FAIRWAY INTELLIGENCE: Enhancing Golf Performance with Digital Twins and Data-Driven Decision-Making

Overview

This paper introduces a groundbreaking Decision Support System (DSS) for golf, utilizing digital twins to revolutionize in-game tactics and long-term training. The system integrates player profiles with geospatial data of golf courses to create realistic simulations. These simulations aid players of all levels in enhancing their performance.


Key Features

  1. Shot Recommendation Engine: Provides tactical in-game recommendations tailored to a player’s position, skill, and risk preferences.
  2. Training Information System: Identifies areas for skill improvement and provides strategic guidance for long-term development.

Digital Twin Integration

  • Player Digital Twin: Captures metrics like shot distance, club speed, and swing precision.
  • Course Digital Twin: Maps detailed geospatial data, including fairways, hazards, and elevation changes.

The integration of these components allows the DSS to model shots, optimize decisions, and evaluate performance under various conditions.


Methodology

  • Physics-Based Simulations: Models realistic shot trajectories, accounting for terrain, club type, and player skill.
  • Markov Decision Process (MDP): Evaluates optimal strategies and guides shot selection based on dynamic course conditions.

Results

  • Risk-neutral agents provided the most consistent performance across simulations.
  • Aggressive strategies showed higher rewards but increased variability, while defensive strategies minimized risk.

The DSS demonstrates significant potential to enhance decision-making in golf, offering tailored insights to optimize both tactical and strategic elements of play.


Applications

  1. Game Play Optimization: Real-time shot recommendations improve in-game decisions.
  2. Training Plans: Customized objectives focus on areas like precision or distance to maximize performance improvements.
  3. Accessibility: The DSS is available via an intuitive GUI and integrates with wearable devices for seamless adoption.

Conclusion

The DSS leverages data-rich digital twins and simulations to provide actionable insights for players. Future developments include integrating real-time tournament analytics and enhancing physics engines for even greater realism.

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