Data Analytics for Sport - Grangegorman

What is... Data Analytics for Sport?

The MSc in Data Analytics for Sport is an advanced programme designed to equip students with the skills and knowledge to analyze and interpret complex data from within the sports industry. This interdisciplinary field combines principles of data science, statistics, and sports science to provide insights that can enhance athletic performance, optimize team strategies, and improve overall organizational efficiency.



Students will learn to collect, process, and analyze large datasets using cutting-edge tools and techniques. The curriculum covers a range of topics including predictive modeling, machine learning, data visualization, and performance analytics. Additionally, students will explore the ethical considerations and data governance issues specific to the sports context.



Practical applications are a key component of the programme. Through hands-on projects and collaborations with sports organizations, students will gain real-world experience in applying data analytics to solve practical problems. This includes analyzing player performance metrics, injury prevention data, fan engagement statistics, and financial data to drive strategic decisions.



Graduates of this program will be well-prepared for careers as data analysts, performance analysts, and data scientists within sports teams, governing bodies, and sports technology companies. They will possess the analytical acumen and industry-specific knowledge to make data-driven decisions that can lead to competitive advantages in the dynamic world of sports.



Oher versions of the MSc Data Analytics are also available. For more information on the other programmes, see separate programme descriptions for MSc Data Analytics and MSc Data Analytics with Precision Diagnostics.

All students will complete the following modules:

Fundamentals of Analytics

Statistics for Analytics

Data Mining

Digital Transformation in Sport Ecosystems

Sport Intelligence Platforms

Data Analytics Research Project Preparation 1

Data Analytics Research Project Preparation 2

Data Analytics Research Project



Students following a conversion pathway (i.e. students without a Computing background) take the following modules:

Programming for Analytics

Data Exploration



Students from a Computing background take the following module:

Advanced Analytics Programming



And one elective module such as:

Machine Learning

Programming for Big Data

Deep Learning

Digital Ethics

Minimum Entry Requirements?

The minimum entry requirement for entry to the MSc Data Analytics, MSc Data Analytics with Precision Diagnostics and Data Analytics for Sport is an honours degree at the level of Upper Second Class Honours (2.1) in the area of Computing, Science, Engineering, Mathematics, or related areas with an appropriate numerate component. Students with an honours degree at the level of Lower Second Class Honours (2.2) with appropriate work experience, may be considered for admission to the programme. Other applicants who do not meet these accredited learning criteria but who have substantial experience in the relevant field may be considered through a Recognition of Prior Learning process, in line with University policy.



Applicants intending to pursue the MSc Data Analytics for Sport pathway must identify this intention at the application stage. To be eligible for this pathway, the applicant must meet the minimum entry requirements for the programme.



Applicants for this programme must have English language proficiency at the level of IELTS (Academic Version) English 6.5 overall (or equivalent) with nothing less than 6 in each component.



Satisfying the minimum entry requirements for the programme does not guarantee applicants a place on the programme.

How to Apply

Applications for this course are now open.



Apply Online - FULL-TIME EU

Apply Online - FULL-TIME NON-EU



For further information on the application process, please visit How To Apply (see "Application Weblink" above).

1 year full-time, on-campus delivery.



Schedule

Teaching takes place from Monday to Friday. As a twelve month programme, classes will commence in early September with the programme running until the end of August. Classes take place weekly throughout the semester and in blocks between semesters. Students will finish their Data Analytics Research Project over the summer period.

Commencement Date: September 2025.