Sports Play Analysis Device Using Temporal Correlation
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Solution Overview
Problem
Existing sports play analysis techniques can only analyze individual swings and fail to consider the interrelated nature of a series of plays, making it difficult to understand game dynamics and improve performance.
Innovation Solution
An analysis device and method that acquire and analyze data on play events from multiple users over a time interval, calculating the degree of correlation and estimating user relations based on temporal relations to analyze plays as a series or set.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If individual swing analysis is performed using detection data, then analysis simplicity is improved, but analysis completeness deteriorates because series or set relations are not captured
Solution Approach 1:
The patent combines multiple individual play analyses into a unified series analysis by integrating detection data from multiple users and multiple plays into a single comprehensive data structure that preserves temporal and relational information across the entire series of plays
Solution Approach 2:
The patent adds a temporal dimension to the analysis by arranging play events in time intervals and calculating temporal relations between plays, transforming the analysis from a single-point individual swing evaluation to a multi-dimensional series evaluation that includes time sequencing and inter-play relationships
2Measurement precision
If data from multiple users and multiple plays is analyzed as a series, then analysis completeness is improved, but computational complexity increases
Solution Approach 1:
The patent segments the complex series analysis into manageable components by dividing plays into discrete play events with specific attributes, allowing the system to process each event independently while maintaining their relational context through time interval calculations and correlation analysis
Solution Approach 2:
The patent transforms raw detection data into structured play event data with specific parameters (time intervals, play types, user identifiers), and further transforms this into correlation metrics that simplify the complex relationships into quantifiable degrees of correlation that are easier to process and analyze
Data Source
AI summary
Provided is an analysis device, including a processor that implements an acquisition function of acquiring data indicating play events that are defined based on motions when a plurality of users play a sport and arranged in a time interval, a calculation function of calculating a degree of correlation of plays of the plurality of users in the interval based on a temporal relation of the play events of the plurality of users, and a relation estimation function of estimating a relation of the plurality of users in the interval based on the degree of correlation.