Welcome to the second installment of DSAU27’s Dashboard Week. Today we looked into the English Women’s Football Database hoping to find insights worthy of a slow-motion replay. The dataset covers game statistics on all matches from the Women’s Super League since the 2011 season as well as all games from the Women’s Championship League since 2014. Also, for today, we’re tackling this challenge in Power BI.
Initial Approach
To start with, I had no idea what I wanted to focus on. Whilst the dataset isn’t extensive, I didn’t want to simply overview basic statistics from the league. After some thinking, I decided to look into the teams who were promoted and relegated between seasons. I thought there may be some unexpected insights regarding those teams’ performances. Unfortunately, I spent too long on this idea, finding that the data was what many would expect – teams with amazing seasons were generally promoted and teams with bad seasons were generally relegated.
With this issue in focus, I pivoted slightly away from the performance of relegated and promoted teams. Instead, I wanted to track and better understand teams that switched divisions frequently. Perhaps some teams are overpowering the competition in one league, but struggling with the more elite competition.
Insights
Switching to the timeline approach massively helped develop not only one data story, but a story for each team! With the assistance of a custom-built timeline, my dashboard shows division changes over all seasons for the filtered team. I have left Bristol City Women as the default, as this team has the most interesting timeline, switching divisions 5 times since 2011. To ensure the end user can interpret the timeline, I also added supplementary text focusing on Bristol, as well as a tooltip for each season.
Future Steps
To supplement the timeline, I am planning to add a drill through for the timeline points. This way users can investigate seasons of interest for specific teams, getting information on each game played.
Thanks for reading. Feel free to check out my dashboard and if you’re keen to explore the data yourself, here is the database link. If you want to know how Day 1 of Dashboard Week went, click here.
