Jun 29, 2017 :
Amaury Sport Organisation (A.S.O.), organisers of the Tour de France, and Dimension Data, the Official Technology Partner of the Tour de France, today announced the introduction of machine learning technologies into Dimension Data’s data analytics platform to provide fans with an even deeper levels of insight on the race.
The platform incorporates machine learning and complex algorithms that combine live and historical race data to give cycling fans an unprecedented experience of this year’s event. Fans will benefit from rider profiles to understand more about environments and circumstances in which riders perform best, live speed and the location of individual riders, distance between riders, and composition of groups within the race.
As part of a new pilot this year, A.S.O. and Dimension Data are exploring the role of predictive analytics technologies to assess the likelihood of various race scenarios, such as whether the peloton will catch the breakaway riders at certain stages of the race. This year, the solution will create and analyse over 3 billion data points during the 21 stages of the Tour, a significant increase from last year’s 128 million data points.
Amaury Sport Organisation (A.S.O.), organisers of the Tour de France, and Dimension Data, the Official Technology Partner of the Tour de France, today announced the introduction of machine learning technologies into Dimension Data’s data analytics platform to provide fans with an even deeper levels of insight on the race.
The platform incorporates machine learning and complex algorithms that combine live and historical race data to give cycling fans an unprecedented experience of this year’s event. Fans will benefit from rider profiles to understand more about environments and circumstances in which riders perform best, live speed and the location of individual riders, distance between riders, and composition of groups within the race.
As part of a new pilot this year, A.S.O. and Dimension Data are exploring the role of predictive analytics technologies to assess the likelihood of various race scenarios, such as whether the peloton will catch the breakaway riders at certain stages of the race. This year, the solution will create and analyse over 3 billion data points during the 21 stages of the Tour, a significant increase from last year’s 128 million data points.
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