Historical Playthrough Matchmaking for Fair Asynchronous Competition
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Solution Overview
Problem
Existing online gaming systems struggle to match players with similar skill levels and availability for competitive play, leading to unfair matches and reduced player engagement.
Innovation Solution
Implementing historical playthrough data to simulate real-time competition by using recorded gameplay of previous players, combined with skill level assessments based on segmented ratings, to facilitate fair and engaging matches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional real-time player matching is used, then players can compete in synchronous gameplay, but it becomes difficult to find players with similar skill levels and availability
Solution Approach 1:
The system records and stores historical gameplay data in advance, creating a library of pre-recorded playthroughs that can be retrieved and matched with current players. This preliminary action allows the system to have ready-made opponents available immediately, eliminating the need to wait for real-time player availability while maintaining skill level matching through systematic evaluation of historical performance data.
2Measurement precision
If historical playthrough data is used to simulate real-time competition, then player matching accuracy improves, but the system complexity increases
Solution Approach 1:
The skill assessment system is divided into separate modular components: historical performance data collection, skill level calculation algorithms, player matching logic, and gameplay simulation. Each module handles a specific aspect of the matching process independently, making the overall complex system more manageable and maintainable while achieving accurate skill-based matching.
Solution Approach 2:
The patent introduces intermediary elements including skill level ratings that mediate between raw gameplay data and player matching decisions, and matchmaking algorithms that serve as intermediaries between historical data and current player selection. These intermediaries simplify the complexity by providing structured layers of abstraction between different system components.
3Reliability
If segmented skill assessment is implemented, then fair competition is achieved, but computational requirements increase
Solution Approach 1:
The skill assessment system evaluates multiple factors including win/loss records, average gameplay performance, and historical match outcomes, but selectively applies different levels of analysis based on available data and matching needs. The system performs comprehensive analysis when necessary for accurate matching but can use simplified assessments when sufficient matching confidence is already achieved, balancing computational effort with fairness requirements.
Data Source
AI summary
Disclosed subject matter including methods, computer systems, and computer-readable media for selecting users to pair for a real-time user of interactive online applications, including skill-based video games. In some examples, when there are not enough other real-time users to pair with the real time user, the real-time user can be paired with a simulated user based on historical playthrough data generated by a prior game session with another user. Various techniques for assessing skill level of users, providing a historical playthrough experience for the real-time user, and selecting game content based on historical records selected based on comparing skill of the real-time user and other real time or historical playthrough users are disclosed. Data structures and techniques for efficiently identifying comparable historical records based on the assessed skill of the real-time user are disclosed.