Dynamic Keno Returns Table for Real-Time Event Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing gaming and keno systems are one-dimensional, lacking interaction and strategy, and fail to integrate real-time information from events like sporting matches, leading to a less engaging user experience.
Innovation Solution
A system and method that maps results of timed events, such as sporting matches, to a number set, allowing users to select numbers based on events like goals scored or time periods without scoring, with a variable returns table for rewarding matching numbers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed returns table is used in conventional keno, then the system is simple to operate, but the user experience becomes one-dimensional and lacks interaction
Solution Approach 1:
The patent transforms the static, fixed returns table into a dynamic system where the returns table is generated in real-time based on event data. The system continuously updates the returns table as events unfold, allowing the game to adapt to live outcomes and creating an interactive experience where users can engage with ongoing events rather than merely waiting for predetermined results.
Solution Approach 2:
The system implements feedback by using real-time event data to influence the game outcomes and returns. Event information (such as sports match results, stock market movements, or other live data) feeds into the system, dynamically adjusting the returns table and drawn numbers based on actual event progression, creating a closed-loop interactive experience.
2Adaptability or versatility
If real-time event information is integrated into the keno system, then user engagement improves, but the system complexity increases
Solution Approach 1:
The patent introduces an intermediary component that bridges event data sources and the keno game system. This intermediary layer processes and translates real-time event information into game-relevant parameters, managing the complexity of data integration while maintaining the core keno gameplay. The intermediary handles data normalization, filtering, and transformation, isolating the game logic from the complexity of real-time data processing.
Solution Approach 2:
The system is designed with universal components that can handle multiple types of events and data sources through a common architecture. The returns table generation mechanism, drawn number selection, and outcome determination are implemented as reusable modules that can work with various event types (sports, finance, entertainment), reducing overall system complexity through standardization and multi-functionality.
3Adaptability or versatility
If a variable returns table is implemented based on event outcomes, then customization and dynamism increase, but the difficulty of detecting and measuring outcomes increases
Solution Approach 1:
The system performs preliminary actions by pre-defining the structure and parameters of the variable returns table before events begin. The framework for outcome determination, including the mapping between event results and game outcomes, is established in advance. This allows the system to dynamically adjust returns based on events while maintaining clear, pre-established rules for outcome measurement and determination.
Data Source
AI summary
The disclosed technology relates generally to a system and methods for matching timed incidents in an event with a number set. The system and methods may compare user-selected numbers to other numbers, such as those representing minutes in which incidents occur during an event having a duration. An incident can correspond to a time during which no goals are scored and/or other actions do not occur. Advantageously, the system and methods may provide for fuller and more interactive user experiences.