Understanding the relationship among launch variables in the golf drive using neural network visualisations.

Area of Science:

• Sports Science
• Biomechanics
• Motor Control

Background:

• Understanding individual differences in golf drive launch conditions is crucial for performance optimization.
• Previous research often provides general launch recommendations, potentially overlooking specific course conditions.

Purpose of the Study:

• To identify and characterize individual variations in golf ball launch conditions from a specific hole during a professional tournament.
• To visualize the complex relationships among launch variables using Self-Organising Maps (SOMs).

Main Methods:

• Analysis of launch data from the 18th tee at the 2009 Dubai World Championship.
• Application of Self-Organising Maps (SOMs) to explore non-linear relationships between launch variables.
• Identification of distinct drive types based on performance metrics.

Main Results:

• Several distinct types of golf drives were identified.
• The longest drives (by carry distance) were not solely dependent on the highest ball speed.
• Optimal launch conditions for maximum carry distance on this specific hole included approximately 2700 rpm backspin, an 11-degree launch angle, a straight or slight right-curving ball flight, and an apex of ~36m.

Conclusions:

• Individual differences in launch conditions significantly impact golf drive performance.
• The identified optimal launch parameters are specific to the 18th hole at the Dubai World Championship.
• These findings suggest that generalized launch condition recommendations may not be universally applicable and specific analysis is warranted.