Game Server Sliding Window Event Scoring for Impressive Play Identification
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Solution Overview
Problem
Current gaming technologies lack mechanisms to effectively identify and display impressive plays in competitive games beyond simple metrics like kills, failing to capture skillful actions such as saving teammates, precise shots, or critical objectives, which are not adequately represented in existing scoring systems.
Innovation Solution
A system where a game server maintains an event log with time-stamped actions, scores events based on various categories (e.g., high score, life saver, sharpshooter, shutdown), and uses a sliding window to aggregate scores, allowing for the identification and display of the most impressive play, which can involve multiple players or teams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If simple metrics like kills are used to score gameplay events, then the scoring system is easy to implement, but it fails to capture skillful actions such as saving teammates, precise shots, or critical objectives
Solution Approach 1:
The patent segments the gameplay evaluation into multiple independent categories (kills, deaths, assists, objectives, precision shots, saving teammates). Each category is scored separately with its own criteria, allowing the system to capture diverse skillful actions without requiring a single complex scoring metric. This segmentation enables comprehensive measurement while keeping each individual scoring criterion relatively simple and implementable.
2Adaptability or versatility
If third-party programs are used to record gameplay, then players can display their skills to others, but the programs require significant setup time and must be explicitly activated each time
Solution Approach 1:
The game system automatically performs the recording and identification of impressive plays without requiring player intervention. The server continuously monitors gameplay events, scores them according to predefined criteria, and automatically identifies and records impressive plays. This self-service approach eliminates the need for players to manually activate third-party recording software, reducing setup time and operational complexity while maintaining the ability to display skills.
3Reliability
If third-party programs record entire gameplay sessions, then all plays are captured, but the storage space required becomes quite large
Solution Approach 1:
The patent extracts only the essential information needed to identify impressive plays from the complete gameplay session. Instead of storing entire gameplay recordings, the system extracts and stores only the scored gameplay events and their metadata. This extraction approach maintains reliability by capturing all relevant play data while dramatically reducing storage requirements by eliminating redundant information from periods where nothing impressive occurs.
4Adaptability or versatility
If third-party programs are used to record gameplay, then impressive plays can be displayed, but any impressive plays are lost if the program is not explicitly activated
Solution Approach 1:
The system performs preliminary action by pre-defining scoring criteria and categories for identifying impressive plays before gameplay begins. The server is pre-configured with the rules for what constitutes an impressive play across multiple categories. This preliminary setup ensures that no impressive plays are lost, as the system is already prepared to recognize and record them automatically from the moment gameplay starts, without requiring any activation by the player.
5Productivity
If recorded videos are significantly edited to leave only impressive gameplay periods, then tedious content is removed, but this cannot be done manually in real time
Solution Approach 1:
The system uses feedback by continuously scoring gameplay events in real-time and using those scores to automatically identify and highlight impressive plays. As gameplay progresses, the server provides feedback about which plays are impressive based on predefined criteria, enabling automatic compilation of highlight reels without manual editing. This feedback mechanism resolves the contradiction by providing real-time identification capability that eliminates the need for complex post-game editing while maintaining high content quality.
Data Source
AI summary
In an approach, a game server records events that occur within a match of a video game played using a plurality of game clients. After the match has concluded, the game server scores the events according to a plurality of criteria corresponding a plurality of play of the game categories. A sliding window is passed over the events in a number of increments. During each increment, the score for each event that falls within the sliding window is aggregated for each of the categories. The game server then selects a play of the game category and determines the top aggregated score for that category. Once determined, the game server sends one or more instructions to the game clients which causes the game clients to display a replay of the events that occurred during the time window increment corresponding to the top aggregated score for the selected category.