Data analytics and machine learning in E-Sports

 

Electronic sports (e-sports) can be defined as multiplayer digital games played competitively by an audience. E-sports mainly includes multiplayer video game competitions between the professionals(generally). The video game most commonly played and associated with e-sports are multiplayer online battle arena (MOBA), first-person shooter (FPS), fighting, card, battle royale, and real-time strategy (RTS) games. Popular e-sports franchises include League of Legends, Dota, Counter-Strike, Valorant, Overwatch, Street Fighter, Super Smash Bros., StarCraft, etc.

What’s the data analytics and its relation to e-sports??

Data analytics can be simply defined as it use for analyzing the data or simplify the data and/or high-velocity data, which presents unique computational and data-handling challenges. Skilled data analytics professionals, who generally have strong expertise in statistics, are called data scientists.

Data is a fundamental requirement in every industry. Analyzing the performance of Competitors and self is e-sports preparation. This naturally involves players watching and analyzing their opponents' gameplay, strengths and weaknesses before tournaments and trying to use this information in key moments during a game. The advent of big data analytics in e-sports means players and teams can make up their information in ways that were not possible before. Powerful AI-supported analytics tools analyze hundreds of data points harvested from digitally recorded games. Data analysts can provide useful statistics, identify weaknesses of competitor players and teams, and predict the likelihood of an opponent’s next move in any given situation. This is valuable information, and players, coaches, and teams are happy to pay for the services that deliver a competitive edge.

What’s Machine learning and its relation to E-sports??

Machine learning is a subfield of artificial intelligence, which is broadly defined as the capability of a machine to imitate intelligent human behavior. Artificial intelligence systems are used to perform complex tasks in a way that is similar to how humans solve problems.

Machine learning can boost the user's experience because it can define the level of the player and give player according to the player or we can say it can set the difficulty level of the game. Which will boost the user experience. Now, the actual work of machine learning is that it uses Data and simplifies and checks what can be the human behavior and how he going to react then depending on all tendencies applying all algorithms it gets on the position of how the game will change.

Elon Musk and Google have created ‘unbeatable’ AI bots that have vanquished their human foes in classic e-sports like Dota 2 (pictured) and StarCraft 2. It’s not going to stop there it’s just beginning. In the upcoming future ML going to be the future of games because technology is the future of all games