Python-based Visualization Platform Implementation of CBA Players' Regular Season 2022-2023 Data

Hailong  Tan; Chaoling Qin; Zhengban Ran; Kai  Wang; Zhirong  Zheng

doi:10.54691/pdxgb824

Authors

Hailong Tan
Chaoling Qin
Zhengban Ran
Kai Wang
Zhirong Zheng

DOI:

https://doi.org/10.54691/pdxgb824

Keywords:

Python; data visualization; basketball game data; CBA.

Abstract

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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