Competition Result Analysis Using Probability Models
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Solution Overview
Problem
Existing methods for analyzing competition results fail to accurately estimate the pure ability of participants and the advantages/disadvantages of options used, as rankings are influenced by factors other than pure ability, such as game methods and option quality.
Innovation Solution
A system and method using a probability model to analyze competition results, which includes information about options and participant ranks, to determine parameters for pure ability and option advantages/disadvantages, employing Bayesian Analysis and Markov Chain Monte Carlo methods to estimate these parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ranking is provided based on competition results, then user attention and spirit of emulation are attracted, but accurate estimation of pure ability of each participant is not achieved due to influence from other factors
Solution Approach 1:
The patent segments the competition result into multiple independent components: pure ability parameter, option advantage parameter, and game method parameter. By dividing the ranking problem into these separate segments, each can be analyzed and estimated independently using probability models, thereby improving measurement precision without overwhelming system complexity
Solution Approach 2:
The patent transforms the competition result from a simple ranking into a multi-parameter probability distribution. By changing the parameter representation from single-dimensional rank to multi-dimensional parameters (ability, option advantage, game method), the system achieves more accurate pure ability estimation while managing complexity through structured parameterization
2Measurement precision
If simple ranking based on competition results is used, then ease of operation is maintained, but the influence of game method and option quality on ability estimation is not eliminated
Solution Approach 1:
The patent introduces probability models and parameter estimation algorithms as intermediary layers between the raw competition results and the final ability estimation. These intermediaries process and separate the various影响因素 (option quality, game method, pure ability), allowing accurate estimation without requiring users to directly manage the complexity of multiple influencing factors
Solution Approach 2:
The patent replaces the simple mechanical ranking system with a probabilistic modeling system. Instead of directly ranking based on raw results, the system uses probability distributions and statistical estimation to separate and evaluate different factors, achieving higher precision while maintaining operational simplicity through automated computation
Data Source
AI summary
A method and system for analyzing competition results is disclosed, the method comprising providing a probability model to analyze competition results including both information about options used for a competition process, and rank information of competition participants; and determining a first parameter about a pure ability of each competition participant, and a second parameter about advantages and disadvantages of the option used for the competition process by analyzing the competition results using the probability model, wherein the first and second parameters are determined by calculating a prior distribution of the second random variable, calculating a likelihood function of the second random variable, and estimating the first and second parameter through the use of the prior distribution of the second random variable and the likelihood function. This method and system can estimate the advantages and disadvantages of the options used for the process of competition, whereby the estimated advantages and disadvantages of the options are reflected on the design of competition or the adjustment of options when designing the competition such as the game, to thereby maximize the interest in competition.