Ideas & Debate

How Formula 1, Tour de France ride on big data

There is vast deployment of internet of things, data analytics and machine learning technologies. FILE PHOTO | NMG
There is vast deployment of internet of things, data analytics and machine learning technologies. FILE PHOTO | NMG 

Chris Froome won the gruelling 2017 Tour De France finishing 54 Secs ahead of Colombian Rigoberto Uran.

For cycling enthusiasts, this year’s race was not any normal race by previous standards. As recently as 2014, the only way to find out real-time information during the Tour de France was from a chalkboard, held up by a race executive sitting as a passenger on a motorbike driving ahead of the cyclists.

The world’s greatest cycle race is transforming its relationship with fans thanks to Dimensions Data, a technology firm behind automation of the Tour de France through vast deployment of internet of things, data analytics and machine learning technologies.

Further afield, for fans accustomed to enhancing their enjoyment and understanding from a deluge of data when watching football, cricket, tennis and other high-profile sports, the world’s greatest cycle race was something of a challenge to watch.

Formula One for instance takes the lead in embracing data driven race strategy. The recent Formula One race held in Britain cost Sebastian Vettel a podium and race finish as a result of the Ferrari engineering team going against telemetry data from sensors mounted on the tyres that warned of the deplorable tyre state.

Perhaps the paddock was motivated by a possible podium finish and threw caution to the wind to their detriment as Vettel wobbled off on the penultimate lap.

For years, Formula One teams have invested immensely in data strategy right from production of the cars, car testing in Jerez Spain to race days. It’s a perfect example of how data is used to drive decisioning and gain competitive edge.

The information on data is protected jealously with rival teams going to the extent of investing in long range cameras to aide in espionage of data dashboards from competing teams.

Leading technology companies like Intel, SAP and Oracle have for long provided data tools ranging form cloud storage, sensor chips and algorithms for predictions of various elements including tyre degradation, weather, and the entire gamut of the cars efficiency. It has been very enviable sport to say the least.

Following Tour De France on television revealed a departure from the past. There was a difference as TV viewers could not only see the timings, watch numerous camera angles, but the subtleties and tactics of elite professional road racing, which were a mystery to all but serious cycling enthusiasts.

Fans have access to more data than ever before, explaining and analysing the performance of Britain’s Chris Froome or Mark Cavendish in intense detail across three weeks of racing.

But unlike Formula One events, which are typically held in a single venue, “Le Tour” presents a unique set of challenges for the technology that now relays data from bike to TV viewer in two seconds. According to Pascal Queirel, CIO, Amaury Sports Organisation, the organiser of the Tour de France, “we need to deploy strong and robust technology – yesterday we were in the mountains, today we are in another town. Other sports are making more use of data and we need to do the same.”

Each of the 198 riders that started the race has a bespoke sensor attached to a clip below the saddle of their bike. The sensor, which weighs just 100g for a weight-obsessed sport, contains a global positioning system (GPS) chip, a radio frequency (RF) chip, and a rechargeable battery with enough power to last the longest of the Tour’s 21 stages.

As a result, race organisers, teams, broadcasters, commentators, TV viewers and fans using the Tour de France mobile app, had access to in-depth statistics on progress of the race and their favourite riders.

The riders wear earpiece radios so their teams can relay real-time data to them while they cycle – no need to keep an eye on that chalkboard anymore. As a result, data feeds from the bikes use the white space in television signals to transmit back to the Dimension Data technology team.

GPS data is transmitted using a mesh network via antenna on race cars following the cyclists, up to a swarm of TV helicopters overhead. From there, signals are relayed to an aircraft further above, and then sent to the TV trucks at the race finish.

There, the data is split back out from the TV feed and picked up by Dimension Data’s “big data truck”, which follows the race around the French countryside every day, waiting at each stage finish.

The data is collected in Dimension Data’s cloud service, based in data centres in London and Amsterdam, where data analytics algorithms combine with external feeds to produce the real-time information sent out to broadcasters, social media and the race app.

The whole process from bike to viewer takes just two seconds. The tech setup would not have been possible without the emergence of the cloud, given the remote nature of much of the race and the fact it changes location each day.

This year, Dimension Data introduced machine learning capabilities for the first time, says the supplier’s Tour de France technology leader, Peter Gray.

Using algorithms devised by a team of cycling experts, data scientists and sports analysts, the system makes predictions before and during the race, based on current and historic data on riders and the state of the race.