ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2016, Vol. 53 ›› Issue (12): 2729-2752.doi: 10.7544/issn1000-1239.2016.20160568

Previous Articles     Next Articles

The Construction and Analysis of Pass Network Graph Based on GraphX

Zhang Tao1, Yu Jiong1, Liao Bin2, Guo Binglei1, Bian Chen1, Wang Yuefei1, Liu Yan3   

  1. 1(School of Information Science and Engineering, Xinjiang University, Urumqi 830046); 2(School of Statistics and Information, Xinjiang University of Finance and Economics, Urumqi 830012); 3(School of Software, Tsinghua University, Beijing 100084)
  • Online:2016-12-01

Abstract: In the field of social networking, finance, public security, health care, etc, the application of big data technology is matured constantly, but its application in competitive sports is still in exploratory stage. Lacking of recording the pass data in basketball technical statistics leads that we can not research the statistical analysis, data mining and application on the pass data. Firstly, as the aggregation from of passing data is graph, based on data acquisition, clean and format conversion, Vertex and Edge table construction, we create the pass network graph with GraphX, which lays the foundation for other applications. Secondly, the PlayerRank algorithm is proposed to distinguish the importance of players, player position personalized the graph vertex’s color, etc, which improves the visual quality of pass network graph. Finally, we can use the pass network graph created by GraphX to analyze the effect of passing quantity and quality on the outcome of the game, and the pass network graph is also used to analyze the team’s passing data, tactical player selection, on-the-spot tactics supporting, subgraph extraction and gaming experience improvement, etc.

Key words: big data application, pass network, GraphX frame, PlayerRank algorithm, player importance

CLC Number: