High stakes, high stress: how we transform Tour de France data into real-time insights

This June, it’s not just images of the world’s toughest cyclists in action that will be beamed all over the world once the Tour de France hits the road – first in Italy, then in France. At the same time, streams of real-time data from myriad sensors will be turned into useful insights for the race organizers, competitors and fans alike.  

The Tour is a data goldmine, with countless variables influencing race outcomes. While the world’s eyes are on the racers, a complex, interlinked system of sensors, networks, edge computing, cloud, real-time analytics and machine learning will operate in the background to deliver statistics and insights to fans, broadcasters, support crews, the organizers and the Race Center team.

It all comes together in Johannesburg, South Africa, where our Tour de France data hub serves as the central command center, staffed by a mix of technical and cycling specialists. The hub’s success lies in its ability to process and disseminate data efficiently, giving teams, commentators and viewers access to the insights they need, when they need them.

Pushing the boundaries of sports technology as NTT DATA

Since April 1, Dimension Data has been known as NTT DATA in the Middle East and Africa. The rebranding reinforces our commitment to pushing the boundaries of what technology can achieve in sports. With NTT DATA’s global reach and local expertise, we’re advancing digital transformation at big events around the world, including the Tour de France, INDYCAR and the Absa Cape Epic cycle race in South Africa.

For the past decade, we have proudly served as the Official Technology Partner of Amaury Sport Organisation (A.S.O.), the organizer of the Tour de France. We introduced the world’s first real-time rider-tracking system in 2015, a landmark innovation that set the stage for subsequent advancements.

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Over the years, the partnership has led to the development and implementation of sophisticated technologies such as a digital twin that has transformed the Tour into the world’s largest connected stadium and set new standards in how sporting events are managed.

Bringing bicycles, people and data together with a digital twin

Our data hub receives raw GPS tracker data from the Tour de France itself, where coordinates and speed readings are collected from the bikes and race support vehicles (including cars, motorbikes and helicopters), among other sources along the route.

Next follows complex AI modeling, which is a core part of our data innovation. Our models predict race outcomes, taking into account factors such as rider performance, the weather conditions and the terrain. Developing and maintaining the models requires a deep understanding of the sport and advanced machine-learning techniques.

The result? A constant stream of high-quality, data-driven insights that make the viewer experience more engaging while supporting team strategies in a sport where every second counts.

We also use the data we collected to create the digital twin of the Tour de France. This virtual replica of the race allows us to simulate and analyze different scenarios. The technology has been instrumental in improving the race organizers’ decision-making and planning, keeping the Tour at the forefront of sports technology.

• ALSO READ → Tour de France: how data-driven innovation fuels a powerful partnership

Play the video to see our Tour de France data flow in action

Data flow and management in the cloud

From the Johannesburg-based data hub, our Middle East and Africa team monitors all the raw data and the platforms and systems that transform it into usable data.

A service delivery manager coordinates the hub operations and handles communications with key stakeholders who connect to the data hub via Webex from various parts of the world – including Europe, the UK, Australia and our NTT DATA Tech Truck in France.

While the data stays in the cloud, some data management is done manually and sent from the hub to our processing platform in the Microsoft Azure cloud. For example, we need to flag to the processing system that a rider has swapped bikes – perhaps after a crash – so our data does not suddenly show the rider speeding off in the wrong direction because their damaged bike is now in a support vehicle.

Making data usable to enhance the race experience

The raw data is “messy” because there are many remote, mountainous areas and tunnels along the 3,492km route of the Tour de France where signals from the bikes are lost altogether – sometimes for minutes at a time. These signals may also be duplicated or inaccurate in terms of speed and position due to the limitations of GPS.

Our real-time analytics platform has been developed from scratch by our team using open-source frameworks including Apache NiFi, Apache Beam and tens of thousands of lines of Python code. It cleans, interpolates and transforms the data into useful, human-readable data fields such as “Distance from the Start”, “Gap to Previous Rider”, “Group Membership”, “Current Braking Force” and “Relative Wind Speed and Direction”.

But, of course, knowing where a cyclist is in the peloton at any given time is only half the fun. We also want to predict stage and race winners, or the probability of a successful breakaway, for example. And which fan would not want to compare rider and team strengths and strategies as the race progresses?

To do this, we have combined mathematical modeling with the knowledge of a sports scientist to develop our own prediction models, which are generated in near real time using cloud-based virtual machines on Microsoft Azure. We then deliver the processed data to the racing teams, organizers and fans.

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Solving the messiest data challenge you can imagine

The Tour de France is very different from everything else we do in terms of the pressures, the stress and the timelines. Our solution tackles complicated data science problems, and everything we do must support the planning and smooth operation of the race.

The event is more important than just the data, but the data we create is central to running and broadcasting the event.

Broadcasters use it in production (such as setting up the most compelling shots) and to enrich their commentary with accurate, real-time numbers. The data also feeds into the publicly accessible Race Center website, which can display the near-real-time position of racers, their speed and the gaps between them.

Our LeTourData team uses the data to send out regular updates for social media and the Race Center, enriched with in-depth analysis and information as each stage unfolds. In addition, the system transmits data to the team vehicles monitoring the position and support needs of their riders during the race.

Because everything’s live and happening in real time, the pressure rises lightning-fast when things go wrong. If we fall more than one second behind, it creates a bottleneck. Things that break need to be fixed quickly – and things do break, because this grueling race winds through remote mountains that interfere with connectivity. In the time it takes us to fix something, fans watching the race may be missing out on important race data.

The Tour de France is a prime example of how data and analytics can revolutionize an industry. Our innovations are not just about enhancing a sporting event; they set new standard for how we interact with and understand sports. As we look to the future, it’s clear that the intersection of sports and technology will continue to be an exciting space for innovation, with data and analytics leading the charge.