Running in a triathlon, a so-called brick run, is uniquely influenced by accumulated load from its preceding disciplines. Crucially, however, and irrespective of race type, the demands of a triathlon always exceed the sum of its parts. Triathletes of all levels commonly report subjectively perceived incoordination within the initial stages of the cycle run transition (T2). Although minimizing it, and its influence on running kinematics, can positively impact running and overall triathlon performance, the mechanisms behind the T2 effect remain unclear. In the present study, we assessed the influence of the pre-load exercise mode focusing on the biomechanical perspective. To analyze inertial sensor-based raw data from both legs, the so-called Attractor Method was applied. The latter represents a sensitive approach, allowing to quantify subtle changes of cyclic motions to uncover the transient effect, a potentially detrimental transient phase at the beginning of a run. The purpose was to analyze the impact of a pre-load on the biomechanics of a brick run during a simulated Olympic Distance triathlon (without the swimming section). Therefore, we assessed the influence of pre-load exercise mode on running pattern (δM) and precision (δD), and on the length of the transient effect (tT) within a 10 km field-based run in 22 well-trained triathletes. We found that δD, but not δM, differed significantly between an isolated run (IRun) and when it was preceded by a 40 km cycle (TRun) or an energetically matched run (RRun). The average distance ran until overcoming the transient phase (tT) was 679 m for TRun, 450 m for RRun, and 29 4 m for IRun. The results demonstrated that especially the first kilometer of a triathlon run is prone to an uncoordinated running sensation, which is also commonly reported by athletes. That is, i) the T2 effect appeared more linked to variability in running style than to running style per se ii) run tT distance was influenced by preceding exercise load mode, being greater for a TRun than for the RRun condition, and iii) the Attractor Method seemed to be a potentially promising method of sensitively monitoring T2 adaptation under ecologically valid conditions.

Cross-Country Skate Skiing techniques evolved since the mid 1980’s. In order to perform optimally in various terrains and slopes, different variations of skating were developed known as gears: offset (V1 left and right), one-skate (V2) and two-skate (V2A left and right). The purpose of the current study was to develop and validate an automated algorithm using the so-called Attractor Method for the classification of Cross-Country Skating Gears based on acceleration data recorded from only one sensor located at the back torso of an athlete. Therefore, eight squad athletes from the German Ski Association (three female, five male) performed a fifteen minute trial with roller skies on a treadmill using all five gears and for classification one five minute trial with alternating gears. Attractors for each gear were calculated using 920 ± 146 cycles of the first fifteen-minute run. A total amount of 1085 cycles collected in the five-minute run, including all gears, were then classified based on these attractors. 98.3% of all cycles were classified correctly. This indicates a high usability in the application of the Attractor Method when classifying gears in Cross-Country Skating.