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#DSDW 2: English Women Football

This post was originally published on The Data School blog between 2018 and July 2025, before our program was renamed to MIP’s Analytics Career Accelerator. References throughout this article to “The Data School” or “DS” all refer to what is now MIP’s Analytics Career Accelerator. The program, its people, and its commitment to launching outstanding analytics careers remain the same – just under a new name.

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Introduction

On day 2 of #DSDW, we’re assigned with English Women Football dataset. I have decided to focus on comparing teams’ home and away performance and if there are any relationship between performance and crowd attendance.

Dataset

The dataset contains match metrics like scores, margins, and details like dates, seasons, etc. However, it doesn’t contain venue details. This would have been a great opportunity to pull in extra data to add context, but I soon realised that it’s quite common for teams to play at a non-home ground for a categorically home match. For example, Chelsea FC Women regularly play at their Meadowbank home ground, but they also do at Stamford Bridge for certain high-profile games. It wouldn’t make sense to pull in venue data for the purpose of this dashboard.

Main findings

1. 10% chance of winning a home game across the dataset. This suggests that home ground is advantageous. To a certain extent.

 

 

2. The dataset suggested that in the most recent season, teams enjoy about 37% chance

3. Top 4 teams score the most from their home matches, which suggests their reliance on winning home matches to secure their positions.

 

Conclusion

  • Within the limitations of the dataset, findings suggest that playing at home grounds does offer some advantages to teams.

 

If you would like to further explore the project, head over to my NovyPro page.

 

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