Virtual Event Segment Biasing via Audience Feedback
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Solution Overview
Problem
Current systems for generating virtual sporting events lack the ability to effectively manipulate outcomes based on audience input, leading to a static and unengaging experience for users.
Innovation Solution
A method that identifies valid event segments, determines outcome categories, and biases the selection of virtual event segments based on audience input, incorporating historical data and programmed objectives to create dynamic and interactive virtual sporting events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the selection of virtual event segments is based purely on random or fixed algorithms, then the system is simple to operate, but the audience engagement and participation are reduced due to lack of interactivity
Solution Approach 1:
The system receives audience input (votes, preferences, or control signals) and uses this feedback to dynamically adjust the selection of virtual event segments. The outcome manipulation module modifies the probability distribution of segment selection based on real-time audience feedback, creating an interactive loop that enhances engagement while maintaining systematic control
Solution Approach 2:
The system transitions from static, predetermined segment selection to dynamic selection that adapts in real-time based on audience input. The probability weights assigned to different event segments are continuously adjusted during the virtual sporting event based on audience preferences, making the system flexible and responsive
2Adaptability or versatility
If the system manipulates outcomes based on real-time audience input, then audience engagement and participation increase, but the system complexity increases due to additional processing requirements
Solution Approach 1:
The outcome manipulation module serves multiple functions: it receives audience input, processes preferences, adjusts probability distributions, and selects event segments. This multi-functional approach consolidates what could be separate complex systems into a single integrated module, managing complexity through functional consolidation
Solution Approach 2:
The system manipulates the probability parameters of segment selection rather than fundamentally changing the selection mechanism. By adjusting numerical weights and probabilities within an existing framework, the system achieves complex adaptive behavior through simple parameter modifications rather than structural overhauls
3Adaptability or versatility
If valid event segments are biased to obtain a predetermined proportion of desired outcomes, then the virtual event becomes more engaging and responsive to audience input, but the randomness and authenticity of the sporting event are reduced
Solution Approach 1:
The system applies partial manipulation by adjusting only the probability distribution of segment selection rather than completely determining outcomes. The biasing maintains some degree of randomness and unpredictability while incorporating audience preferences, achieving engagement without completely sacrificing authenticity
Solution Approach 2:
The system modifies the probability parameters of segment selection to reflect audience preferences while maintaining the underlying random selection process. By changing numerical weights rather than the fundamental selection mechanism, the system preserves element of chance and authenticity while achieving desired outcome biasing
Data Source
AI summary
Provided are systems and processes for manipulating outcomes of virtual sporting events. An example method comprises identifying a set of valid event segments for a given time segment of a virtual sporting event. An outcome category is determined for each of the valid event segments, which indicates an outcome of a play corresponding to the valid event segment. Audience input is obtained over a network from a plurality of client devices associated with a plurality of audience members. The audience input indicates a desired outcome for the given time segment. A valid event segment is then selected as a virtual event segment for the given time segment based on at least the desired outcome. Selection of the virtual event segment may comprise biasing the set of valid event segments to obtain a predetermined proportion of valid event segments with outcome categories corresponding to the desired outcome.