Fantasy Sports Salary Determination via Weighted Algorithm
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Solution Overview
Problem
Existing manual approaches for determining fantasy sports athlete salaries are inaccurate, time-consuming, and impractical for large-scale online fantasy sports systems, as they require extensive human effort and are prone to errors, especially given the high frequency and volume of contests and athletes involved.
Innovation Solution
An automated system that determines fantasy sports athlete salaries using a weighted combination of factors such as fantasy point projection, past performance, and ownership, with the ability to adjust weights and incorporate global and individual salary floors to ensure accuracy and fairness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual approaches are used to determine fantasy salaries, then accuracy can be maintained through human judgment, but the process becomes time-consuming and impractical for large-scale systems
Solution Approach 1:
The system performs self-service by automatically determining fantasy salaries using computational algorithms that process performance data, ownership statistics, and salary cap constraints without requiring manual human intervention for each salary determination
Solution Approach 2:
The patent replaces the manual mechanical process of salary determination with an automated computational system that uses algorithms to calculate salaries based on multiple factors including player performance, ownership rates, and salary cap optimization
2Productivity
If automated systems are used to determine fantasy salaries, then speed and efficiency are improved, but accuracy and fairness may be compromised
Solution Approach 1:
The system changes parameters by incorporating multiple variables into the salary determination algorithm, including performance metrics, ownership statistics, and salary cap constraints, to achieve both speed and accuracy simultaneously
Solution Approach 2:
The patent implements feedback mechanisms where the system iteratively adjusts salary allocations based on optimization goals, ensuring that the automated determination achieves fairness and accuracy while maintaining high productivity
3Ease of operation
If contestants draft identical teams, then the drafting process is simplified, but it becomes difficult to rank contestants and award prizes
Solution Approach 1:
The patent applies local quality by making each athlete have unique fantasy salary characteristics based on their individual performance data and ownership statistics, ensuring that while the drafting process remains simple, each selection has distinct value that enables reliable ranking
4Adaptability or versatility
If fantasy salaries are set manually, then flexibility in adjustment is maintained, but the process is prone to errors and not scalable
Solution Approach 1:
The system implements dynamics by allowing fantasy salaries to be automatically adjusted based on changing conditions such as player performance updates, ownership rate changes, and salary cap modifications, providing both flexibility and reliability through algorithmic adaptation
Data Source
AI summary
Disclosed are systems and methods for improving interactions with and between computers in content generating, searching, hosting and/or providing systems supported by or configured with personal computing devices, servers and/or platforms. The systems interact to identify and retrieve data within or across platforms, which can be used to improve the quality of data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide systems and methods for automatic fantasy sports data analysis, including analysis of data to equalize player attractiveness in contestant composition of a fantasy sports team.