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 model An in-season model The goal ofContinue reading “Game projection model – In-season Model (Part II)”

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”

Building the game projection model

Abstract: In the previous article I laid the groundwork for my game projection model. Now I will use the actual starting lineups and add in season adjustments using the ELO ranking principle. The data used in this article is from the 2016/2017 season to the 2019/2020 season. Finding the starting lineups: I used Evolving-Hockey’s ShiftContinue reading “Building the game projection model”

Converting season projections to game Projections

Abstract: The goal in this article is to convert my projection model (Read more here and here) from season projections into game projections. From season projections to game projections: The model as it stands right now uses p-sGAA to project team strength. I want to convert that into Win%, which is the projected number ofContinue reading “Converting season projections to game Projections”