AI Sports Betting Odds Engine for Dynamic Profit Retention Balance
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Solution Overview
Problem
In the sports betting industry, operators face challenges in setting odds that balance profitability with maintaining customer interest and retention, as fixed odd wagers often lead to long-term player losses, and adjusting odds to incentivize players results in some loss to the operator.
Innovation Solution
The implementation of an AI-driven system that uses machine learning and algorithms to dynamically adjust odds in real-time based on current and historical data, combining odds from multiple algorithms, and incorporating user behavior analysis to maximize user interest while managing risk and profit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed odd wagers are used, then profitability is maintained, but player retention and engagement deteriorate
Solution Approach 1:
The patent applies dynamics by transitioning from fixed odds to dynamically adjusted odds that change in real-time based on player behavior, event progress, and predictive analytics. The system continuously monitors player activity and adjusts wagering parameters accordingly, allowing the odds to adapt to current conditions rather than remaining static, thereby maintaining both profitability and player engagement
Solution Approach 2:
The patent implements feedback mechanisms where player behavior data is collected, analyzed, and used to adjust odds and wagering parameters. The system provides feedback to players through personalized offers and adjusts the betting environment based on observed player responses, creating a closed-loop system that optimizes both retention and profitability
2Adaptability or versatility
If odds are adjusted to incentivize players, then player engagement improves, but operator profit margins deteriorate
Solution Approach 1:
The patent applies local quality by providing personalized odds and incentives to specific player segments rather than uniformly adjusting odds for all players. The system identifies different player types and behaviors, then applies tailored wagering conditions to each segment, allowing engagement enhancement for active players while maintaining profit margins through selective incentive application
Solution Approach 2:
The patent utilizes parameter changes by dynamically modifying wagering parameters such as odds, bet limits, and payout structures based on real-time player behavior and predictive models. The system adjusts these parameters continuously to optimize the balance between player engagement and operator profitability, rather than using fixed odds throughout
3Adaptability or versatility
If real-time odds adjustment is implemented, then player retention improves, but system complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex odds adjustment system into separate functional modules: data collection, predictive analytics, odds calculation, and real-time adjustment. Each module handles a specific aspect of the process, making the overall system more manageable and maintainable while enabling sophisticated real-time adjustments
Solution Approach 2:
The patent introduces intermediary components such as predictive analytics models and data processing layers that mediate between raw player behavior data and final odds adjustments. These intermediaries simplify the relationship between data input and output, making the complex real-time adjustment process more manageable and scalable
Data Source
AI summary
A system for wagering on outcomes of a live sporting event. The system further includes using AI to balance itself between how much it will lose bets to encourage game players to bet more, ultimately to win more profit and gain a larger game player user base. This allows the system to reduce immediate profits in exchange for long term profits due to a larger market share.