Computer Science ›› 2017, Vol. 44 ›› Issue (12): 175-182.doi: 10.11896/j.issn.1002-137X.2017.12.033

Previous Articles     Next Articles

Research on Passing Quality Quantification Based on GraphX Passing Network

LIAO Bin, ZHANG Tao, GUO Bing-lei, YU Jiong, NIU Ya-feng, ZHANG Xu-guang and LIU Yan   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Although the big data technology continues to mature,relevant application research in the field of competitive sports is still in the exploratory stage.Conventional basketball technical statistics lacks the record of the passing data as well as the statistical analysis,data mining,and application of the passing data.Firstly,based on GraphX,we created the passing network graph,which laid a foundation of future research on passing quality.Secondly,PESV (Pass Expectation Score Value),a method of evaluating the quality of passing basketball,was proposed.Compared with the traditional ATR (Assist Turnover Ratio) that defined the ratio of assists to turnovers,PESV can make a more comprehensive eva-luation of the passing quality.Finally,we introduced a few application scenarios of PESV based on passing network,including the analysis of the impact of passing quality on game result,passing route selection based on PESV value,and taking the Chinese player Jeremy Lin as an example to calculate his passing expectation values in the 2015-2016 seasons.

Key words: Big data application,Passing network,GraphX,Quantitative pass quality,Player evaluation

[1] GHEMAWAT S,GOBIOFF H,LEUNG S T.The google gile system[C]∥Proceedings of 19th ACM Symposium on Opera-ting System Principles.New York:ACM,2003:29-43.
[2] DEAN J,GHEMAWAT S.MapReduce:Simplifed data proces-sing on large clusters[C]∥Proceedings of the Conference on Operating System Design and Implementation(OSDI).New York:ACM,2004:137-150.
[3] ZAHARIA M,CHOWDHURY M, FRANKLIN M J,et al.Spark:cluster computing with working sets[C]∥ Usenix Conference on Hot Topics in Cloud Computing.USENIX Association,2010:1765-1773.
[4] ZAHARIA M,CHOWDHURY M,DAS T,et al.Resilient distributed datasets:a fault-tolerant abstraction for in-memory cluster computing[C]∥ Usenix Conference on Networked Systems Design and Implementation.2012:141-146.
[5] XIN R S,GONZALEZ J E,FRANKLIN M J,et al.GraphX:a resilient distributed graph system on Spark[C]∥ International Workshop on Graph Data Management Experiences and Systems.2013:1-6.
[6] LOW Y,BICKSON D,GONZALEZ J,et al.Distributed Graph-Lab:a framework for machine learning and data mining in the cloud[J].Proceedings of the VLDB Endowment,2012,5(8):716-727.
[7] HAN M,DAUDJEE K.Giraph unchained:barrierless asyn-chronous parallel execution in pregel-like graph processing systems[J].Proceedings of the VLDB Endowment,2015,8(9):950-961.
[8] YAN Y L,DONG Y H,HE X M,et al.FSMBUS:A Frequent Subgraph Mining Algorithm in Single Large-Scale Graph Using Spark[J].Journal of Computer Research and Development,2015,52(8):1768-1783.(in Chinese) 严玉良,董一鸿,何贤芒,等.FSMBUS:一种基于 Spark 的大规模频繁子图挖掘算法[J].计算机研究与发展,2015,52(8):1768-1783.
[9] CERVONE D,D AMOUR A,BORNN L,et al.POINTWISE:Predicting points and valuing decisions in real time with nba optical tracking data[C]∥Proceedings of the 8th MIT Sloan Sports Analytics Conference.Boston,MA,USA,2014:1-9.
[10] MAHESWARAN R,CHANG Y H,SU J,et al.The three dimensions of rebounding[C]∥Proceedings of the 8th MIT Sloan Sports Analytics Conference.Boston,MA,USA,2014:1-7.
[11] MAYMIN P.Acceleration in the NBA:Towards an algorithmic taxonomy of basketball plays[C]∥Proceedings of the 7th MIT Sloan Sports Analytics Conference.Boston,MA,USA,2013:1-7.
[12] GOLDMAN M,RAO J M.Live by the Three,Die by the Three? The Price of Risk in the NBA[C]∥Proceedings of the 7th MIT Sloan Sports Analytics Conference.Boston,MA,USA,2013:1-15.
[13] FRANKS A,MILLER A,BORNN L,et al.Counterpoints:Advanced defensive metrics for nba basketball[C]∥Proceedings of the 9th MIT Sloan Sports Analytics Conference.Boston,MA,USA,2015:1-8.
[14] WIENS J,GUHA BALAKRISHNAN J B,GUTTAG J.ToCrash or Not To Crash:A quantitative look at the relationship between offensive rebounding and transition defense in the NBA[C]∥Proceedings of the 7th MIT Sloan Sports Analytics Conference.Boston,MA,USA,2013:1-7.
[15] REN L,DU Y,MA S,et al.Visual analytics towards big data[J].Journal of Software,2014,25(9):1909-1936.(in Chinese).任磊,杜一,马帅,等.大数据可视分析综述[J].软件学报,2014,25(9):1909-1936.
[16] HERMAN I,MELANCON G,MARSHALL M S.Graph visua-lization and navigation in information visualization:A survey[J].IEEE Transaction on Visualization and Computer Gra-phics,2000,6(1):24-43.
[17] ZHANG X,YUAN X R.Treemap visualization[J].Journal of Computer-Aided Design & Computer Graphics,2012,4(9):1113-1124.
[18] BALZER M,DEUSSEN O.Voronoi Treemaps[C]∥IEEE Sympo-sium on Information Visualization.Los Alamitos:IEEE,2005:49-56.
[19] GOU L,ZHANG X.Treenetviz:Revealing patterns of networks over tree structures[J].IEEE Transaction on Visualization and Computer Graphics,2011,17(12):2449-2458.
[20] ZHANG T,YU J,LIAO B,et al.The Construction and Analysis of Pass Network Graph Based on GraphX[J].Journal of Computer Research and Development,2016,53(12):2729-2752.(in Chinese) 张陶,于炯,廖彬,等.基于GraphX的传球网络构建及分析研究[J].计算机研究与发展,2016,53(12):2729-2752.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!