基于高效前沿的十项全能评分乘法

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS
Manuel Schütz, Chris Tofallis
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引用次数: 0

摘要

十项全能比赛由十个项目组成,这些项目的得分经汇总后确定最终排名。我们开发的十项全能评分方法比现有的标准表(IAAF1984)简单得多,因为影响总排名的参数只有 9 个而不是 30 个。我们首先确定那些处于帕累托效率前沿的运动员,即那些不受其他任何人支配的运动员。然后,我们剔除这些前沿运动员,再次挑选所有未被支配的运动员,以获得第二个支配组/帕累托前沿,并对 1986 年至 2020 年的十项全能数据重复这一过程。然后,每个组都以其十个中位数成绩为特征。因此,从最后一组到最高一组的进步可以被视为一条从最低成绩中位数到最高成绩中位数的进步之路。每个事件都应具有相同的重要性,因此我们对数据进行归一化处理,使进步路径尽可能遵循十维超立方的空间对角线。此外,对基准的任何调整都不会改变任何实际的十项全能成绩,因此不会出现任何不必要的排名颠倒。这样一来,如果需要引入新的标枪类型来缩小范围,就可以在将来顺利调整这些表格。我们将当前 7000 分至 9000 分之间的成绩归一化,使其与我们的积分表保持在同一范围内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A multiplicative approach to decathlon scoring based on efficient frontiers
The decathlon consists of ten events with scores which are then aggregated to determine the final ranking. We develop a decathlon scoring method which is far simpler than the existing standard (IAAF1984) tables, as there are only 9 parameters instead of 30 which have an impact on the overall rank. We first identify athletes who are on the Pareto-efficient frontier i.e. those who are not dominated by anyone else. We then remove these frontier athletes and again pick all non-dominated athletes to obtain a second dominating group/Pareto frontier and iterate this procedure for the decathlon data from 1986 to 2020. Each of these groups are then characterized by their set of ten median performances. Improving from the last to the top group can then be seen as a path of progress, leading from the lowest to the highest set of median performances. Every event should have the same importance, so we normalize the data such that the path of progress follows as much as possible a space diagonal of a ten dimensional hypercube. Furthermore, any adjustment of a benchmark does not change any actual decathlon performance, hence there cannot be any unwanted rank reversals. This allows a smooth adjustment of these tables in the future, if for instance a new type of javelin needs to be introduced to reduce the range. We normalize such that current performances between 7000 and 9000 points still fall into the same range with our point tables.
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来源期刊
Journal of Quantitative Analysis in Sports
Journal of Quantitative Analysis in Sports SOCIAL SCIENCES, MATHEMATICAL METHODS-
CiteScore
2.00
自引率
12.50%
发文量
15
期刊介绍: The Journal of Quantitative Analysis in Sports (JQAS), an official journal of the American Statistical Association, publishes timely, high-quality peer-reviewed research on the quantitative aspects of professional and amateur sports, including collegiate and Olympic competition. The scope of application reflects the increasing demand for novel methods to analyze and understand data in the growing field of sports analytics. Articles come from a wide variety of sports and diverse perspectives, and address topics such as game outcome models, measurement and evaluation of player performance, tournament structure, analysis of rules and adjudication, within-game strategy, analysis of sporting technologies, and player and team ranking methods. JQAS seeks to publish manuscripts that demonstrate original ways of approaching problems, develop cutting edge methods, and apply innovative thinking to solve difficult challenges in sports contexts. JQAS brings together researchers from various disciplines, including statistics, operations research, machine learning, scientific computing, econometrics, and sports management.
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