New Work on Other Websites

I recently wrote a fan post on Broad Street Hockey breaking down how the Flyers have drafted since the lockout, as well as some general leaguewide draft analysis. Here's a link. Additionally, several of these graphs or a close equivalent were featured in this article on the Islanders draft history by Arthur Staple from The Athletic.

I also wrote a tutorial on using gganimate and R to create shot location game gifs. This can be found at http://barloweanalytics.com/gganimate.html

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Tape to Tape Tracker Visualization

tapetotapetracker.com has created an excellent way to track shots, shot assists, and zone entries. Using an 11 game sample of 5v5 data from here provided by Prashanth Iyer, I created a Tableau visualization to map the shot and shot assist data. This data includes all shot attempts classified by type, and when relevant the pass leading up to the shot. The "origin" is where the passer makes the pass, and "destination" is where the pass is received. Finally, each shot is denoted as "goal" "shot"- SOG or "missed shot", and the location is where the shot was taken. Some features include viewing by the shooter, passer, team, and game. You can also select specific events and results. Result filters an entire event by what its end result was. For example, if "goal" is selected, it will show all events (origin+destination+shot) which resulted in a goal. Similarly, event filters for individual events. This means that specific types...

Tape to Tape Shot Visualization

In this post, I'll be breaking down my newest (and favorite) viz, which acts as a pretty comprehensive overview of tape to tape shot data. This is based on my previous tape to tape viz but has many new features. I'm going to go through each component of the display below, and explain how they work. You'll be able to work with the viz at the bottom of the page, and any feedback or suggestions are greatly appreciated. 1) The Rink First I'm going to explain what you're directly looking at. There are three parts to the rink: the points, the lines, and the tooltip (the box that pops out when you hover over a point/line). Both points and lines are colored by the event result. Goals are green, shots on goal are blue, and missed shots are tan. There are two different points: a circle and a square. Circles represent either where a pass was made or received. Squares represent the location of shot attempts. Lines show the flow of events. They grow in size as the eve...

Who Plays Where? Determining Skater Positions Using Clustering

While browsing through various different websites keeping NHL player stats, I realized that the league does a terrible job of keeping updated player positions. I’m not exactly sure how or where they get their data from, but it is quite inaccurate. All sites do distinguish between forwards and defenseman, which is enough for most analysis, but I still think more specific player positions hold value, especially when looking at team depth and related areas. In an attempt to solve this problem, I decided to use k-means clustering on location information within play-by-play data (thanks to Emmanuel Perry and Corsica Hockey for making this cleaned data available to the public). Clustering has been used pretty frequently in hockey analysis, most recently (I believe) to identify different styles of goal scorers by Alex Novet. It has also been used by Ryan Stimson to identify team and player styles with data collected from his passing project and similarly on DTM About Heart’s old blog...

Three Point Games

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