<h2>Overview:</h2>
<p>DataBall is a project that combines data science and sports by attempting to predict NBA winners against the spread. The project uses statistics pulled from the NBA stats website, point spreads, and over/under lines from covers.com. All predictions are made using Python and the scikit-learn machine learning library.</p>
<h2>Features:</h2>
<ul>
<li><strong>Scraping data</strong>: The project includes a Scrapy project that can scrape point spreads and over/under lines from covers.com.</li>
<li><strong>Support functions</strong>: The project includes a Python module called "databall" that provides support functions for tasks such as collecting stats to a SQLite database, simulating seasons, and customizing plots.</li>
<li><strong>Documentation</strong>: The "docs" folder contains the necessary code to build the GitHub Pages site for this project.</li>
<li><strong>Notebooks</strong>: The "notebooks" folder contains Jupyter notebooks of all analyses.</li>
<li><strong>Report</strong>: The "report" folder contains LaTeX files for the report and slides.</li>
</ul>


Klane

Databall