey, although there is some debate with goalie statistics not based off of save percentage (like GAA or Win% that just adds a team component to a goalie’s save percentage). It could even be in contention for just the worst statistic in sport.

Now, some people may read that and think I’m simply saying this because I value shot metrics over goal metrics in player evaluations. While I do feel that way, it is only one of a few reasons that that plus/minus fails in being useful.

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Hockey Graphs and Vancouver Canucks Co-Host Vancouver Hockey Analytics Conference 2017

Garret Hohl Conferences Leave a comment

 

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Hockey Graphs is excited to announce that we will be co-hosting the Vancouver Hockey Analytics Conference (#VanHAC) with the Vancouver Canucks along with HockeyData and Canucks Army.

Date: Saturday, March 11th, 2017

Location: Rogers Arena, Vancouver, Canada

Website: HockeyGraphs.com/VanHAC

The call for speakers is currently open with a deadline of January 10th, 2017.  See the website for more details or go here to submit your submission.  

Registration has yet to open as we tabulate the final costs to host the venue, among other factors. Check back here or on Twitter for more information when it will open. (Note: Expect participants to be capped at around 100 people.)

Watch the VanHAC page for updates as they are released!

Introducing the 2016 – 2017 Forechecking Project

Ryan Stimson Forechecking Data Leave a comment

Passing and Zone Entries are so last year.

When Corey Sznajder decided to track microstats for the upcoming season and began incorporating my passing concepts into his work on last season’s playoffs, I wondered if we really needed to track this season. Instead, Corey and I chatted a bit and decided the best use of everyone’s time would be if myself and the other passing project volunteers continued to work on last season*, with the hope that we can build a solid sample by the time Corey finishes the 2016 – 2017 season. Having two (nearly) full seasons of data would be excellent to have.

However, this also gave another idea to explore something we really haven’t done a lot of: forechecking.

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2016-17 Hockey Graphs Top 50 Players

omgitsdomi NHL League-Wide Analysis 4 Comments

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

Ryan Stimson Exploring Context, NHL League-Wide Analysis, Practical Concerns 2 Comments

*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

Garret Hohl Behind the Numbers, Neutral Zone Analysis Leave a comment
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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

Jack.Han Theory, Uncategorized Tags: , , , , , , 1 Comment

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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