This chapter presents recent advancements in artificial intelligenceArtificial Intelligence (AI) (AI) application for data collection and analytics in badmintonBadminton match preparation. The latest developments in computer visionComputer Vision (CV) have enabled comprehensive data collection directly from broadcasted matches and single-view camera recordings. This capability allows researchers and analysts to automatically gather extensive, high-quality datasets, significantly increasing the volume and variety of available data. It also makes it possible to collect data from elite-level matches without requiring players to attend laboratory settings and from local competitions, provided these matches are video-recorded. In this chapter, we detail the complete AI-driven analytical pipeline used. This encompasses video preprocessing, court calibration, player detection, kinematic data extraction, and automatic tagging of strokes. These steps culminate in developing relevant key performance indicators (KPIs), offering a precise and objective quantification of player performance in badmintonBadminton. Players and coaches gain valuable insights into individual strengths and weaknesses by identifying recurrent actions or patterns that correlate with positive and negative outcomes. This information can significantly inform targeted training strategies and enhance tactical preparation for upcoming matches, fostering improved competitive performance.