An Australian data and analytics company is using AI and advanced analytics to predict the outcome of the main two races of the UCI World Championships currently being held in Wollongong.
“Machine Learning is a form of Artificial Intelligence which uses advanced data analytics solve complex issues,” said Decision Inc. Australia CEO, Aiden Heke. “It uses algorithms to best imitate how humans solve problems or predict outcomes. People see forms of Machine Learning whenever they open your Google news feed on their phone, for example, and the news stream is populated with stories that pique their interest.”
Heke said since the technology has evolved so much over the past few decades, “why not use it to predict the outcome of the UCI World Championships?”
Decision Inc. Australia’s expert team of data analysts and cycling enthusiasts developed the modelling which was then integrated into an advanced Machine Learning tool from real-time data integration. The subsequent analysis of the data through the AutoML tool has revealed the following outcomes of the Elite Road Races.
Women Elite Road Race – Saturday 24 September | Men Elite Road Race – Sunday 25 September |
VOS Marianne | VAN AERT Wout |
VAN VLEUTEN Anne | MATTHEWS Michael |
VOLLERING Demi | VAN DER POEL Mathieu |
LONGO BORGHINI Elisa | ALMEIDA João |
BALSAMO Elisa | POGACAR Tadej |
LUFDWIG Cecile Uttrup | KÜNG Stefan |
KOPECKY Lotte | ALAPHILIPPE Julian |
NIEWIADOMA Katarzyna | STUYVEN Jasper |
LABOUS Juliette | LAPORTE Christophe |
SPRATT Amanda | EVENEPOEL Remco |
The consultancy is so confident of the results that it is putting a call out to the public to pick the top three placegetters in the men’s and women’s elite events; the three contestants in each race who can most accurately predict the top three placegetters will take home signed cycling packs from Australian Olympic cycling legends Sara Carrigan or Grace Brown (in the event of a tiebreak, contestants who enter first will take the prize).
“We’re encouraging everyone, from cycling enthusiasts to the general public, to enter the competition and test themselves against the Machine, in something we compare to a modern-day version of Computer vs Kasparov,” said Heke.
In 1996, a very early version of Machine Learning from IBM, called Deep Blue, beat world chess champion Garry Kasporov in a six-game chess series. At one point, it was estimated Deep Blue was analysing more than 100 million chess positions a second.
“It’s crazy to think that this kind of analytics power was available in 1997 and it’s advanced exponentially since then,” said Heke. “It’s why we’re putting it to the test, to see just how far it’s come. And we’re keen for everyone who fancies themselves as a bit of an expert on Cycling to see if they can win where Kasparov couldn’t: against the Machine.”
The competition is free to enter, and a link to the voting page can be found on Decision Inc. Australia’s Instagram page@decision_Inc_Australia, where predictions will be declared and progress tracked all the way up to, and including through, the championships.