A relational dataset of international badminton singles matches with ranking and Elo measures, 2006–2025

Abstract

Abstract International badminton competitions generate rich records of individual athletic performance; however, no publicly available dataset integrates match outcomes, rankings, and dynamic performance ratings across all competition tiers in a unified relational structure. This paper presents a relational dataset of 178,896 international badminton singles matches drawn from 1,847 Badminton World Federation (BWF)-sanctioned tournaments spanning 2006 to 2025. The match data encompass men’s singles ( n = 108,590) and women’s singles ( n = 70,306) from 172 national associations across all major competition tiers, with annual updates planned. Three linked tables—namely tournaments, players, and matches—support the longitudinal tracking of player careers and repeated rivalries. Each match record includes set-level scores, match duration, pre-match BWF world rankings, and Elo ratings constructed using a badminton-specific framework (Elo-rated favorites won 67.3% of all matches), with complementary predictive content relative to official rankings. This dataset fills a gap in publicly available longitudinal sports performance data and provides a foundation for large-scale research on athletic careers, competitive dynamics, and performance measurements across sports analytics, economics, and behavioral science.