Towards a more objective time standard in competitive rowing

Author:

Kimmins Kenneth M.1ORCID,Tsai Ming-Chang2

Affiliation:

1. Institute of Biomedical Engineering , University of Toronto , 164 College Street, Room 407 , Toronto M5S 3G9 , ON , Canada

2. Biomechanics & Performance Analysis , Canadian Sport Institute Pacific , Victoria , BC , Canada

Abstract

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.

Publisher

Walter de Gruyter GmbH

Subject

Decision Sciences (miscellaneous),Social Sciences (miscellaneous)

Reference12 articles.

1. Barber, H. L. 2018. “Effect of Wind in the Field of Play for Elite Sprint Kayakers.” Master’s diss., Carleton University.

2. Coen, B., A. Urhausen, and W. Kinderrnann. 2003. “Sport Specific Performance Diagnosis in Rowing: An Incremental Graded Exercise Test in Coxless Pairs.” International Journal of Sports Medicine 24 (6): 428–32. https://doi.org/10.1055/s-2003-41178.

3. Cornett, J., P. Bush, and N. Cummings. 2008. “An 8-Factor Model for Evaluating Crew Race Performance Model of Crew Race Performance.” International Journal of Sports Science and Engineering 2 (3): 169–84.

4. Diafas, V., S. Kaloupsis, V. Bachev, E. Dimakopoulou, and V. Diamanti. 2006. “Weather Conditions During Athens Olympic Rowing and Flatwater Canoe-Kayak Regatta at the Olympic Rowing Center in Schinias.” Kinesiology 38 (1): 72–7.

5. Ely, M. R., S. N. Cheuvront, W. O. Roberts, and S. J. Montain. 2007. “Impact of Weather on Marathon-Running Performance.” Medicine & Science in Sports & Exercise 39 (3): 487–93. https://doi.org/10.1249/mss.0b013e31802d3aba.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3