In-Play Betting Odds Adjustment via Real-Time Audience Feedback
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Solution Overview
Problem
In live sports betting, bookmakers face challenges in setting accurate and optimal odds for In-Play propositions in real-time, as they lack direct feedback from the betting audience's collective wisdom, leading to reduced frequency and flexibility in generating unique propositions, and increased risk due to reliance on historical data and AI systems.
Innovation Solution
A system that utilizes real-time data from skill game operators to adjust In-Play betting odds based on the collective predictive input from viewers, allowing for immediate recalculations and presentation of more accurate odds, thereby optimizing bookmaking returns and increasing engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If bookmakers set In-Play betting odds using historical data and AI systems without real-time audience feedback, then the odds setting process can be automated, but the accuracy and reliability of the odds are reduced due to lack of direct feedback from the betting audience
Solution Approach 1:
The patent implements real-time feedback loops where betting audience responses to In-Play propositions are immediately captured and used to adjust odds. The system continuously monitors betting patterns, audience engagement metrics, and proposition outcomes, feeding this data back to the odds calculation engine to dynamically refine odds accuracy while maintaining automation.
Solution Approach 2:
The patent introduces an intermediary layer between the AI system and final odds setting that processes real-time audience feedback. This intermediary component aggregates data from multiple sources including betting volumes, audience predictions, and live game statistics, then synthesizes this information to adjust odds before presentation to bettors.
2Productivity
If bookmakers increase the frequency of In-Play propositions to maximize profit, then more betting opportunities are created, but the risk increases due to lack of historical data on unique game situations
Solution Approach 1:
The patent applies preliminary action by pre-establishing risk parameters, validation rules, and odds adjustment thresholds before In-Play propositions are presented. The system pre-configures risk management protocols that automatically evaluate each unique proposition against established criteria, enabling high-frequency proposition generation while maintaining controlled risk exposure through pre-defined safety mechanisms.
Solution Approach 2:
The patent dynamically changes risk parameters based on real-time conditions. The system adjusts proposition acceptance criteria, odds margins, and exposure limits according to game context, audience behavior patterns, and historical performance data, allowing flexible risk management that adapts to each unique In-Play situation while maintaining high proposition frequency.
3Adaptability or versatility
If bookmakers rely on subjective judgment of live bookmakers to set odds under time pressure, then flexibility in creating unique propositions is maintained, but the speed and consistency of odds setting are reduced
Solution Approach 1:
The patent segments the odds setting process into distinct automated functions: proposition generation, real-time data collection, risk assessment, odds calculation, and presentation. Each segment is handled by specialized automated components that operate independently but coordinate through standardized interfaces, enabling both customization and high-speed execution without subjective judgment bottlenecks.
Solution Approach 2:
The system implements self-service by enabling automated proposition creation and odds setting that does not require human intervention. The AI-driven platform autonomously generates In-Play propositions, evaluates game state data, calculates optimal odds, and presents betting opportunities, completely replacing the need for subjective human judgment while maintaining adaptability through machine learning algorithms.
Data Source
AI summary
A skill game operator provides real time propositions to a viewing audience, and based on the input received from those propositions, comparable In-Play wagering propositions are able to be generated, and the odds of the In-Play propositions are able to be accurately adjusted based on the actual input received from the same participating audience the skill game operator's responses to the same propositions.