Wearable Technologies and Sports Analytics (Coursera)

Wearable Technologies and Sports Analytics (Coursera)

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.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

This course is an introduction to wearable technology devices and their use in training and competition as part of the larger field of sport sciences. It includes an introduction to the physiological principles that are relevant to exercise training and sport performance and how wearable devices can be used to help characterize both training and performance. It includes access to some large sport team datasets and uses programming in python to explore concepts related to training, recovery and performance.

Course 4 of 5 in the Sports Performance Analytics Specialization

Syllabus

WEEK 1
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”.

WEEK 2
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.

WEEK 3
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.

WEEK 4
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.

WEEK 5
Global Metrics
In this module, we will discuss the exciting new global metrics that have been developed and/or used by many of the consumer devices that are available today. Although these new metrics are exciting, we want to be cognizant of the limitations of these devices. Therefore, we will discuss what sensors are actually employed to provide these new metrics and highlight where validation is feasible.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

L'analyse marketing (Coursera) Coursera
University of Virginia

L'analyse marketing (Coursera)

Les organisations, quelle que soit leur taille, sont inondées de données sur les choix des consommateurs. Mais cette abondance d'informations ne se traduit pas toujours en de meilleures décisions. Savoir interpréter les données est le défi à relever, et il est de plus en plus attendu que les professionnels du marketing utilisent l'analyse pour éclairer et justifier leurs décisions.

Nov 9th 2026
5-12 Weeks
MedTech: Digital Health and Wearable Technology (FutureLearn) FutureLearn
University of Leeds

MedTech: Digital Health and Wearable Technology (FutureLearn)

Discover digital health and learn how wearable technology is transforming healthcare with this online MedTech course. Explore the opportunities and challenges of using digital devices in healthcare. Digital devices are revolutionising healthcare as we know it. On this course, you will explore the impact of these new technologies on healthcare professionals and their patients. Learn how digital devices in healthcare are designed and regulated, and explore if clinical supervision in MedTech is always important.

Self Paced
2 Weeks
Network Analysis in Systems Biology (Coursera) Coursera
Icahn School of Medicine at Mount Sinai

Network Analysis in Systems Biology (Coursera)

An introduction to data integration and statistical methods used in contemporary Systems Biology, Bioinformatics and Systems Pharmacology research. The course covers methods to process raw data from genome-wide mRNA expression studies (microarrays and RNA-seq) including data normalization, differential expression, clustering, enrichment analysis and network construction. The course contains practical tutorials for using tools and setting up pipelines, but it also covers the mathematics behind the methods applied within the tools.

Nov 23rd 2026
5-12 Weeks
Successfully Evaluating Predictive Modelling (edX) EdX
University of Edinburgh,EdinburghX

Successfully Evaluating Predictive Modelling (edX)

Gain an in-depth understanding of evaluation and sampling approaches for effective predictive modelling using Python. A predictive exercise is not finished when a model is built. This course will equip you with essential skills for understanding performance evaluation metrics, using Python, to determine whether a model is performing adequately.

Oct 26th 2021
5-12 Weeks
Disease Screening in Public Health (Coursera) Coursera
University of Geneva

Disease Screening in Public Health (Coursera)

Current and future public health is characterized by the increase of chronic and degenerative diseases, corresponding to the worldwide ageing of the population. The increasing prevalence of these conditions together with the long incubation period of the chronic diseases and the restless technological innovations, offer new opportunities to develop strategies for early diagnosis.

Nov 9th 2026
5-12 Weeks
Advanced Linear Models for Data Science 2: Statistical Linear Models (Coursera) Coursera
Johns Hopkins University

Advanced Linear Models for Data Science 2: Statistical Linear Models (Coursera)

Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: a basic understanding of linear algebra and multivariate calculus; a basic understanding of statistics and regression models; at least a little familiarity with proof based mathematics; basic knowledge of the R programming language.

Nov 23rd 2026
4 Weeks
Understanding China, 1700-2000: A Data Analytic Approach, Part 1 (Coursera) Coursera
The Hong Kong University of Science and Technology - HKUST

Understanding China, 1700-2000: A Data Analytic Approach, Part 1 (Coursera)

The purpose of this course is to summarize new directions in Chinese history and social science produced by the creation and analysis of big historical datasets based on newly opened Chinese archival holdings, and to organize this knowledge in a framework that encourages learning about China in comparative perspective. Our course demonstrates how a new scholarship of discovery is redefining what is singular about modern China and modern Chinese history.

Nov 23rd 2026
5-12 Weeks
Moneyball and Beyond (Coursera) Coursera
University of Michigan

Moneyball and Beyond (Coursera)

The book Moneyball triggered a revolution in the analysis of performance statistics in professional sports, by showing that data analytics could be used to increase team winning percentage. This course shows how to program data using Python to test the claims that lie behind the Moneyball story, and to examine the evolution of Moneyball statistics since the book was published.

Nov 9th 2026
5-12 Weeks