Vinué Guillermo
Faculty of Mathematics, University of Valencia, Valencia, Spain.
Big Data. 2020 Feb;8(1):70-86. doi: 10.1089/big.2018.0124. Epub 2020 Jan 31.
The statistical analysis of basketball games is a fast-growing field. Certainly, basketball data are scientifically relevant because an appropriate analysis provides a great deal of information about the performance of both players and teams. The number of games played each season generates a large amount of data worth analyzing. Basketball analytics is well established in U.S. leagues. In Europe, however, it has not been duly developed. This study focuses on the top three European team competitions: the EuroLeague, the EuroCup, and the Spanish ACB (Association of Basketball Clubs, acronym in Spanish) league. Their official websites provide access to game data for anyone who is interested, but they are only represented in a static tabular form. As a consequence, it is difficult to gain any valuable insights from them. This article presents a highly useful interactive tool, created with the free statistical software R, which makes it possible to visualize and explore basketball data from a large number of seasons. We will demonstrate its core functionality. An accompanying R package is presented in the Supplementary Data.
篮球比赛的统计分析是一个快速发展的领域。当然，篮球数据具有科学相关性，因为恰当的分析能提供大量有关球员和球队表现的信息。每个赛季进行的比赛数量产生了大量值得分析的数据。篮球分析在美国联赛中已很成熟。然而，在欧洲，它尚未得到充分发展。本研究聚焦于欧洲顶级的三项球队赛事：欧洲篮球联赛、欧洲杯以及西班牙篮球甲级联赛（西班牙语篮球俱乐部协会的首字母缩写）。它们的官方网站为任何感兴趣的人提供比赛数据访问，但这些数据仅以静态表格形式呈现。因此，很难从中获得任何有价值的见解。本文展示了一个非常有用的交互式工具，它是用免费统计软件R创建的，能够可视化并探索多个赛季的篮球数据。我们将演示其核心功能。补充数据中展示了一个配套的R包。
