Turning Players Demand into Revenue: B1’s AI Sports Strategy

Honestly, it comes down to two different problems, and each product solves one.

Cricket has a huge, passionate audience, but the calendar is lumpy. You get massive spikes around the IPL or a big Test series, and then long stretches where the operator has a cricket-loving player base and very little to offer them. B1’s AI Cricket keeps that audience betting between the big moments, with matches that look and play like real cricket.

Table tennis is a different story. Volume was never the issue there: it’s already one of the most traded sports in the world. The issue is that a lot of that volume comes from low-tier events with a history of integrity concerns. B1’s AI Table Tennis gives operators the same fast, high-frequency format their players already love, but with full control over the product and greatly reduced traditional match-fixing risks.

The first question is always about realism. Will a real-sports bettor actually engage with this, or will it feel like a slot machine dressed up as a sport? If you don’t pass that test, nothing else matters.

After that it’s practical. How hard is the integration, and can it come through a feed or platform they already use? Is it certified, and does it fit their licence in the markets they operate in? And what does the commercial model look like? Most operators don’t want a big fixed fee for a new vertical. They want rev-share, so we only make money when the product performs.

With real sports, the price of the content is only part of the cost. Behind every market there’s a trading team building odds from statistics, official data and live streams, and every link in that chain can break. A trader misprices a line, the data feed lags a few seconds behind the action, a stream drops, a result gets corrected after settlement. Each of those costs the operator money, whether through sharp bettors exploiting latency, voided bets or palps.

AI Sports removes most of that chain. The event, data, and odds come from the same system, so there’s no gap between what happens and what the operator knows. Minimal latency to exploit, no manual pricing errors, no postponements or abandoned matches. The operator gets a schedule built around their peak hours and a margin that’s designed into the product, not left to chance.

Mostly as part of a wider strategy, and that’s how it should be. It usually fills quiet hours or the off-season, and once the numbers come through, it earns a permanent place next to virtuals and esports.

The exception is cricket-first markets, where AI Cricket can almost stand on its own because the sport carries the audience. And for us, it’s often part of a bigger relationship. An operator already using our B1 Sports Data Feed has a clear reason to add AI Sports, and it works the other way, too.

The biggest lesson was to go where the audience already is. With AI Cricket, the fastest-moving conversations were with operators who had a cricket audience they couldn’t monetise year-round. We stopped trying to create demand and started serving existing demand.

The second was distribution. Selling operator by operator is slow. Working through aggregators and platform providers gets you onto dozens of sportsbooks through a single integration, so we put that at the centre of the Table Tennis plan from day one.

And the third, which sounds simple but really matters: show the product early. The moment an operator sees the gameplay, the conversation changes from “what is this?” to “how quickly can we go live?

The questions have changed. Not long ago, operators wanted to know whether this was a gimmick. Now they ask about margin, turnover per hour and integration timelines. That’s a buyer’s conversation, not a curiosity.

We’re also seeing tier-one operators take demos, and major platform providers enter the pipeline. And we’ve gone from one sport to a portfolio because clients asked for it. When you build the second and third product on the same foundation because the market is pulling, it’s no longer an experiment. Our B1 team already knows this for sure.