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Collect/clean NFL data via web scraping, visualize data with Plotly

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chriskeating603/nfl_visualizations

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Visualizing Fourth Down in the NFL, 2013-2020


Background

Every Sunday, you can hear an announcer talk about "going for it" on fourth down in the NFL. This has certainly changed in the past decade. (For those that aren't familiar with the NFL or fourth down, this is essentially a risky play that can have a large impact on win probabilities depending on the outcome.) There are many interesting questions to ask regarding fourth down:

  • Has risk tolerance really increase over the past decade?
  • Which teams were at the leading edge, and which team lagged behind?
  • What is the difference between 1 yard and 2 yards? 3 yards and 4 yards?

I genuinely enjoyed working on this project. I watch the NFL on Sundays, play in a fantasy football league, and listen to football analytics/betting podcasts, but I thought it was time for me to jump into it myself!


The Project

Here are some skills I demonstrate in this project:

  • writing clean, organized, and modular code
  • visualizing complex trends in intuitive ways using Plotly
  • web scraping using requests and BeautifulSoup
  • feature engineering

License

MIT


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Collect/clean NFL data via web scraping, visualize data with Plotly

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