A comprehensive guide to building volleyball analytics workflows in R, covering data collection, cleaning, and analysis. The tutorial demonstrates how to calculate key performance indicators like sideout efficiency, break point percentage, and serve pressure. It includes practical R code for rotation analysis, attack
•23m read time• From r-bloggers.com
Table of contents
Table of ContentsWhy Volleyball Analytics (and Why R)Volleyball Data Model: Events, Rally, Set, MatchData Sources: Manual Logs, Video Tags, DataVolley-Style ExportsR Project Setup & ReproducibilityImport & Clean Volleyball Event DataCore Volleyball KPIs (Serve, Pass, Attack, Block, Dig)Sideout, Break Point, Transition & Rally Phase AnalyticsRotation, Lineup, Setter Distribution & MatchupsServe & Serve-Receive Analytics (Zones, Heatmaps, Pressure)Attack Shot Charts, Zones, Tendencies & ScoutingModeling: Expected Sideout, Win Probability, Elo, Markov ChainsPredictive Modeling with tidymodelsBayesian Volleyball Analytics in RVisualization: ggplot2 Templates for VolleyballDashboards: Shiny Scouting ReportsAutomation: Reports to HTML/PDF + CIBest Practices + Common PitfallsRecommended BookFAQSort: