Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA.
Center for the Study of Complex Systems, University of Michigan, Ann Arbor, MI 48109, USA.
Sci Adv. 2024 Nov 8;10(45):eadn2654. doi: 10.1126/sciadv.adn2654. Epub 2024 Nov 6.
Patterns of wins and lo sses in pairwise contests, such as occur in sports and games, consumer research and paired comparison studies, and human and animal social hierarchies, are commonly analyzed using probabilistic models that allow one to quantify the strength of competitors or predict the outcome of future contests. Here, we generalize this approach to incorporate two additional features: an element of randomness or luck that leads to upset wins, and a "depth of competition" variable that measures the complexity of a game or hierarchy. Fitting the resulting model, we estimate depth and luck in a range of games, sports, and social situations. In general, we find that social competition tends to be "deep," meaning it has a pronounced hierarchy with many distinct levels, but also that there is often a nonzero chance of an upset victory. Competition in sports and games, by contrast, tends to be shallow, and in most cases, there is little evidence of upset wins.
在体育和游戏、消费者研究和配对比较研究以及人类和动物社会等级等方面,经常会出现两两竞争的胜负模式,这些模式通常使用概率模型进行分析,这些模型可以量化竞争者的实力或预测未来竞争的结果。在这里,我们将这种方法推广到包含两个额外的特征:导致意外胜利的随机性或运气因素,以及衡量比赛或等级制度复杂性的“竞争深度”变量。通过拟合得到的模型,我们估计了一系列游戏、运动和社会情境中的深度和运气。总的来说,我们发现社会竞争往往是“深刻的”,这意味着它有一个明显的等级制度,有许多不同的层次,但也往往有一定的意外胜利的机会。相比之下,体育和游戏中的竞争往往是肤浅的,在大多数情况下,几乎没有意外胜利的证据。