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Importance of AI and ML for eSports and Gaming

ML and AI for eSports and gaming to track scores on the screen: a gamer is holding a joystick in each hand while sitting on the sofa with his back to the camera

As Industry 4.0 unfolds before our eyes, artificial intelligence and machine learning are paving their way into more and more industries of today. From healthcare to education to security businesses rely on these technologies to power up the existing capacities and create new possibilities. Gaming and eSports are no exception. In this article, SOLVVE will open up on the importance of AI and ML for this domain and the potential it holds for the fast-growing industry.

Possible applications of AI and ML for eSports and Gaming


While the argument goes that current AI capacities cannot fully comprehend the complexity of human interaction in the games, AI can make a rather useful coach at certain levels of training. It is good at learning and understanding individual players’ strengths and weaknesses as well as peculiarities of the game settings. Thus, it can provide comprehensive skill development for beginners or give feedback on strategies.

With the growing popularity of an eSports athlete as a career choice, the demand for coaching is hard to meet. There are only so many professional players. Moreover, being good at playing the game and having skills for teaching to play the game do not always come together. Thus, using AI as a substitute for in-person training can help to close the gap in demand in supply for coaching. 

Broadcasting and commentaries

eSports events gather a huge amount of viewers. However, even these impressive numbers of spectators represent only a fraction of the potential audience. The main reason being the difficulty to comprehend what is happening on the screen in the fast-paced competitive games unless you have a certain history of playing the game title. 

Still, many of those who watch gameplays never actually play the game itself. Getting the grasp of gameplay may be a challenge and articulate commentaries can potentially boost the viewership among people who do not have a deep involvement with a certain game title. The main challenge to overcome here is to focus on the key gameplay events that shape the outcome and present it to casters and viewers. Otherwise, they might get overlooked.

This aspect has already been challenged by IBM’s Watson AI  that “scans through hundreds of hours of esports video to create dynamic highlight reels in real time.” Curating the content with such technologies makes viewing eSports events much more enjoyable and lower the entrance level for people with less experience in eSports.

Rankings and matchmaking

Although partially automated, keeping records and ranking is still a chore and sometimes leads to mistakes, if not deliberately planned fraud, like match-fixing only to be discovered later on. Engaging AI to correctly register game results and oversee the tournament scoring is crucial to maintain fair gameplay.

Moreover, AI can help to match players within the tournament so that everyone plays with an opponent of equal strengths. It can also help to prevent cases when two of the strongest players or teams meet too early in the tournament table making the rest of the event less interesting for the audience to track.

Behavior supervision and anti-cheat

You might have already encountered this application in action when you heard reports about discovered cases of aim-bots use in shooters or someone leveling up at an incredible speed. AI is extremely useful in finding out and pointing out such cases, which otherwise can only be detected manually and brought to inspection through reporting systems, followed by an investigation. These time-consuming practices keep the hands of the organisers full with tedious jobs while those could be handled by AI.

However, there is much more to it. Some other applications of AI and ML in eSports and gaming include a wide spectrum of monitoring capabilities to eliminate profanity and aggressive behaviors in text and voice chats, identifying spammers, fake accounts, or cases of identity thefts. There is also a potential for players’ engagement boost through powerful recommender systems integrated into social platforms used to play, watch, compete, or discuss eSports and gaming.


With the rise of eSports rose the betting industry in this area. Similar to betting in traditional sports, bookmakers need statistical data to deliver quotes. Some game titles already harbored years of data on individual players, team performance, tournaments’ outcomes, etc. Other titles are only evolving which gives them a chance to think about and properly implement gathering of game data for further analysis.

Having this data with the possibility to dig into such peculiarities as players’ conditions, tournaments, or training history can provide huge value for bookmakers and bring betting in eSports to a new level.

As you can see, the applications of AI and ML for eSports and Gaming are numerous and we will probably see their number grow by the day. From organisation of events to broadcasting and scorekeeping, this technology is essential to the whole industry and adopting such solutions very fast. If you have any questions or ideas related to the application of AI and ML for eSports and gaming in your business projects, do not hesitate to contact us. Let us make this happen!