Tag Archives: NHL

New Visualization – Player Profiles

In the coming days and weeks, I hope to add new features/visualizations to the Statistics Tab. The new profile visualization can be found by clicking on Player Statistics 23/24. If you enjoy my work and wish support my continued work you can either donate a small amount below or Subscribe to my website (10$ annually).Continue reading “New Visualization – Player Profiles”

NHL Guide: 2023/2024

The following article is part of the NHL Guide 2023/2024. If you want access to the full guide (including Visualizations) or you just want to support my continued work, you should subscribe for just 10$ annually. Model Description 3-year weighted data: The season projections are based on performances from the previous 3 seasons. Last seasonContinue reading “NHL Guide: 2023/2024”

Explainer – Player Cards

In this piece I want to talk about the newly created Player Cards. The player cards are meant to describe the performance in the 22/23 NHL season. These cards should be seen as temporary cards until the new models are ready. In the coming weeks (or months) I will rebuild the models that all myContinue reading “Explainer – Player Cards”

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 aContinue reading “Hockey Deployment Management analysis using Machine Learning”

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 GARContinue reading “Game projection model – The Variables (Part I)”

Deep Dive into Offensive and Defensive Quality in the NHL

This article is written by ImPCT Sport. Make sure to give them a follow on Twitter @ImpctSport. In my previous publication, I covered the ImPCT Engine. The ImPCT engine is a machine learning based algorithm that was developed to process large amounts of sport related data and provide meaningful intelligence on the performance of players.Continue reading “Deep Dive into Offensive and Defensive Quality in the NHL”

Deep Learning Modeling of Hockey Game Contribution

The article below is written by Chris Tremblay from ImPCT Sport. Make sure you’re following them on Twitter @ImpctSport. They’ve created a player evaluation model based on machine learning, and here’s a short introduction to the model. More to come from ImPCT Sport in the future. Player profiles using the ImPCT engine Assessing player’s entireContinue reading “Deep Learning Modeling of Hockey Game Contribution”

Blog 8: Player tiers based on LS-GAA

In this blog I will try to put players into tiers based on their LS-GAA. To start with I will look at the forwards. The thought process is that there’s an elite tier with a small, but very impactful group of players. I have made 5 tiers – Tier 1: Elite players, tier 2: 1stContinue reading “Blog 8: Player tiers based on LS-GAA”