Creating Impactful Data Visualisation for Football
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In today’s issue of football progression path I’m going to teach you how to create effective data visualisations in football.
Data visualisation is a powerful tool that translates intricate football data into visual formats.
It helps to reveal patterns and facilitating understanding. It's also crucial for every area of football, from recruitment to performance analysis. By turning numbers into insights, you can communicate effectively with decision-makers at clubs, complementing written and verbal communication.
Most roles in football use data visualisation in some format. So it’s vital we develop skills beyond using the basic tools in excel.
The common mistake is that we over complicate data visualisation with too much colour, too much detail and not enough context.
Data visualisation is just communication. It should be specific, purposeful and impactful. Just like other forms of communication.
Let’s run through
- How to create buy-in
- Tools and techniques
- Accessibility and colour
- Common pitfalls
Creating Impactful Visuals
To create effective data visualisations, simplicity is key. Avoid overcomplicating visuals or designing them merely for aesthetics. Use charts, tables, bar charts, or scatter plots to clearly convey insights. Strategic use of annotation, colour, and layout can highlight key points and facilitate interpretation.
Building Buy-In
Engage your audience with self-service applications using tools like Streamlit or Shiny.
Balance attractiveness with effective communication, tailoring visuals to the knowledge and understanding of your audience, whether they are coaches, scouts, or heads of recruitment.
Tools and Techniques
Starting out? Tableau Public is a good option to get going. Other beginner-friendly tools include Flourish and DataWrapper, which allow you to upload data and create visuals immediately.
Practice using different chart types to enhance your ability to analyze datasets and choose the most effective chart type.
Advanced Tools
For those looking to create web app tools, learning Python or R can be beneficial. Python's MPLSoccer package and R's WorldFootballR package are excellent for creating football-focused visuals.
Accessibility and Colour Use
Consider accessibility when creating visuals. Use a colour blindness checker to ensure your visuals are accessible to everyone.
Also use colour strategically to draw attention to specific parts of a visual. Here are five ways to use colour effectively:
- Categorical: Different colours for different categories.
- Sequential: Ordered colours from low to high.
- Diverging: Colours diverging from a midpoint.
- Highlight: Colours to draw attention to specific elements.
- Alert: Bold contrasting colours to warn or highlight.
Avoiding Common Pitfalls
Avoid creating visuals just for the sake of it. Consider if a complex visual is necessary or if a simple table or bar chart suffices. Customise built-in tools to suit your specific purposes, and ensure annotations and context are clear and concise.
Simplifying Visuals
Overcomplicating visuals with excessive detail can overwhelm your audience. Simplify by removing nonessential elements and using grey colours to mute the other data points into the background.
Tailoring to Your Audience
Understand your audience's needs and knowledge level.
Tailor visuals to meet their needs, whether presenting to players, analysts, or heads of recruitment. Customise your approach rather than relying on a one-size-fits-all design.
Data visualisation is a crucial skill for any football analyst or scout.
By mastering it, you can enhance your understanding, grow your network, and increase your opportunities in football. Start by exploring the tools and techniques mentioned here, and take the first step towards creating thoughtful data visuals in football.
Remember, the best analysts are like magpies, collecting and sharing knowledge to create a brighter future for themselves and their teams.
Have a great week an go well.
Liam
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