Overview

This unit introduces students to data analytics (finding meaningful patterns in data sets) and its use in a range of sport business contexts. Students will gain experience in how to source and appraise data captured in various sport settings and learn foundation analytics and statistical techniques to help support and facilitate decision-making. Students will gain hands-on experience in problem conceptualisation, analysis and communicating evidence from sport business data settings including match day performance, stadium and event operations and attendance, finance and pricing, media consumption, sponsorship, and participant, customer and member experience. A focus on understanding and building capacity and capability for progressing data-focused sport organisations is included in the unit.

Requisites

Prerequisites

100 credit points

Teaching periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Teaching Period 3
Location
Online
Start and end dates
04-November-2024
09-February-2025
Last self-enrolment date
17-November-2024
Census date
29-November-2024
Last withdraw without fail date
27-December-2024
Results released date
04-March-2025
Semester 2
Location
Hawthorn
Start and end dates
04-August-2025
02-November-2025
Last self-enrolment date
17-August-2025
Census date
31-August-2025
Last withdraw without fail date
19-September-2025
Results released date
09-December-2025
Teaching Period 3
Location
Online
Start and end dates
03-November-2025
08-February-2026
Last self-enrolment date
16-November-2025
Census date
28-November-2025
Last withdraw without fail date
02-January-2026
Results released date
03-March-2026

Learning outcomes

Students who successfully complete this unit will be able to:

  • Apply coherent knowledge of sport analytics methods and concepts in diverse contexts and applications
  • Apply problem solving, design and decision-making methodologies to identify and provide innovative solutions to sport business problems.
  • Analyse and interpret data using a variety of techniques to provide clear and meaningful outputs for decision making in an sporting context.
  • Communicate proficiently in professional practice to a variety of audiences
  • Function as an effective member or leader of a team

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
On-campus
Class
2.00 12 weeks 24
Online
Lecture
1.00 12 weeks 12
Unspecified Activities
Independent Learning
9.50 12 weeks 114
TOTAL150

Swinburne Online

Type Hours per week Number of weeks Total (number of hours)
Online
Directed Online Learning and Independent Learning
12.50 12 weeks 150
TOTAL150

Assessment

Type Task Weighting ULO's
Assignment 1Group 30 - 40% 1,2,4,5 
Assignment 2Individual 30 - 40% 1,2,3 
Case Study ReportIndividual 20 - 40% 1,2,3 

Content

  • What is Analytics? Foundations and Building Blocks of Analytical Organisations
  • Complex Data and the "Data Age" of Sport Business
  • Data Sources, Management and Infrastructure
  • Problems and Questions in the Sport Business Setting
  • Statistics, Simulation and Modelling
  • Geospatial and Temporal Data Analysis
  • Knowledge Discovery in Databases and Data Mining
  • Communication and Visualisation of Data
  • Sports Analytics Applications I: Events, Operations and Consumer Experience
  • Sports Analytics Applications II: Marketing, Sponsorship and Media
  • Sport Analytics Applications III: Finance, Pricing, Organisational and HR
  • Towards Data and Analytics Focused Sport Organisations

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.