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Final Project: Analysis on NBA & WNBA pre and post COVID-19 player performance using Machine Learning.

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Final-Project-Covid-19's Impact on the NBA & WNBA

Group Members:

Tyler Speck, Matt Debnar, Sarah Grant, Caiti Donovan, Amanda Luna, Dhara Bhansali.

Overview:

  • Used the API from sportradar to fetch the data for both NBA & WNBA and cleaned the data using Pandas in jupyter notebook.
  • Created a website using HTML5/CSS and Bootstrap.
  • Interactive Visualizations were created using D3, Plotly, Matplotlib and Tableau.
  • Data was trained using Linear Regression and built Machine Learning model using nearly complete season statistics for the NBA & WNBA to determine probability of a "win."

Webiste:

Our project has been deloyed here: Final Project Website

Award:

  • Group Project awarded as “Most Potential For Impact” by Columbia Engineering;
  • Presented as CU’s Demo Day 2020.

Tech Environment Used:

Python, Pandas, JavaScript, VSCode, HTML, CSS, Bootstrap, D3, Plotly, API,Tableau, Matplotlib, Machine Learning, Tensorflow, keras, Jupyter Notebook, GitHub, Zoom, Slack.

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 97.5%
  • HTML 2.4%
  • Other 0.1%