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Match score dataset for team ball sports
Thaksheel Alleck1, Tommaso Giovannelli1, Luis Nunes Vicente1
1Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, PA 18015-1582, USA.
Data in Brief
|July 15, 2024
Summary
This data article presents a comprehensive dataset of international team ball sport match scores for 12 sports. Researchers can use this sports analytics data to analyze team performance and build predictive models.
Area of Science:
- Sports Analytics
- Data Science
- Computational Statistics
Background:
- International competitions in 12 team ball sports generate vast amounts of match data.
- Existing datasets may lack comprehensive coverage or accessibility for advanced analytics.
- Sports analytics research requires robust data for performance evaluation and prediction.
Purpose of the Study:
- To present a novel dataset of international team ball sport match scores.
- To provide researchers with accessible data for sports analytics applications.
- To facilitate the development of new analytical models and performance metrics.
Main Methods:
- Data collection via web scraping from Wikipedia.
- Extraction of match details including teams, scores, and winners.
- Compilation of data for 12 popular team ball sports.
Main Results:
- A curated dataset containing match scores from major international competitions.
- Data includes year, opposing teams, scores, and winning team for each match.
- The dataset covers basketball, soccer, ice hockey, and more.
Conclusions:
- The presented dataset is a valuable resource for sports analytics.
- Enables computation of team statistics, ranking, and performance trend analysis.
- Supports the development of predictive models and machine learning algorithm evaluation.
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