2020/12/26 by Xin Du, Weihong Cai, Du, Xin +9
Computer Science · Economics, Econometrics and Finance · #Data Visualization and Analytics #FOS: Computer and information sciences #Social and Information Networks (cs.SI) #Sports Analytics and Performance #Time Series Analysis and Forecasting
paper · pdf · doi:10.48550/arxiv.2012.15734
openalex publication_date 2020/12/26 · openalex created_date 2021/02/01 · openalex updated_date 2026/07/28
Determining the value of basketball players through analyzing the players' behavior is important for the managers of modern basketball teams. However, conventional methods always utilize isolated statistical data, leading to ineffective and inaccurate evaluations. Existing models based on dynamic network theory offer major improvements to the results of such evaluations, but said models remain imprecise because they focus merely on evaluating the values of individual players rather than considering them within their current teams. To solve this problem, we propose an analysis and evaluation model based on networks and a hidden Markov model. To the best of our knowledge, we are the first to combine a network form representing the players who are playing with the use of a hidden Markov model to mine the network and generate the desired results. Applying our approach to SportVU data collected from the National Basketball Association shows that this analysis and evaluation model can effectively analyze the performance of each player in a game and provides an assistive tool for team managers.