In this paper, we develop a novel depth-based testing procedure on spatial point processes to examine the difference in made and missed field goal attempts for NBA players. Specifically, our testing procedure can statistically detect the differences between made and missed field goal attempts for NBA players. We first obtain the depths of two processes under the polar coordinate system. A two-dimensional Kolmogorov-Smirnov test is then performed to test the difference between the depths of the two processes. Throughout extensive simulation studies, we show our testing procedure with good frequentist properties under both null hypothesis and alternative hypothesis. A comparison against the competing methods shows that our proposed procedure has better testing reliability and testing power. Application to the shot chart data of 191 NBA players in the 2017-2018 regular season offers interesting insights about these players' made and missed shot patterns.

翻译：本文针对空间点过程提出了一种新颖的基于深度的检验流程，旨在分析NBA球员进球与投失投篮尝试的差异。具体而言，我们的检验流程能够从统计角度检测NBA球员进球与投失投篮尝试之间的差异。我们首先在极坐标系下获得两个过程的深度值，随后执行二维科尔莫戈罗夫-斯米尔诺夫检验以判别这两个过程的深度差异。通过广泛的模拟研究，我们证明了该检验流程在原假设和备择假设下均具备良好的频率学派性质。与现有方法的对比表明，我们提出的方法在检验可靠性和检验效能方面表现更优。将模型应用于2017-2018赛季191名NBA球员的投篮分布数据，为理解这些球员的进球与投失模式提供了富有洞察力的结论。