Rio 2016 EYC3 Virtual Race

Congratulations

Congratulations to the winners of the Rio 2016 EYC3 Virtual Race! Using your Strava data from the last 12 months (until EOFY16), the EYC3 data scientists simulated your performance on the 2016 Rio Olympics road race to predict the gold, silver and bronze podium winners. Through a new interactive app, members watched themselves and their peers push through climbs and sprint across the flats in real time towards the finish line.

Want your chance to wear a Champions jersey too? Sign up for the Norway 2017 ICE World Champions below.

Rio 2016 Course Flyover

The sprint to the finish!

Watch the virtual race streaming in real-time on your mobile or desktop

Guide:

  • Follow the leaderboard along the course and search for yourself (or your rivals) by name or Strava ID.
  • X marks the spot – if you search for yourself or your rivals, you can pinpoint their position in the profile view at the bottom.
  • Control what you want to see across the course in Manual camera view or follow the riders in the Automatic view.
  • As you move along the circuit, every rider’s performance information will change depending on where you are in the race and the output (for example, if you are on a particularly steep climb).
  • Speed is recorded down to the second – where 1 second equates to 10.4 seconds in the actual race.

Rio 2016 Podium Winners

Make sure to congratulate (and challenge!) the winners when you see them out on the road in their gold, silver and bronze ICE kits.

How did you stack up in Rio 2016?

Compare results by industry, role and country.

Like the change in Australia’s 2-speed economy, Retail Trade fell from first place in 2015 to 11th in 2016. Why are ICE members’ riding performance so accurately reflecting Australia’s economic performance? Some analysis may be required!

Consistently holding their (bottom of the pack) rank is Procurement, alas procurement seem perpetually slow! Interestingly, we see a big performance drop from Innovation (as the leading business function) as they swap leader ranking with Marketing and Communications.

Leading the pack with an average total race time of just over 7 hours is the UAE, followed closely by USA in around 8 hours. Rounding out the top three is Singapore trailing only 6 minutes behind USA.

A truly international result, the UK, Australia, Hong Kong and Luxembourg round out the top 7 competing countries.

While ICE has its legacy in Australia, we need to lift our overall performance to stay globally competitive!

Insights during your year in training

How did you stack up against your competitors? Check out the Top 10 by number of rides, kms and elevation, and how Australia faired versus the world!

*Data date range: January 2016 to mid-March 2016

  • The highest number of rides by a single cyclist is 158, more than 3 times higher than the average number of rides at 50
  • The most common number of rides was between 30 and 40
  • New South Wales (AU) cyclists made up 6 out of the Top 10 Cyclists by number of rides
  • Victorian cyclists (AU) were the highest represented state/country on the Top 10 leader board
  • The average number of kilometres a cyclist rode in total is approximately 2200 km
  • An anonymous rider from New South Wales (AU) has the highest number of kilometres on record at 7931 km, this is over 2000 km more than second place
  • Once again Victoria topped the leader board with 6 cyclists being in the Top 10 for elevation gain
  • Less than half of cyclists had over 20km of elevation gain
  • On average cyclists climbed approximately 1 km for every 120 km travelled
  • The country with the highest amount of time spent cycling per cyclist is Hong Kong
  • The UK and USA had the lowest amount cycle time on average per cyclist
  • This scatter plot represents the number of rides against the average length of each ride for all cyclists
  • Ed Tollinton only rode one time but travelled over 200 km on that trip
  • Simon Osborne on the other hand had 110 rides but were only 4.9 km on average in length
  • Queensland cyclists on average rode the furthest (2827 km) and had the highest elevation gain (31.8 km)
  • From this is it expected that Queenslanders rode more in mountainous areas
  • South Australian cyclists had the lowest amount of elevation at 20.7 km
  • This means South Australians spend most of their time riding on flat ground
  • Tasmanian cyclists had the lowest amount of distance travelled on average at 1795 km
  • Victoria has the highest average number of rides per cyclist at 55, 3 more then Queensland in second place
  • Australian Capital Territory cyclists on average burn the highest number of calories at 1261 calories per ride
  • South Australian cyclists conversely burned only 1014 calories per ride on average
  • Since Queenslander cyclists had a large number of rides on average as well as a high number of calories burned per ride they burned more calories in total per cyclist (60,862 calories) than any other state
  • Conversely Tasmanians had the least number of rides per cyclists and less calorie intensive rides so per cyclist they only burnt 45,997 calories, the least of all states

SIGN UP FOR NORWAY 2017

The Norway 2017 ICE World Championships is set to be another spectacular international race as you cycle through Bergen in western-Norway. To compete, simply complete the ICE survey. If you’ve already completed the survey, you’re automatically registered for this race.

Six Champion jerseys have now been awarded (2015 TdF yellow, green and polka dot and Rio 2016 gold, silver and bronze). Don’t miss out on your chance to wear the coveted 2017 World Championship Rainbow Jersey!

Channel your inner Eddy Merckx – beat your personal best, dominate the competition and you’ll be regarded as one of the greatest ICE cyclists of all time!

Your Strava data from July 2016 to June 2017 will drive your Norway World Championship opportunity so “ride as much or as little, as long or as short as your feel. But ride” – Eddy Merckx.

CHECK OUT THE 2015 VIRTUAL ROAD RACE

Following the same route as the 2015 Tour de France Stage 20, EYC3 used predictive machine learning analytics across ICE member Strava data – more than 1 billion data points – and constructed a virtual race to predict the yellow, green and polka dot jersey winners, and prescribed interventions to change the outcome. Watch how they did it.

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