In a country where distance has always been the great sorter of sporting dreams, a smartphone pointed at a teenager in Innisfail or Emerald might soon carry as much weight as a scout's eye at an elite private school oval. That, at least, is the ambition behind Queensland's YouFor2032 app, a tool the Queensland Academy of Sport is billing as a world-first in athlete identification technology.
The app, which launched in August last year, asks users to record themselves performing basic physical movements: jumping, sprinting, push-ups. Artificial intelligence then analyses the footage in real time using computer vision, overlaying biomechanical data to measure metrics that trained scouts traditionally assess in person. According to ABC News, nearly 6,000 Queenslanders have downloaded the app since its release, and those who show promising results will be invited to face-to-face testing during the QAS's first regional tour since the app went live.
Alex Roberts, QAS head of talent and holder of a PhD in athlete talent identification, describes the system as "the only app that uses computer vision and artificial intelligence in order to remotely screen athletes." The programme covers 15 Olympic and seven Paralympic sports, including boxing, diving, and hockey, and is open to Queenslanders aged 13 to 23 for Olympic pathways and 13 to 30 for Paralympic ones. Crucially, it is also the first known talent search technology in the world to include Para sports, a distinction the Crisafulli Government has pointed to with evident pride.
The logic behind the programme is sound from both a fiscal and a sporting standpoint. Traditional talent identification relies on physical roadshows: scouts in vans covering thousands of kilometres, with opportunities concentrated in towns large enough to justify a stop. Young people outside those centres, or whose parents cannot take a day off work for a two-hour drive, simply miss out. An app-based screen does not eliminate that inequality, but it compresses it considerably.
From Proserpine to the podium
Mac Rogers is a useful illustration of what the pipeline can look like when it works. The 21-year-old from Proserpine attended a talent search event in Mackay in 2022, a trip that required an hour-and-a-half drive and a morning off school. QAS scouts noticed that his height and wingspan were better suited to sports other than his chosen discipline of gymnastics. They offered him five options: beach volleyball, sprint kayak, boxing, pole vault, and rowing. He chose rowing, relocated to Brisbane the following year, and has since medalled at both the Queensland and New South Wales state championships. He is now targeting the national championships in March, with Brisbane 2032 as the longer horizon.
Rogers was identified before the app existed, which makes his case both an endorsement and a caution. The system worked for him because his mother was willing and able to drive him to Mackay. The app addresses that specific barrier. But his success also depended on relocating to Brisbane, on QAS coaches taking him under their wing, and on the existence of a structured rowing programme that simply does not exist in Proserpine. The technology can find talent anywhere. Infrastructure, however, remains anchored to geography.
A global pattern, with local stakes
Queensland is not operating in isolation. The broader shift toward AI-assisted scouting is visible across professional sport, with Premier League clubs and top-tier European and North American teams deploying AI cameras to monitor amateur games in dozens of countries. At the Olympic level, the International Olympic Committee partnered with Intel to deploy a similar smartphone-based tool in Senegal ahead of the Youth Olympic Games Dakar 2026. As sports scientist Richard Felton-Thomas described in a recent TED Talk, the Senegal programme scanned thousands of children in schools and military settings, ultimately identifying 40 prospects now training for the Games in wrestling, athletics, and football. The IOC-Intel trial deployed across six villages, analysed more than 1,000 children, and produced over 1,000 biomechanical data points per participant in a matter of minutes.
The QAS claims its app goes further than anything else currently available, specifically in its ability to assess a broad range of movements remotely and to include Para sport screening. Roberts says the computer vision system can calculate elbow angles during a push-up, measure depth, and determine whether a repetition meets the required standard, all from footage captured on a standard phone. Results are returned to the user in real time, allowing them to attempt a movement again before progressing.
The harder question after the scan
There are legitimate questions to raise about what happens once the algorithm does its work. Digital screening at scale is genuinely valuable, and the scepticism that sometimes greets government-backed sporting technology programmes is not always warranted here. The QAS has already tested athletes across more than 40 locations including 26 regional centres, ranging from Warwick to Emerald and from the Gold Coast to Yarrabah, according to Queensland government statements. That is a serious logistical effort, and the app extends reach further still.
Yet the equity argument that underpins the programme cuts in two directions. Identifying a kid from a remote town as a potential elite rower is meaningful only if there is a pathway for that kid that does not require an immediate move to a capital city and parental resources to support it. The technology solves the discovery problem. The development problem, with its demands for coaching, facilities, travel, and time, is the more expensive and politically complex one. Advocates of expanded regional sport investment would argue this app simply makes the case for that funding more visible.
What is clear is that the technology itself is credible, the ambition is genuine, and Brisbane 2032 provides a rare fixed deadline that concentrates minds and budgets in ways that peacetime sporting policy rarely does. Whether the YouFor2032 app becomes a footnote or a genuine legacy instrument will depend less on the quality of its computer vision and more on whether the programmes that follow a promising scan are funded, sustained, and accessible to the young people who need them most. For now, the algorithm is doing its job. The harder work comes next.