Real-Time Event Data Clustering for Live Sports Betting

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Solution Overview

Problem

Conventional sports betting systems fail to provide unique interactions with live data, relying on post-event data for payouts and lacking real-time engagement.

Innovation Solution

A computer-implemented method that receives real-time event data, determines statistic categories, calculates weighted categories, clusters statistics, and updates them based on changes, allowing users to make skill allocation point selections for real-time score calculations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If conventional sports betting systems are used, then users can place bets on outcomes and collect payouts, but the system cannot provide unique interactions with live data and relies on post-event data gathering

Engineering Contradiction:

Improveinteraction with live dataVSAvoiddata gathering time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system pre-calculates and displays predicted statistics and outcomes before the event concludes, allowing users to make betting decisions in real-time rather than waiting for post-event data. The interface proactively presents relevant statistical information and predicted values during the event, enabling immediate user interaction with live data.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously updates predicted statistics and outcomes based on real-time event data, providing dynamic feedback to users during the event. This feedback mechanism allows users to see how live event data affects predicted values and make informed betting decisions accordingly, creating an interactive loop between live data and user decisions.

Inventive Principle:

Principle #23Feedback

2Ease of operation

If conventional micro-betting on statistics is used, then users can bet on whether stats exceed or fall below lines, but the system lacks real-time engagement and unique user interactions

Engineering Contradiction:

Improvereal-time engagementVSAvoidbetting system complexity

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The system segments statistical data into multiple predicted categories (e.g., total points, total rebounds, total assists) and allows users to make independent betting decisions on each category. This segmentation simplifies the betting interface while enabling diverse real-time interactions, as users can focus on specific statistical aspects rather than managing a complex monolithic betting system.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The betting system dynamically adjusts predicted statistics and betting parameters in real-time based on live event data. The interface adapts to changing event conditions, updating predicted values and available betting options moment-to-moment, which enhances real-time engagement while maintaining operational simplicity through automated adjustments.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS20240403330A1Interactive systems and methods using clustered real-time event data

Publication Date: 2024.12.05 WINCAST CORP

AI summary

A system may receive real-time event data for a real-time event. A system may determine statistic categories from the real-time event data. A system may calculate weighted statistic categories using weight functions. A system may cluster the weighted statistic categories into clustered real-time statistics. A system may receive skill allocation point selections. A system may calculate a real-time score using the clustered real-time statistics and the skill allocation point selections.