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Wearable Technologies and Sports Analytics
  • Level Professional
  • Duration 28 hours
  • Course by University of Michigan
  • Offered by

About

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. 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.

Modules

Introduction to Sensors and How They Work

    • 2 Videos
    • 3 Readings
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2 Videos

  • Welcome to the Course!
  • Introduction to Wearable Technology

3 Readings

  • Wearable Technologies Course Syllabus
  • Help Us Learn More About You
  • Introduction to the Gamut Workbook

The Endless Possibilities of Wearables

    • 1 Videos
    • 1 Readings
    • 1 ExternalTool
    • 1 Assignment
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1 Assignment

  • Do You Know Your Wearables?

1 External Tool

  • Gamut Workbook: How Do You Think Wearables Can Help People?

1 Videos

  • Wearable Technology Sensors

1 Readings

  • More About Sensors

The World of Athletics and Wearable Technology

    • 1 Videos
    • 1 Readings
    • 1 Lab
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1 Labs

  • Using Python to Explore a Volleyball Dataset

1 Videos

  • The Wearables of Athletics

1 Readings

  • Jumping Into the G-Vert

Week 1 Assignment

    • 2 Readings
    • 1 Lab
    • 1 Assignment
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1 Assignment

  • Analyzing an Entire Season of Jumping in Volleyball

1 Labs

  • Week 1 Assignment - Exploring the Volleyball Dataset

2 Readings

  • Week 1 - Assignment Instructions
  • Week 1 - Sample Notebook

Benefits of Wearables with External Sensors

    • 1 Videos
    • 1 ExternalTool
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1 External Tool

  • Gamut Workbook: Player Load Relative to Body Mass

1 Videos

  • External Loads of Wearable Technology

Improving Team Training Through the Use of Wearables

    • 1 Videos
    • 1 Assignment
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1 Assignment

  • Do You Know Your External Wearables?

1 Videos

  • Training and Performance Measures

The Acute to Chronic Workload Ratio

    • 1 Videos
    • 1 Readings
    • 1 Discussion
    • 1 ExternalTool
    • 1 Lab
    • 1 Assignment
Show info about module content

1 Assignment

  • Machine Learning and ACWR

1 External Tool

  • Gamut Workbook: Machine Learning Reflection

1 Discussions

  • What Should Be Next for Machine Learning?

1 Labs

  • Applying ACWR to a Soccer Team Dataset

1 Videos

  • Predicting and Preventing Injury

1 Readings

  • Machine Learning with Boxing: Identifying Striking Patterns

Week 2 Assignment

    • 2 Readings
    • 1 Lab
    • 1 Assignment
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1 Assignment

  • Applying ACWR to a Soccer Team Dataset (Part 2)

1 Labs

  • Week 2 Assignment Workspace - Applying ACWR to a Soccer Team Dataset (Part 1)

2 Readings

  • Week 2 - Assignment Instructions
  • Week 2 - Sample Notebook

Internal Measures

    • 1 Videos
    • 1 Discussion
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1 Discussions

  • The Utility of Internal Measures

1 Videos

  • Internal Measures of Wearable Technology

What Internal Measures Provide the Most Information?

    • 2 Videos
    • 1 ExternalTool
    • 1 Assignment
Show info about module content

1 Assignment

  • Internal Measures and the Information They Provide

1 External Tool

  • Gamut Workbook: Considering the Benefit of Internal Measures for Your Favorite Sport

2 Videos

  • Is HR a Passé Measure of Stress? What Can Other Measures Add?
  • What Is So Magical About Heart Rate Variability?

Tracking Intensity

    • 2 Videos
    • 1 Lab
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1 Labs

  • Evaluating Internal Training Load During Basketball Game (Practice Workbook)

2 Videos

  • Evaluating Multiple Internal Measures -- Which Is Best?
  • Difference Between Chest-Strap and Wrist-Strap HR Data

Week 3 Assignment

    • 2 Readings
    • 1 Lab
    • 1 Assignment
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1 Assignment

  • Evaluating Game Intensity (Part 2)

1 Labs

  • Week 3 Assignment Workspace - Evaluating Game Intensity (Part 1)

2 Readings

  • Week 3 - Assignment Instructions
  • Week 3 - Sample Notebook

The Special Sauce: Combining Internal and External Measures

    • 1 Videos
    • 1 Readings
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1 Videos

  • Benefits of Combining Internal and External Meaures

1 Readings

  • Estimation of Fitness (Firstbeat Method)

Application of the Sauce: Applications of Combining Internal and External Measures

    • 1 Videos
    • 1 ExternalTool
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1 External Tool

  • Gamut Workbook: Internal and External Measures

1 Videos

  • Evaluating External Load Relative to the Internal Load

Tracking Intensity and Recovery with a Team Dataset

    • 1 Videos
    • 2 Readings
    • 1 Lab
    • 1 Assignment
Show info about module content

1 Assignment

  • Internal and External Metrics

1 Labs

  • Calculate a “Recovery Variable” Using External Load and HR Data for a Field Hockey Team (Part 1)

1 Videos

  • Evaluating Internal and External Measures Together to Determine Metrics

2 Readings

  • Garmin Metrics
  • Stryd

Week 4 Assignment

    • 2 Readings
    • 1 Lab
    • 1 Assignment
Show info about module content

1 Assignment

  • Calculate a "Training Intensity Variable" Using External Load and HR Data for a Field Hockey Team (Part 2)

1 Labs

  • Week 4 Assignment Workspace - Calculating a "Training Intensity Variable"

2 Readings

  • Week 4 - Assignment Instructions
  • Week 4 - Sample Notebook

Revisiting the "Global Metrics"

    • 1 Videos
    • 1 ExternalTool
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1 External Tool

  • Gamut Workbook: Global Metrics in Your Own Life

1 Videos

  • Introduction to the Attraction and Dangers of “Global Metrics”

What Other Predication Can We Make with Current Sensors?

    • 2 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Global Metrics

2 Videos

  • Which Wearable Metrics Do We Not Have a Gold Standard to Compare Against?
  • Which Wearable Metrics Can We Actually Validate?

1 Readings

  • Future of Hydration Prediction

Sleep Metrics (Sleep Score and Tests for Validating a REM Sleep Measure)

    • 2 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Sleep Metrics Dataset Exploration

2 Videos

  • Global Metrics Example: Sleep Score
  • Testing the Validity of the REM Sleep Measure via Direct Measure With Sleep Study

1 Readings

  • (Optional) The Original Validity Testing of REM Sleep

Week 5 Assignment

    • 3 Readings
    • 1 Lab
    • 1 Assignment
Show info about module content

1 Assignment

  • Performance Metrics Assessment Quiz

1 Labs

  • Week 5 Assignment Notebook - Performance Metrics

3 Readings

  • Week 5 - Assignment Instructions
  • Week 5 - Sample Notebook
  • Post-Course Survey

Auto Summary

Explore the fascinating world of sports analytics with "Wearable Technologies and Sports Analytics," taught by Coursera. This professional-level course delves into the use of wearable devices in sports, examining massive datasets to optimize training, recovery, and performance. With a focus on big data and analytics, learners gain insights into physiological principles, injury prevention, and athlete feedback. Over 1680 minutes, participants will work with large sport team datasets and employ Python programming. Available through Starter and Professional subscriptions, this course is ideal for those passionate about sports science and data analysis.

Peter F. Bodary
Instructor

Peter F. Bodary