赛道特征是48小时超级马拉松跑步中最重要的预测因素
Beat Knechtle1,2, David Valero3, Elias Villiger4
1Medbase St. Gallen Am Vadianplatz, Vadianstrasse 26, 9001, St. Gallen, Switzerland. beat.knechtle@hispeed.ch.
Scientific reports
|March 29, 2025
概括
最快的48小时超级马拉松跑者来自日本,以色列和冰岛. 特定国家的平面,基于轨道的课程为超级马拉松运动员提供了最佳的性能潜力.
科学领域:
- 体育科学和生理学 体育科学和生理学
- 数据科学和机器学习在体育中的应用
背景情况:
- 超级马拉松跑步,包括48小时的比赛,在全球越来越受欢迎.
- 关于48小时超级马拉松跑者和最快的比赛地点的地理来源的知识有限.
研究的目的:
- 为了确定最快的48小时超级马拉松跑者的原籍国.
- 为了确定最快的48小时超级马拉松比赛的地点.
- 分析影响48小时超级马拉松表现的预测因素.
主要方法:
- 利用机器学习 (ML) 模型,特别是XG Boost算法,来预测运行速度.
- 分析了来自60个国家的7,075名跑步者的16,233个比赛记录 (1980-2022).
- 使用模型可解释性工具调查的变量包括运动员的年龄,性别,原籍国,赛事国家,赛道高度和表面.
主要成果:
- 来自日本,以色列和冰岛的运动员展示了最快的平均跑步速度.
- 最快的48小时比赛在日本,法国,英国,荷兰和埃及举办.
- 平坦的赛道和赛道表面显著影响了跑步速度;运动员的原籍国和赛事国家对预测的速度范围产生了最大的影响. 男人比女人更快,45-49岁的年龄组表现最好.
结论:
- 赛道的高度 (平面) 和表面 (赛道) 是快速的48小时超级马拉松表现的关键决定因素.
- 运动员的原籍国和赛事的主办国对性能潜力有很大影响.
- 旨在实现个人最佳状态的跑步者可以通过选择最佳赛道和了解地理性能趋势来利用这些发现.
相关概念视频
Longitudinal Research
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
Construction of Frequency Distribution
A frequency distribution table can be constructed using the steps given below.
First, make a table with two columns—one with the title of the data that needs to be organized, and the other column for frequency. [Draw a third column for tally marks if needed]. Then, take a look at the items given in the data set and decide if an ungrouped frequency distribution table or a grouped frequency distribution table would be more suitable. If there are large sets of different values, then it is best to...
First, make a table with two columns—one with the title of the data that needs to be organized, and the other column for frequency. [Draw a third column for tally marks if needed]. Then, take a look at the items given in the data set and decide if an ungrouped frequency distribution table or a grouped frequency distribution table would be more suitable. If there are large sets of different values, then it is best to...
Factors Influencing Heart Rate
The heart rate, or pulse rate, is a vital indicator of cardiovascular health. It reflects the number of times the heart beats per minute. Various physiological and environmental factors influence heart rate, increasing or decreasing cardiac output. Understanding these factors is crucial for assessing heart function and identifying potential health issues.
Let us explore the significant factors affecting heart rate, including age, body temperature, posture, acute pain, chemical influences,...
Let us explore the significant factors affecting heart rate, including age, body temperature, posture, acute pain, chemical influences,...
Assumptions of Survival Analysis
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
Run Charts
Run charts serve as an essential instrument for visualizing the performance of various processes over time, enabling the identification of trends and patterns crucial for quality improvement. These charts map out a series of data points chronologically, offering insights into the stability and efficiency of a process. A run chart's creation involves plotting data points on a graph, with the time intervals on the horizontal axis and the specific measurements on the vertical axis. For example,...
Interpreting Run Charts
Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...


