How AI can Influence the Future of Sports Betting

The ongoing AI revolution has been an enormous talking point over the past couple of years. It’s a tech story, certainly, but one which has certainly crossed over into mainstream discussion. In this article we’ll take a quick look at AI’s rise, before assessing its impact on one industry in particular: sports betting.

The Rise of AI

Development of the actual technology behind AI’s advancements has been ongoing for years, of course. It was arguably the boom in popularity of ChatGPT, however, which suddenly catapulted AI into the popular consciousness.

ChatGPT is just one example of modern AI, of course. But it has neatly encapsulated the many, many applications AI already has. It can be used in both casual and professional capacities alike, to help with research, learning, or simply as a new type of hobby.

With that said, money talks, and commercial applications are likely to drive much of AI’s advancements. It has already had a significant impact on industry in recent years, and that impact will only continue to widen.

AI’s Impact on Sports Betting

Sports betting is worth billions of dollars in the US alone. It is an industry which never sits still for long, and – therefore – is a perfect test case for how AI is already making an impact. That’s true not only for odds-makers, but also punters who are trying to make money from them.

Data Analysis

There’s obviously a limit to how much data a single person, or even a group, can process. Algorithms can certainly help with this, but have various limitations, including relying completely on people to create them in the first place, and not adapting to the data they’re processing.

AI tools are already seeing heavy use from data-driven organizations, to collect, assess, then visualize data. Professional bettors are exclusively data-driven, giving short shrift to falsehoods like ‘gut feelings’ and hot and cold ‘streaks’. Those aforementioned tools can help them analyze a greater volume of betting data (odds movements, form, player and team stats, etc.) than ever before, and process it more effectively.

Predictive Modeling

Predictive modeling is similar to data analysis, in that it gathers and assesses a significant amount of historical data. In this case though, it is specifically doing so in order to try and predict future results through forecasting and simulation. It can try to give a probability for something happening in the future, or provide a range of possible/probable results.

You can probably see where this is going. All the uses we just listed above have obvious and powerful applications for gamblers. The entire name of the game in sports betting is to assess the probabilities of future events, and make the best predictions you can. AI’s predictive modeling can help out enormously here.

Odds Optimization

While the previous two applications were for users, this one’s very much for the bookies. Arriving at the right odds is easier said than done. That’s one of the main reasons why sports betting sites adjust the odds they initially set. True, this can also be in response to too much action piling into one side of the market, but that’s also usually a result of inaccurate odds.

Sportsbooks have long been using algorithms to set their initial odds. You can bet your bottom dollar, however, that they’ll be keeping abreast of all the latest AI developments, and – amongst other applications – using them to optimize their prices. It’s easy to see how both data analysis and predictive modeling can be used here, for looking not only at historical data to gauge probabilities, but also for reacting to other bookies’ pricing and adjusting in real time.

Author Profile

John Day

John Day is a seasoned sports writer and brings a unique blend of insightful analysis and covers the stories that matter most to sports enthusiasts everywhere.