Sports Analytics with R
Description: This will be a crash course on how to use R to conduct data science for sports. After this course, participants will be able to scrape sports data from the Web, use graphics to explore data, apply statistical and machine learning models to address interesting questions in sport, and publish their findings to the Web.
Prerequisites: Basic proficiency in R and familiarity with the dplyr and ggplot2 packages.
Requirements: Laptop loaded with latest version of R. The specific packages to be pre-installed will be provided prior to the tutorial.
1. Getting the data: Web scraping and wrangling with sports data
2. Exploratory data analysis in 2D and 3D
3. Advanced programming to define new classes and methods for unique data types in sport
4. Introduction to common ranking methods and predictions models in sport
5. Sports blogging with markdown, github and interactive graphics