Data Literacy Modules
Data literacy includes the ability to read, work with, analyse and argue with data. High performance (HP) sport is becoming increasingly data driven, with more emphasis being placed on using data to assess performance, draw conclusions and make decisions regarding athlete programming. As technology continues evolving, the role of data science in high performance sport will keep increasing. Capitalizing on data science will be fundamental to the success of our high performance athletes. As such, data literacy is a vital skill for sport practitioners.
In 2019, Own the Podium formed the Data Sciences and Technology Working Group, the primary task of which was to specify the competencies required for this new discipline. These competencies would serve as a framework for recruiting, developing, and deploying practitioners within this discipline across the HP Canadian sport ecosystem. One of the initial observations from the work of this group is that there exists a mismatch between the needed contemporary data science skills and the capabilities of HP sport practitioners. To that end, one recommendation is to provide opportunities to up-skill practitioners currently involved within the HP Canadian sport system. The Data Science module is a resource for you to refresh your data science knowledge and just one way to support this aim.
Purpose of the Data Science in Sport module:
As a sport practitioner, understanding data science concepts and applying these skills in your work is one way you can help your athletes perform at their best. In fact, Own the Podium has identified data handling and management as a core competency in its High Performance Certification. In this 60-minute online course, you will learn about and apply data science concepts and skills related to the following topics:
- Data science fundamentals
- Planning to investigate performance
- Managing and preparing data for analysis
- Analyzing data and communicating results
Modules can be taken at your own pace.
Approximate time: 30 minutes
Please take the survey once you have completed the module.
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Frequently Asked Questions
- Data science framework
- Data governance and risk management best practices
- Data collection and management best practices
- Measurement properties
- Data formatting and processing
- Descriptive and inferential statistics
- Reporting best practices