Construction of Value Classification Model by Tracking NBA Center Players’ Performance with Virtual IoT Tagging Technology

Abstract

Every basketball star’s performance is an important asset and commodity for the coaches for personnel dispatch and team management. In this study, each star was regarded as an IoT object. National Basketball Association (NBA) centers were taken as an example to develop a traceable virtual tag. With the 15 items of game data published after each NBA game, synchronous tracking was linked, and the technique for order preference by similarity to ideal solution (TOPSIS) method was used to develop a relative value classification model for players of the same type from an objective point of view. The main contributions of this work are as follows: (1) Tampermonkey script is used to develop virtual IOT tags to track players’ real-time game results, and (2) the model provides players with instant knowledge of their rankings relative to other players and provides reference for team management and commodity endorsement pricing.