Quarterback Decision Analysis via Interactive Simulation

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Solution Overview

Problem

Assessing and improving the decision-making skills of American football quarterbacks in fast-paced scenarios is challenging due to the difficulty in objectively evaluating their cognitive abilities and learning potential, especially considering the varied skill levels and offensive schemes across different schools and teams.

Innovation Solution

A teaching and evaluation application with modules like Gameplay, Learning Center, and Insights that uses interactive simulations to measure and improve decision-making skills, incorporating a unique formula to calculate a quarterback intellect (QBi) score based on decision time, situational importance, and game context, providing predictive analysis for coaches and scouts.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional subjective evaluation methods are used to assess quarterback decision-making, then the evaluation process is simple and quick, but the measurement precision and objectivity are insufficient

Engineering Contradiction:

Improvedecision-making evaluation precisionVSAvoidevaluation system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent replaces subjective human evaluation with an automated computer-based evaluation system that uses machine learning algorithms and predictive models to objectively assess quarterback decision-making. The system substitutes mechanical/manual assessment with automated digital processing, capturing metrics like decision time, accuracy, and learning potential through software analysis of simulation gameplay data.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces a computer-based simulation environment as an intermediary between the quarterback and the evaluation process. This intermediary captures detailed performance data that would be impossible to obtain through direct observation, using the simulation as a mediator to translate complex cognitive decisions into measurable metrics for objective assessment.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If comprehensive data collection and analysis systems are implemented to objectively evaluate quarterbacks, then measurement precision improves, but the device complexity and implementation difficulty increase

Engineering Contradiction:

Improvecognitive ability evaluation precisionVSAvoidsystem implementation ease

Core Design Contradiction:

Measurement precisionVSEase of manufacture

Solution Approach 1:

The patent creates a multi-functional evaluation system that simultaneously assesses multiple quarterback attributes (decision time, accuracy, learning potential, cognitive abilities) through a single integrated platform. The system serves multiple purposes: evaluating current performance, predicting future potential, identifying training needs, and comparing players, thereby simplifying implementation despite comprehensive measurement capabilities.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system employs machine learning algorithms that automatically process and analyze collected data without requiring manual intervention for each assessment. The predictive models self-adjust and improve through repeated use, reducing the need for complex manual calibration and making the system easier to implement and maintain while maintaining high measurement precision.

Inventive Principle:

Principle #25Self-service

3Productivity

If repetitive training and detailed analytics are provided to improve quarterback skills, then learning potential and decision-making abilities improve, but the time and resource investment increase

Engineering Contradiction:

Improvedecision-making skill developmentVSAvoidtraining time investment

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent implements continuous feedback loops where the system provides real-time and post-session analytics to quarterbacks about their performance metrics, decision patterns, and areas for improvement. This feedback mechanism enables targeted practice that maximizes skill development efficiency, allowing quarterbacks to focus training time on specific weaknesses identified by the system rather than generic repetitive drills.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system uses predictive analytics to identify future performance trends and potential issues before they manifest in actual gameplay. By providing preliminary insights into learning potential and cognitive ability trajectories, the system enables proactive training interventions that prevent problems rather than merely reacting to them, optimizing the use of training time and resources.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20230419857A1Quarterback decision making and learning potential analyses and predictions

Publication Date: 2023.12.28 CRUCIBLETECH INC

AI summary

The present disclosure presents systems and methods for analyzing a user's cognitive abilities related to decision-making in fast-paced scenarios. One such method comprises inputting, by the computing device, the one or more matrix metrics into a predictive model of a learning potential for the user; executing, by the computing device, the predictive model of the learning potential of the user; predicting, by the computing device using the predictive model, the learning potential of the user; and outputting, by the computing device, the predicted learning potential of the user.