According to the duo from A5 Labs, most of today's bots aren't some 'perfect solvers' striving for an unbeatable GTO (game theory optimal) strategy. On the contrary, they are scripts or semi-automated systems tailored to specific types of opponents. Rather than playing 'correctly,’ they aim to exploit the common mistakes of average players.
These bots are often set up by the players themselves – it's not rocket science. You can choose a more aggressive or passive style and let the system play according to simple rules that work against the average population. Thus, an 'exploit bot' is born – not a machine for perfect play, but a tool to hunt the weak. And that's where their weakness lies. When someone plays the same way over time, making the same decisions in the same spots, a pattern emerges. One that can be found in the data, unraveling the whole scam.
How to Detect Bots?
One of the most fascinating parts of the podcast is the insight into identifying cheaters without invading players' privacy by accessing their computers. A5 Labs explains that today's detection work operates on two fronts. The first is the so-called contextual approach – monitoring the player's device, system processes, and running programs. However, this approach is very invasive, and many platforms (and players) resist it.
The second, and according to the hosts, much more elegant method is purely gameplay-based – the so-called gameplay analysis. This looks solely at what a player does at the table – what decisions they make, how often they bet, call, or fold in specific situations, how long each decision takes, and whether their behavior resembles natural human play. This method doesn't require system access. It only needs to analyze a large number of hands and find a pattern that a human can't consistently mimic. And this is precisely what A5 Labs focuses on.
A Pattern That Can't Be Hidden
Humans behave unpredictably in games. Not by choice, but because we are emotional beings, sometimes we take more risks, other times we play it safe. Our energy, mood, and concentration change. And all this reflects at the table.
A bot, however, operates differently. To maximize profits, it must be consistent. In similar situations, it makes the same decisions – not because it's mimicking a solver, but because it's following instructions set by a 'programmer.' This unnaturally high consistency is, according to experts from A5 Labs, the most reliable signal that something is amiss.
How does this work in practice? Teams like A5 Labs develop massive behavioral models that have databases showing how humans behave, how bots behave, and how players using RTA behave. Then, they examine a particular player’s behavior and compare it with these patterns. The closer your style is to the suspicious profile, the higher the risk score you earn.
This method doesn't require access to player software – it is based solely on what the player did at the table. And since bots must be profitable, they can't afford to 'play badly just to hide.' Eventually, their pattern will surface.
What Happens When You're Caught
Spotting a bot is one thing – but then what? The podcast emphasizes an important point: platforms shouldn't handle suspicious behavior with a simple one-click 'ban.' A5 Labs suggests a range of measures that are fairer and more transparent. The first step might be preventive blocking – if the system detects you’re running risky software or showing suspicious behavior, it simply won't let you play.
The next step is more detailed monitoring of your decisions (gameplay monitoring), still allowing you to play but under supervision. If suspicions are confirmed, it may lead to a 'range conversation' – the platform asks you to explain your decisions in specific hands. If it doesn’t add up or you seemed to have an undue advantage, stricter actions may follow – account removal, fund seizure, or redistribution of winnings back to affected players.
However, the hosts stress: the player must have a chance to defend themselves. If it’s a mistake or misunderstanding, there should be an opportunity to explain the situation. In some cases, supervised play – monitored gameplay via camera or screen sharing – can be used to verify that the player is indeed playing alone and without assistance.
How You Can Be Cautious
The podcast suggests that technology is advancing to protect fairness – but players can also help keep online poker safe. Here are a few things you can watch for at the table:
- Overly 'textbook' decisions: a player who makes the same decisions in the same spots may be a bot or using assistive tools
- Extremely consistent reaction times: people naturally take varying lengths to think, bots do not
- Suspicious win rates without context: if an anonymous player consistently dominates the field without a single mistake, it’s worth noting
- If you suspect something, don’t just share screenshots on forums – communicate with the platform specifically, factually, and through data. You are part of the ecosystem that you can help protect.
This episode of Joe Ingram's podcast isn’t just about finding bots – it's about the future of online poker. It shows that fairness can be protected intelligently, without unnecessary paranoia or harsh bans that would deter honest players. If you're interested in how online poker defends itself against those trying to bend the system, this episode is a must-listen.
