Introduction To Hockey Statistics – First Chapter

Table of contents Introduction Shot Statistics2.1 Shot Hierarchy2.2 Shot Formulas2.3 Shot Tracking2.4 Summary Predictability3.1 Descriptive vs. Predictive3.2 Test setup3.3 Results3.4 Conclusion3.5 Sustainability vs. Luck3.6 Summary Data categories4.1 Team-, Individual- and On-Ice Statistics4.2 Player models4.3 Summary Analyzing a team sport5.1 Productivity5.2 Output vs. talent5.3 Summary Data Interpretation6.1 Biases6.2 Sample size6.3 Context6.4 Summary Data Sources7.1 Statistics sources7.2Continue reading “Introduction To Hockey Statistics – First Chapter”

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,Continue reading “BDC 2022 – Transforming Event Data Into Possession Data”

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 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,Continue reading “Game projection model – The Variables (Part IB)”

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”


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