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Of the more than $9 billion per year that is estimated to be spent on sports betting in the U.S. by 2025, almost $7 billion is expected to come from in-play and micro-betting.

This is an opportunity which was notably picked up on by Jake Paul and Joey Levy, who raised $50 million in August to launch a new company called Betr - focused specifically on this segment within betting.

PhillyGodfather ® Sports Bettor @phillygodfather

Jake Paul and business partner Joey Levy have raised $50 million to launch a new media and micro-betting company called Betr. “Micro-betting is the TikTok-ification of sports betting and I am excited to bring it to the masses through Betr,” Paul said in a statement.

Essentially, micro-betting is a type of in-play betting (happening during the event), which provides almost instant action. For example, betting on the outcome of the next drive in an NFL game or if a batter is going to strike out on the next throw.

While in-play betting has already picked up in popularity, the micro-betting subcategory currently still faces a number of challenges before the floodgates fully open for it to really contribute to those estimated billions of dollars of revenue.

The primary challenge? Data. Specifically, vendors ability to access enough data to service the most relevant betting options at the speed and scale required.

This, however, is where artificial intelligence (AI) and machine learning (ML) are expected to have a big impact in the near term.

Sportradar, for instance, recently rolled out its Computer Vision product within table tennis, a live tracking system which utilises AI software.

Sportradar @Sportradar

Another successful #ICELONDON2023! It was great to showcase our AI-driven Computer Vision technology and catch up with familiar faces and people new to the event. Thank you to all our clients, partners, and fantastic team who made this happen! #SportradarAtICE2023 @ICE365Global

Computer vision, in case you were wondering, is a field of AI which trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects — and then react to what they ‘see.’

“The easiest way to look at it is, it tries to do exactly what the human vision system tries to do,” explains Luka Pataky, Chief Product Officer for Computer Vision at Sportradar.
“It’s not a new technology,” Pataky admits. “Computer vision has been around for decades and in some industries, it has been used a lot – manufacturing, production lines.”

For Sportradar and Pataky, this technology has initially been rolled out within table tennis as the sport requires just one camera to collect the relevant data. From that single source, the Computer Vision can analyse a live video feed at 120 frames per second and collect 100 times the data that would usually be collected in that time.

This data can then all be fed into other Sportradar products such as creating live graphics, 3D replays, virtual advertising, and, most importantly, gambling data.

The impact of this technology is two-fold;

“One is that it creates so much more data that is keeping players longer on the live stream. And that immediately means that they are engaged for longer,” explained Pataky.
And secondly, “it also facilitates a better micro betting experience, because the process of data collection to trading can be automated. That allows us to start building odds and markets extremely fast. We are talking about 30-second cycles from placing the bet to getting the result. So, it’s very interesting for newer generations of bettors with a shorter attention span.”

Sportradar @Sportradar

We're introducing our advanced, AI-driven Computer Vision technology, unlocking for the first time a depth of data with the potential to transform how athletes, fans and bettors experience and engage with the sport. #SportradarAtICE2023 #ICE2023 @ICE365Global

“We believe that this AI-driven tech has the potential to transform how fans engage and experience sport now and in the future,” says Pataky. “We really see computer vision as a game-changer to get to scale [with a micro-betting offering].”

As such, table tennis won’t be the final stop. Pataky is excited about the opportunity to take this further and start applying it across other sports with Tennis expected to be next. He has hinted that there is also a very real focus on expanding into U.S. sports in the near future.

This is interesting as many of the most popular sports in the U.S. consist of constant, impactful micro events with many possible outcomes. For example, the idea of predicting outcomes such as whether a team will get a first down on 3rd is already long ingrained into the way that casual American sports fans talk and think about sports.

Finally, if you pair this with the reach of the major U.S. sports leagues and with the fact that consumption patterns are trending more towards digital, on-demand, short-form entertainment, it all seems set up for micro betting to eventually become the predominant form of betting across the U.S., hurried along by these technological innovations in AI.

Just as fantasy sports changed the sports industry by engaging fans in the performances of players outside of their favourite teams, there is an expectation that micro-betting is set to have a similarly profound impact on the U.S. sporting ecosystem, too.

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AI Opportunity: Computer Vision could bring…