Picture the scene: the year is 2022 and England have reached the final of the football World Cup in Qatar. The team’s success has been built on a new method of managing player performance and health: by building a digital twin of each player. The emerging technology uses sensors and analytics to create virtual representations of every squad member, which can be
Picture the scene: the year is 2022 and England have reached the final of the football World Cup in Qatar. The team’s success has been built on a new method of managing player performance and health: by building a digital twin of each player.
The emerging technology uses sensors and analytics to create virtual representations of every squad member, which can be simulated into game situations and training regimes to identify what they need to improve or protect in real-time.
They’ve now won a last-minute penalty that could decide the game. Fresh from an unprecedented recovery from a broken metatarsal, the team’s star striker steps up to the spot…
Wishful thinking? Perhaps, from a sporting perspective, but technologically the concept is very real. Digital twins are gaining prominence in industrial settings, providing virtual replicas of physical objects – like aircraft engines or even entire nuclear power stations – which can then be simulated into real-world scenarios to optimise performance, reduce maintenance costs and even self-heal.
The method is starting to shift asset management strategies from analysing the past to predicting the future. Analysts at Gartner predict that by 2021, half of all large industrial companies will use digital twins, which will provide them with an average improvement in effectiveness of around 10 percent.
These industrial versions of digital twins create virtual proxies of physical objects, and the concept could also be applied to people.
Digital twins of athletes would gather information on physical attributes, health and activity from wearables, video observations, brain scans and electronic medical records, and then apply analytics and AI to each data point to identify methods of maximising performance and minimising risk.
Coaches could work with these models to test drills and tactics, trainers for strength and conditioning regimes, physiotherapists for rehabilitation regimes, nutritionists for diets, and doctors for medical treatments. They could all then pick the best option for each player’s individual skills and health at any specific point in their career.
Professor Kenneth Loh is one prominent proponent of the idea. His team in the Active, Responsive, Multifunctional, and Ordered-materials Research (ARMOR) Laboratory of the University of California, San Diego already uses digital twins to simulate the performance of military assets. Why not use the model to create a virtual representation of Harry Kane or Tom Brady?
“Nowadays, we have the capabilities to take all sorts of data and all sorts of measurements and use a digital twin as a platform to be able to fuse and integrate everything together so that we can improve player performance and player wellness,” Loh explained during a roundtable on next-generation sports performance at the Teradata Universe conference in Denver, Colorado last month. “That’s the ultimate goal.”
Low’s proposal clearly has enormous potential, but is yet to gain traction in sports and athletics. The biggest barrier to adoption is likely aligning incentives.
Athletes, coaches, fans, franchises, leagues and media would all have different perspectives on how digital twins should be used.
Athletes would have to decide which outcomes they want to optimise. They may want to prioritise short-term gains, extending their career, or the quality of their life after sports.
General managers may be more focused on commercial concerns. They could use the digital twins to gain deeper insights into how players affect the business, incorporating ticket sales and smart venue insights to understand the influence that individual performances on profits.
“The reality is, we’re going to use whatever data we can to determine player performance and project that out. So yes, there is a risk associated with collecting that data,” admitted Dustin Spangler, VP of data and analytics at Larry H. Miller Sports and Entertainment, the owner of sports teams including the NBA’s Utah Jazz
“But it’s also something that’s on file, and the flip side is if you see a player who is entering his early thirties but is still projected to continue to develop, or maintain, and not hit the decline phase of his career, then maybe they have then an opportunity for a better contract.”
Betting companies would also be extremely interested in the data.
“There are a lot of different agents in that equation and their incentives are not always in alignment,” said Jay Tucker, executive director at UCLA’s Center for MEMES (Media, Entertainment & Sports). “That friction is going to create some very interesting times ahead when more data becomes available.”
New developments in technology are always adding further data points. At the Teradata roundtable in Denver, WAVi Co unveiled one example of this: a headset that scans electrical activity in the brain to measure mental response speed and attention span.
“Using the brain to tweak the team can be all the difference,” said WAVi co-CEO David Oakley.
Add to such innovations the drop in sensor prices and developments in IoT and AI, and the concept could become practical and affordable.
Sports teams and athletes may still need more convincing, but digital twins may find earlier adoption in e-sports, where mental skills supersede physical ones and the stationary environment is more conducive to data analysis.
A similar technology to WAVi’s is already being used by Spanish telecoms giant Telefónica to identify correlations between emotions and in-game events which affect the mentality of the Movistar Riders eSports team, by connecting them to brain-computer interfaces that evaluate their neurological activity while they’re playing.
Pedro Antonio de Alarcón, director of the Big Data for Social Good initiative at Telefónica’s LUCA data lab, told Techworld last year that the same system would be tricky to adapt to his work with cyclists.
“The problem it has is it’s a bit intrusive. You need to wear a helmet, and the cyclists are very picky about the things you put on top of their bike,” he said. “You basically can not touch, you cannot add any element to the bike. This is such a competitive world, that anything that you touch – just a small change in the shirt, for example – is changing the aerodynamics and affecting the competition.”
These barriers make it unlikely that digital twins will be used by Gareth Southgate’s England football team by the 2022 World Cup, but the technology would probably not have proved decisive in that final. As every England fan knows, the star striker would likely have missed the penalty anyway.