Identifying Pacing Profiles in 2000 Metre World Championship Rowing

Pub Date : 2023-03-04 DOI:10.3233/jsa-220497
Dani Chu, M. Tsai, Ryan Sheehan, Jack Davis, R. Doig
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Abstract

The pacing strategy adopted by athletes is a major determinants of success during timed competition. Various pacing profiles are reported in the literature and its importance depends on the mode of sport. However, in 2000 metre rowing, the definition of these pacing profiles has been limited by the minimal availability of data. Purpose: Our aim is to objectively identify pacing profiles used in World Championship 2000 metre rowing races using reproducible methods. Methods: We use the average speed for each 50 metre split for each available boat in every race of the Rowing World Championships from 2010-2017. This data was scraped from www.worldrowing.com. This data set is publicly available (https://github.com/danichusfu/rowing_pacing_profiles) to help the field of rowing research. Pacing profiles are determined by using k-shape clustering, a time series clustering method. A multinomial logistic regression is then fit to test whether variables such as boat size, gender, round, or rank are associated with pacing profiles. Results: Four pacing strategies (Even, Positive, Reverse J-Shaped, and U-Shaped) are identified from the clustering process. Boat size, round (Heat vs Finals), rank, gender, and weight class are all found to affect pacing profiles. Conclusion: We use an objective methodology with more granular data to identify four pacing strategies. We identify important associations between these pacing profiles and race factors. Finally, we make the full data set public to further rowing research and to replicate our results.
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2000年世界米赛艇锦标赛节奏特征分析
在计时赛中,运动员采用的节奏策略是成功的主要决定因素。文献中报道了各种起搏情况,其重要性取决于运动模式。然而,在2000米赛艇比赛中,这些起搏曲线的定义受到数据可用性最低的限制。目的:我们的目的是使用可重复的方法,客观地确定世界锦标赛2000米赛艇比赛中使用的起搏曲线。方法:我们使用2010-2017年世界赛艇锦标赛每场比赛中每艘可用船只每50米的平均速度。这些数据是从www.worldrowing.com上截取的。这些数据集是公开的(https://github.com/danichusfu/rowing_pacing_profiles)以帮助赛艇研究领域。起搏剖面是通过使用k形聚类(一种时间序列聚类方法)来确定的。然后拟合多项式逻辑回归来测试船只大小、性别、轮数或级别等变量是否与起搏特征相关。结果:从聚类过程中识别出四种起搏策略(偶数、正、反向J形和U形)。船的大小、轮数(热火队vs总决赛)、级别、性别和体重等级都会影响节奏。结论:我们使用一种具有更细粒度数据的客观方法来确定四种起搏策略。我们确定了这些起搏特征和种族因素之间的重要关联。最后,我们公开了完整的数据集,以进一步进行赛艇研究并复制我们的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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