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”
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”
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”
How well do cap hits correlate with player performance (LS-GAA)?
Discussing the voodoo that is goaltending – can you isolate and evaluate goaltender performance?
How does LS-GAA rank defenders? We take look here.
A deeper look into LS-GAA at the player level. Focus is on the forwards.
Using LS-GAA to compare teams.
Creating my own model (LS-GAA) from existing GAR models.
How corsi, expected goals and PDO correlates with winning