在赛艇比赛中建立更客观的时间标准

IF 1.1 Q3 SOCIAL SCIENCES, MATHEMATICAL METHODS
Kenneth M. Kimmins, M. Tsai
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引用次数: 2

摘要

赛艇需要一个标准化的金牌标准(GMS),以便在比赛中清晰地比较不同级别赛艇的表现。在这里,我们报告了一种方法来排除环境影响,为个人赛艇项目开发一个更公平的GMS。我们使用世界赛艇锦标赛和奥运会(2005-2016)的结果来计算当天最快获胜时间与同一天其他项目获胜时间之间的差异。由此,我们通过重复的k倍交叉验证线性回归计算了每个事件的预后GMS时间。然后,我们将这些值与10年平均获胜时间和世界最佳时间(WBT)进行比较。我们重复这一过程来制定预测平台标准(PS)时间。预测GMS次数(RMSE = 9.47;r2 = 0.875)普遍比WBT(当前GMS)平均慢6.2秒,但比10年平均值快12.3秒。预后PS次数(RMSE = 10.5;r2 = 897)也比WBT慢,但比10年平均值快,分别快12.2秒和6.3秒。我们基于历史数据的时差预测模型产生非离群预测时间。该方法利用相对时差,提供了一个独立于环境条件的选择标准,易于适用于不同的运动项目。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards a more objective time standard in competitive rowing
Abstract Rowing needs a standardized Gold Medal Standard (GMS) to clearly compare performance across boat classes in competition. Here, we report a method to factor out environmental effects, developing a fairer GMS for individual rowing events. We used results from World Rowing Championships and Olympics Games (2005–2016) to calculate the difference between the fastest winning time of the day and other event winning times on the same day. From this, we calculated a prognostic GMS time for each event via repeated k-fold cross-validation linear regression. Then, we compared these values with the 10-year average winning time and the World Best Time (WBT). We repeated this process to develop prognostic podium standard (PS) times. The prognostic GMS times (RMSE = 9.47; R 2 = 0.875) were universally slower than the WBT (current GMS) by 6.2 s on average but faster than the 10-year average by 12.3 s. The prognostic PS times (RMSE = 10.5; R 2 = 897) were also slower than the WBT but faster than the 10-year average, by 12.2 and 6.3 s respectively. Our time-difference prediction model based on historical data generates non-outlier prognostic times. With the utilization of relative time difference, this approach promises a selection standard independent of environmental conditions, easily applicable across different sports.
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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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