VREN: Volleyball Rally Dataset with Expression Notation Language
Haotian Xia, Rhys Tracy, Yun Zhao, Erwan Fraisse, Yuan-Fang Wang,, Linda Petzold

TL;DR
This paper introduces VREN, a comprehensive volleyball rally dataset and a descriptive language for rally analysis, enabling automated prediction and tactical insights to advance volleyball research and coaching.
Contribution
It creates the first detailed indoor volleyball dataset with a new descriptive language and defines three tasks for automated rally analysis and tactical understanding.
Findings
Baseline results established for rally outcome prediction
Effective models for setting and hitting type prediction
Insights into volleyball tactics and attack zones
Abstract
This research is intended to accomplish two goals: The first goal is to curate a large and information rich dataset that contains crucial and succinct summaries on the players' actions and positions and the back-and-forth travel patterns of the volleyball in professional and NCAA Div-I indoor volleyball games. While several prior studies have aimed to create similar datasets for other sports (e.g. badminton and soccer), creating such a dataset for indoor volleyball is not yet realized. The second goal is to introduce a volleyball descriptive language to fully describe the rally processes in the games and apply the language to our dataset. Based on the curated dataset and our descriptive sports language, we introduce three tasks for automated volleyball action and tactic analysis using our dataset: (1) Volleyball Rally Prediction, aimed at predicting the outcome of a rally and helping…
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Taxonomy
TopicsSports Analytics and Performance · Sports Performance and Training · Software System Performance and Reliability
MethodsEmirates Airlines Office in Dubai
