Running with numbers: career opportunities in sports data

3D skeletons, Formula 1 sailing boats and high-tech bikes – welcome to the sports data revolution.

Ever wondered how our Aussie Olympians get the edge on the opposition? Sure, it’s eating the right food, training hard and having a killer attitude, but now they have a new weapon: data analytics.

Sports science has changed massively in just a few years thanks to hundreds of millions of data records. This sports data revolution is creating a big demand for maths, stats and data scientists to help Australia stay on the top of the Olympic podium.

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Stuart Morgan, head of analytics at the Australian Institute of Sport (AIS), says what the organisation needs is “people who understand sport, but it’s those crucial data science skills and capabilities that will make their career in sports science right now”.

Triathlon Australia uses data to protect athletes from injury

One recent successful sports data project has been with triathlons – an Olympic sport that includes running. swimming and cycling.

Triathlon Australia hired an athlete health specialist in 2018 to monitor health and training data and conduct daily surveys with athletes. Wade Hobbs, data analyst at Triathlon Australia, says that “injuries in triathletes who have been part of this athlete health system have plummeted”.

As a data analyst at Triathlon Australia, Wade Hobbs uses numbers every day on the job. Image: Triathlon Australia

“Bone stress injuries, which represent the highest cost in terms of training and competition time lost, have been reduced by 72%, so it’s been a real win,” he says.

Artificial Intelligence is emerging as a key tool in sports science

“The real battleground now is artificial intelligence (AI),” says Stuart, “and the people doing this work are largely computer scientists who are providing us with algorithms that we can use to monitor and improve performance.”

“We’re building AI algorithms that can interpret what athletes are doing just from broadcast vision,” explains Stuart, who also leads AIS’s Computer Vision and Machine Learning group. “Our objective is to help our athletes but also to understand more about our opponents than they understand about themselves.”

RELATED: 5 minutes with a data analyst

Start your maths, data + sports career here



  • Data analyst: $51K–$107K
  • Data scientist: $63K–$132K
  • Exercise physiologist: $47K–$73K*

*salaries according to

This article originally appears in Careers with STEM: Maths 2020.

STEM Contributor

Author: STEM Contributor

This article was written by a STEM Contributor for Careers with STEM. To learn more, please visit our contact page.


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