基于 Python 的 2022-2023 年 CBA 球员常规赛数据可视化平台实现

Hailong Tan, Chaoling Qin, Zhengban Ran, Kai Wang, Zhirong Zheng
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引用次数: 0

摘要

基于当前CBA联赛对数据可视化手段运用不足,相关从业人员缺乏数据分析意识的现状,该平台通过Python获取CBA2022-2023赛季常规赛球员场均基础数据和总基础数据,再利用计算公式计算出NBA联赛中常用的球员PER值作为高阶数据的分析指标,最后结合Echarts、Flask等工具完成数据可视化平台的构建,设计并实现了平台的三种可视化分析功能:一是球员平均数据排名分析。二是选手能力对比分析。三是高阶数据 PER 值与球员平均基础数据之间的分析。针对平台的功能缺陷和CBA联赛数据统计与分析的缺陷,本研究提出两点可行性建议:一是CBA联赛应充分借鉴NBA联赛的数据统计与管理方法,进一步完善比赛数据的统计。二是针对CBA联赛现有的统计数据,进一步丰富可视化平台的功能,提高分析的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Python-based Visualization Platform Implementation of CBA Players' Regular Season 2022-2023 Data
Based on the current CBA league's insufficient use of data visualization means and the lack of data analysis awareness of relevant practitioners, the platform obtains the CBA 2022-2023 regular season players' average base data and total base data through Python, then uses the calculation formula to calculate the commonly used players' PER value in the NBA league as an analysis index for higher-order data, and finally combines with the Echarts, Flask and other tools to complete the construction of the data visualization platform, designed and implemented the platform's three kinds of visualization and analysis functions: first, the analysis of the players' average data ranking. The second is the comparative analysis of players' ability. The third is the analysis between the higher-order data PER value and the players' average basic data. Aiming at the functional deficiencies of the platform and the defects of the CBA league's data statistics and analysis, this study puts forward two feasibility suggestions: first, the CBA league should fully learn from the NBA league's statistics and management methods of the data, and further improve the statistics of the game data. The second is to further enrich the functions of the visualization platform for the existing statistics of the CBA league to improve the applicability of the analysis.
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