A new AI system named 'TacticAI' claims to accurately predict the outcome of corner kicks and provide realistic and accurate tactical suggestions in soccer matches.

Using "high-quality" tracking data, the AI can identify strategic patterns to produce "predictive and generative outcomes" - both in attack and counter-attack - ultimately helping teams win more games.

As part of the announcement of the revolutionary AI system, experts surveyed English Premier League club Liverpool and staff were found to be in favour of the technology over current tactics used by coaches, 90 per cent of the time.

The research will be published in the Nature Communications journal on Wednesday after more than 20 authors contributed to the paper. It was developed at Google Deep Mind using geometric deep learning to identify patterns and create predictive outcomes.

The authors suggest that the method could be generalised to other set pieces, such as throw-ins, and to other team sports with suspended play situations.

Liverpool assisted the group of international researchers providing the dataset of 7176 corner kicks from the 2020 and 2021 EPL seasons.

A Liverpool assistant coach, three data scientists and a video analyst found that "the tactical setups it generated were realistic and indistinguishable from real-world scenarios".

The development could mark the start of an exciting new approach to coaching and analysis in sports in pursuit of more effective in-game outcomes.

"The research could lay the groundwork for the next generation of AI assistants to help coaches determine optimal player setups and develop counter-tactics to maximise the chances of winning," a statement read.

"TacticAI was able to accurately predict the first receiver of the ball after a corner kick is taken and the direct result of the kick.

"The system could also evaluate the possible outcomes with alternative player setups and generate tactical variations that improve match outcomes.

"The method could be generalised to other set pieces, such as throw-ins, and to other team sports with suspended play situations."

The use of analytics in sport in recent decades has become more prominent in game-planning and helped revolutionise the way in which clubs approach coaching as well as how they recruit players.

The famous award-winning, 2011 Hollywood film Moneyball brought this "sabermetrics" approach to the mainstream.

It portrayed the rise of the Oakland Athletics US baseball team under general manager Billy Beane, who had a limited budget but got the most out of players he signed, highlighting the statistics other clubs had missed, and using them to his advantage.

The application of AI to existing sporting statistical data analysis promises to turbo-charge the possibilities of its application, however AI has been proven not to be completely foolproof.

In many ways AI promises to make everyday operations easier - from facial recognition or voice assistants on mobile phones, to advanced robotics simplifying business logistics.

But some AI applications have been problematic, such as Chat GPT being used by students to help complete - and in some cases cheat - in their assignments, or auto-drive vehicles which can lead to accidents.

There is also concern that AI could lead to job losses. Earlier this year, the International Monetary Fund claimed AI would affect 60 per cent of advanced economy jobs, partly with a negative impact and partly boosting productivity.

In January the federal government introduced its plan to have new relegations about high-risk technology without impeding the growth and use of helpful low-risk options.

"We have heard loud and clear that Australians want stronger guardrails to manage higher-risk AI," Industry Minister Ed Husic said.