| 1. |
- Ivarsson, Oscar, 1988, et al.
(author)
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Towards Machine Learning on Data from Professional Cyclists
- 2018
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In: Proceedings of the XII World Congress of Performance Analysis of Sport. ; 2018
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Conference paper (peer-reviewed)abstract
- Professional sports are developing towards increasingly scientific training methods with increasing amounts of data being collected from laboratory tests, training sessions and competitions. In cycling, it is standard to equip bicycles with small computers recording data from sensors such as power-meters, in addition to heart-rate, speed, altitude etc. Recently, machine learning techniques have provided huge success in a wide variety of areas where large amounts of data (“big data”) is available. In this paper, we perform a pilot experiment on machine learning to model physical response in elite cyclists. As a first experiment, we show that it is possible to train a LSTM machine learning algorithm to predict the heart-rate response of a cyclist during a training session. This work is a promising first step towards developing more elaborate models based on big data and machine learning to capture performance aspects of athletes.
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| 2. |
- Sandbakk, Øyvind, et al.
(author)
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The Evolution of World-Class Endurance Training: The Scientist's View on Current and Future Trends
- 2023
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In: International Journal of Sports Physiology and Performance. - : Human Kinetics. - 1555-0265 .- 1555-0273. ; 18:8, s. 885-889
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Journal article (peer-reviewed)abstract
- Background: Elite sport is continuously evolving. World records keep falling and athletes from a longer list of countries are involved.Purpose: This commentary was designed to provide insights into present and future trends associated with world-class endurance training based on the perspectives, experience, and knowledge of an expert panel of 25 applied sport scientists.Results: The key drivers of development observed in the past 10-15 years were related to (1) more accessible scientific knowledge for coaches and athletes combined with (2) better integration of practical and scientific exchange across multidisciplinary perspectives within professionalized elite athlete support structures, as well as (3) utilization of new technological advances. Based on these perspectives, we discerned and exemplified the main trends in the practice of endurance sports into the following categories: better understanding of sport-specific demands; improved competition execution; larger, more specific, and more precise training loads; improved training quality; and a more professional and healthier lifestyle. The main areas expected to drive future improvements were associated with more extensive use of advanced technology for monitoring and prescribing training and recovery, more precise use of environmental and nutritional interventions, better understanding of athlete- equipment interactions, and greater emphasis on preventing injuries and illnesses.Conclusions: These expert insights can serve as a platform and inspiration to develop new hypotheses and ideas, encourage future collaboration between researchers and sport practitioners, and, perhaps most important, stimulate curiosity and further collaborative studies about the training, physiology, and performance of endurance athletes.
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