How Formula 1 uses Machine learning to transform their sport – and change the game
This post was published on 13 Aug, 2018

Entertainers and sporting organisations compete for eyeballs and leisure time. Contemporary audiences have more options than ever – and more channels than ever – to select from. In order to maintain and build their fanbase, Formula 1 is using the latest big data and analytics technologies to stay ahead – and win the race.

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Digital platform

Combining on-demand video, websites and social media channels, there is a big push for Formula 1 to retain and expand their audiences. Digital media is the most basic and simple of the technologies they are currently deploying, but this is key to retaining audiences for them. Integrating their digital platforms will keep the fans entertained in relevant, accessible ways. Millennials especially are increasingly choosing to interact with their chosen sporting providers in new ways. 

Historical data – and new capabilities

Formula 1’s new technological deployment begins, ironically, 65 years ago. That is how much historical race data they have available. With that much information at their disposal, it is a relatively simple matter for data scientists to build models. These models are then the framework through which they run the numbers – and with Machine Learning – the models are iterated automatically until statistically likely outcomes are presented. 

This can help teams develop strategy – and even predict the outcomes of races. It becomes possible to optimise pit stops by the rapid selection – using several hundred thousand individual data points – of the perfect time window. 

Engineering simulations

Even the design of new Formula 1 cars can benefit from machine learning capabilities. New car specifications are fine tuned by running fluid dynamics engineering simulations on the designs, ensuring that the vehicles are more aerodynamic than ever before. 

Heading for the cloud 

Formula 1 has selected AWS (Amazon Web Services) to be their cloud provider for all this number crunching. This enables them to rapidly scale all the computations involved – from streamlining their entertainment platforms, to designing new cars, to calibrating strategies, all the way to predicting racing outcomes. 

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