Aerodynamic drag is a key determinant of cycling performance. The distribution of yaw angles that a cyclist experiences is equally important. Analysis and presentation of aerodynamic data in cycling, generally, has not combined these two effects. A theoretical derivation of a probability density function for yaw angle weighting, based on the theory of Wind Averaged Drag is presented. The weighting function allows for functional variation of yaw distribution according to road and wind speed as well as the visual representation of yaw distribution applied to graphical wind tunnel data. A normalised average of the weighted curve combines both drag and yaw angle data into a single value which is essential for performance modelling. This approach provides a more intuitive way to view and interpret yaw angle data and aerodynamic performance. This has the potential to standardise performance analysis in the industry and improve athletes` understanding of complex aerodynamic phenomena.
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