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
Uģis Ciematnieks
Structural Unit
Department of Sports Theory
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.Describe sports technologies and their applicability in training, competition and rehabilitation processes.
2.Identify smart wearable devices used outside laboratory conditions (measures heart rate, heart rate variability, ventilatory thresholds VT1, VT2, etc.) and explain their operating principles.
3.Identify portable digital devices that can be used in a gym or stadium outside the laboratory (portable contact mats for determining the height and power of vertical jumps, digital hand dynamometers for measuring the strength of different muscle groups, hardware for determining the volume of the heart systole in loads by measurement of the electrical resistance of the thorax, etc.) and explain their operating principles.
4.Compares and analyzes methods of acquisition, structuring, pre-production and visualization of data in sports analytics.
5.Explains 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.
6.Describe the ethical and data protection aspects of the use of sports data.
Skills
1.Analyses and interprets data from wearable, portable devices and digital surveillance systems.
2.Identify software tools (Excel, video Analyzer pro, etc.) and analyze the quantitative and visual indicators they produce.
3.Evaluate workout load, recovery and athletic performance progress and interpret their biometric and performance data
4.Describes generative AI tools for simulating athletic performance and risk assessment.
5.Apply VR/AR scenarios and video analysis to improve the training process and evaluate athletes.
Competences
1.Analyse multimodal sports data and develop data-based recommendations for athletes to optimize the training process.
2.The reliability and practical applicability of sports technology data shall be critically evaluated.
3.Integrates generative AI-assisted analysis into training planning and monitoring.
4.Collaborate on interdisciplinary teams with coaches, data analysts and technology experts
5.Understand and ensure the use of sports technologies in accordance with ethical and data protection principles (including GDPR).
Assessment
Individual work
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Title
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% from total grade
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Grade
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|---|---|---|
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1.
Practical work (led by lecturer and partly independently) |
25.00% from total grade
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10 points
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Using wearable and/or other laboratory-available technologies that can be used outside the laboratory in the environment, the student independently conducts an experimental study without a lecturer present. Measurements, calculations and visualizations are performed. Data in Excel, Word, or other format is sent to the lecturer. The lecturer shall assess the correctness of the data transmitted according to the quantitative and qualitative criteria generally accepted in science. |
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2.
Presentation of the project |
40.00% from total grade
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10 points
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The student’s presentation on the pilot study carried out is evaluated. The student’s ability to incorporate his or her narrative in time, ability to present concise unsaturated information on presentation slides, ability to present study results in graphical or tabular images that are easy to perceive, ability to critically analyze the objectivity of his or her results, and ability to answer questions asked in the audience are evaluated. |
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Examination
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Title
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% from total grade
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Grade
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|---|---|---|
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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
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10 points
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At the beginning of the study course, the student will become acquainted with topics from which he or she will be able to choose one to describe in the examination, in the form of a review study, at the end of the study course. The student must include at least 5 references in his or her description (the first author and the year in which the study was conducted). The description form consists of the introductory part (presentation of topicality, problem), the main part (description of evidence-based results), the discussion part (student analyses topicality from different perspectives) and the conclusion part (student conclusions based on the literature report described) |
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2.
Test for the topics acquired in the study course |
10.00% from total grade
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Test
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The student will have to complete a test offering options for answers on all the topics offered in the study course. The student will take a closed-type question test. |
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Study Course Theme Plan
FULL-TIME
Part 1
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Lecture
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Modality
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Location
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Contact hours
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On site
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Study room
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2
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Topics
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Use of sports technologies and developments
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Lecture
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Modality
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Contact hours
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On site
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Study room
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2
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Topics
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Use of sports technologies and developments
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Lecture
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Modality
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Location
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Contact hours
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On site
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Study room
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2
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Topics
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Collection and interpretation of data from wearable devices.
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Lecture
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Modality
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Location
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Contact hours
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On site
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Study room
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2
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Topics
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Data structure and pre-production in sports analytics
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Lecture
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Modality
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Location
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Contact hours
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On site
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Study room
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2
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Topics
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Visualisation and interpretation of sports data
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Lecture
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Modality
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Location
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Contact hours
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On site
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Study room
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2
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Topics
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Software tools for sports data analysis (Excel, video analyzer pro, etc.)
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Lecture
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Modality
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Location
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On site
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2
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Topics
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Software tools for sports data analysis (Excel, video analyzer pro, etc.)
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Lecture
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Modality
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Location
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On site
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2
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Topics
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Assessment, modelling and risk assessment of athletes’ performance
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Lecture
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Analysis of real-world data (project work)
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Lecture
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On site
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2
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Topics
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Analytics of sports data in decision making
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Lecture
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2
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Topics
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Virtual and augmented reality in sports training
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Lecture
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Assessment, modelling and risk assessment of athletes’ performance
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Virtual and augmented reality in sports training
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Lecture
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Laboratory
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2
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Topics
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Assessment, modelling and risk assessment of athletes’ performance
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Lecture
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On site
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2
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Topics
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Digital surveillance and video analysis
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Lecture
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On site
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Study room
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2
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Topics
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Ethical and data protection issues for sports technology
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Test
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Modality
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Location
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Contact hours
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|---|---|---|
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On site
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Study room
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2
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Topics
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Use of sports technologies and developments
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Collection and interpretation of data from wearable devices.
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Data structure and pre-production in sports analytics
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Visualisation and interpretation of sports data
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Software tools for sports data analysis (Excel, video analyzer pro, etc.)
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Assessment, modelling and risk assessment of athletes’ performance
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Analysis of real-world data (project work)
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Analytics of sports data in decision making
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Virtual and augmented reality in sports training
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Digital surveillance and video analysis
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Ethical and data protection issues for sports technology
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Test
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Modality
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Location
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Contact hours
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|---|---|---|
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On site
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Study room
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2
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Topics
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Use of sports technologies and developments
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Collection and interpretation of data from wearable devices.
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Data structure and pre-production in sports analytics
|
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Visualisation and interpretation of sports data
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|
Software tools for sports data analysis (Excel, video analyzer pro, etc.)
|
|
Assessment, modelling and risk assessment of athletes’ performance
|
|
Analysis of real-world data (project work)
|
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Analytics of sports data in decision making
|
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Virtual and augmented reality in sports training
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Digital surveillance and video analysis
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Ethical and data protection issues for sports technology
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Class/Seminar
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Modality
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Location
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Contact hours
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On site
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2
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Use of sports technologies and developments
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Use of sports technologies and developments
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On site
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Study room
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2
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Topics
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Collection and interpretation of data from wearable devices.
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Class/Seminar
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On site
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2
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Collection and interpretation of data from wearable devices.
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On site
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2
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Collection and interpretation of data from wearable devices.
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On site
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2
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Collection and interpretation of data from wearable devices.
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On site
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Study room
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2
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Topics
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Data structure and pre-production in sports analytics
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On site
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2
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Data structure and pre-production in sports analytics
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On site
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Study room
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2
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Topics
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Visualisation and interpretation of sports data
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On site
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2
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Visualisation and interpretation of sports data
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On site
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2
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Topics
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Software tools for sports data analysis (Excel, video analyzer pro, etc.)
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Location
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On site
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2
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Software tools for sports data analysis (Excel, video analyzer pro, etc.)
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Location
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On site
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2
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Software tools for sports data analysis (Excel, video analyzer pro, etc.)
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Modality
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Location
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On site
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2
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Topics
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Software tools for sports data analysis (Excel, video analyzer pro, etc.)
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Modality
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Location
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On site
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Study room
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2
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Assessment, modelling and risk assessment of athletes’ performance
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On site
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Assessment, modelling and risk assessment of athletes’ performance
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Assessment, modelling and risk assessment of athletes’ performance
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Assessment, modelling and risk assessment of athletes’ performance
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On site
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4
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Assessment, modelling and risk assessment of athletes’ performance
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Assessment, modelling and risk assessment of athletes’ performance
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Virtual and augmented reality in sports training
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Virtual and augmented reality in sports training
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Virtual and augmented reality in sports training
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Virtual and augmented reality in sports training
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Digital surveillance and video analysis
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Digital surveillance and video analysis
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Assessment, modelling and risk assessment of athletes’ performance
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Software tools for sports data analysis (Excel, video analyzer pro, etc.)
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Software tools for sports data analysis (Excel, video analyzer pro, etc.)
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Software tools for sports data analysis (Excel, video analyzer pro, etc.)
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Analytics of sports data in decision making
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Analytics of sports data in decision making
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2
|
Topics
|
Analysis of real-world data (project work)
|
-
Class/Seminar
|
Modality
|
Location
|
Contact hours
|
|---|---|---|
|
On site
|
Study room
|
2
|
Topics
|
Analysis of real-world data (project work)
|
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.