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A Basketball Big Data Platform for Box Score and Play-by-Play Data.
1Valencia, Valencian Community, Spain.
Big Data
|April 12, 2024
Summary
This study enhances basketball data analysis in Spain by introducing a new dashboard for advanced play-by-play statistics. It provides deeper insights into player and team performance beyond basic box scores.
Area of Science:
- Sports Analytics
- Data Management
- Basketball Performance Metrics
Background:
- The Spanish Association of Basketball Clubs (ACB) is a top European league with significant talent, yet lacks advanced data analysis.
- Previous research introduced basic box score visualization, highlighting a need for more sophisticated data treatment.
- Current basketball statistics in the ACB are rudimentary, limiting performance insights.
Purpose of the Study:
- To develop advanced analytical tools for basketball data management in Spain.
- To present a novel dashboard for interactive play-by-play data visualization.
- To create a comprehensive data platform integrating both box score and play-by-play statistics for the ACB.
Main Methods:
- Development of an interactive web application for play-by-play data analysis.
- Integration of play-by-play data with existing box score visualization tools.
- Creation of a comprehensive data platform for Spanish basketball statistics.
Main Results:
- A new dashboard enabling novel perspectives on play-by-play basketball data analysis.
- Enhanced insights into player and team performance through advanced data visualization.
- A unified platform for accessing and analyzing both box score and play-by-play ACB data.
Conclusions:
- The developed tools significantly advance basketball data management and analysis in Spain.
- Play-by-play data offers deeper performance insights compared to traditional box scores.
- The comprehensive platform supports improved understanding and utilization of basketball statistics.
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