Video tutorial: Working with Shot data
Video 1: Combining Shot Statistics data from multiple seasons into one pivot table in Excel Video 2: Creating a Shot visualization in Power BI Files: Shot Statistics Data (Onedrive link with updated data), Rink Image and Power BI project. Online link to the Project In order to publish Power BI projects you will need a…
Video Tutorial: Creating a Shot Visualization Tool
The primary goal with this video tutorial is to show that shot tracking and shot plotting doesn’t have to be that complicated. The visualization is created in Excel, because it’s what I know, but also because Excel is less intimidating to most people. The end goal is to get more people interested in hockey statistics!…
Building an xG model – v. 1.0
In this article I will take a first crack at building an xG model from scratch. As with most things I do, the approach is slightly different from the other public xG models. Background and purpose: Before we get to the actual model building, it’s important to understand what an xG model is… And what…
Introduction To Hockey Statistics – First Chapter
You can find the full book here: https://hockeyskytte.gumroad.com/l/Hockey-Statistics Table of contents 2. Shot statistics Most statistics in hockey is based on shots. So, that will naturally be the focus in the first chapter. I think the best way to describe shot statistics is through a shot hierarchy. At the top you have the result, and…
BDC 2022 – Transforming Event Data Into Possession Data
Abstract The event data by Stathletes for the Big Data Cup is very detailed. This should allow us to determine when (time), where (coordinates) and how (event) a player gains possession of the puck. Likewise, it should be possible to determine when, where and how a player losses possession of the puck. In other words,…
Game projection model – Pre-season Model (Part IIIA)
This is the continued saga of “how to build a game projection”. I’d recommend reading the three previous articles of the series before you continue reading this post: The goal in this article is to lay the groundwork for the final game projection model. In the previous article I built the in-season model. Today I…
Game projection model – In-season Model (Part II)
In this article I will start building my game projection model. I’d recommend reading the two first articles of the series before you continue reading this post: The model construction The idea is to build a game projection model that actually consists of two separate models: A pre-season modelAn in-season model The goal of the…
Hockey Deployment Management analysis using Machine Learning
This article is written by Chris from ImPCT Sport. Follow them on Twitter: @ImpctSport. Here’s the previous articles written by ImPCT Sport: Lineup deployment management is a subject of debate in the sport community. By lineup deployment, I mean the manner in which ice time and starts are divided (or spread) between players during a…
Game projection model – The Variables (Part IB)
After I published the last article, I had a great conversation @IanGraph. Based on this conversation, I’ve decided to make a follow-up article. The main question is: Why does my findings on predictability differ from other research on the subject? Tests typically show that corsi and expected goals are better predictors than actual goals. However,…
Game projection model – The Variables (Part I)
The goal with this series is to build a new game projection model. In this first article I will focus on the different variables/metrics. I want to test how well they predict future results. The old model But first a few comments on the old model. It was built on the basis of Evolving-Hockey’s GAR…
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