Hey everyone, welcome to my Dashboard Week journey 2.0.

Today’s task was to create a cool dashboard about any sport we like.  After the journey 1.0 experience, I’ve learned the importance of time management and not to spend too much time on one thing.  I made a quick decision on choosing the topic – tennis, which I consider to have sufficient data as well as being something I like.


First things first, I needed data. A good dataset would make the next steps a lot easier. The dataset I had only went up to 2018, so I had to hunt down some more recent stuff. After some digging, I hit up Kaggle and got some extra data to spice up my project.

But here’s where it got tricky. The dataset I got was all about match records, and that’s not great for player-level analysis. So, I had to roll up my sleeves and pivot the data around ‘player1’ and ‘player2’. I also had to reformat other columns like ‘rank1’ and ‘rank2’ to make sure everything was player-specific. It was a bit of a data wrangling marathon, but I knew it was essential.


To tackle this data transformation, I turned to Alteryx, a nifty data transformation tool. Alteryx helped me whip my data into shape and create a workflow that made sense for my project. It was a lifesaver.

With my data sorted, I was stoked to start building the dashboard. My initial idea was to create a network chart with all tennis players and their opponents. This soon turned out to be a not so great path as I struggled with the data formatting. I tried to use Ladataviz, but it just wouldn’t cooperate.  I had to change gears and focus on a selected group of tennis legends to narrow down the work. With that in mind, I picked Roger Federer, Rafal Nadal, Novak Djokovic, and Andy Murray, my all time favourite players.


I decided to use their images as filters, allowing me to drill down into their performance data. This pivot helped me analyse their gameplay at a player-specific level and maybe even find the next tennis GOAT. Plus, I set up some parameters to dissect their performance on different surfaces, in various tournaments, and across different rounds. This is how my final dashboard looks like:

Link: Who will be the GOAT?


To sum it up, Dashboard Week was a wild ride. From battling data transformations in Alteryx to adjusting my dashboard plans on the fly, I learned that you’ve got to be flexible and creative when working with data. Despite the hiccups, I managed to create a tennis dashboard that gave me some cool insights into the performance of tennis legends.


Whether you’re a tennis nut or just into data visualisation, I hope you enjoyed hearing about my Dashboard Week adventure. Stay tuned for more data-driven stories and insights down the road!




The Data School
Author: The Data School