A new study has utilized explainable artificial intelligence (XAI) to analyze golf swing characteristics and their impact on ball carry distance. This approach identifies key biomechanical factors determining "carry" distance (the distance the ball travels in the air before landing), offering deeper insights than traditional, often black-box, AI models. The research focused on how clubhead speed, angle of attack, and club path influence the final outcome, providing valuable information for golfers and coaches.

Traditionally, golf swing analysis has relied on coach expertise and complex biomechanical models. However, AI's ability to process large volumes of swing data and XAI's interpretability open new avenues for unraveling causal relationships. This work not only predicts distance but also explains why certain swing adjustments can improve or reduce it, representing a significant advance in applying AI to sports analysis.

The study used real golf swing data, applying XAI algorithms to decompose the contribution of each variable. Results showed that clubhead speed is, as expected, the most influential factor, but also highlighted the importance of angle of attack and club path in optimizing distance. XAI's ability to generate clear, understandable explanations for its predictions is crucial for golfers to effectively apply these findings in their training.