1  Introduction to the module

1.1 Overview

This module introduces you to the use of data visualisation in sport. Sport teams and coaches collect a vast amount of data. While this data appears on the surface to be of great benefit to the teams/individuals there are significant challenges in summarising and sharing the results of any data analytics procedures. In this module you will gain an understanding of different data visualisation methods used in sports, learn how to tailor these based on the different needs of end users and gain expertise that is increasingly sought-after in professional sports.

1.1.1 What will be covered?

You will become familiar with key principles of data visualisation and we will discuss the importance of developing clear and concise visualisations.

As the module progresses, we will work through creating a variety of data visualisations and we will discuss how to refine these and tell a story. We will also look at the inclusion of interactivity.

The module will include individual tasks, an wide range of practicals using both R and Tableau to enhance your understanding and foster practical application of theoretical concepts. You will gain experience in using R and Tableau to prepare, analyse and visualise data.

1.1.2 Staff information

The module will be led and delivered by Dr Xanne Janssen (xanne.janssen@strath.ac.uk), who is based in Graham Hills 533.

1.1.3 Learning objectives

  1. You will be able to evaluate the different data visualisation methods available in a professional sporting context.

  2. You will be able to formulate the steps required to visualise data in a clear and understandable manner.

  3. You will be able to manipulate and organise data and identify the correct data visualisation methods depending on their aim and audience.

  4. You will be able to critique for and against the use of specific data visualisation methods depending on the message they want to share and audience they target.

  5. You will be able to use Tableau to create interactive dashboards sharing sports performance data

1.2 Module Structure

1.2.1 Overview

The module will start with a 2-week block in which we go over the fundamentals and principles for data visualisation. During week 3 we will examine how data visualisation is currently used within sport. Week 4 to 8 will cover a wide variety of different data visualisations and you will gain practical experience in both R and Tableau. We will implement the key principles we learned during week 1 and 2. Lastly, during week 9 and 10 we will look at how we can pull it all together and tell a story which engages the audience. We will look at how to build a storyline and how to include interactivity. Throughout the module you will discover the theoretical background of the topic, and gain extensive experience in using R and Tableau. The module will finish with a recap week.

1.2.2 Weekly syllabus

The module is delivered over 11 weeks. Each week contains two hours of face-to-face contact time and additional self-study tasks. Some of these tasks will require you to work independently, whereas others require you to work as part of a group.

Week One: Introduction to Data visualisation

  • Fundamentals of data visualisation part 1

  • Fundamentals of data visualisation part 2

Week Two: Principles of figure design

  • Principles of figure design

  • Assessment brief

  • Introduction to Tableau

  • Practical 1: Intro to Tableau

Week Three: Data visualisation in Sport

  • Purpose of sports data visualisation

  • Data types and recap data preparation

  • Practical 2: Data cleaning in Tableau Prep

  • Practical 3: Data cleaning in R (recap)

Week Four: Exploratory data analysis and visualisation

  • Exploratory data analysis and its role in data visualization

  • Data summarisation and visualization techniques

  • Practical 4: Exploratory data analysis in Tableau

  • Practical 5: Exploratory data analysis in R

Week Five: Basic plots

  • Recap on different plot types and the importance of visualisation

  • Creating plots in Tableau

  • Practical 6: Creating basic plots in Tableau

  • Practical 7: Creating basic plots in R

Week Six: Assessment hand in & self-study

  • Self-study/ recap

  • Assessment 1 submission

Week Seven: Advanced plots part 1

  • Advanced plots in sports data analytics

  • Practical 8: Advanced plots in Tableau part 1

  • Practical 9: Advanced plots in R part 1

Week Eight: Advanced plots part 2

  • Introduction to interactive data visualization

  • Practical 10: Advanced plots in Tableau part 2

  • Practical 11: Advanced plots in R part 2

Week Nine: Storytelling with Data

  • The art of data storytelling

  • Designing data narratives in R and Tableau

  • Practical 12: creating dashboards in Tableau

Week Ten: Shiny Apps

  • Practical 13: creating dashboards in R

Week Eleven: Assessment

  • Assessment Q&A

  • Assessment prep

1.3 Module Assessment

1.3.1 Assessment one

The first assessment for the module is due during Module Week 6 . This assessment is worth 20% of your overall grade for the module.

For this assessment you will submit a 500-word written critique. You will be given a sport data visualisation and will be asked to outline the strengths and weaknesses of this visualisation. You will use published literature to support your critique.

An assessment briefing will be held during week 2.

1.3.2 Assessment two

The second assessment for the module is due during week 14. This assessment is worth 80% of your overall grade for the module.

For this assessment, you will be asked to create a tableau data visualisation based on a publicly available sport data set. You will work through the 7-steps of data visualisation and use R and Tableau to create your dashboard.

You are expected to show evidence of reading in the academic literature, as well as drawing evidence from the practical case-studies included within the teaching programme.

A briefing for this assessment will be held during Module Week 7.

1.4 Reading List

The most up to date reading list can be found on myplace

1.5 Additional Comments

This module makes use of R and Tableau. It is recommend you install R and R Studio on your personal computer. R and R studio are available from: https://posit.co/download/rstudio-desktop/

To gain access to Tableau on your personal computer please go to Tableau for Students to register, download the program and obtain a free licence.