NBA与CBA联赛大数据应用的对比研究

发布时间：2018-02-01 00:08

本文关键词： NBA CBA 大数据应用　出处：《北京体育大学》2017年硕士论文　论文类型：学位论文

【摘要】：本文运用文献资料法、比较分析法、专家访谈法、逻辑分析法对NBA与CBA联赛大数据的历史发展进程、大数据的收集与处理、大数据分析、大数据处理人员状况、大数据的挖掘与运用这几方面分别进行研究,并将各个方面进行对比,找出CBA大数据在应用过程中存在的不足之处,提出有针对性的应对策略。本研究结论如下:(1)NBA大数据的应用已经非常成熟。NBA形成了一个统计指标全面、数据结构合理的庞大数据库。NBA利用SportVU系统、HANA平台、可穿戴设备、FreeD技术和回放中心对比赛和训练数据进行收集与处理。对数据的分析形成了以SportVU数据分析体系、细粒度的高阶统计分析体系、可视化数据信息体系、录像分析为主的四大分析体系。数据分析人员充足,有很多专业的数据分析师和录像分析师。数据分析人员利用科学的分析方法对数据进行挖掘,将挖掘的结果运用到NBA各个方面,有效地提升了 NBA联赛水平,促进了 NBA联盟的发展。(2)CBA大数据的应用处于起步阶段。从1995年赛制改革到现在,经过20多年的发展,CBA数据库初步成型。数据的收集与处理以现场技术统计和录像为主,数据分析利用录像分析软件对比赛录像进行分析。与大数据处理相关的基础性工作人员基本能够满足,专业的数据分析人员严重匮乏,大部分都是由录像分析师完成数据分析。中国篮协和球队的教练们对数据的重视程度参差不齐,严重限制了大数据在CBA的运用,使得CBA的整体水平和关注度不能得到有效地提高。(3)CBA大数据的应用对教练、运动员、观众和CBA整体水平的提高都有着重要的意义。但通过与NBA大数据相比较,发现CBA大数据在应用过程中存在着不少问题,主要是:数据积累的量不够大,统计指标不够深化,数据统计过程不规范,资源浪费严重,数据分析不全面,技术重视程度不够高,自主研发意识薄弱,缺乏专业的人才以及专业的设备和软件等。(4)面对诸多问题,可以从以下几方面进行解决:加强CBA数据库的建设,完善历史数据,深化研究统计指标,规范数据统计过程,提供便捷的数据查询端口;改良大数据的收集方式,将官方数据统计和球队数据统计合二为一;加强数据分析人才的培养,积极吸引人才为联赛服务;完善相关制度,在政策上予以支持和约束;增加资金投入,引进先进的设备和软件,坚持自主研发;抓住互联网发展机遇,加强与互联网机构合作。
[Abstract]:This paper uses the methods of literature, comparative analysis, expert interview, logic analysis to analyze the historical development of big data in NBA and CBA league, the collection and treatment of big data, and big data analysis. Big data deal with the situation of personnel, big data mining and application of these aspects are studied, and the comparison of various aspects, to find out the CBA big data in the application process of deficiencies. The conclusions of this study are as follows: the application of NBA big data has been very mature. NBA has formed a comprehensive statistical index. The large database with reasonable data structure. NBA uses SportVU system to make use of HANA platform, wearable device. The FreeD technology and playback center collect and process the competition and training data. The analysis of the data forms a SportVU data analysis system, a fine-grained high-order statistical analysis system. Visual data information system, video analysis based on the four analysis systems. There are many professional data analysts and video analysts. Data analysts use scientific analysis methods to mine data and apply the results of mining to all aspects of NBA. Effectively improve the level of NBA league, promote the development of NBA league. The application of big data is in its infancy. From 1995 to now. After more than 20 years' development, the CBA database has been preliminarily formed. The collection and processing of the data are mainly based on the field technical statistics and video recording. Data analysis using video analysis software to analyze the game video. Big data processing related to the basic staff can basically meet the serious shortage of professional data analysts. Most of the data analysis was done by video analysts. The uneven attention given to the data by the China Basketball Association and team coaches severely limited big data's use of CBA. So that the overall level and attention of the CBA can not be effectively improved by the application of big data to coaches and athletes. The improvement of the audience and the overall level of CBA is of great significance, but by comparing with NBA big data, we find that there are many problems in the application of CBA big data. Mainly: the amount of data accumulation is not enough, the statistical index is not deep enough, the process of data statistics is not standardized, the waste of resources is serious, the data analysis is not comprehensive, the degree of technical attention is not high enough, the consciousness of independent research and development is weak. Lack of professional personnel and professional equipment and software facing many problems, can be solved from the following aspects: strengthen the construction of CBA database, improve historical data, deepen the study of statistical indicators. Standardizing the process of data statistics and providing convenient data query ports; Improve big data's collection method, combining official statistics with team statistics; Strengthen the training of data analysis talents, actively attract talents to serve the league; Perfect the relevant system, support and restrain in the policy; Increase capital input, introduce advanced equipment and software, and adhere to independent R & D; Seize the opportunity of Internet development, and strengthen cooperation with Internet institutions.
【学位授予单位】：北京体育大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：G841

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