Sports analytics now include massive datasets from athletes and teams that quantify both training and competition efforts. Wearable technology devices are being worn by athletes everyday and provide considerable opportunities for an in-depth look at the stress and recovery of athletes across entire seasons. The capturing of these large datasets has led to new hypotheses and strategies regarding injury prevention as well as detailed feedback for athletes to try and optimize training and recovery.
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课程信息
Learners should have some familiarity with Python before starting this course. We recommend Python for Everybody Specialization.
Learners should have some familiarity with Python before starting this course. We recommend Python for Everybody Specialization.
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密歇根大学
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
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Introduction to Wearable Technology
In this module, we will introduce different types of wearable devices that are used by athletes and teams to improve training and recovery. We will start by highlighting what types of sensors are used within the wearable devices and how the data coming from these sensors can provide insights, such as training intensity and or physiologic “readiness”.
External Loads of Wearable Technology
In this module, we will focus on what we have introduced as “external” measures. We will point out some of the (inaccurate) assumptions that are made regarding external measures of “load” and “effort”. In addition, we will outline how the continuous use of wearable devices has led to new opportunities for quantifying effort as well as (in theory) reducing injury and improving performance. We will finish by describing the “acute to chronic workload” and the reasons it has gained a lot of attention in the past several years.
Internal Measures of Wearable Technology
In this module, we will dive more into the physiology of training and recovery, focusing on what we have introduced as “internal” measures. We will further explore the use of internal sensors to provide a glimpse of how the individual athlete is responding to the stress induced by training and/or competition. We will also highlight the pros and cons of using internal measures to evaluate individual and team training and recovery.
Combination of Internal and External Wearable Technology
In this module, we combine external and internal measures to provide a much more nuanced look at training and recovery. The external measures can provide a highly quantified evaluation of the movements and motions that have taken place, while the internal measures provide feedback about how the athlete is tolerating the training. Combining them can be instrumental for evaluating performance improvements and preventing or reducing overuse injuries.
关于 Sports Performance Analytics 专项课程
Sports analytics has emerged as a field of research with increasing popularity propelled, in part, by the real-world success illustrated by the best-selling book and motion picture, Moneyball. Analysis of team and player performance data has continued to revolutionize the sports industry on the field, court, and ice as well as in living rooms among fantasy sports players and online sports gambling.

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