Gambarelli Gianfranco
Department of Mathematics, Statistics, Computer Science and Applications, University of Bergamo, Bergamo, Italy.
J Sports Sci. 2008 Aug;26(10):1091-5. doi: 10.1080/02640410801930135.
I propose a method to synthesize the performance scores for artistic sports such as rhythmic gymnastics, figure skating, synchronized swimming, and diving by taking into account inter-judge variability, while maintaining all the reliable scores. This procedure is based on the assumption that the majority of the scores in each event are reliable and they relate well to those scores that are closest to them. The method consists of putting scores in order and considering clusters of m consecutive scores, where m is the number of judges making up the simple majority. For each cluster, the difference between the highest and the lowest score is calculated. In cases where the minimum difference is positive, the arithmetic mean of those scores that belong to clusters where the difference is minimal is computed. In cases where the minimum difference is zero (i.e. if the majority of judges unanimously assign the same score), then the set of the scores to consider within the mean is extended to those scores that are very near to those of the majority of the judges. A comparison between the actual evaluation procedures and the proposed model is provided.
我提出了一种方法,通过考虑评委间的差异来合成艺术体操、花样滑冰、花样游泳和跳水等竞技体育项目的成绩得分,同时保留所有可靠分数。该程序基于这样的假设:每个项目中的大多数分数是可靠的,并且它们与最接近它们的分数密切相关。该方法包括将分数排序,并考虑连续m个分数的聚类,其中m是构成简单多数的评委人数。对于每个聚类,计算最高分与最低分之间的差值。在最小差值为正的情况下,计算属于最小差值聚类的那些分数的算术平均值。在最小差值为零的情况下(即如果大多数评委一致给出相同分数),则在计算平均值时要考虑的分数集扩展到与大多数评委的分数非常接近的那些分数。还提供了实际评估程序与所提出模型之间的比较。