Volleyball Analytics with R: Spike Data, Team Performance & Visualization is an in-depth, thesis-level handbook for coaches, analysts, and data-savvy volleyball enthusiasts who want to turn match statistics into actionable performance insight using R. The book bridges the gap between traditional volleyball box scores and modern data science by showing how to acquire data from professional sources, structure it into analysis-ready tables, and apply reproducible, code-driven methods to evaluate players, lineups, rotations, and team strategy.
It begins by establishing the statistical “language” of volleyball—kills, errors, attempts, aces, reception quality, blocks, digs—and then builds toward the metrics that actually drive winning: attack efficiency, serve risk–reward, sideout and breakpoint rates, error pressure, and contribution by phase of play. Along the way, it demonstrates how to work with volleyball-focused R tooling (including workflows for scouting-style play-by-play data and league-level datasets), how to validate and clean messy match logs, and how to design analyses that remain comparable across matches, opponents, and seasons.
A major emphasis is visualization: the book explains how to create coach-friendly graphics such as attack distribution heatmaps, serve placement and pressure maps, rally/run momentum charts, and role-based player profiles. It also introduces modeling approaches that elevate descriptive stats into predictive and explanatory analytics—such as logistic models for point and set outcomes, lineup and rotation comparisons, clustering for role identification, and simulation-based “what-if” analysis to quantify how improvements in sideout or serving translate into match win probability.
Written in a professional academic tone while remaining code-forward and practical, the book serves as both a complete learning path and a reference manual for building volleyball analytics projects in R—from single-match scouting reports to season-long performance monitoring and advanced research workflows.
Pages: 25
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