There a several categories of climbing; with each having it own set of ethics, equipment types and focus. In general terms, climbing involves traversing a wall (man-made or natural) using agility, strength and balance; the three primary elements that climbing training regimes aim to improve. The ClimbAX project used wrist worn accelerometers to measure and quantify movement types that are specific to climbing. In collaboration with national team coaches, two AX3 band devices (one on each wrist) were used to capture data from climbers, and machine learning algorithms were developed to compute the characteristics that coaches use as traditional performance measures. ClimbAX is an example of how sensor-based measures can be developed, validated and deployed in challenging contexts; not only to enhance traditional approaches to training, but to make assessment more objective, repeatable and accessible.