Jul 12

Training Stress Balance

Categories: Glossary, Performance

Training Stress Balance (TSB) is a concept used in athlete performance monitoring to assess an athlete’s readiness for competition. It provides a measure of the accumulated training load and its impact on an athlete’s readiness and fatigue (often poorly termed fitness & freshness). TSB is often used in endurance sports such as running, cycling, and swimming.

TSB is based on the principle of acute and chronic training load. Acute training load refers to the short-term or immediate training stress placed on an athlete, typically measured over a period of one week. Chronic training load, on the other hand, represents the long-term or accumulated training stress over a longer period, often several weeks or months.

Eric Bannister et al, devised TSB in the early 1990s. It is a simplification of previous works (including his own), and importantly does not help to predict performance, only relative performance. It is very commonly stated that TSB was created by Andrew Coggan, however, this is incorrect. The missunderstanding appears to have arisen as Coggan devised the Training Stress Score (TSS) used within the TrainingPeaks software to estimate the stress of a single cycling workout, which is then applied to the TSB formula.

To calculate TSB, the acute training load is subtracted from the chronic training load. The formula is as follows:

TSB = Chronic Training Load – Acute Training Load

The chronic training load provides an estimate of an athlete’s overall fitness level and is a reflection of their training history. It takes into account the duration, intensity, and frequency of training sessions over an extended period. The acute training load, on the other hand, represents the recent training stress that an athlete has experienced, usually measured over the past week.

By subtracting the acute training load from the chronic training load, TSB provides an indication of an athlete’s fatigue or freshness. A positive TSB indicates a state of freshness, suggesting that an athlete is well-rested and has recovered from previous training. A negative TSB, on the other hand, indicates accumulated fatigue, suggesting that an athlete may be at a higher risk of injury or experiencing decreased performance.

To support their use, it is commonly stated with conviction that TSB and its allied models have been verified and validated. This should be taken with some caution. For example, a literature search only demonstrates 1 study in this area looking specifically at runners. And the model validation in this study was performed on 2 subjects. The subjects being the authors of the study itself.

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About The Author

Dr. Sean Radford, the Founder & CEO of TrainAsONE, is a medical doctor, IT expert, coach and podium finisher in international endurance events. He has dedicated more than 20 years to the research of health, fitness and social well-being of the general population. He has been developing Artificially Intelligent (AI) and Machine Learning (ML) tools to help tackle some of the world’s leading health issues. Dr Radford is a Tech Ambassador for the UK, considered a leading expert in his field, and is a regular speaker at key events, as well as an author of numerous research publications.