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Updated: May 19, 2026

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
Understanding the relationship among launch variables in the golf drive using neural network visualisations
1Faculty of Sports and Health Science, Technical University of Munich, Munich, Germany. peter.lamb@tum.de
Abstract:
The aim of this study was to identify and characterise individual differences in launch conditions measured from the same hole during four rounds of a professional golf tournament. Launch data from the 18th tee at the 2009 Dubai World Championship were used for the analysis. Self-organising maps (SOMs) were chosen to visualise the potentially non-linear relationship among the launch variables. Several distinctly different types of drives were identified on the output map. Drives which carried the furthest were not necessarily associated with the highest rates of ball speed. As indicated by carry distance, the longest drives had backspin rates of roughly 2700 rpm, a launch angle of 11 degrees, a straight or slightly left-to-right curving ball flight (for right-handers), and reached an apex of about 36 m. These values are specific to the 18th hole at the Dubai World Championship and differ from the general launch recommendations found in the literature.
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