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Hi, I’m Andrew!

Hello there! I’m Andrew Weatherman, an avid open-source R developer and a die-hard college basketball enthusiast. My journey with R began during COVID, and I am entirely self-taught. In 2022, I ventured into the realm of “real coding” and developed the toRvik package, a tool for accessing college basketball data. It was my first major project and, despite its success, presented a fair share of challenges in maintenance.

In May 2023, I embarked on a new project: cbbdata. This Flask-based API is designed to deliver comprehensive, up-to-date college basketball statistics faster and more efficiently than its predecessor, toRvik. cbbdata has been a significant undertaking, and I’m excited to finally share it with the community.

A bit more about me for those joining from Twitter: I graduated from Duke University in 2023. During my time there, I was a student manager for the men’s basketball program, coinciding with Coach K’s final run and Jon Scheyer’s first season.

What is cbbdata?

cbbdata is an R package designed for anyone passionate about college basketball statistics. It simplifies the process of accessing and analyzing a wealth of college basketball data, making it more efficient and user-friendly than ever before.

Key Features of cbbdata

cbbdata ships with 26 functions, and there is a lot to love about this package. Here are some brief highlights:

  • Comprehensive Game-by-Game Logs: Access detailed box scores and advanced metrics for players and teams dating back to 2008 (cbd_torvik_player_game() and cbd_torvik_game_box()/ cbd_torvik_factors()). You can further find per-game player and team splits on month, location, result, and game type factors (cbd_torvik_player()/cbd_torvik_team_split()).

  • Daily Updated NET Rankings: Find the latest NET rankings every morning (cbd_torvik_current_resume()).

  • Game Predictions with Barttorvik: Simulate any matchup, real or otherwise, using our game prediction feature, powered by Barttorvik (cbd_torvik_game_prediction()). It’s perfect for pre-game analyses and hypothetical scenario discussions.

  • Plot team logos with gt: Okay, sure, this one isn’t data-focused, but it’s perhaps my favorite function. Rebuild your team column with a logo and team name and render in a gt table. Gone are the days of awkwardly having separate columns for your logo and team name (cbd_gt_logos()). Just like here!

Why cbbdata?

cbbdata is designed with the end-user in mind. It’s built from the ground up to be more powerful, yet as intuitive as toRvik. The package aims to address some of the limitations of toRvik while introducing new features and capabilities. Importantly, say goodbye to loops! With cbbdata, you can access full data files by passing no arguments to functions. Otherwise, you can filter by year, team, conference, etc.

A Note on Documentation

I am aware that the documentation is still a work in progress. As a developer passionate about this project, I wanted to release cbbdata to the community as soon as possible. Continuous improvements and updates to the documentation will be made.

This release marks just the beginning. I am committed to regular updates and improvements to cbbdata, based on community feedback and evolving needs.

Get Started with cbbdata

cbbdata is now available for use! Start by signing up for a free API key, and you’ll be on your way to exploring the depths of college basketball statistics.

Install

# install.packages("devtools")
devtools::install_github("andreweatherman/cbbdata")

Registering

cbbdata::cbd_create_account(username, email, password, confirm_password)

Your Feedback Matters

As with toRvik, your feedback is invaluable in shaping cbbdata. I encourage you to share your experiences, suggestions, and questions. You can find me on Twitter.