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This paper studies the effect of moisture on the handling performance of rugby balls, where different moisture conditions will cause a change in skin friction between finger pads and rugby balls. In this study, a set of rugby ball passing tests was performed under wet conditions to test the effect of skin hydration on the performance of ball handling. A comprehensive analysis was then conducted to assess skin frictional properties at various moisture levels. It was observed that skin moisture is strongly associated with the handling performance of rugby balls. Based on the collected experimental data, intelligent data-driven models were finally developed, including a neural network and a fuzzy rule-based system. These models will likely enhance the anticipation of the handling performance of rugby players, which helps in designing specific training programmes and better preparing for rugby games to cope with wet conditions.

Analysing and Data-Driven Modelling the Handling Performance of Rugby Balls under Wet Conditions