Modeling the Badminton Stroke Pattern Through the Sequential Pattern Discovery Using Equivalent Classes (SPADE) Algorithm

Abstract

Badminton is one of the most popular sports in the world, especially in Asia. It has a parent organization called Badminton World Federation (BWF). Discussion about player strategies in winning various championships held by BWF is an interesting topic to discuss. This paper aims to analyze the hitting patterns of badminton players by paying attention to the sequence of types of strokes made by the players, including lobs, netting, smashes, drives, and dropshots. Sequential pattern discovery using the equivalent class algorithm (SPADE) is the appropriate method to identify these problems because it can determine the rules and probabilities of player's hitting patterns based on the order of the types of strokes. In this paper, we analyze the stroke pattern of the two top-ranked badminton players in the men's singles sector at the Malaysia Open 2022 championship, where Viktor Axelsen and Kento Momota met in the final. Based on the results of these research, we analyze the strategies and recommended hitting patterns from the information on the two players' patterns. The results of this study, in general, can be used as information for players to understand and analyze the opponent's performance or strategy before competing.

Keywords

• Badminton
• Kento Momota
• Rules
• SPADE
• Stroke Pattern
• Viktor Axelsen