Every Wednesday I will upload a new video to YouTube. I will add the videos in this article as we go along.
Schedule
2024-08-21: Getting data from the NHL Api based on date selection
2024-08-28: Scrape Shift data from the NHL HTML reports
2024-09-04: Get Play-by-Play and shift data for a full season at a time
2024-09-11: Scrape Play-by-Play and TOI data from the PWHL or the AHL
2024-09-18: Install MySQL and load data to a database
2024-09-25: Clean the NHL Play-by-Play data in MySQL
2024-10-02: Clean and transform the NHL Shift data in MySQL
2024-10-10: Combine the Play-by-Play and Shift data
2024-10-23: Prepare shot data for logistic regression modelling
2024-10-30: Make an xG model in Python using Scikit-learn
2024-11-06: Install Power BI desktop and load data from the MySQL database
2024-11-13: Build a Shot Visualization in Power BI using Icon Map
2024-11-20: Add Rink zones with GeoJSON
2024-11-27: Build a Line Tool visualization
Introduction
Video 1 – Getting data from the NHL Api based on a date selection
In the first video we build a tool to get play-by-play and shift data from NHL Api based on a date selection. This is useful if the goal is to do daily updates.
Video 2 – Scraping Shift Data from the NHL HTML reports
In the second video we scrape and clean shift data directly from the HTML reports. This is relevant if you want to get live shift data – The shift data in the NHL Api doesn’t update until after the game.
Video 3 – Getting data from the NHL Api based on a season selection
In the third video we build a tool to get data for a full season at a time. This is relevant if you want to build a database with historic data.
Video 4 – Scraping Play-By-Play data from the PWHL (or the AHL)
In the fourth and final video about getting data we will build a tool to scrape data from the PWHL website. We will also do some data cleaning directly in Power Query.
Video 5 – Installing and Loading NHL data into MySQL database
In the fifth video we learn how to install and load data into MySQL.
Link to the MySQL Installation Guide
Video 6 – Transforming and Cleaning Play-By-Play NHL Data in MySQL
In the sixth video we’re transforming and cleaning the play-by-play data in our database.
Video 7 – Transforming and Cleaning Shift Data from NHL Api in MySQL
In the seventh video we’re transforming and cleaning the Shift data in our database.
Video 8 – Combining Play-By-Play and Shift Data from the NHL in MySQL
In the eighth video we’re combining the play-by-play and shift data. This allows us to determine who is on the ice for every event.
Video 9 – Prepare Shot Data for logistic regression modelling (xG) – MySQL
In the ninth video we do some final preparations before building the xG model and write the data to a csv file from MySQL.
Video 10 – Build an xG model in Python using Scikit learn
In this video we’re building an xG model in Python using the Scikit Learn library.
Contact
If you have questions or comments you’re more than welcome to contact me.
email: hockeystatistics.com@gmail.com
Twitter: https://twitter.com/HockeySkytte
YouTube: https://www.youtube.com/@hockey-statistics268
Support
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