Projects

Here are some recent and on-going projects.

Exploring Patterns and Trends in MMA
(Presentation Slides)

The motivation behind this project was to analyze UFC match data and identify interesting patterns and trends in the sport. The data was obtained from http://ufcstats.com/statistics/events/completed via web scraping with Python and Beautiful Soup Python Library. The data source provides comprehensive data on fighters and matches in past events. The collected data included events from UFC 1 (Nov 12, 1993) to UFC on ESPN (May 30, 2020).

The following questions were explored in the preliminary analyses:

  • How do fights end?
  • How has that changed over time?
  • How does fight outcome differ by weight class? By men’s or women’s divisions?
  • How do performance metrics influence fight outcome?

Technologies used: Python, Pandas/NumPy, Matplotlib, Plot.ly, Scikit-learn Beautiful Soup, HTML/CSS


Visualizing The Elite – A Data Analytics Approach to All Elite Wrestling
(https://vizelite.com/)

Visualizing the Elite combines two things I really enjoy: professional wrestling and data analytics. The motivation behind this project is to utilize match data to provide an overview of things like how your favorite wrestlers are performing in terms of wins and losses, how often wrestlers are used on specific programs, and how wrestlers are being featured in in-ring competitions. The interactive dashboards can be used to enable users to explore the rankings and statistics among wrestlers. The analytical platform can be used to assist in developing storylines among wrestlers.

Technologies used: Python, Beautiful Soup, JSON, Tableau, HTML/CSS, Bootstrap


All Elite Wrestling Dynamite Twitter Activity Report
(http://twitter.vizelite.com)

The motivation behind this project is to capture user activity on Twitter during a major television broadcast and observe how well the program is resonating with their audience. The analysis can identify popular topics and hashtags, locate key users, and provide additional insights on how content is being shared.

I applied this to AEW Dynamite which airs on TNT every Wednesday at 7pm CST for its 2 hour broadcast of wrestling matches and promos. The episode on Wednesday, March 18th, 2020 was especially interesting for several reasons – from anticipated reveals to the first time having to air with no live audience due to the Coronavirus pandemic.

Technologies used: Python, Pandas, NumPY, PostgreSQL, Plot.ly, HTML/CSS, Bootstrap