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This page will take you through the journey behind the Formula 1 project. It was the first big piece of work I've undertaken and I thought it was fitting to base it on Formula 1, a sport that I follow closely and have worked with in the past. My undergraduate dissertation modelled the relationship between driver and car and was eventually published in the Journal of Quantitative Analysis in Sport, read here.

Each component of the final viz deals with different aspects of the history & components that make Formula  1 one of the world’s most followed sports!


To rank the drivers I created a starting grid in Illustrator and sorted the top 10 drivers by total points won. I tried several different approaches here, such as using number of points on the Y-Axis, but unfortunately Schumacher was so far ahead of everyone that the other drivers would have appeared too crowded at the bottom!

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Nationality is a hugely important part of F1 – its global fan base are attracted to watching Drivers & Constructors from their home nation – Dutch fans using clogs to clap their favourite Max Verstappen springs to mind! I used flags to represent the patriotic relationship between a Driver and their home nation, but also to quickly show the pattern of winners across time - the dominance of UK, Germany & Italy flags becomes instantly obvious.


The Sankey Diagram was the most important piece of the viz and I wanted the colours to really grab the attention. The link between the driver and the car produces the competition that compels the sport’s fans so it had to be done well (think Schumacher’s Ferrari, Senna’s McLaren, Vettel’s Red Bull). I created this in Tableau using an online tutorial I watched on youtube and then added a filter to show just those scoring over 300 points in their career (the original Sankey was completely unreadable and looked like a piece of expressionist art, see above). I then coloured the constructors by their most recently used team colours to make it as eye catching as possible – the liveries that F1 teams are designed to do this so my job was half done!

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I spent ages tweaking this graph to try and achieve some kind of balance between being able to interpret it and allowing it to visually represent a wheel (although when I showed friends most said it reminded them of a track so I failed in that respect!)

The inspiration came from Adam McCann’s Game of Thrones viz on Tableau Public, I followed his tutorial and tweaked several of the parameters to produce what I called a ‘wheel graph’. When I showed people the majority of the early iterations they said it looked nice but had no idea what it was trying to say.

I added a number of extra items in Illustrator to try and compensate for this, such as the 10 year intervals on the inner circle and two keys to demonstrate the meaning of the shapes and colours. I’m still not certain that it was the best way of showing the data but I spent so long on fine tuning it that it had to go in, I’d be interested to hear any comments on it, good or bad!


Tableau makes mapping incredibly easy! I wanted to be able to show the dominance of Europe in the F1 calendar and add callouts with some interesting facts. The colour scheme, as throughout, was chosen to represent the F1 logo (black and red) with the background mirroring the grey of the track.

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The Tyres section was a tricky one – they are hugely important in F1 and tyre strategy can often define a race but since 2011 there has been no competition between manufacturers as all cars have to use the same brand – Pirelli. I decided to try and show the importance of both by looking at the history of different manufacturers and also the current setup which allows the driver a choice of 5 ‘slick’ or ‘dry’ compound tyres and 2 alternatives for varying degrees of rain.


I had some fun with this one in Illustrator – I took a couple of icons and traced them before removing the inside of the engine and replacing it with a bubble chart sized by the number of wins and using a few curved lines to maintain the engine-feel of the diagram. I did a similar thing with the pistons on the left hand side to show the link between today’s engine manufacturers and their teams.

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A big thank you to the Ergast Developer API through which I was able to scrape all of the data I needed for the viz. I wrote a script in R to automate the process and performed some initial data cleansing and restructuring using the jsonlite package and several loops to export a data frame into a csv format, ready for Tableau to digest. I performed some further cleansing in Tableau to generate the ‘normalised points’ scoring system and get the data in the right format for some of the graphs. The normalised points system was required to provide a fairer approach to different era’s in which the number of points given for a race win has varied significantly over time. It was only partly successful in this, however, as the F1 calendar has also developed over time meaning modern drivers have the opportunity to score points in far more races than their predecessors. This will ultimately skew the points ranking to the modern era of Formula 1, though it was the best way of normalising the points system in my mind without over complicating it. I was not the first to try and compare drivers from different era’s and I certainly won’t be the last!

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