Pass Distribution Matrix Spine Visualization for Soccer Performance
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Solution Overview
Problem
Coaches and players in soccer face challenges in objectively measuring and improving player performance due to limited data, lack of Role Models, and subjective feedback, making it difficult to set and achieve measurable goals.
Innovation Solution
The system provides objective measurement and analysis of player performance using a pass distribution matrix, generating a 'spine' for the team to visualize passes and their effectiveness, and setting quantifiable goals based on elite player standards, enabling players to track progress and receive feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional subjective feedback methods are used to assess player performance, then coaches can provide qualitative guidance, but the measurement lacks objectivity and precision
Solution Approach 1:
The patent replaces traditional mechanical/manual performance assessment methods with automated computer vision and tracking systems. The system uses machine learning models to automatically detect and analyze player actions, passing the ball, and performance metrics without manual intervention, thereby achieving objective measurement while managing complexity through automation.
Solution Approach 2:
The patent introduces an intermediary assessment engine that processes raw tracking data and transforms it into meaningful performance metrics. This engine acts as a mediator between the complex data collection infrastructure and the simple user interface, filtering and interpreting data to provide objective feedback without exposing users to underlying system complexity.
2Measurement precision
If detailed granular data collection is implemented to improve performance analysis, then measurement precision increases, but the ease of operation decreases due to complex data processing requirements
Solution Approach 1:
The patent extracts only the most relevant performance metrics from the comprehensive data set collected by the tracking system. Instead of presenting all raw data, the system selectively extracts key metrics such as passing accuracy, movement patterns, and performance trends, making the information digestible and actionable for coaches and players without overwhelming them.
Solution Approach 2:
The patent segments performance data into distinct, manageable categories such as individual player statistics, team dynamics, and positional analysis. This segmentation allows users to focus on specific aspects of performance relevant to their needs, simplifying the user experience while maintaining access to granular data when required.
3Loss of information
If comprehensive player performance tracking is implemented, then information completeness improves, but the loss of time for data processing and analysis increases
Solution Approach 1:
The patent performs preliminary processing and analysis of performance data during the game itself rather than after. The assessment engine continuously processes tracking data in real-time, generating immediate feedback on player performance, which eliminates the need for lengthy post-game analysis and allows coaches to make timely adjustments.
Solution Approach 2:
The patent maintains continuous data collection and processing throughout the game, ensuring no performance information is lost. The system operates continuously to track player movements and actions, processing data in real-time streams rather than batch processing after the game, thereby maintaining information completeness while minimizing processing delays.
Data Source
AI summary
Systems and methods for assessing performance of a player or a team comprising a plurality of players are described. An example method includes receiving a pass distribution matrix corresponding to a number of completed passes within a field of play for one or more players of the plurality of players, selecting a particular player from the one or more players, and generating a spine for the team. In an example, generating the spine for the team includes producing a visual representation of the field of play that illustrates a position of the particular player and at least one other player within the field of play, and automatically varying, on the visual representation, a thickness of each of a plurality of connecting lines between the particular player and the at least one other player based on the number of completed passes for the particular player.