Fantasy Lineup Multipliers for Dynamic Risk-Reward Thresholds
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Solution Overview
Problem
Conventional fantasy sports contest platforms lack flexibility in gameplay strategy, failing to accommodate participants' varying confidence levels and sports knowledge, leading to a homogeneous and less engaging experience.
Innovation Solution
A dynamic system that allows participants to adjust game parameters through user-selected multipliers, using statistical algorithms and real-time data to calculate performance thresholds and payout options, incorporating machine learning for adaptability and strategic depth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional fantasy sports platforms use static scoring mechanisms, then the system is simple to operate, but the adaptability to participant strategy and confidence levels is limited
Solution Approach 1:
The patent implements dynamic scoring mechanisms that adjust in real-time based on participant strategy, confidence levels, and game state. The system transitions from static predetermined scoring to dynamic adaptive scoring that responds to participant inputs and game developments, resolving the contradiction between adaptability and complexity by making the system flexible rather than rigid
Solution Approach 2:
The system allows participants to modify scoring parameters such as confidence levels and strategic weights during gameplay. By enabling parameter changes rather than fixing them beforehand, the system achieves adaptability to participant strategy while maintaining manageable complexity through structured parameter adjustment interfaces
2Ease of operation
If fantasy sports platforms provide fixed payout structures, then the system is easy to understand, but the engagement and strategic depth are reduced
Solution Approach 1:
The patent segments the payout structure into multiple components including base payouts, confidence-based modifiers, and strategic bonuses. This segmentation allows the system to remain understandable through clear component breakdown while achieving strategic depth through the interaction of multiple payout elements that respond to different participant decisions
Solution Approach 2:
Different portions of the payout structure provide different levels of complexity and strategic engagement. Basic payouts remain simple and easy to understand, while advanced strategic bonuses provide depth for experienced participants. This local differentiation of quality resolves the contradiction by making each part of the system appropriate to its function
3Adaptability or versatility
If the system allows dynamic adjustment of game parameters, then user engagement is enhanced, but the computational requirements and data processing load increase
Solution Approach 1:
The system performs preliminary calculations and pre-computes potential game states and payout scenarios before they are actually needed. By preparing computational frameworks in advance and caching results, the system reduces real-time computational energy consumption while maintaining dynamic adjustment capabilities when participants modify game parameters
Data Source
AI summary
The disclosed system discussed herein may include systems, methods, and devices for dynamically adjusting contest parameters for a fantasy sports contest. A performance indicator (e.g., passing yards, rushing yards, points scored, assists, rebounds, or goals) associated with a fantasy sports player may be received from a participant of a fantasy sports contest. A selection of a multiplier (e.g., selected from a predefined range that includes values from 2× to 20×) associated with the performance indicator may be received from the participant of the fantasy sports contest. A performance threshold for the fantasy sports player may be determined based on the multiplier. An award may be transmitted to the participant based on the performance threshold and an outcome associated with the selection.