‘Smurfing,’ the word that comes from the carefree blue cult cartoon characters, couldn’t be a more misleading term to describe fake ‘noob’ accounts. However, this is gaming, and almost anything can be traced back to a few bored players or devs who wanted to make the experience more fun, even though it ended up creating a scenario where you innocently join a Counter-Strike server and get a headshot in seconds. It’s all fun and games until it becomes a popular prank high-ranked players pull on lower-ranked ones, and even an issue in amateur esports competitions where the former would join and unfairly get all the cash prizes. It has always been an issue, and it still is, even though games have tried implementing anti-smurfing rules and systems that have made a somewhat different but are still easy to bypass. The line between strict rules and morally wrong, but still technically ok behaviour tends to blend when it comes to smurfing, and here is where AI comes in to save the day and even the field.

The Real Problem of Smurfing

The Origin of Smurfing dates back to 1997, when two Warcraft players, Shlonglor and Warp, became so good that no one wanted to play against them. The solution? Open two new accounts, innocently name them ‘Papa Smurf’ and ‘Smurffete’ and wait for whoever picked up the bait. There was nothing wrong with it until other games picked it up, and expanded beyond control when automatic matchmaking systems made it so that a pro could easily end up undetected in your game, to the point that you had to be aware if a name in the server sounded too funny or random. Technically, it’s not forbidden to want to play with your noob friends or just enjoy the game at an easy level. Morally, it’s debatable; not everyone agrees on what is right and wrong, and there’s even solid research to back this all up! PhD student Charles Monge and Prof. Nicholas Matthews conducted a study of 328 people. They found that 69% reported that they smurfed at least sometimes, 94% thought other people smurf sometimes, but the main takeaway was that players thought there were different nuances of bad for smurfing, and it was ok when they did, but turned toxic if others did it! Other studies were also conducted, yielding similar results and expanding the concept beyond gaming into a real-life scenario of pointing fingers. Thus, it was clear that the problem with smurfing lies with the people; therefore, the solution must be sought by the companies, or so we thought. Valve did an impressive job of banning over 90,000 smurf accounts in their game DOTA2, declaring that Smurfing is objectively against the rules. Other games, like Valoras, the free online shooter, make it so easy to access that you only need an email account, leaving complete free rein to smurfing. Riot, the company behind the game, was initially not interested at all and did not even consider it a problem. It all starts to make sense when you consider how popular the game became by Pro players posting smurfing sessions, annihilating lower-ranked players on YouTube as a gag. How do you get this situation under control if the cause-and-effect blends in, and most people swing from one side to the other of the argument? You get the hint that this is where AI kicks in.

Let the Machine Be the Judge

Getting back to Riot, once Smurfing had been acknowledged as a problem, the developers applied a machine learning-backed system as early as 2022 to detect smurfing. The system analyses the players’ behaviour in-game and automatically identifies Smurf accounts. While not perfect, it produced results. According to them,  alternate accounts are down ~17% compared to earlier in the year. BattleEye and FairFight are good examples of AI-backed anti-cheating systems used in PUBG and Rainbow Six. While they are still struggling to deal with Smurfing, in theory, they could adapt these systems to address the issue by using machine learning models to track metrics such as win rates, reaction times, and decision-making speed, along with account parameters like the date it was created. Blizzard had long used players’ gameplay data in the Matchmaking system in Overwatch 2. How they do it is pretty ingenious. The game employs a hidden numerical Matchmaking Rating (MMR) as its primary tool for quantifying a player’s skill level relative to the entire player base. The visible rank displayed to players, such as “Gold 3,” is not directly factored into the actual match creation process. Slowly but surely, Blizzard is starting to introduce more AI to the process in direct ways, but also subtly by deciding that the first five rounds of the game will be against AI models.

It’s Never as Easy as It Seems

AI systems are not perfect, and there have been multiple cases of players getting banned unfairly. In the case of smurfing, it becomes even trickier, as technical problems behind detecting players are not the only reasons that make it hard for companies. Only in 2025 did Riot state that they are considering using digital ID verification for new accounts, which would significantly help address the issue of alternate accounts. The technology was available long ago, but it could have players spend less time in the game or find it challenging to open accounts; both scenarios that the devs do not want to happen. Another factor to consider is the player’s age. Legally, it would be challenging to handle a scenario where an underage player needs to provide identification, a significant factor that tends to push companies towards ignoring smurfing issues. Additionally, acquiring as many players as possible and encouraging them to engage with microtransactions proved to be a successful model that no one would dare risk.

Is There a Way Out?

The issue addressed would result in a fairer outcome for everyone, not just competitive gamers. It’s no fun casually opening League of Legends after a hard day’s work and spending that hard-fought extra hour before sleep getting bullied out of the game. However, it seems that smurfing is a problem that depends on context, with both pro players and developers finding an advantage to it, while AI systems, implemented to support existing anti-cheat mechanisms, only partially work. What would then be another scenario that doesn’t eliminate AI but allows it to have more transparency and a ‘softer’ touch? Perhaps giving the AI more independence, in the form of it turning into an AI companion that studies the player’s behaviour in a one-to-one scenario and can recognise the patterns among millions of players. Independent of the account, it would know the players behind the controller. Another use would be for the AI to evolve into a coaching tool that follows the player, learn about them and their behaviour, and if a loss was due to smurfing and not poor performance, contextualises and reports it automatically. If it sounds too optimistic, keep in mind that companies like Candy AI have already successfully built AI girlfriend models that have emotional connections to humans and have cracked a big part of the puzzle of making companions work. Nonetheless, the future of solving the smurfing issue is undoubtedly related to AI, and all the new tech will smoothly find its way into balancing out the situation. Whether that will be for the gamer or the companies’ interest is still to be seen.