Introduction

Introduction

In the world of modern poker gaming, the fusion of data analytics and statistical insights has become an essential strategy for players seeking a competitive edge and to refine their gameplay.

While there are a number of software producing all kind of pre-defined and pre-formatted poker statistics, those numbers generally form a tedious list of static data, making difficult to efficiently apprehend and memorize them.

Texas Miner supports the core functionalities a robust analysis tool must provide:

· Data Collection: Allow for collection of relevant data about any player’s gameplay logged in the history files.

· Provide key statistical metrics forming the building blocks for understanding playing styles and tendencies such as: VPIP (Voluntarily Put money in Pot), PFR (Pre-Flop Raises) and more.

· Range Composition: A must in modern poker where the player has to think “range” instead of hand.

Texas Miner goes beyond the competition by allowing to dynamically and bi-directionally query the data source and show the reflection of any change on all other variables simultaneously.

This capability is Texas Miner’s strong differentiator.

Basics

Texas Miner imports hands histories into a database and is then able to produce a dynamic UI that will allow the user to simulate different configurations or scenarios in a “what-if?” approach.

Variables and states

A large number of discrete variables can be extracted from the database, such as: player’s seat, player’s first action on the flop, hand showdown, etc.

A variable contains several (at least two), mutually exclusive, states. This means that the sum of all states probabilities is always 1.

A powerful tool

To get an idea of how powerful Texas Miner is, just consider the “Flop” view, which reports how the player is acting on the flop, given the board, his hand, and the preflop action.

This view is made of 9 variables of 2 to 5 states each.

Texas Miner makes it possible to ask 14,400 (2*4*3*2*2*2*3*5*5) “atomic” questions or queries through this simple view, where a query is defined when a state is set for every variable.

And this number even grows much higher if we account for partial configurations, where only some variables have a state set, or excluded, which actually results in a sum or combinations of “atomic” questions.

Other views propose even more possible queries.

This is how the high complexity is hidden from the user thanks to a graphic interface that lets the user easily ask the few queries he is most interested in, while ignoring the details behind and the exploding combinatory.