What makes every competitive sport similar to betting is the fact that every chance, win, and loss can be equally expressed by numbers. We use numbers to record scores in different forms, like points, goals, and ranks. They are the final display of each sporting performance. With betting, we use the same digits for mathematic analyses, calculating odds, outcomes, and even predicting exact results.
For any reliable statistics, researchers need to collect a large number of accurate data. But imagine that instead of human input, this job can be assigned to the particular algorithm that is capable of using data that no human could ever perceive.
Therefore, sports betting is one of the best growing fields where AI technology can evolve. With a large number of available statistics and precise target that is always on one winner, sports betting is an excellent base for applying Machine Learning algorithms.
Any Machine Learning will be initially fed with standard statistics, like the percentage of lost balls, assists per each game, or successful first serve for tennis players. These data are usually available and used in standard analytics. However, the AI algorithm will be able to capture data that is not evident, for example, the average distance that one player covers during a match, or the favorite place from which they shoot, to create a bigger picture.
Yet, even supreme technology like AI can find some obstacles in collecting data. Many sports never reveal too much information about the game. And, while you will find a comprehensive summary after every baseball match, in tennis, for example, it is almost impossible to gather the necessary numbers.
Also, data accuracy can be another barrier to AI prediction in sports betting. Statistics are changing, and the algorithm might take into account data from the past while, from that moment, one team can change almost the entire lineup of players. Moreover, AI can’t take into account things like intuition, a “click” between players or any human behavior that could affect the final result of the game.
The factor of luck has always been present in every type of gambling, even when we are familiar with statistics. With the introduction of AI in sports betting, analytics will be based solely on accurate numbers and exact data. Things like gut or luck don’t exist in predictive analytics, and betting outlines the industry created of probability and figures.
Obviously, advanced technology can significantly improve the probability of predicting the outcome, even guessing the exact result of a match. With this fact, the question is — when will Artificial Intelligence stop working for the house and send the sports betting we know to history?
Still, no algorithm can predict human behavior. That’s why both of these aspects need to be considered for an accurate prediction. For example, the London-based Startup Stratagem uses AI algorithms and the help of expert analysts for the best predictive analytics.
Unanimous AI is the most successful startup that uses cognitive technology, but not for prediction analytics. They apply AI for gathering human knowledge and skills into the so-called “collective brain.” It delivers stunningly accurate results in betting analytics so high that they could predict a final Super Bowl result last year.
Until sports betting becomes a fully automated process, pioneering AI should be used in correlation with human knowledge and gaming preference, for as many accurate results as possible, but also for the excitement that only a winning ticket could bring.