I think a lot of people might assume there's more AI stuff flowing in here and I have kept a sandbox of sorts around the algorithms and the way they rate things because often these ML engines can take on a bit of bias depending on who's creating them.
How has sifting through all this data to search for comebacks, upsets, rivalries, individual performances - or any other exciting aspect - changed with advancements in machine learning?
It's a great question. I think the biggest thing for me when you look at ML is restraint, as wild as that sounds. As we built these algorithms for figuring out when games get exciting there’s almost a philosophical debate. Let's say you have an NBA game tied with 30 seconds to go, and a WNBA game tied with 30 seconds to go. Which one should you rate as more exciting? I think reasonable people can disagree. Some can argue the NBA is bigger, it has more global fans and that's inherently more exciting. Others can say that's just bias creeping in, basketball is basketball, it should be the same. I think a lot of people might assume there's more AI stuff flowing in here and I have kept a sandbox of sorts around the algorithms and the way they rate things because often these ML engines can take on a bit of bias depending on who's creating them.
Unfortunately, there isn't a source of truth about which game is more exciting than others. If Manchester United and Manchester City are 0-0, that could be a thrilling or boring game and it's difficult to
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ascertain. Tere are all sorts of different ways that ML and AI could take this in the wrong direction, so we've tried to be very thoughtful about how we use it. We use it a lot for rivalries because I think it's very easy to assume what a rivalry is and not look at the data of what it really is.
It's not always about geography. Yankees - Red Sox is a rivalry, but not as much as it used to be. In cricket India and Pakistan are massive rivals. Some people say it’s because they're geographically close, but arguably the second biggest rivalry is Australia and England and they're on opposite sides of the world. We do like to rely on the engine for things like rivalries, but we don't do it too frequently.
Is your passion for curation and discovery reflected by the conversations you've been having with operators, including at the recent G2E convention in Las Vegas?
I think curation and discovery will be fundamental for operators by the end of 2025. Instead of giving me a spreadsheet of rows and columns with games that I must sift through myself, they need to say, "this is the most interesting game this weekend" or "out of the
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