Motorsport is an adrenalin filled sport for drivers, teams, and fans alike. It is like no other sport on the globe, where money is spent at an alarming rate to gain superiority over the competition. In 2017, the estimated global spend in motorsport was US$5.75 billion. Just a single Formula One team can spend over US$400m every year, in order to develop and race two cars at 21 race tracks around the world.
Motorsport is a $5.75b entertainment industry.
Motorsport is an extremely technical sport, where success is measured in milliseconds at both a grassroots and professional level. As such, teams are going to great lengths to find a competitive advantage over their rivals.
Motorsport is an industry I have grown up around my whole life. By working across various Australasian teams as a data and race engineer, I have gained some valuable insight into the way data is used both in the moment to find that competitive edge. It has always interested me how many teams underutilised the data they collected, and act on impulse, rather than making data driven decisions.
The Motorsport Data Lifecycle
We live in an age where data is integral to our everyday lives, and motorsport is no different. Data in motorsport is often thought of as the ‘squiggly lines’ that Engineers are seen pouring over on TV. However there is a lot more to the motorsport data lifecycle than this. Teams will collate weather conditions prior to each session on track, and capture any changes in set up made to the car. Tyre pressures will be set based on current weather conditions, and the driver briefed on what is expected from them during the upcoming session. The Engineer must inform the mechanics of any required set up changes for the car. This can be passed on verbally, written in books, on notepads, or even a text message!
Data is often linked to the “squiggly lines” engineers use to understand car performance
After the session, the driver will give their feedback to their Engineer, generally a mixture of written notes and verbal communication. The Engineer will then ingest the car, driver, tyre, and weather data, to make a decision on strategy and car set up for the next session. This is all data, and can be broken up into five main areas:
- Embedded sensor data
- Weather information
- Driver feedback
- Car setup parameters
- Tyre information
This same process is repeated throughout a race weekend. Those who do it well win races, and those who don’t are left scratching their heads.
Throughout this process, it is important to leverage data not only from the current event, but also all past events at that same location. But more on that later.
So What?
A typical scenario at a professional level is; car telemetry data is stored on a laptop, tyre usage and car set ups are stored in two different excel spreadsheets, and driver notes are written on a piece of paper, and stored in a folder. The difficulty that most team members face is all the information they require for decision making is spread across multiple sources, with a complex relationship between data points.
Engineers must ingest this data from spreadsheets, bespoke software, books and emails. By adding in a high intensity, time pressured environment, this inevitably leads to mistakes being made. More concerning to teams is the lack of use of any historical data. Digging up two year old spreadsheets to find what has worked in the past is inefficient – and that’s only if you can remember the exact event to search for. Any data recorded on paper from previous seasons will typically be left on a bookshelf back at the office.
Under-utilised historical data leads to two scenarios. The first is sub optimal car and driver performance, and the second is repeated testing, usually in this order. Sound familiar?
The hidden truth
The question is, how can we best utilise the data captured at the race track. As series rulebooks grow thicker, we have an increasing reliance on data to find the marginal gains that separate the best from the rest. It is critical we ensure an increase in the data captured actually leads to better performance. In some cases it can decrease performance, as there is too much data to consume, and the crucial gems of useful information are hidden amongst the noise.
There is so much information presented to an Engineer, that for any given decision it is impossible to understand the full implications. This inevitably leads to a lot of guess work.
What is the solution?
This is where the idea for pitbox.io was born from! pitbox.io is a cloud-based, single platform service to capture, store and analyse the science behind motor racing. This is truly modern technology, to compliment a high-tech sport. We want to empower Drivers, Engineers, and Team Owners to use their time effectively; less data analysis and more problem solving! By doing all of the analysis work pitbox.io allows for just this.
pitbox.io is built with the simple aim to increase efficiency, to ultimately increase performance and reduce costs. The key factor is that all of the aforementioned data points will be cloud stored, accessible anywhere, anytime by the relevant team members. Using artificial intelligence, it guides engineers through recommended setups. Algorithms are able to ingest data since the first logged event in the matter of seconds, looking for patterns and similarities to the present event to dictate set up direction.
It also enhances intra-team communication, so no more need for post-it notes! Once Engineers decide on a set up change, this is pushed to a Mechanic with a push notification. Drivers are now able to communicate directly with their coaches, who may be in a different city, or even country. This will include debrief notes, and any insight from the engineer or team manager. On the subject of team managers, they are able to overlook proceedings away from the track, if there are multiple events on the same weekend.
It is time for the motorsport industry to step up and better utilise the data they capture, to help improve their own competitive advantage over rivals. By spending a fraction of what a single test day costs, motorsport teams can have a more consistent and analytical approach to optimising a race car at each event.
Data driven motorsport is the future.