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.Acquire knowledge of the use of sports technologies and digital solutions in training, competition and rehabilitation processes, as well as the operating principles and capabilities of wearable smart devices in the acquisition of physiological data outside the laboratory. Students acquire knowledge of the basic principles of acquisition, structuring, processing and visualization of sports data, as well as the potential of VR/AR, video analysis and AI solutions and aspects of data ethics in the development of the training process.
Individual work and tests
Test for the topics acquired in the study course
Skills
1.1. Acquires and is able to process data from wearable devices and digital surveillance systems. Uses software tools for analyzing and visualizing sports data. Explain and discuss the results obtained in a reasoned manner. 2. Able to interpret biometrics and performance data by assessing workout load, recovery and athletic performance progress. 3. Uses artificial intelligence and machine learning tools, for simulating athletic performance and risk assessment. 4. Apply VR/AR scenarios and video analysis to improve the training process and evaluate athletes.
Individual work and tests
Practical work (led by lecturer and partly independently) • Presentation of the project
Competences
1.1. Independently analyse multimodal sports data and develop data-based recommendations for coaches and athletes to optimize the training process. 2. The reliability and practical applicability of sports technology data shall be critically evaluated based on scientific evidence-based literature. 3. Integrates 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).
Individual work and tests
Description of the review study on the selected topic (writing of the description takes place on the spot during the exam)
Assessment
Individual work
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Presentation of the project |
40.00% from total grade
|
10 points
|
|
The student prepares one presentation and presents the results of his or her experiment. The presentation consists of an introduction (presentation of chosen topic in the chosen field of science); purpose of the experiment; the methodological part (organisation of the experiment, presentation of the measuring instruments to be used); results; analysis of results (discussion, limitations that could have affected the objectivity of the results). |
||
|
2.
Practical work (led by lecturer and partly independently) |
25.00% from total grade
|
10 points
|
|
The student participates in practical works organised by the lectors. In addition to the student, one experiment must be conducted independently, the results of which will be presented by the student in front of the audience. |
||
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
|
Collection and interpretation of data from wearable devices.
Description
Looks at today’s sports technology types, their application across different sports and key developments including digitisation and AI integration. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Collection and interpretation of data from wearable devices.
Description
Looks at today’s sports technology types, their application across different sports and key developments including digitisation and AI integration. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Data structure and pre-production in sports analytics
Description
Presents the operating principles and capabilities of wearable devices for the acquisition of physiological and movement data, as well as the basic principles for the interpretation of these data. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Data structure and pre-production in sports analytics
Description
Presents the operating principles and capabilities of wearable devices for the acquisition of physiological and movement data, as well as the basic principles for the interpretation of these data. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Visualisation and interpretation of sports data
Description
Provide an understanding of data organisation, quality assurance and pre-processing methods necessary for further analysis. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Visualisation and interpretation of sports data
Description
Provide an understanding of data organisation, quality assurance and pre-processing methods necessary for further analysis. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Software tools for sports data analysis (Excel, video analyzer pro, Opencap, etc.)
Description
Looks at data display methods and tools to help identify trends, relationships, and make informed decisions. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Software tools for sports data analysis (Excel, video analyzer pro, Opencap, etc.)
Description
Looks at data display methods and tools to help identify trends, relationships, and make informed decisions. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
Description
Presents practical tools for data processing, biomechanical analysis and motion evaluation. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
Description
Presents practical tools for data processing, biomechanical analysis and motion evaluation. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Laboratory
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
Description
Presents practical tools for data processing, biomechanical analysis and motion evaluation. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Analysis of real-world data (project work)
Description
Analyse approaches for assessing, predicting and/or identifying injury or overload risks of athletic performance. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Analysis of real-world data (project work)
Description
Analyse approaches for assessing, predicting and/or identifying injury or overload risks of athletic performance. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Analytics of sports data in decision making
Description
Looks at how data is used in training planning, load docking and strategic decision making. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Analytics of sports data in decision making
Description
Looks at how data is used in training planning, load docking and strategic decision making. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
Description
Introduces VR and THE use of technology in motor skills development, cognitive skills training, competition stress control and reduction. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
Description
Introduces VR and THE use of technology in motor skills development, cognitive skills training, competition stress control and reduction. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
Description
Presents practical tools for data processing, biomechanical analysis and motion evaluation. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
Description
Introduces VR and THE use of technology in motor skills development, cognitive skills training, competition stress control and reduction. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
Description
Introduces VR and THE use of technology in motor skills development, cognitive skills training, competition stress control and reduction. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
Description
Introduces VR and THE use of technology in motor skills development, cognitive skills training, competition stress control and reduction. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
Description
Introduces VR and THE use of technology in motor skills development, cognitive skills training, competition stress control and reduction. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Laboratory
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
Description
Presents practical tools for data processing, biomechanical analysis and motion evaluation. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Virtual and augmented reality in sports training
Description
Introduces VR and THE use of technology in motor skills development, cognitive skills training, competition stress control and reduction. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Digital surveillance and video analysis
Description
Looks at motion recording, analysis and feedback methods using digital tools. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Digital surveillance and video analysis
Description
Looks at motion recording, analysis and feedback methods using digital tools. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Digital surveillance and video analysis
Description
Looks at motion recording, analysis and feedback methods using digital tools. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
Description
Presents practical tools for data processing, biomechanical analysis and motion evaluation. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Digital surveillance and video analysis
Description
Looks at motion recording, analysis and feedback methods using digital tools. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Assessment, modelling and risk assessment of athletes’ performance
Description
Presents practical tools for data processing, biomechanical analysis and motion evaluation. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Ethical and data protection issues for sports technology
Description
Provides an understanding of data security, privacy and ethical principles in the collection and use of sports data. |
-
Lecture
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Ethical and data protection issues for sports technology
Description
Provides an understanding of data security, privacy and ethical principles in the collection and use of sports data. |
-
Test
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Collection and interpretation of data from wearable devices.
Description
Looks at today’s sports technology types, their application across different sports and key developments including digitisation and AI integration. |
|
Data structure and pre-production in sports analytics
Description
Presents the operating principles and capabilities of wearable devices for the acquisition of physiological and movement data, as well as the basic principles for the interpretation of these data. |
|
Visualisation and interpretation of sports data
Description
Provide an understanding of data organisation, quality assurance and pre-processing methods necessary for further analysis. |
|
Software tools for sports data analysis (Excel, video analyzer pro, Opencap, etc.)
Description
Looks at data display methods and tools to help identify trends, relationships, and make informed decisions. |
|
Assessment, modelling and risk assessment of athletes’ performance
Description
Presents practical tools for data processing, biomechanical analysis and motion evaluation. |
|
Analysis of real-world data (project work)
Description
Analyse approaches for assessing, predicting and/or identifying injury or overload risks of athletic performance. |
|
Analytics of sports data in decision making
Description
Looks at how data is used in training planning, load docking and strategic decision making. |
|
Virtual and augmented reality in sports training
Description
Introduces VR and THE use of technology in motor skills development, cognitive skills training, competition stress control and reduction. |
|
Digital surveillance and video analysis
Description
Looks at motion recording, analysis and feedback methods using digital tools. |
|
Ethical and data protection issues for sports technology
Description
Provides an understanding of data security, privacy and ethical principles in the collection and use of sports data. |
-
Test
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Collection and interpretation of data from wearable devices.
Description
Looks at today’s sports technology types, their application across different sports and key developments including digitisation and AI integration. |
|
Data structure and pre-production in sports analytics
Description
Presents the operating principles and capabilities of wearable devices for the acquisition of physiological and movement data, as well as the basic principles for the interpretation of these data. |
|
Visualisation and interpretation of sports data
Description
Provide an understanding of data organisation, quality assurance and pre-processing methods necessary for further analysis. |
|
Software tools for sports data analysis (Excel, video analyzer pro, Opencap, etc.)
Description
Looks at data display methods and tools to help identify trends, relationships, and make informed decisions. |
|
Assessment, modelling and risk assessment of athletes’ performance
Description
Presents practical tools for data processing, biomechanical analysis and motion evaluation. |
|
Analysis of real-world data (project work)
Description
Analyse approaches for assessing, predicting and/or identifying injury or overload risks of athletic performance. |
|
Analytics of sports data in decision making
Description
Looks at how data is used in training planning, load docking and strategic decision making. |
|
Virtual and augmented reality in sports training
Description
Introduces VR and THE use of technology in motor skills development, cognitive skills training, competition stress control and reduction. |
|
Digital surveillance and video analysis
Description
Looks at motion recording, analysis and feedback methods using digital tools. |
|
Ethical and data protection issues for sports technology
Description
Provides an understanding of data security, privacy and ethical principles in the collection and use of sports data. |
-
Test
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Collection and interpretation of data from wearable devices.
Description
Looks at today’s sports technology types, their application across different sports and key developments including digitisation and AI integration. |
|
Data structure and pre-production in sports analytics
Description
Presents the operating principles and capabilities of wearable devices for the acquisition of physiological and movement data, as well as the basic principles for the interpretation of these data. |
|
Visualisation and interpretation of sports data
Description
Provide an understanding of data organisation, quality assurance and pre-processing methods necessary for further analysis. |
|
Software tools for sports data analysis (Excel, video analyzer pro, Opencap, etc.)
Description
Looks at data display methods and tools to help identify trends, relationships, and make informed decisions. |
|
Assessment, modelling and risk assessment of athletes’ performance
Description
Presents practical tools for data processing, biomechanical analysis and motion evaluation. |
|
Analysis of real-world data (project work)
Description
Analyse approaches for assessing, predicting and/or identifying injury or overload risks of athletic performance. |
|
Analytics of sports data in decision making
Description
Looks at how data is used in training planning, load docking and strategic decision making. |
|
Virtual and augmented reality in sports training
Description
Introduces VR and THE use of technology in motor skills development, cognitive skills training, competition stress control and reduction. |
|
Digital surveillance and video analysis
Description
Looks at motion recording, analysis and feedback methods using digital tools. |
|
Ethical and data protection issues for sports technology
Description
Provides an understanding of data security, privacy and ethical principles in the collection and use of sports data. |
-
Test
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Collection and interpretation of data from wearable devices.
Description
Looks at today’s sports technology types, their application across different sports and key developments including digitisation and AI integration. |
|
Data structure and pre-production in sports analytics
Description
Presents the operating principles and capabilities of wearable devices for the acquisition of physiological and movement data, as well as the basic principles for the interpretation of these data. |
|
Visualisation and interpretation of sports data
Description
Provide an understanding of data organisation, quality assurance and pre-processing methods necessary for further analysis. |
|
Software tools for sports data analysis (Excel, video analyzer pro, Opencap, etc.)
Description
Looks at data display methods and tools to help identify trends, relationships, and make informed decisions. |
|
Assessment, modelling and risk assessment of athletes’ performance
Description
Presents practical tools for data processing, biomechanical analysis and motion evaluation. |
|
Analysis of real-world data (project work)
Description
Analyse approaches for assessing, predicting and/or identifying injury or overload risks of athletic performance. |
|
Analytics of sports data in decision making
Description
Looks at how data is used in training planning, load docking and strategic decision making. |
|
Virtual and augmented reality in sports training
Description
Introduces VR and THE use of technology in motor skills development, cognitive skills training, competition stress control and reduction. |
|
Digital surveillance and video analysis
Description
Looks at motion recording, analysis and feedback methods using digital tools. |
|
Ethical and data protection issues for sports technology
Description
Provides an understanding of data security, privacy and ethical principles in the collection and use of sports data. |
Total ECTS (Creditpoints):
8.00
Contact hours:
72 Academic Hours
Final Examination:
Exam (Written)
Bibliography
Required Reading
1.
OUTLIVE. ILGMŪŽĪBAS ZINĀTNE UN MĀKSLA Outlive. The science & art of longevity Autors(i): Dr. Pīters Atija, Bils Gifords. III daļa: *12. nodaļa: 1) Aerobā efektivitāte: 2. zona (243. - 250. lpp.); 2) Maksimālā aerobā veiktspēja: VO2 max (250. - 257. lpp.); 3) Spēks (257. - 267. lpp.). *13. Nodaļa: 1) Stabilitātes evaņģēlijs (268. - 292. lpp.); 2) Fizisko aktivitāšu spēks. Berijs (292. - 295. lpp.).Suitable for English stream
2.
Dindorf, C., Bartaguiz, E., Gassmann, F., & Fröhlich, M. (Eds.). (2024). Artificial intelligence in sports, movement, and health. Springer Nature Switzerland **Part III:** **Chapter 1:** 1) Popularity of artificial intelligence in sports: trends and adoption (pp. 15–35.); 2) Contributions to performance optimization and injury prevention (pp. 35–55.); 3) Future perspectives and challenges (pp. 55–75.).Suitable for English stream
3.
James, Daniel A., & Petrone, Nicola. (2016). Sensors and Wearable Technologies in Sport: Technologies, Trends and Approaches for Implementation. Springer Singapore. Part III: Chapter 12: 1) Pull-up devices: technologies and sensors (pp. 150–165.); 2) Their use in professional sports: gait analysis and performance (pp. 165–180.); 3) Trends and implementation approaches (pp. 180–200.).Suitable 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.
Benson, R., & Connolly, D. (2020). Heart rate training (2nd ed.). Human Kinetics. **Part III:** **Chapter 2:** 1) Cardio zones (training zones): basics and calculation (pp. 23–40.); 2) Customization to individual performance (pp. 40–60.); 3) Application in aerobic and anaerobic training (pp. 60–80.).Suitable for English stream
4.
Hassan Doosti, "Ethics in Statistics: Opportunities and Challenges.", Cambridge, UK: Ethics International Press Ltd, 2024.
Other Information Sources
1.
Cariati I, Bonanni R, Cifelli P, D'Arcangelo G, Padua E, Annino G, Tancredi V. "Virtual reality and sports performance: a systematic review of randomized controlled trials exploring balance.". Front Sports Act Living. 2025 Apr 29;7:1497161.
2.
Abdullah Alzahrani and Arif Ullah. "Advanced biomechanical analytics: Wearable technologies for precision health monitoring in sports performance.". DIGITAL HEALTH Volume 10Sep 2024
3.
Zhou, DiWei, Keogh, Justin W. L., Ma, YingLiang, Tong, Raymond K. Y., Khan, Abdul R. and Jennings, Nicholas R. "Artificial intelligence in sport: A narrative review of applications, challenges and future trends.". Journal of Sports Sciences, 2025.