Basketball statistics have numerous publically available datasets. I will be utilizing many of these datasets to practice scrapping data, cleaning data, creating graphics and building models in both R and Python.
Models Created:
- Predicting Vucevic Double-Doubles: Use logistic regression to predict if Nikola Vucevic is likely to achieve a double-double. Full project from webscrapping, data cleaning, to testing and evaulating models.
Visaulization Projects:
- Fultz Magic v Philly: Visualizing the change in Fultz's Game Score over time both with Philly and the Orlando Magic. Pulled before his 2021 injury.
- Is Our Rookie Better Than Your Rookie?: Visually compares the Magic's PG Cole Anthony against other members of the 2021 NBA rookie class through numerous ggplot graphs after scrapping and cleaning datasets.
- Should the Magic Sign a Point Guard?: Uses visualizations to compare potential point guards. First created immediately following Fultz's injury and before Cole Anthony became the Magic's starting Point Guard. Extensive use of rvest for web scrapping and ggplot2 to create graphs.
Web Scraping How-To:
- Web Scraping All-Star Stats: Use rvest to scrape Basketball-Reference data from All Star players and combine with indivdual player stats for Shaquille O'Neal.
Datasets Utilized:
- Baksetball Reference Orlando Magic Game Log: https://www.basketball-reference.com/teams/ORL/2010/gamelog/
- Stathead GmSc for Orlando Magic Players: https://stathead.com/basketball/pgl_finder.cgi?request=1&match=game&order_by_asc=0&order_by=pts&lg_id=NBA&is_playoffs=N&age_min=0&age_max=99&team_id=ORL&season_start=1&season_end=-1&positions%5B%5D=G&positions%5B%5D=GF&positions%5B%5D=F&positions%5B%5D=FG&positions%5B%5D=FC&positions%5B%5D=C&positions%5B%5D=CF&game_month=0