The 6 Types of Reg – Which One Are You? (Chapter 2)

01 Sep 2025

Intermediate

This material is for medium-skilled players

In the first part of this series, we broke down three common reg archetypes: the Reg-Creational, the Volatile Aggro, and the ABC Reg. Each has its own strengths, flaws, and blind spots – and chances are, you probably recognized yourself in at least one of them.

But the story doesn’t end there. The poker landscape is full of players who grind day in, day out, yet get stuck repeating the same mistakes because they don’t truly understand their own style. That’s where self-awareness becomes your sharpest weapon.

In Chapter 2, we’re going deeper. We’ll continue dissecting the remaining reg types, looking at how they think, where they go wrong, and what you can learn from them. The goal isn’t just to put yourself in a box – it’s to understand the box you’re in, and then break out of it. So let’s pick up where we left off.

To be clear, some GTO concepts do matter. It’s crucial to understand where EV actually comes from: when to value bet, when to bluff, what thresholds matter, which sizings are optimal in specific spots, or when slow-playing makes sense. These fundamentals fall under the umbrella of poker theory. They are non-exploitative, structural truths about how the game functions. But theory and GTO are not the same thing.

Poker Theory vs. GTO

When I say poker theory, I mean the objective mechanics of the game – the “laws of physics” that govern it. Poker theory is about the nuts and bolts: how EV is generated, what actions are valid in certain contexts, the natural structure of ranges.

When players talk about GTO, what they usually mean is something different: the exact strategy spit out by a solver once it reaches a pseudo-equilibrium. That’s the point where neither side can improve without the other adapting. It’s an interesting idea in theory, but in practice it creates problems.

The GTO Reg often starts on the right path – usually a sharp, analytical person who loves strategy games. But somewhere along the way, he gets lost. Instead of focusing on real EV, he obsesses over mimicry, balance, and abstract ideas like perfect bluff-to-value ratios.

He may spend hours trying to build his own perfectly symmetrical range:

• Five bluffs for every seven value bets.
• This blocker, not that one.
• This exact frequency in this exact node.

He imagines that if he builds his “temple of perfection”, poker success will magically follow. But that’s not how the win rate is built. EV isn’t generated by theoretical balance alone – it comes from understanding where value is extracted and how opponents actually play.

Lost in the Solver Caves

GTO solutions do contain valuable lessons: thresholds for value betting, optimal sizing patterns, when bluffing is mandatory or impossible, and so on. But they also contain a ton of noise – adjustments designed only to preserve equilibrium.

So, the GTO reg has gone astray. It’s like that rebellious teenage phase: messy, confusing, full of bad fashion choices… but not permanent. The GTO reg can be brought back. You can shake him out of the solver caverns and remind him. So what actually transfers from solver to real-life play:

• Hand class hierarchy → Knowing which hands are theoretical value bets or bluffs.
• Breakeven vs. profitable plays → Recognizing when a line is close in EV and adjusting it based on the villain.
• Understanding range composition → Seeing why certain combos are included or excluded from aggression.

These are gold. They’re tools you can actually use against humans.

And here’s what doesn’t transfer:

• Exact bluffing frequencies → 33% vs 27% doesn’t matter when your opponent isn’t folding anyway.
• Solver-mandated balance → Real players are rarely balanced. Exploit that.
• Over-optimization of tiny EV edges → No one cares if a line is +0.02bb in theory if your opponent is calling down with a third pair.

If your opponent only plays rock, you don’t “slightly increase paper frequency”. You just slam down paper every single time. Poker works the same way: if someone folds too much, you bluff relentlessly; if they call too much, you stop bluffing. No fine-tuning needed.

That's how the GTO reg can be saved:

• He can realize that theory is a map, but the players in front of him are the territory;
• He can stop obsessing over solver outputs and start thinking like a predator again;
• He can re-discover that poker is a game of humans, not machines.

When that happens, his game levels up. He’s no longer chained to his sim outputs. He’s adaptable, dangerous, alive at the table again.

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Once you free yourself from solver dogma, a new world opens up. You start leaning on things solvers can’t touch:

• Timing tells.
• Live reads.
• Popular poker tendencies.
• Human vs. human history.

And yes… if you’re a pure GTO-only grinder, chances are you’ve got a little Star Trek fan in you. Nothing wrong with that – but poker isn’t sci-fi. It’s flesh and blood.

Okay, let’s move on. The fifth (and penultimate) type of reg to understand in today’s era is the MDA reg – the Mass Data Analysis specialist. Over a decade ago, MDA lived in a grey area:

• Frowned upon.
• Hard to access.
• A few tech wizards quietly run scripts in the background.

Now? It’s mainstream. Entire courses (like Grade E of Carrot Poker School) are built around it. Data is data – and humans, for the most part, behave the same way everywhere.

• Regs are predictable across playing pools.
• Reg-vs-reg dynamics shift with stakes (but the lower you go, the less it matters).
• Uniformity always means exploitability.

The beauty of MDA is that you don’t need a nameplate on your opponent. You don’t need a HUD with 50k hands. You just need to know the type:

• This spot is overfolded → I bluff;
• This line is under-bluffed → I call;
• This sizing screams nutted → I fold.

That’s it – ain’t no second-guessing here. No mental gymnastics, just data-backed autopilot.

And that’s main reasons why MDA regs win:

• Confidence from evidence → They don’t tilt about “what if”. They trust the numbers.
• Works in anonymous pools → Perfect for environments like Zoom or sites without HUDs.
• Solid theoretical base → Most MDA grinders also understand GTO – they just use it as a skeleton and let the data add flesh.

The result? They print consistently, even without deep player-specific reads. Data is powerful – but it’s not a silver bullet. To really thrive, you need both:

• Practical EV against humans (real-world reads, psychology, adaptability);
• Theoretical grounding (so you understand why a spot works, not just that it does).

But here’s the problem: many low- to mid-stakes MDA players skip the theory part. They grab a playbook from a stable, copy a coach’s spreadsheet, or just memorize “auto-click” exploits without understanding the deeper logic. That’s when you see absurd patterns:

• Raising every single river small bet, regardless of context.
• Bluffing with hands that should just call and bank EV.
• Forcing aggression when the data doesn’t justify it.

At the end of the day they leak. And the lower the stakes, the more of these “bad MDA regs” you’ll run into.

Good, Bad, and Average MDA Regs

Also you need to know about fact that not all MDA regs are equal:

• Good ones → Blend data with theory, play dynamically, and print.
• Average ones → Over-rely on charts, sometimes solid, sometimes spewy.
• Bad ones → Click buttons blindly, creating massive holes in their strategy.

And spotting which type you’re up against is half the battle. Here’s the truth: If you’re playing NL100+ in 2025, you’re surrounded by MDA regs. They’re everywhere – often coming out of the same stables, working with the same datasets, and repeating the same moves. Countering them isn’t optional. It’s survival.

Think of it like this:

• Infestation of rats? → You buy traps.
• Infestation of MDA regs? → You need counter-strategies.

If you’re an MDA reg, congrats – you’re probably doing well. Data-driven play is the single most effective way to instantly boost your win rate in today’s climate. But don’t stop there. Don’t just be “the MDA guy”. Because when someone knows your dataset inside and out… your edges vanish.

The next evolution? The Ultimate (or Hybrid reg). The player who combines three key elements:

1. Theory

Understanding the game’s nuts and bolts: how EV functions in the objective sense, what makes a value bet profitable, when bluffing is correct, and the overall mechanics of the game.

2. Data

Knowing which spots are overfolded, underbluffed, overbluffed, or underbluffed. Understanding where you can deviate significantly from theory, where only minor adjustments are needed, and learning patterns and regimes to maximize EV.

3. Exploitation

Reading opponents in real time: their betsizing, tendencies, timing tells – essentially, human-versus-human detective work at the table. How sharp are your senses? How quick is your wit? These factors matter just as much as theory and data.

Even when you find the right balance, there’s always room to grow – improving one area can temporarily break your rhythm, requiring recalibration. Poker is a constant cycle of three steps forward, two steps back, and that’s the path to mastery.

The key is thoroughness: study, review hands, discuss with peers, and engage in proper poker education. Don’t just show up and expect to be good at all three elements – the right calibration is what allows you to wield them together effectively.

Aspire to be the all-round ultimate hybrid reg – someone who can combine theory, data, and real-time exploitation seamlessly. Avoid over-reliance on any single element:

• Don’t play only by instinct; it will only take you so far.
• Also don’t get lost in the GTO cave – immerse yourself in theory, but always keep EV as your guiding principle.
• If you work with mass data, remember it’s only part of the equation. You still need game theory understanding and sharp table sense to know when to deviate.

These three components are interwoven – inseparable, but together they make the ultimate player.

So, there you have it – the six distinct types of regs you’ll encounter at the tables:

• Reg-creational – skilled in spots, but mostly play for fun; exploit them cautiously;
• Aggro volatile reg – fearless and highly aggressive, but tilt-prone; a potential rocket if refined;
• ABC reg – conservative and one-dimensional; struggles to embrace good aggression;
• GTO reg – lost in solver minutiae; brilliant in theory but often forgets real-world EV;
• MDA reg – data-driven and methodical; powerful if properly backed by theory and mental game;
• The ultimate hybrid reg – the ideal: combines theory, data, and human exploitation seamlessly.

Each type still has its strengths, weaknesses, and areas for growth. Whether you’re trying to improve your own game or understand your opponents, knowing which reg you’re facing – or which you are – gives you a massive advantage.

Since 1 September, it’s the perfect time to kick off a productive, money-making autumn at the tables – sharpen your strategy, study your opponents, and take your game to the next level. Remember, the goal isn’t to become a copy of any one type. The ultimate reg is versatile, observant, and balanced, able to leverage all three pillars of poker: theory, data, and live reads.

So that was all for today! Take care, keep studying, and aim to be the hybrid reg: smart, data-driven, and ruthlessly exploitative. By the way, If you missed Chapter 1, where we explored the first 3 types of regs and set the stage for this deeper dive, don’t worry – you can catch up now!