Golf Swing Scoring Through Ten-Position Analysis and Training Feedback
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Solution Overview
Problem
Existing golf training methods lack effective means for users to measure their performance against professional golfers and provide actionable feedback for improvement.
Innovation Solution
A system and method for calculating a Swingscore by comparing user golf swing data to model player data sets, utilizing a launch monitor to capture club characteristics at key swing positions, and providing a visual feedback through a display module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If professional golfer swing data is displayed abstractly for comparison, then players can see their performance relative to pros, but the feedback lacks actionable training value and specific improvement guidance
Solution Approach 1:
The patent segments the golf swing into ten distinct positions (P1-P10) including address, takeaway, backswing, top of swing, downswing, preimpact, impact, release, and finish. Each position is captured and analyzed separately, allowing players to receive specific feedback on individual swing phases rather than abstract overall performance metrics.
Solution Approach 2:
The patent adds temporal and spatial dimensions to swing analysis by capturing club characteristics (velocity, height, face position) at multiple positions throughout the swing sequence. This transforms abstract performance comparison into detailed, actionable feedback across multiple dimensions of swing mechanics.
2Ease of operation
If comprehensive swing data at multiple positions is captured and analyzed, then actionable training feedback is provided, but system complexity and data processing requirements increase
Solution Approach 1:
The launch monitor is designed as a multi-functional device that captures multiple club characteristics (velocity, height, face position) across multiple swing positions simultaneously. This universal measurement capability provides comprehensive training feedback without requiring multiple separate devices or complex coordinated systems.
Solution Approach 2:
The system automatically captures, processes, and analyzes swing data without requiring manual intervention. The launch monitor and processing system work autonomously to generate SwingScores and training recommendations, reducing operational complexity despite the comprehensive nature of the analysis.
3Measurement precision
If SwingScore is calculated using multiple club characteristics and positions, then measurement accuracy improves, but calculation complexity and processing time increase
Solution Approach 1:
The system pre-establishes the ten swing positions and the specific club characteristics to be measured at each position. This preliminary structuring of the measurement framework allows for efficient, automated data collection and processing during actual swings, reducing calculation time while maintaining comprehensive analysis.
Solution Approach 2:
The system focuses on measuring specific key parameters (velocity, height, face position) at critical swing positions rather than attempting to measure all possible swing characteristics. This selective parameter approach maintains high measurement precision while optimizing processing efficiency.
Data Source
AI summary
In one embodiment, a method for training a golfer and providing a Swingscore includes, tabulating a plurality of model player data sets for a plurality of clubs to create a tabulated plurality of model player sets. The method further including capturing a user player data set for a plurality of clubs. The method further including comparing the user player data set of the plurality of model player data sets. The method further including determining a Swingscore based on the comparison. In one configuration, the Swingscore is determined by comparing two positions of a set of ten positions of the user player data set to corresponding two positions of the tabulated plurality of model player data sets.