Full-suspension mountain bikes display a wide diversity of kinematic designs to control the motion of the rear wheel. Differences between these designs are present in functional curves such as leverage ratio, anti-rise, anti-squat, pedal kickback, and axle path. Due to the complex nature of these curves, comparing and understanding how different curve shapes will impact riding behavior is difficult.

In this paper, we begin by extracting the characteristic curves from specialized software as graphs for various models of mountain bikes. We then demonstrate JMP Scripting to import these images and perform basic image analysis, extracting the functional curves from these graphs. Additionally, we show Python scripting within JMP to collect reviews of the corresponding models from popular bike review websites. Then, using both the Functional Data Explorer and Text Explorer in JMP Pro, we examine the patterns in suspension curves that correlate with changes in the sentiment of the reviews examined.