Server Event Data Segmentation for Online Gaming Prediction

The system segments the overwhelming event data into discrete, structured coordinates within a table format. Each coordinate represents a specific outcome possibility (e.g., specific score combinations, player statistics ranges), allowing the system to process data in manageable units rather than as an undifferentiated mass. This segmentation enables efficient tracking and enumeration of numerous possibilities without overwhelming the system.

The patent transforms complex multi-dimensional event data into a two-dimensional table structure with rows and columns representing different outcome parameters. By mapping numerous possibilities onto this dimensional framework, the system can efficiently organize, store, and process data that would otherwise require complex hierarchical or nested structures, thereby improving processing efficiency while handling large quantities of event data.

The system implements feedback mechanisms by comparing user predictions against actual event outcomes that occur. When events are tracked and outcomes recorded, the system can evaluate which user predictions were accurate and provide feedback for future prediction accuracy assessment. This feedback loop enables the system to identify reliable predictors even as the volume of data grows, by continuously validating predictions against actual results.

The patent replaces manual or mechanical methods of evaluating predictions with automated computational systems that can process and compare large volumes of prediction data against actual outcomes. This substitution enables efficient identification of accurate predictions by using algorithmic comparison and statistical analysis rather than manual evaluation, thereby reducing the difficulty of detecting accurate predictions as data volume increases.