Skill Assessment System for Competitive Simulation Team Composition
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Solution Overview
Problem
Current computer simulations lack effective tools for users to improve their proficiency, particularly in competitive environments, where assessing and matching users by skill level is not efficiently managed, leading to suboptimal team compositions and individual performance.
Innovation Solution
A system that includes user devices and servers to administer skill assessment tests, collect metrics, and determine suitable roles for users by comparing their performance across multiple skill tests, allowing for team matching based on proficiency levels and optimal skill compositions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users participate in competitive computer simulations, then entertainment and competitive performance are improved, but lack of skill assessment tools results in suboptimal team compositions and individual performance
Solution Approach 1:
The system performs skill assessment tests before users join teams or tournaments. By evaluating users' skills in advance through multiple tests covering different aspects (aiming, movement, strategy, teamwork), the system creates a skill profile that can be used for optimal team composition without requiring continuous assessment during actual gameplay.
Solution Approach 2:
The system collects performance metrics from skill assessment tests and provides feedback to users about their strengths and weaknesses. This feedback mechanism includes skill rankings, comparative performance data, and recommendations for improvement, which helps users understand their skill level and guides team formation decisions.
2Measurement precision
If comprehensive skill assessment tests are administered to evaluate user proficiency, then user matching accuracy is improved, but time required for assessment increases
Solution Approach 1:
The skill assessment is divided into multiple independent tests, each evaluating a specific skill aspect (aiming accuracy, movement speed, strategic decision-making, teamwork coordination). Users can complete these tests at their own pace, and the system aggregates results from all segments to provide a comprehensive skill profile, balancing thoroughness with user convenience.
Solution Approach 2:
The system administers a comprehensive set of skill tests that may include more assessments than strictly necessary for basic matching. By providing excessive measurement coverage across multiple skill dimensions, the system ensures high measurement precision and creates detailed skill profiles that enable sophisticated team composition optimization.
3Productivity
If users are matched based on detailed skill profiles and role compatibility, then team performance is improved, but system complexity increases
Solution Approach 1:
The matching system divides team composition into distinct roles (e.g., leader, strategist, executor, support) and evaluates users against specific skill criteria for each role. By segmenting the matching process into role-based evaluations rather than treating the team as a monolithic unit, the system simplifies the complexity of optimizing overall team performance.
Solution Approach 2:
The system applies different matching criteria and skill thresholds to different roles within a team. Each role has specific skill requirements (e.g., leadership skills for team leaders, strategic thinking for strategists) that are evaluated independently. This localized evaluation approach allows for optimized team composition while maintaining manageable system complexity through role-specific rule sets.
Data Source
AI summary
Techniques are disclosed pertaining to determining a level of proficiency of a user at a computer simulation through the use of a plurality of skill assessment tests. Each skill assessment test can test a respective skill for use in the computer simulation. The techniques can also be used to train a user for the computer simulation and/or to determine team composition using roles for use in the computer simulation. In some aspects, skill assessment tests may incorporate multiple iterations in including a first base line iteration and subsequent iterations that differ between user devices. In some embodiments, metrics that are indicative of a level of proficiency of the user can be made with respect to metrics of other users to determine a user's level of skill with respect to various groups of other users.