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Virtual technologies make a big step forward also in the world of mountain bike sport. Monitoring the progress of performances during sports training is the eternal desire of each competitive mountain biker. They can measure or analyse data directly from their trainings. As some previous study shows some sophisticated data analytical methods such as data mining are becoming increasingly useful tools in analysing sport performance and also by supporting decision making. For example on the basis of this specific data it is able to create algorithm for planning the sport specific training sessions. In this way sport applications may help also coaches to develop more sophisticated training program for their athletes. All this virtual technologies has led to the idea that they can put the concept of a complex computer system, which is virtual coach, which is based on the principle of cyclization/periodization of sports training. That will be also main focus in our study to show how virtual coaching may work for example for endurance athletes in our case mountain bikers.
Introduction. Relative Energy Deficiency in Sport (RED-S) has many known negative consequences on health and performance parameters. However, less is clear about the impact on performance in men, especially when athletes do not exhibit clear symptoms of RED-S like serious eating disorder or low bone mineral density with recurring stress fractures. In addition, there is still no available questionnaire for easy detection of RED-S in men. Aim of Study. To determine if a greater risk for RED-S, assessed by a short questionnaire, impacts cycling performance. Material and Methods. Young competitive male road cyclists (n = 47, age 14-22) completed the questionnaire, body composition analysis with bioelectrical impedance and incremental testing (measuring VO₂max, peak power, relative peak power per kg and body fat percentage). These results were expressed relative to the results of cyclists competing at the same age and performing incremental testing in our laboratory (n = 580). In the questionnaire, we assessed number of sick days and injury-related days-of-training and a significant loss of body mass in the last month (>5%). If they had a significant weight loss or number of missed training days in the upper quartile, their risk for RED-S was recognized as increased. Results. 21 of 47 cyclists had an increased risk for RED-S that affected relative peak power (p = 0.008). We found no effect on VO₂max, absolute peak power, and body fat percentage. Conclusions. An increased risk for RED-S as assessed with a short questionnaire affects relative peak power compared to relative peak power in competitive cyclists of the same age. This is a crucial parameter in cycling performance. A high number of cyclists with an increased risk (44.7%) is in agreement with studies suggesting the prevalence of RED-S in competitive cycling is high.
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