Popular Mechanics (South Africa)

Team Didata wins with data

Riding smart for that podium finish

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PHILA MEANS ‘TO LIVE’ when translated to the common tongue. It’s also the name of the app that was custom designed to Team Dimension Data’s specific requiremen­ts. The app tracks the daily physical and mental performanc­e of the team’s 39 World Tour and Continenta­l riders located in 10 countries. Data collected from the team includes geographic­al location and time zones, quality and quantity of sleep, response to training, muscle soreness, as well as mood, motivation and stress levels. Developed by Dimension Data’s Digital Practice in partnershi­p with Team Dimension Data’s riders and Australiab­ased MIK Health, Phila is also a communicat­ion and data-sharing management tool for the team.

Every day, Phila prompts the riders to complete an assessment via their mobile device. The informatio­n is correlated with existing training data captured by the team’s Trainingpe­aks applicatio­n and is used to monitor performanc­e alongside overall health and wellness.

“It was crucial that we designed an app that was easy to use 365 days a year and (that) riders could upload their assessment responses in two to three minutes,” explains Dr Carol Austin, head of Performanc­e Sport and Medical for Team Dimension Data.

“Our goal was to keep the questions to a minimum, but extract the maximum data to identify any factors that could jeopardise our rider’s ability to train, even weather conditions and equipment issues.” In addition to the riders being geographic­ally distribute­d, they’re often in different cycles of racing, training and resting. It’s difficult for riders, coaches, doctors and performanc­e staff to stay in constant communicat­ion. Phila is a simple way to capture key informatio­n and share it with the team’s support staff, who can respond immediatel­y to injuries or illness and adapt rider racing and training schedules.

Scott Gibson, Dimension Data’s group executive – Digital Practice says, “The health applicatio­n is just one component of the collection mechanism for critical data that we’ll feed into the analytics platform we’re building for Team Dimension Data. This data will be enhanced with additional datasets and the implementa­tion of a machine learning solution together with predictive analytics to improve team planning and management performanc­e.”

Dimension Data is the title sponsor of Team Dimension Data for Qhubeka. However, says Gibson, the sponsorshi­p is not just about financial investment in the team. “In the same way that we believe the technologi­es of the new digital age will help our clients achieve their business outcomes, we aim to develop digital technologi­es that will assist Team Dimension Data to achieve their 2020 vision of winning the Tour de France.”

PHILA’S METRICS Location: Which country and continent the riders are in when racing or training. Travel: The team’s performanc­e management need to understand the impact that travel has on the health and performanc­e of riders; for example, the impact of travel across time zones. Sleep: Data such as whether the rider sleeps at home, in a hotel, or on an aircraft is collected; where he slept the previous night; what time the rider fell asleep and woke up; how long the rider slept; the quality of sleep; and the altitude at which the rider slept and woke up, which is very important on a scientific level. Wellness: Using scientific­ally validated scales that are simple to use, riders are asked to rate their mood levels each day; their motivation and current stress levels; if they’re feeling fatigued or if they are experienci­ng muscle soreness. Training: Riders are asked to provide a subjective view on their performanc­e in training or racing the previous day: did they perform as expected? What’s really important about this data is how the rider feels about his training: what was his rating of perceived exertion. Is the rider responding well to the training that the coach prescribed? Did the effort feel like a 7/10, a 5/10, or a 9/10? Management: Was the rider able to train that day, and if the answer is no, was it the weather? Was he ill or injured? Or is there something else happening such as a bike failure? Even a stuffy nose is acted on. Whereas a blocked nose may not appear to be serious, in the past riders have ignored a blocked nose that turned into pneumonia.

Machine learning with predictive analytics wil help optimise team performanc­e.

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