Dynamic Well's Progression
See the story behind every string — optimize, adjust, win.
Software Details
A huge betting application that automates a structured, data-driven staking progression, records every bet and result, and helps users manage risk and analyze performance across sports markets.
Video Tutorial
Main Features
- Dynamic Wells is a betting module that implements a reworked, “dynamic” version of the Wells progression strategy.
- The software records and archives every progression with timestamps and cash-history so you can review wins, losses and long-term percentages.
- It provides real-time indicators (e.g. win probability, average odds, target quota to return to zero) and shows the current step and required stake.
- The tool works across sports (football, tennis, ping-pong, horse racing, etc.) and can be paired with prediction tools like Poisson to improve selection.
- Offers a detailed archive and cash-history view with controls to inspect past strings, undo the last entry, and reset progressions for analysis.
Software information
- Category: soccer
- Package: Progression Sports / Silver Sports / Silver Mix 2
- Launch date: 30 October, 2024
- Tutorial Completo
- Guida Rapida
How does the software work
- Before the first progression, the user sets initial parameters — base unit, target profit per string, and preferred sports/markets — which the software uses to compute stakes and progression rules.
- The workflow starts with a unit stake: you enter the selected outcome and its odds and the software updates the current progression step in real time.
- Instead of blind doubling, the module uses an oscillating unitary progression that increases or decreases the stake based on wins/losses and the software’s suggested target odds (e.g. 1.50, 1.33, 2.00).
- The program calculates and displays running metrics (percentage win per progression, average odds, net result) and lets you reset, undo the last entry, or inspect archived strings.
- You can run multiple strings for different sports or markets simultaneously and combine the module’s logic with external predictors (Poisson, other prediction engines) to find “value” odds and manage risk.