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R workshop 2022

Structure: 5 x two-hour sessions, each with presentation of course material, and time during which participants can work on exercises or with their own data.

Preparation

Participants are asked to install R, RStudio, Git, and some R packages in preparation for the workshop, if they do not already have these on their computer.

  1. Download and install R

    https://cran.r-project.org/

  2. Download and install RStudio

    https://www.rstudio.com/products/rstudio/download/#download

  3. Download and install Git

    https://git-scm.com/downloads (Accept all the default options when installing)

  4. Start RStudio and install some packages. This will take a while to run:

    install.packages(c("tidyverse", "remotes"))

    And finally:

    install.packages("datavolley", repos = c("https://openvolley.r-universe.dev", "https://cloud.r-project.org"))

Course sessions

  1. An introduction to R
    Introductions and a general overview of R.

  2. The R datavolley package
    Focus on the datavolley package in R, reading your data in and working with it.

  3. Advanced reports
    Different methods of conveying information (tables, graphs, court plots, video) and how to generate these in R. Heatmaps, video playlists, and more.

  4. Advanced analytics
    Advanced analytics to support decision making, match preparation, and similar. Examples of statistical models, simulating matches.

  5. Computer vision in R
    Other odds and ends, including computer vision and video processing.

Acknowledgements

The example data used in this workshop was provided by:

  • DE Men 2019 - 10 matches from the 2019/20 German 1. Bundesliga (Men) season, provided by Michael Mattes
  • DE Women 2020 - 3 matches from the 2020/21 German 1. Bundesliga (Women) season, provided by Michael Mattes
  • VNL_Women_2021.csv - a summary of team performance from the 2021 Women's Volleyball Nations League. Match data provided by Pablo Sánchez Morillas and Lauren Bertolacci, and analyzed with https://apps.untan.gl
  • NCAA_D1W_2019.csv - set scores from the 2019 NCAA D1 season, from https://stats.ncaa.org/
  • Serve_Speed_Example - serve speed data, provided by Felipe Aparecido Lima
  • rec_height_ITA - long-term player heights and passing performance from the Italian A1 league, from http://www.legavolley.it/