In many sports, sports scientists and coaches are interested in defining the key techniques of elite athletes. Athletes are monitored with inertial sensors and high speed video and it is necessary to merge this data to extract the parameters of elite technique. The upper arm and forearm rotations are critical in a number of sports. Monitoring this rotation is essential for the enhancement of the athlete’s performance, since it contributes to the speed of the serve in tennis [1], to the propulsion of swimmers [2] and to the fast bowling in cricket [3,4], among others. This study investigates the digitising and merging of video and sensor data for the cricket bowling arm action. In recent years new techniques have been developed for monitoring upper arm and forearm rotations. Inertial sensors (accelerometers and gyroscopes) are being widely used in the sports community, the sensors respond to minute changes in inertia in the linear and radial directions [5]. Vicon's standard plug-in-gait together with geometric calculations and a mapping of the space is also used to calculate these rotations [1]. This work presents a video digitising user interface for monitoring upper arm and forearm rotations of cricket bowlers, by using a marker-based system that pointed at the bowler’s wrist and elbow from every high speed motion video frame. Associated software read the sensors and automatically found the ‘overs’ in the sensor data. This allowed the quick matching of video and sensor inputs for bowling deliveries. To fine tune the relationship between the sensors and the video data, by digitising the video, virtual accelerometer data was produced which could be used to align the video with the sensors.