This research systematically investigates Sudoku difficulty assessment based on real-world human solving experience. We designed and implemented the Cloud Sudoku mobile application to collect large-scale player-solving records and establish a public dataset with human-perceived difficulty metrics. The resulting framework integrates data collection, metric design, and empirical validation, providing a standardized and realistic foundation for developing and evaluating Sudoku difficulty-rating algorithms.