"Most decisions are not binary, and there are usually better answers waiting to be found if you do the analysis..."

My 2023-2024 NBA Player Comparative Performance Analysis project represents a transformative approach to understanding the dynamics of professional basketball, blending deep statistical insights with innovative data analysis techniques. As a student in ACAD-220: Data Analytics and Innovation, I was tasked with examining player performance across two consecutive NBA seasons, focusing on uncovering patterns and trends that can offer a clearer view into player consistency and development.

Thoughtful analysis, human insights, and DNA of the game.

Talent wins games, but teamwork and intelligence wins championships. - MJ

Drawing inspiration from advanced data analysis techniques, specifically paired t-tests and predictive modeling, I proposed a robust framework for examining year-over-year changes in player performance. The analysis centered on extracting meaningful insights from over 75 players’ statistics—balancing the technical rigor of statistical exploration with dynamic visualizations that made the findings accessible to a broad audience. These visualizations helped uncover shifts in key performance metrics such as scoring averages, shooting accuracy, and minutes played.

• Conceptualized and executed a comprehensive data analysis process that merged exploratory analysis with predictive modeling
• Created memorable insights by leveraging Python-based data cleaning, analysis, and visualization tools
• Engineered comparisons between 2023 and 2024 NBA playoffs to identify consistent and high-impact performers

Teamwork makes the dreamwork.

It was a tremendous opportunity and great pleasure to apply my data science skills to sports—a lifelong passion of mine—and to contribute fresh perspectives on the evolving game. Here's a few things I learned:

• Acquired a deep understanding of sports analytics workflows, from data preparation to visualization
• Mastered the art of extracting meaningful trends from large datasets and presenting them effectively
• Cultivated the ability to bridge technical findings with insights relevant to teams, analysts, and fans

For the love of the game...

After completing this project, I delved deeper into the potential of data-driven insights in sports, focusing on how analytics can support player development and team strategy—a focus reflected in the findings shared here.

See more from this project: ‍

‍"Shoot my shot, Steph Curry it's a swish"