Veidlapa Nr. M-3 (8)
Study Course Description
Sports Technology, Digital Solutions and Data Analytics
Course Code
LSPA_632
Branch of Science
Health sciences
ECTS
8.00
Target Audience
Public Health; Sports Science; Sports Trainer
LQF
Level 7
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Katrīna Volgemute
Structure Unit Manager
Diāna Laipniece
Structural Unit
Latvian Academy of Sport Education (LASE)
Contacts
LSPA, Brīvības gatve 333, Riga, LV-1006
About Study Course
Objective
Develop in-depth knowledge and practical skills in the use of sports technologies, digital solutions and data analytics in planning, managing and evaluating the training process. The course encourages data-based decision-making using smart devices and sensors that allow athletes to be evaluated outside laboratory conditions -- in training and competitive environments. AI and machine learning techniques in data processing, model building and athletic performance prediction are also being learned.
Preliminary Knowledge
• Basic knowledge of sports science and training process planning.
• basic knowledge of statistics and data processing.
• Prior experience with digital tools (e.g. Excel, SPSS, RSTUDIO Statistics) is desirable.
Learning Outcomes
Knowledge
1.1. Knowledge of sports technologies and their applicability in training, competition and rehabilitation processes has been acquired. 2. Knowledge of the operating principles of wearable smart devices (measures heart rate, heart rate variability, ventilation thresholds VT1, VT2, etc.) and the possibilities for data collection outside the laboratory has been acquired. 3. Is familiar with data acquisition, structuring, pre-production and visualization techniques in sports analytics. 4. Understand the potential of VR (virtual reality with and without VR headset)/AR (augmented reality) technologies, digital video analysis, and AI solutions to improve the training process. 5. Recognises the ethical and data protection aspects of the use of sports data.
Skills
1.1. Collect and process data from wearable devices and digital surveillance systems. 2. Use software tools (Excel, video Analyzer pro, Opencap, etc.) to analyze and visualize sports data. 3. Interpret biometrics and performance data by evaluating workout load, recovery and athletic performance progress. 4. Use AI and machine learning tools to model athletic performance and assess risk. 6. Apply VR/AR scenarios and video analysis to improve the training process and evaluate athletes.
Competences
1.1. To analyse independently multimodal sports data and develop data-based recommendations for coaches and athletes to optimize the training process. 2. Ability to critically evaluate the reliability and practical applicability of sports technology data. 3. Ability to integrate AI-supported analytics into training planning and monitoring. 4. Able to collaborate on interdisciplinary teams with coaches, data analysts and technology experts. 5. Ensure the use of sports technologies in accordance with ethical and data protection principles (including GDPR).
Assessment
Individual work
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Presentation of the project |
40.00% from total grade
|
10 points
|
|
2.
Practical work (led by lecturer and partly independently) |
25.00% from total grade
|
10 points
|
Examination
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Description of the review study on the selected topic (writing of the description takes place on the spot during the exam) |
25.00% from total grade
|
10 points
|
|
At the beginning of the study course, the student will become acquainted with topics from which it will be possible to choose one to describe in the exam in the form of a review study at the end of the study course. |
||
|
2.
Test for the topics acquired in the study course |
10.00% from total grade
|
Test
|
Study Course Theme Plan
FULL-TIME
Part 1
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Use of sports technologies and developments
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Use of sports technologies and developments
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Collection and interpretation of data from wearable devices.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Collection and interpretation of data from wearable devices.
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Data structure and pre-production in sports analytics
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Data structure and pre-production in sports analytics
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Use of sports technologies and developments
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Use of sports technologies and developments
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Visualisation and interpretation of sports data
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Visualisation and interpretation of sports data
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Software tools for sports data analysis (Excel, video analyzer pro, Opencap, etc.)
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Software tools for sports data analysis (Excel, video analyzer pro, Opencap, etc.)
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Laboratory
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Analysis of real-world data (project work)
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Analysis of real-world data (project work)
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Analytics of sports data in decision making
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Analytics of sports data in decision making
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Laboratory
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Digital surveillance and video analysis
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Digital surveillance and video analysis
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Digital surveillance and video analysis
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Digital surveillance and video analysis
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Ethical and data protection issues for sports technology
|
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Ethical and data protection issues for sports technology
|
-
Test
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Use of sports technologies and developments
|
|
Collection and interpretation of data from wearable devices.
|
|
Data structure and pre-production in sports analytics
|
|
Visualisation and interpretation of sports data
|
|
Software tools for sports data analysis (Excel, video analyzer pro, Opencap, etc.)
|
|
Assessment, modelling and risk assessment of athletes’ performance
|
|
Analysis of real-world data (project work)
|
|
Analytics of sports data in decision making
|
|
Virtual and augmented reality in sports training
|
|
Digital surveillance and video analysis
|
|
Ethical and data protection issues for sports technology
|
-
Test
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Use of sports technologies and developments
|
|
Collection and interpretation of data from wearable devices.
|
|
Data structure and pre-production in sports analytics
|
|
Visualisation and interpretation of sports data
|
|
Software tools for sports data analysis (Excel, video analyzer pro, Opencap, etc.)
|
|
Assessment, modelling and risk assessment of athletes’ performance
|
|
Analysis of real-world data (project work)
|
|
Analytics of sports data in decision making
|
|
Virtual and augmented reality in sports training
|
|
Digital surveillance and video analysis
|
|
Ethical and data protection issues for sports technology
|
-
Test
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Use of sports technologies and developments
|
|
Collection and interpretation of data from wearable devices.
|
|
Data structure and pre-production in sports analytics
|
|
Visualisation and interpretation of sports data
|
|
Software tools for sports data analysis (Excel, video analyzer pro, Opencap, etc.)
|
|
Assessment, modelling and risk assessment of athletes’ performance
|
|
Analysis of real-world data (project work)
|
|
Analytics of sports data in decision making
|
|
Virtual and augmented reality in sports training
|
|
Digital surveillance and video analysis
|
|
Ethical and data protection issues for sports technology
|
-
Test
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Use of sports technologies and developments
|
|
Collection and interpretation of data from wearable devices.
|
|
Data structure and pre-production in sports analytics
|
|
Visualisation and interpretation of sports data
|
|
Software tools for sports data analysis (Excel, video analyzer pro, Opencap, etc.)
|
|
Assessment, modelling and risk assessment of athletes’ performance
|
|
Analysis of real-world data (project work)
|
|
Analytics of sports data in decision making
|
|
Virtual and augmented reality in sports training
|
|
Digital surveillance and video analysis
|
|
Ethical and data protection issues for sports technology
|
Total ECTS (Creditpoints):
8.00
Contact hours:
72 Academic Hours
Final Examination:
Exam (Written)
Bibliography
Required Reading
1.
James, Daniel A., & Petrone, Nicola. (2016). Sensors and Wearable Technologies in Sport: Technologies, Trends and Approaches for Implementation. Springer Singapore.Suitable for English stream
2.
Benson, R., & Connolly, D. (2020). Heart rate training (2nd ed.). Human Kinetics.Suitable for English stream
3.
Dindorf, C., Bartaguiz, E., Gassmann, F., & Fröhlich, M. (Eds.). (2024). Artificial intelligence in sports, movement, and health. Springer Nature SwitzerlandSuitable for English stream
Additional Reading
1.
Kato, Jumba K. (2025). “Wearable Technology for Performance Monitoring in Athletes.” Eurasian Experiment Journal of Scientific and Applied Research, vol. 7, no. 2, pp. 71-77Suitable for English stream
2.
Craig, A., & Shih, P. (2020). Augmented reality and virtual reality: New trends in immersive technology. SpringerSuitable for English stream
3.
Castillo Alvira & Raya-González. (2020). An Essential Guide to Sports Performance.Suitable for English stream