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How Artificial Intelligence Expands Tennis Sport

Published Sat, Jun 04 2022 13:53 pm
by The Silicon Trend


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How Artificial Intelligence Expands Tennis Sport

From the age of 14, Bridie Lynch was immersed in tennis, as her parents run a local tennis club in Wales. Thus, she has been playing and coaching the sport ever since. One aspect she has noted is the acceptance of technology at all levels of tennis. As a result, she leverages various techniques and apps for her own matches and coaching, including a smartphone-related video system - SwingVision, which breaks down her performance with details like backhand winners and forehand errors.


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Data Analytics has been lingering around for a long time in the sport. Perhaps the best-known example of its use is from 2002 when the Oakland Athletics baseball team leveraged statistical analysis to choose their team, rather than the knowledge of scouts and trainers and their favored metrics.

Tennis strategist and coach - Craig O'Shannessy said tennis has also seen this revolution as data expanded the sport. For him, the Australian Open 2015 was a pivotal moment. As Andy Murray and Novak Djokovic battled on the court, powerful computers crunched the data and categorized rally length into three groups, essentially short, medium, and long.


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AI Identify Patterns that Humans Can't

Mr. O'Shannessy, who worked with Novak Djokovic between 2017-2019, says that insight made him realize that the way players train was all wrong. He highlighted that 90% of training is targeted on consistency, while only 10% of the match court is in rallies of more than 9 points, and this data transformed the sport forever.

That data manipulation has been taken to the next level. Trainers now have AI, where sophisticated software is trained with an unimaginable data set. The resulting AI can identify patterns that a human can't. For example, Mr. O'Shannessy said, humans, do a terrible job categorizing data, whereas AI can do it in split seconds.

The AI is also speeding up media coverage of the tournament. For example, AI is dicing data to create video content in seconds, a task that will typically take the multimedia team hours to execute.


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