Reviewed existing RL studies in sports.

Identified gaps: small datasets, poor real-world validation, low adaptability.

Use real sports data and simulated environments (OpenAI Gym / Unity ML-Agents).

Apply data augmentation to overcome limited datasets.

Compare RL models with traditional methods.

Techniques: A/B Testing, Monte Carlo Tree Search (MCTS).

Environment