Tutorial Sports Analytics with R

Last updated on Oct 1, 2021

👋 Welcome!

This website includes the tutorial R-Markdown files that analyzes the 2019 Final of the Australian Open between Novak Djokovic (SER) and Rafael Nadal (ESP) using Robert Seidl’s hand-coded data.

Why R?

👉 It’s one of the most popular tools used for data analysis
It can handle large amounts of data (unlimited!)
It’s perfect for unstructured data (Twitter, Facebook, News, Reedit, Linkedin, IMBD, etc)
It makes some of the best pictures in the business
It records every step of your analysis (easier replicability!)
It has a huge online community of users/supporters

What will we do in the tutorial?

We will get an introduction to R by following the steps recommended by the book “R for Data Science” (reference below). These are basic steps that anyone wishing to embark in a data analysis project should follow:

Import (from a file, a database, a website, etc)
Tidy (mainly clean and make it consistent)
Understand: Transform -> Visualize -> Model -> Repeat … (Graphs, Statistical Models, Machine Learning, etc)
Communicate

What should I do before the tutorial?

You can get ready for the tutorial by either

Installing R and R Studio in your own computer
Or Signing-up in RStudio Cloud before the tutorial. It’s free. It’s easy. It’s in the cloud. If you want, you can log in, create a project and start playing with RStudio.
Then, the day of the tutorial (or before if you have the time). Please login into your RStudio Cloud account, create a project and upload the tutorial files to your new project.

Please be sure to download Tutorial Files before the meeting time

Useful References

Grolemund, G. and Wickham, H. (2017) “R for Data Science”, O’Reilly Media
R Markdown Cheasheet
Tidyverse: a collection of the most commonly used packages used in data science
Documentation of ggplot2: package to make nice looking graphs
Documentation of PivotTabler: package to make pivot tables
Documentation of glmnet: package that fits generalizable linear models