Sports Science MA, Performance and Data Analysis, 7.5 credits

Aim

This course aims to provide students with the skills required for advanced data analyses in elite sports as well as provide the fundamentals of sports analytics. Following this course students will have the knowledge to generate data informed insights in various sports disciplines with a primary focus on performance and injury risk.

Course objectives

After the course, the students should be able to: 
1. Apply basic data analysis and analytics to practical performance situations. 
2. Understand advanced data analysis, analytics and programming methods.
3. Understand the basics of signal processing and its importance for generating performance insights. 
4. Develop athlete monitoring databases from performance data such as RPE, GPS and HR 
5. Generate appropriate data visualision for interpretation and reporting of performance data to coaches and athletes 
6. Understand the basics of notational analysis and its importance within the high-performance environment.

Content

Basics of sports analytics

Advanced data analysis / programming basics

Signal processing

Athlete monitoring database

Data reduction

Data visualization

Notational analysis

Entry requirements

A Bachelor degree with at least 180 credits, including a degree project of at least 15 credits, in Sports Science, Sports Medicine or Physiotherapy.

OR

A Bachelor degree consisting of at least 180 credits, including a degree project of at least 15 credits, and a minimum of 60 credits in one or more of the following subjects: clinical epidemiology, exercise physiology, testing methods in sports science, kinesiology, biomechanics, coaching and leadership, sports nutrition, sports medicine, training sciences.

AND English course 6 or equivalent.

Selection rules and procedures

The selection process is in accordance with the Higher Education Ordinance and the local order of admission.

Teaching form

A range of teaching methods will be used, e.g., lectures, seminars, discussions, practical labs and individual reflection. The course will be delivered predominantly online and entirely in English. There will be one compulsory campus meeting (combined with the parallel course, “Research Methods and Statistics”). Compulsory seminars, presentations and independent project will also form part of the assessment.

Examination form

1101: Module 1 - Individual written project work, 2.5 Credits
Grade scale: Three-grade scale
Individual written project work - independent development of a data analysis related case within a sport of choice.

2101: Module 2 - Campus-based practicals, 2.5 Credits
Grade scale: Two-grade scale
Campus-based practicals - active participation and demonstrable practical competence in all laboratory and seminar activities on campus.

3101: Module 3 - Individual practical exam, 2.5 Credits
Grade scale: Three-grade scale
Individual practical exam (written/computer-based).

Link to subject-specific grade criteria: www.miun.se/betygskriterier

The examiner has the right to offer alternative examination arrangements to students who have been granted the right to special suport by Mid Sweden Universitys disabilities advisor.

Grading system

Three-grade scale

Other information

Course certificate, credit transer, appeal, etc are regulated by the Higher Education Ordinance.