In the summer of 2017, the National Basketball Association reduced the number of total timeouts, along with other rule changes, to regulate the flow of the game. With these rule changes, it becomes increasingly important for coaches to effectively manage their timeouts. Understanding the utility of a timeout under various game scenarios, e.g., during an opposing team's run, is of the utmost importance. There are two schools of thought when the opposition is on a run: (1) call a timeout and allow your team to rest and regroup, or (2) save a timeout and hope your team can make corrections during play. This paper investigates the credence of these tenets using the Rubin causal model framework to quantify the causal effect of a timeout in the presence of an opposing team's run. Too often overlooked, we carefully consider the stable unit-treatment-value assumption (SUTVA) in this context and use SUTVA to motivate our definition of units. To measure the effect of a timeout, we introduce a novel, interpretable outcome based on the score difference to describe broad changes in the scoring dynamics. This outcome is well-suited for situations where the quantity of interest fluctuates frequently, a commonality in many sports analytics applications. We conclude from our analysis that while comebacks frequently occur after a run, it is slightly disadvantageous to call a timeout during a run by the opposing team and further demonstrate that the magnitude of this effect varies by franchise.
翻译:2017年夏季, 国家篮球协会减少了总超时次数, 以及其他规则变化, 以调节游戏的流动。 随着这些规则变化, 教练们越来越有必要有效地管理其超时。 理解不同游戏场景下超时的效用至关重要, 比如在对立团队运行期间, 理解在不同的游戏场景下超时的效用至关重要。 当反对派在运行时, 有两派想法:(1) 调用超时, 允许您的团队休息和重组, 或者(2) 省下超时, 希望您的团队可以在游戏中做出纠正。 本文用Rubin因果模型框架来调查这些信条的正确性, 以量化在对立团队运行时超时的因果效应。 我们常常忽略了在这种背景下仔细考虑稳定的单位- 处理值假设( SUTVA ), 并使用 SUTVA 来激励我们定义单位。 为了测量超时的效果, 我们根据分差的差异, 引入了一个新的、 可解释的结果, 来描述得分数的变化。 本文用Rubin 示范框架来量化的结果, 来量化, 在运动场后, 我们的变数分析常常会得出一个不易变化。