6B054E - Applied Science and Athlete Monitoring 01 Sep 2026 - 31 Aug 2032 | Version 0

Associated Module Information

Module Code: 6B054E
Module Title: Applied Science and Athlete Monitoring
Faculty: Faculty of Life Sciences and Education
Faculty Group: Sport
Faculty Sub Group: Sports Coaching
Module Leader: Peter Ashcroft
Module Team: Nathan Evans
First Intended Intake: SEP 2026 Final Year of Intake: 2031
Date Closed:
Credit Value: 30 Credit Level: 6
Language: English
Percentage of Module Taught in Welsh: 0
Equivalent Module:
HECOS codes: 101379 - sport technology
HECOS Code Weighting: 100

Document Version Information

Version 0
Valid From 01 Sep 2026
Valid To 31 Aug 2032

Module Aims

The main aims of the module are: 

  • Develop an understanding of contemporary athlete monitoring practices. 

  • Develop knowledge and applied skills in the use of sport science technologies, for the collection and interpretation of athlete data in applied settings. 

  • Develop competence in data analysis, visualisation and communication, using platforms such as Power Bi. 

Content Summary

 Athlete monitoring is a key part of modern strength and conditioning, supporting practitioners in tracking training load, managing fatigue, and reducing injury risk. With advancements in sport technology, tools such as GPS units, heart rate monitors, and force plates now provide detailed performance and recovery data. This content will be delivered alongside industry professionals, ensuring learners develop the ability to collect, interpret, and apply these data streams—now a core competency in high-performance sport. 

 

This module develops the knowledge and applied skills required to monitor athlete performance using contemporary sport science technologies. Through a mix of seminars and practical workshops, you'll learn how to collect data, use monitoring equipment and follow real-world protocols. 

A key feature of the module is the integration of Power BI and R Studio for data analysis and dashboard creation, supported by AI. These powerful tools will allow you to analyse data and build dashboards. You’ll learn how to turn raw data into coach-facing reports. These skills aren’t just useful for strength and conditioning; they’re highly transferable across sport, health, and data-driven industries. Developing confidence with these tools will boost your employability and prepare you for real-world professional roles.  

The knowledge and skills developed during this module are aligned with the expectations of the following strength and conditioning and sport and exercise science professional bodies: 

  • UK Strength and Conditioning Association (UKSCA) 

  • National Strength and Conditioning Association (NSCA) 

  • International Universities Strength and Conditioning Association (IUSCA) 

  • Chartered Association of Sport and Exercise Sciences (CASES)  

Learning and Teaching Methods

Activity Type Hours
Seminar 28
Practical Classes and Workshops 28
Guided Study 104
Problem/Challenge based learning 70
Formative Assessment 10
Summative Assessment 60
Total Hours Selected 300

Learning Outcomes

# Learning Outcome
LO1 Critically evaluate athlete monitoring strategies by analysing internal and external load metrics, assessing the validity and reliability of sport science technologies, and applying evidence-based frameworks to support performance decision-making
LO2 Demonstrate competence in data analysis and visual communication by using Power BI to process athlete monitoring data, create interactive dashboards, and present actionable insights.

Module Requisites

N/A

Assessment Criteria

Assessment Category Assessment Type Description Duration Word Count Weight (%) Best of? Pass Mark
Asynchronous Assessment Essay 1 The critical essay requires students to evaluate athlete monitoring strategies using evidence-based reasoning. This assessment supports the development of critical thinking, ethical awareness, and professional judgement, key attributes for sport science graduates. It also mirrors the analytical demands of roles in performance sport, where practitioners must justify monitoring decisions using valid and reliable evidence 0 3000 50 No 40
Asynchronous Assessment Student Choice The portfolio: dashboard project involves the creation of an interactive Power BI dashboard using athlete monitoring datasets. Students must integrate multiple data sources, apply analytical techniques, and present actionable insights. This assessment builds digital literacy, visual communication, and stakeholder engagement, all of which are essential for employability in sport science and related sectors. students are given the option to choose their preferred format. They may either submit a written essay/report or deliver a recorded presentation. Each format is intentionally designed to develop and assess a broad set of transferable skills, including verbal and written communication, the effective use of visual data, and the capacity to provide evidence-based justification. 15 1000 50 No 40

Assessment Matrix

Assessment Type Learning Outcomes
LO1 LO2
Essay 1
Student Choice

Reading List

Week 1: Foundations of Athlete Monitoring 

Essential: 

  • McGuigan, M. (2017). Monitoring Training and Performance in Athletes. Human Kinetics. Chapters 1–2. 

  • Gabbett, T. J. (2016). The ACWR: A flawed ratio or a useful tool? British Journal of Sports Medicine. 

Supplementary: 

  • Halson, S. L. (2014). Monitoring Training Load to Understand Fatigue in Athletes. Sports Medicine. 

  • Bourdon et al. (2017). Monitoring Athlete Training Loads: Consensus Statement. International Journal of Sports Physiology and Performance. 

Week 2: External Training Load 

Essential: 

  • Akenhead, R., & Nassis, G. P. (2016). Training Load and Fitness Monitoring in Football. Sports Medicine. 

  • Cummins et al. (2013). Global Positioning Systems (GPS) and Microtechnology Sensors in Team Sports. Sports Medicine. 

Supplementary: 

  • Malone et al. (2017). High-Speed Running and Injury Risk in Elite Football. British Journal of Sports Medicine. 

Week 3: Internal Training Load 

Essential: 

  • Impellizzeri et al. (2005). Use of RPE-Based Training Load in Soccer. Medicine & Science in Sports & Exercise. 

  • Buchheit, M. (2014). Monitoring training status with HR measures: do all roads lead to Rome? Frontiers in physiology. 

Supplementary: 

  • Gabbett, T. J. (2016). Influence of Training Load on Injury Risk in Professional Rugby League Players. Journal of Sports Sciences. 

  • Foster et al. (2001). A New Approach to Monitoring Exercise Training. Journal of Strength and Conditioning Research. 

Week 4: Training Response 

Essential: 

  • Gathercole et al. (2015). Monitoring Fatigue with Jump and Sprint Tests. International Journal of Sports Physiology and Performance.  

  • McGuigan, M. (2017). Monitoring Training and Performance in Athletes. Human Kinetics. Chapters 4–5. 

Supplementary: 

  • Kellmann, M. (2010). Preventing Overtraining in Athletes in High-Intensity Sports. Psychology of Sport and Exercise. 

Week 5: Data Integration & Reporting 

Essential: 

  • O'Donoghue, P. (2014). Data Analysis in Sport. Routledge. Chapters on dashboarding and reporting. 

  • Few, S. (2012). Show Me the Numbers: Designing Tables and Graphs to Enlighten. Analytics Press. 

Supplementary: 

  • Gabbett, T. J. (2020). Load Management: More Than Just Numbers. British Journal of Sports Medicine. 

Week 6: Scenario-Based Case Studies 

Essential: 

  • McGuigan, M. (2017). Monitoring Training and Performance in Athletes. Human Kinetics. Case study chapters. 

  • Oliveira W. K. et al. (2018). Monitoring training load in beach volleyball players: a case study with an Olympic team.?Motriz: Revista de Educação Física. 

  • Zeller, Set al. (2017). Monitoring training load in handcycling: a case study.?The Journal of Strength & Conditioning Research.