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The Poisson model limits in NBA basketball: Complexity in team sports

机译:泊松模型在NBA篮球中的局限性:团队运动的复杂性

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摘要

Team sports are frequently studied by researchers. There is presumption that scoring in basketball is a random process and that can be described using the Poisson Model. Basketball is a collaboration-opposition sport, where the non-linear local interactions among players are reflected in the evolution of the score that ultimately determines the winner. In the NBA, the outcomes of close games are often decided in the last minute, where fouls play a main role. We examined 6130 NBA games in order to analyze the time intervals between baskets and scoring dynamics. Most numbers of baskets (n) over a time interval (Delta T) follow a Poisson distribution, but some (e.g., Delta T = 10 s, n > 3) behave as a Power Law. The Poisson distribution includes most baskets in any game, in most game situations, but in close games in the last minute, the numbers of events are distributed following a Power Law. The number of events can be adjusted by a mixture of two distributions. In close games, both teams try to maintain their advantage solely in order to reach the last minute: a completely different game. For this reason, we propose to use the Poisson model as a reference. The complex dynamics will emerge from the limits of this model. (C) 2016 Elsevier B.V. All rights reserved.
机译:团队运动经常被研究人员研究。推测篮球得分是一个随机过程,可以用泊松模型来描述。篮球是一项协作对立运动,其中球员之间的非线性局部互动反映在最终决定获胜者的得分变化中。在NBA中,近距离比赛的结果通常是在犯规起主要作用的最后一刻决定的。我们分析了6130场NBA比赛,以分析篮球比赛和得分动态之间的时间间隔。在时间间隔(Delta T)中,大多数篮(n)遵循泊松分布,但有些(例如Delta T = 10 s,n> 3)表现为幂律。在大多数游戏情况下,泊松分布包括所有游戏中的大多数篮筐,但是在最后一分钟的封闭游戏中,事件数是根据幂定律进行分配的。事件的数量可以通过两种分布的混合来调整。在近距离比赛中,两个团队都试图仅保持自己的优势才能到达最后一刻:一场完全不同的比赛。因此,我们建议使用泊松模型作为参考。这种模型的局限性将产生复杂的动力。 (C)2016 Elsevier B.V.保留所有权利。

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