My Projects

On this page you can find more information about all of my past, current and future data science personal projects.

NHL Deep Dive

NEW

May 2023 | Hockey Analytics | Data Visualization | Python | Power BI

IN PROGRESS

Sometimes NHL data can be hard to understand or feel overwhelming for a hockey fan when looking a large data table of various statistics. We can have a general idea of the performance of a player or team just by analyzing a game's scoresheet, but most of the time we aren't getting the full picture just by looking at surface-level data.

This project's goal is to offer fans a tool to take a deep dive into a player and their team's performance based on many different data points that are represented in clear visualizations that make it easy to understand different aspects of the game. A complete dashboard with extensive filters allows fans to drill down to specific data points to discover a whole other side of the game they might've missed just by watching it live.

Pass Trackr

2022 | Hockey Analytics | Data Collection | Python

We often time don't give enough credit to one of the most important aspects of the game of hockey, passing. Setting up plays, de-escalating plays in the defensive zone, creating scoring opportunities... you name it! However, from the publicly accessible NHL datasets out there, there aren't any that have data for passes. That is why I took it upon myself to create a program that allowed me to manually track passes with ease and then transforms the data into pertinent information to discover a player's passing tendencies.

NHL Playoffs Rundown

March 2022 | Hockey Analytics | Data Visualization | Python

During the 2021-2022 NHL season, I wanted to put myself to the test and create different visualizations to compare two teams going head-to-head in the 2022 NHL playoffs. An extensive summary of both team's regular season performance allowed fans to gain a better understanding of how these teams compare to each other and which aspects of the game a certain team could take advantage of to gain an edge over their opponent.

A different visualization for each match-up was created for every round of the post-season, highlighting each team's tendencies, performance at every manpower situation, and their leading players for different categories.