Bridgegap: a Smart Behavioral Profiling and Matchmaking System for Bridge Players Using Real-time Gameplay Analytics
Year: 2025
Type: conference-paper
Abstract: BridgeGap is a mobile platform designed to connect Bridge players based on real-time behavioral insights. The project addresses the challenge of partner matching and community-building in modern Bridge by leveraging in-game data such as bidding frequency, collaboration scores, and player performance [1]. The system includes three major components: matchmaking, gameplay session management, and a visual profile with radar chart analytics. Firebase services are used for user authentication, live data updates, and stat storage. Two experiments were conducted: one to validate behavioral preference detection, and another to test engagement in competitive scenarios. Results showed high accuracy in classifying player types and valuable insights for user retention. Compared to traditional studies using surveys and interviews, BridgeGap’s method is more scalable and immediate, offering real-time personalization and data-driven matchmaking [2]. Despite limitations in subjective metric definition and small sample size, BridgeGap proves to be a powerful step toward a smarter, more connected Bridge community.
Authors: Fuyao Ling, Andrew Park
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Reduced inequalities
Open Access status: gold
OpenAlex ID: W4412812230