A Study on Sports Data Matching for Virtual Competitions

Abstract

Technological advances have given rise to increasingly diverse sports data and applications. Among them, integrated sensors, big data and cloud computing are the most intriguing ones. Their combination with social media enables users to share their sports data, expanding their network. In this study, we will go through a screening analysis model that employed advanced mathematics, and derive our solution through the approximation theory. Our goal is to find a more accurate matching model for users of a big sports database to join a virtual competition. Compared with traditional sports rating methods, our desired model can more flexibly match each piece of sports data in a practical manner.