Newsletters

We regularly publish newsletters, along with our other hockey analytics and AI content. We group the newsletters into series using custom tags, which you can find below.

This series is for absolute beginners. If you're looking to become a Data Analyst, Sports Scientist or Data Scientist but are new to hockey, then this is a great first step in the journey.

For more details, visit Puck 101.

We've built three levels of Data, AI and Hockey content into this newsletter series. You might consider it a newsletter-based course. We cover beginner, intermediate and advanced topics that will help launch your Hockey Analyst career.

Level 100

• What is Hockey Analytics?
• What are Data Types When Analyzing Hockey Data?
• What are Good Sources of Hockey Data?
• How will AI Impact Hockey Analytics?
• What is Descriptive Analytics for Hockey?
• What is a Team Performance Report?
• What are Common Data Analysis Tools?
• What is a Player Performance Report?
• PDO: How Lucky are Ya?
• What Makes a Winning Playoff Team?

Level 200

• Who are the Top Ten Playmakers in the NHL?
• How can I create a Team Summary Dashboard in Power BI?
• Instant Hockey Analyses using ChatGPT and AI
• Creating and Designing a Player Performance Dashboard using Power BI
• Analyzing Shots and their Relationship to Goals
• Enhancing your Power BI Reports with Linear Regression Models
• Where are all the Enforcers?
• Guardians between the Pipes: The Stats Behind Hockey's Top Goalies
• Ice Breakers: Decoding the Impact of Injuries in Hockey

Level 300

• How Successful is our Power Play Strategy by Goals?
• What is the relationship between Shot Percentage and Wins?
• What is a Good Predictor for Goals?
• Can you use Winning Percentage to Predict a Team Winning?
• Are your Athletes ready for Game Day?
• More Money, More Wins?
• Using Linear Regression to Predict Goals
• Overview of Goals Versus Threshold

For more details, visit Analytics & AI Camp.

• Instant Hockey Analyses using ChatGPT and AI
• Finding the Top Snipers using K-Means Clustering
• Predicting Game Wins using Logistic Regression
• Using Linear Regression to Predict Goals
• Predicting Wins using Support Vector Machine Models
• Driverless AI: Building the Perfect Predictive Model
• Optimizing your Predictive Models
• Predicting Wins using k-Nearest Neighbors

In this series, we focus more on exploring sports data to create narratives and tell a story.

For more details, visit Sports Data Storytelling.

In this series, we look at different scenarios and create reports and dashboards using Microsoft Excel and Power BI.

For more details, visit Dashboard Daze.

This series covers our NHL Draft analyses for the 2024-2025 season, which look at the incoming draft prospects into the NHL.

For more details, visit NHL Draft 2024.

This series explores strategies and tactics to bring analytics into the world of DFS Fantasy Hockey.

For more details, visit DFS Fantasy Hockey.

In this series, we explore data extending back 108 years that covers the full NHL history and analyze the different eras of hockey, key players throughout history and how the game has changed.

For more details, visit Vintage Hockey Series.

This series features analyses of the four nations that are participating in the NHL's Four Nations Face-Off tournament in February, 2025. We'll be doing a deep dive on each team, ending the series with a prediction on who will win the tournament.

For more details, visit 4 Nations Face-Off Tournament.

Subscribe to our newsletter to get the latest and greatest content on all things hockey analytics!