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# Methodology

# 1. GTO Solutions Library

To build our GTO solutions, we use HoldemResources Calculator (HRC) (opens new window).
HRC is considered an authoritative solver in the poker industry because:

  • it is widely used by poker schools, professional players, and coaches,
  • it has a long history and reputation for accuracy.

HRC provides reliable Nash Equilibrium calculations, making it a trustworthy source of "pure theory".

We provide two types of solutions in the Library:

# GTO (Pure Solver Output)

  • These are the unaltered outputs directly from the solver.
  • They contain all original mixed frequencies (e.g. 37% raise, 63% call).
  • This format allows users to study poker theory at its deepest and most accurate level.

# Simplified GTO

  • The same solutions, but with rounded frequencies in 25% steps (0%, 25%, 50%, 75%, 100%).
  • The overall strategic frequencies of the ranges remain nearly unchanged.
  • This format makes the charts more "human-friendly" and easier to memorize and train.

# 2. Onboarding Ranges & Trainings

When new users register at Freebetrange, they can choose their game type during onboarding (Cash, MTT, Spin & Go).
Based on this selection, they receive a preloaded set of ranges and trainings that help them start learning immediately.

# Source of the Onboarding Ranges

  • These starting charts are derived from our Simplified GTO solutions.
  • We filtered the game situations by frequency, selecting the most common and relevant scenarios.
  • Frequencies in these charts are rounded (25% steps), making them easier to study and train without losing strategic accuracy.

This ensures that new players have direct access to the core of GTO strategy right from the start.

# Structured Trainings

The preloaded trainings are grouped by situation type, for example:

  • RFI (Raise First In),
  • BB Defense,
  • 3-bets,
  • and other key preflop spots.

This allows users to practice specific areas of their game with our Trainer and improve efficiently.

# 3. Expert Input

All calculations and configurations are prepared with the involvement of professional players and coaches. They:

  • define the calculation parameters (stack depths, bet sizes, decision tree structures),
  • review solver outputs for practical applicability,
  • select and adapt the most relevant spots for onboarding ranges,
  • structure the training modules by situation type.

This ensures that all Freebetrange content is backed by real playing experience and represents a structured learning material of poker theory.

# 4. Data Relevance

We review all educational content, including the Library and onboarding ranges, every 6 months to keep it accurate and relevant.
This ensures that players always study from materials aligned with current poker theory and best practices.

# 5. Custom Ranges

In addition to the Library and onboarding configurations, Freebetrange allows users to create their own ranges with the built-in Editor.

  • Full control over strategy — players can design ranges that fit their personal approach to the game.
  • Effective exploitation of opponents — custom ranges can be used to build exploitative adjustments for specific situations.
  • Learning to think in ranges — by creating their own charts, players train their strategic thinking and improve their understanding of poker theory.

Custom ranges are a powerful educational tool, helping players not only to study preflop theory but also to actively practice creating and testing strategies.

# 6. MDA

MDA ranges are built from a large real-game dataset and a dedicated reconstruction pipeline designed for preflop population modeling.

# Data Source

  • We use a dataset of 300M+ real cash-game hand histories.
  • Data is pooled by key game conditions (stakes, table size, ante, room groups) and by player archetype.
  • To keep population tendencies up to date, the MDA dataset is refreshed every 6 months.

# Core Challenge: Showdown Bias

Raw showdown frequencies are not enough to build accurate population ranges, because many hands are folded before showdown and remain hidden.
If we relied only on revealed hands, the final frequencies would be systematically distorted.

# Reconstruction Pipeline

To estimate realistic preflop ranges, we use a statistical pipeline that:

  • reconstructs hidden hand distributions from observed context and actions,
  • uses showdown hands as one signal (not as the only source of truth),
  • applies bias correction and combinatorial consistency checks,
  • applies smoothing and validation to keep ranges stable and practical.

As a result, MDA ranges are designed to reflect how different player archetypes actually play preflop in real games.

# 7. Disclaimer

All solutions are provided for educational purposes only.
Freebetrange does not guarantee winnings or specific results in poker.

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