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Modeling Offensive Player Movement in Professional Basketball

机译:模拟职业篮球中的进攻球员运动

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The 2013 arrival of SportVU player tracking data in all NBA arenas introduced an overwhelming amount of on-court information-information which the league is still learning how to maximize for insights into player performance and basketball strategy. The data contain the spatial coordinates for the ball and every player on the court for 25 frames per second, which opens up avenues of player and team performance analysis that was not possible before this technology existed. This article serves as a step-by-step guide for how to leverage a data feed from SportVU for one NBA game into visualizable components that can model any player's movement on offense. We detail some utility functions that are helpful for manipulating SportVU data before applying it to the task of visualizing player offensive movement. We conclude with visualizations of the resulting output for one NBA game, as well as what the results look like aggregated across an entire season for three NBA stars with very different offensive tendencies.
机译:SportVU球员追踪数据于2013年到达所有NBA场地,引入了大量的场上信息,联盟仍在学习如何最大限度地了解球员表现和篮球策略。数据包含球和场上每个球员每秒25帧的空间坐标,这开辟了球员和球队绩效分析的途径,而这项技术在存在之前是不可能的。本文是有关如何将SportVU一项NBA游戏的数据馈入可可视化的组件的逐步指南,该可视化组件可以为任何球员的进攻动作建模。在将SportVU数据应用于可视化玩家进攻动作的任务之前,我们将详细介绍一些有助于操纵SportVU数据的实用程序功能。我们以可视化的方式结束了一场NBA比赛的结果输出,以及三名进攻趋势截然不同的NBA明星在整个赛季中的结果汇总。

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