[Preview] Can We Predict NHL Success from WJC Performance?

Coming soon I will look come to any reasonable conclusions about the success of prospects using WJC U20 tournament data.

Data via: nhl.com, hockeyabstract.com, eliteprospects.com

Comments

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...

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...

Measuring Consistency

A while back I decided to look into player consistency, but after doing initial calculations, I never went any further. After Namita Nandakumar's VANHAC presentation on consistency, I decided to go back, refine my old work, and release the results. Namita's methodology is likely much more statistically relevant and meaningful, but nonetheless, I use a different approach that I think is worth sharing. The methodology I adopted was taken from this article on Nylon Calculus on NBA player consistency written by Hal Brown. This consistency metric gets the normalized variance of a player's performance for a given metric. In this post, I will be calculating the consistency of a player's game score (GS) in individual seasons, from 2007-08 to 2015-16, using the data provided at the bottom of the linked game score article. I also have a folder with my code + better resolution graphs + data at the bottom of the article if you'd like to check it out. Calculation T...

Three Point Games

Search This Blog