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()
andcbd_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 yourteam
column with a logo and team name and render in agt
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.
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.