Basketball Shot Placement Normalization for Performance Evaluation
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Solution Overview
Problem
Existing systems for evaluating basketball shooting performance struggle to accurately assess shot placement and shooter tendencies due to variations in shot angles and locations on the court, making it difficult to provide effective feedback for improving shooting skills.
Innovation Solution
A system that uses cameras and processors to capture and analyze shot trajectories and placements, normalizing data to a common reference point to evaluate shot placement relative to a 'guaranteed make zone' across different court locations, and generates placement maps to identify shooter tendencies and provide feedback for adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If shot placement is tracked using fixed hoop coordinates, then shot placement data can be captured, but accurate assessment of shooter tendencies is compromised due to variations in shot angles and locations
Solution Approach 1:
The system transforms shot placement data from fixed hoop coordinates to a normalized coordinate system that accounts for shot angle and location. This parameter transformation allows shots from different positions and angles to be evaluated consistently relative to the guaranteed make zone, resolving the contradiction between measurement precision and adaptability
Solution Approach 2:
The system introduces an intermediary normalization process that acts as a mediator between raw shot placement data and performance evaluation. This intermediary layer converts diverse shot data into a unified framework, enabling accurate assessment across varying shot conditions without sacrificing precision
2Adaptability or versatility
If multiple camera angles are used to capture shots from different locations, then coverage of all court positions is improved, but data normalization complexity increases
Solution Approach 1:
The system implements a universal normalization algorithm that handles multiple camera angles and court locations through a single processing framework. This multi-functional approach consolidates what would otherwise require separate processing paths, reducing overall system complexity while maintaining comprehensive coverage
Solution Approach 2:
The system applies consistent parameter transformation rules regardless of camera angle or shot location. By using uniform mathematical transformations to convert all shots into the normalized coordinate system, the system avoids creating separate complex processing pipelines for different camera views
Data Source
AI summary
Systems and methods relating to evaluating the performance of a person playing basketball are described. The systems and methods can be used to provide an evaluation sequence that can determine and evaluate the performance level of a person at one or more basketball skills. The evaluation sequence for the person can include a first sequence of actions that are the same each person being evaluated for a particular skill and a second sequence of actions that is based on the results of the first sequence and may be different for each person. Once the first and second sequences have been completed by the person, the system can determine a performance level for the person for the skills being evaluated.