Introducing ZiloBet, a football prediction and analysis platform that is currently in its early public phase.
ZiloBet was built as a data-driven system for analyzing football matches, with the aim of providing structured insights rather than promoting direct real-money betting. The platform focuses on how predictions are formed, how risk is represented, and how users can interact with football data in a transparent way.
Below is a breakdown of the main components and how they work.
Match analysis and prediction logicZiloBet generates match predictions using a combination of historical team form, recent results, goal patterns, and bookmaker odds structure. These inputs are processed to produce outcome probabilities across common markets such as 1X2, over/under goals, and both teams to score. The intent is not to claim certainty, but to summarize multiple data points into a consistent analytical output.
Confidence scoring systemEach prediction is accompanied by a confidence score. This score is designed to represent relative reliability based on data alignment, not guaranteed success. Higher confidence scores generally indicate stronger agreement between form trends and market signals, while lower scores indicate higher uncertainty. This allows users to differentiate between higher-risk and lower-risk scenarios.
Categorized picks (bankers, specials, goals, BTTS)The platform groups predictions into categories such as bankers, specials, over goals, and BTTS. These categories are not arbitrary labels. They are derived from confidence thresholds and market-specific logic. For example, banker picks represent selections with stronger statistical support, while specials may highlight value opportunities or less common market conditions.
Smart bet slip generatorZiloBet includes a configurable bet slip generator that allows users to generate multiple match selections based on their own criteria. Users can define parameters such as minimum confidence level, market type, and number of matches. The system then filters available predictions to produce a slip that matches those constraints. This feature is intended to demonstrate how different filters affect overall risk.
Free-to-play engagement mechanicsRather than requiring deposits, the platform includes free engagement mechanics where users can earn in-app credits through activity and participation. These credits are used to interact with features on the platform and are designed for experimentation and learning, not financial gain. This approach allows users to explore prediction behavior without monetary pressure.
Mobile-first web architectureZiloBet is built as a mobile-first web application, optimized for performance, clarity, and scalability. The interface prioritizes fast loading, structured presentation of data, and minimal friction when navigating between matches, leagues, and prediction categories.
Purpose and directionZiloBet is intended as an analytical and educational layer for football enthusiasts who are interested in how predictions are constructed and how risk can be represented numerically. It is not positioned as a betting operator, and it does not attempt to replace bookmakers or guarantee outcomes.
Feedback and discussionThe platform is still under active development. Feedback is particularly welcome on prediction methodology, confidence modeling, categorization logic, and overall system design. Input from users with interest in data analysis, modeling, or sports analytics is especially valuable at this stage.
Disclaimer:ZiloBet does not provide financial or betting advice. All predictions are probabilistic and should not be interpreted as guarantees. Football matches involve inherent uncertainty. The platform does not require or promote real-money wagering, and any in-app credits or engagement features are intended solely for entertainment, testing, and educational purposes. Users are responsible for how they interpret and apply any information provided.Thank you for reading. I’m happy to answer questions or discuss the technical ideas behind the project.