It’s a special race because:
The clock does not stop and there are no prizes. It follows gravel, single and double track and old colonial pistes that have long been forgotten and fallen into disrepair. There is very little tarmac. There is some walking, and at times there is great distances between resupply points.(https://atlasmountainrace.cc/)

After completing a race, it is nice to hear the stories of other riders and see photos to look back at this intense experience from different perspectives. Last couple of weeks, there have been several nice posts, but it seems overwhelming to catch up with all the riders by manually going through these posts.

At C°F, we’re intrigued by experimenting with existing data to create new perspectives. We decided to retrieve the stories of cyclists at AMR by using the raw GPS data in a unique and personalized way.

The race at a glance

Throughout the race, all riders carry a GPS tracker that updates their location every 15 minutes.

Dotwatching on https://amr2020.maprogress.com/

This tracker performs both as security, checking whether the riders are safe, and as validation to make sure that nobody is cheating along the way.

It also helps to highlight small stories during the race. People following the race, also called ‘dotwatchers’, anxiously check these moving dots: https://dotwatcher.cc/race/atlas-mountain-race-2020.

At first glance, the data tells us something very straightforward: A total of 123 riders made it to the finish within 8 days. All at their own distinct pace. This graph shows the road to the finish and highlights the 3 main checkpoints to the finish for all riders.

Graph showing race progress for all riders

These lines already tell the first story how the race went down. How the riders in front took short stops and rarely crossed each other. While further in the pack there is more variety in the way riders progress. Can you spot the person walking large parts between checkpoints 2 and 3?

Ways riders have different rhythms that make them cross and overlap

The longer you look, the more lines you see intertwine and cross each other. Personally, this is something I experienced on the road as well. A kind of social fabric emerges during the race, where you meet a variety of riders all with their own pace. You never feel alone on the road.

Some riders have a similar cycling speed as you do, which makes you occasionally ride together on the route. Others suddenly appear out of nothing at a lunch spot. Then you wonder, where do they come from and how did they arrive at this spot all of a sudden?

Rhythm of day and night

As it is a race, everybody is triggered to cover as much distance as possible during a day. There are a variety of strategies how to achieve that.

The very definition of how long a day is differs tremendously for each rider. Some make optimal use of daytime by covering as many kilometers as possible and regaining energy, while sleeping through the night. Others ride steadily through the night at a more moderate pace.

We captured these day/night patterns by generating a representative emblem highlighting the unique characteristics of each rider’s journey.

First sketches and a first embroidery test

For the design it is apparent that we got inspired by the stunning geometric patterns that you find everywhere in Morocco.

• Circles in the background of the emblem visualize the number of days it took from start to finish. The more circles mean the more days on the road.
• Bars show show the distance traveled: white bars for daytime, black for nighttime. Revealing when progress was made.
• Dots in the outer ring show the 100 kilometer markers, in small dots, and the three main checkpoints, in large dots. This gives a rough indication how time was spend along the route.

Design of the data generated emblem

Altogether, they tell a story of all unique journeys. Some observations when looking at these emblems:

• The longer the ride is, the more apparent the day and rhythm becomes.
• Some patterns look remarkably steady and repetitive. Others suddenly show a gap; do they ride more impulsive or did something happen?

The last push to the finish is apparent: most hours on the bike were captured during the last two days.

Autogenerated patches based on each rider’s GPS data

Data-driven embroidery

Next, we would love to return these data emblems to their rightful owners. Our idea is to automatically generate an embroidery file for these emblems so they can be produced uniquely for each rider.

Bikes from the Atlas Mountain Race, with an example of the data generated patch: https://bikepacking.com/bikes/2020-atlas-mountain-race-rigs/

This is similar to the patches that riders get for other cycling events, yet so much more personal. A great way to celebrate those unique journeys: the long days and nights on the saddle, the rough gravel roads that many of the riders can still feel in their legs and replay in their heads. Wouldn’t that make the bikes that create these memories much more distinctive?

Visit our C°F Experiments page to read more about this experiment and many more that explore creative ways to work with data.