1. A programmed processor-based system for optimizing training, the system comprising: at least one sensor for measuring a mechanical load parameter which is indicative of a mechanical load of the training, the mechanical load parameter being taken from the group consisting of: number of steps, distance, rate of pronation, maximal pronation, timing, rate of loading, impact peak, active peak, alignment of joints, technique, force, impact, speed, rotation, rotation speed, leg stiffness, vertical stiffness, torsional stiffness, floor-foot contact time,and acceleration; a storage module for storing data which are dispatched by the least one sensor in a log file; a training advice module which is arranged for determining a personal training advice related to a load assessment of the user based on at least data stored in the log file; and at least one output device for outputting said training advice to said user, wherein the training advice module is configured to base the training advice on a mechanical load assessment of the user based on a cumulative mechanical load parameter that is indicative of the mechanical load history of the training sessions which occurred before the training session to be determined, the training advice comprising a type of training to be performed in a next training session so that: when the cumulative mechanical load parameter or mechanical load history is high in a load range, the training advice module schedules a training, session having a relatively low mechanical load, thereby promoting recovery of the user, and when the cumulative mechanical load parameter is low in the load range, the training advice module schedules a training session having a relatively high mechanical load, thereby stimulating expanding biomechanical loadability of the user through supercompensation.