| Learning Outcomes |
PO |
MME |
| The students who succeeded in this course: |
|
|
| LO-1 |
To gain the ability to collect and analyze athlete performance data. |
PO-3 Can effectively carry out data collection, analysis, and reporting processes related to sports sciences.
|
Examination
|
| LO-2 |
To be able to apply the results of data analysis to training programs. |
PO-3 Can effectively carry out data collection, analysis, and reporting processes related to sports sciences.
PO-4 Can design training programs based on scientific principles and apply them at an individual or team level.
|
Examination
|
| LO-3 |
To be able to present findings effectively using data visualization and reporting techniques. |
PO-3 Can effectively carry out data collection, analysis, and reporting processes related to sports sciences.
PO-11 Adopts multidisciplinary approaches in sports sciences and can collaborate with other disciplines.
PO-12 Can apply performance analysis and evaluation processes to support the development of athletes.
|
Examination
|
| LO-4 |
To be able to apply ethical and confidentiality principles in athlete tracking and data analysis. |
PO-3 Can effectively carry out data collection, analysis, and reporting processes related to sports sciences.
|
Examination
|
PO: Programme Outcomes
MME:Method of measurement & Evaluation |
| Course Contents |
| Starting from the basic concepts of collecting data on training and competition performance with global tracking devices (GPS) in sports sciences, analysis of the data obtained, data collection methods and technologies, performance measurement techniques, data analytics and statistical methods, software and tools for athlete tracking, data visualization and reporting techniques, data-driven training planning, ethics and confidentiality. |
| Weekly Course Content |
| Week |
Subject |
Learning Activities and Teaching Methods |
| 1 |
Introduction to data analytics and GPS technologies in sports science |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 2 |
Principles and applications of GPS tracking devices |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 3 |
Data collection methods and technologies |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 4 |
Performance measurement techniques: Speed, distance, and load metrics |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 5 |
Basic statistical methods for data analysis |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 6 |
Data visualization: Charts and reporting techniques |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 7 |
Data-driven training program planning for athlete performance |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 8 |
mid-term exam |
|
| 9 |
Introduction and usage of software and tools for athlete tracking |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 10 |
Analysis of data impacts on athlete health and performance |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 11 |
Ethical and privacy principles: Data security and sharing |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 12 |
Advanced data analysis and modeling techniques |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 13 |
Practical examples: Data collection and analysis projects |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 14 |
Project presentations and group evaluations |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 15 |
General review and discussions |
Lecture and Discussion,
Applied Data Collection and Use of GPS,
Data Analytics and Statistics Studies,
Case Studies and Group Projects,
Data Visualization and Reporting Studies |
| 16 |
final exam |
|
| Recommend Course Book / Supplementary Book/Reading |
| Required Course instruments and materials |
|
