Blog post by Marco Altini This is a short post to highlight some changes to the training load analysis that you can find under Insights in HRV4Training. In particular, we re-worked the last plot of the page, the one showing injury risk, to better reflect current state of the art models used to determine injury risk for endurance athletes as well as teams. We now report the acute to chronic ratio and a few thresholds (color-coded) that highlight which ratios are optimal and which ratios should trigger more caution. For more details on the training load features, please refer to our previous post where we explain the Banister model and reference to a few other articles that explain very well the theory behind computing chronic and acute training loads as markers of fitness and fatigue. Initially, we used the difference between chronic and acute training loads to compute injury risk, however the model based on the difference suffers from a few shortcomings: units are arbitrary and change based on the training impulse units, making it difficult to compare or standardize risks (e.g. using thresholds that we can all share and learn from), and is also less readable than the ratio. The acute to chronic training load ratio has been used a lot recently to estimate injury risk, especially by Tim Gabbett (please check out this article for a comprehensive analysis by Tim). Similarly to any other aspect of training load monitoring and performance optimization, there is no one size fits all and many parameters need to be considered. However, the acute to chronic ratio can be a valuable tool to keep things under control and make sure we do not introduce too much acute load based on our recent chronic load. The new analysis is available in both HRV4Training and HRV4Training Coach, see two screenshots below: What you can see above is an optimal area in which training load should be, in order to trigger positive adaptations (this is a ratio of approximately 0.8 to 1.3). A lower ratio, white area, would cause loss of fitness, as basically there is not enough training. An higher ratio, would instead increase injury risk, as it means we are training too much with respect to what we are used to take. We show two "higher risk areas", one between 1.3 and 1.75 in yellow and one above 1.75 in orange.
The new feature will be available by mid December, 2016. We hope you'll find it useful in better managing your training load.
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Marco Altini, founder of HRV4Training Blog Index The Ultimate Guide to HRV 1: Measurement setup 2: Interpreting your data 3: Case studies and practical examples How To 1. Intro to HRV 2. How to use HRV, the basics 3. HRV guided training 4. HRV and training load 5. HRV, strength & power 6. Overview in HRV4Training Pro 7. HRV in team sports HRV Measurements Best Practices 1. Context & Time of the Day 2. Duration 3. Paced breathing 4. Orthostatic Test 5. Slides HRV overview 6. Normal values and historical data 7. HRV features Data Analysis 1a. Acute Changes in HRV (individual level) 1b. Acute Changes in HRV (population level) 1c. Acute Changes in HRV & measurement consistency 1d. Acute Changes in HRV in endurance and power sports 2a. Interpreting HRV Trends 2b. HRV Baseline Trends & CV 3. Tags & Correlations 4. Ectopic beats & motion artifacts 5. HRV4Training Insights 6. HRV4Training & Sports Science 7. HRV & fitness / training load 8. HRV & performance 9. VO2max models 10. Repeated HRV measurements 11. VO2max and performance 12. HR, HRV and performance 13. Training intensity & performance 14. Publication: VO2max & running performance 15. Estimating running performance 16. Coefficient of Variation 17. More on CV and the big picture 18. Case study marathon training 19. Case study injury and lifestyle stress 20. HRV and menstrual cycle 21. Cardiac decoupling 22. FTP, lactate threshold, half and full marathon time estimates 23. Training Monotony Camera & Sensors 1. ECG vs Polar & Mio Alpha 2a. Camera vs Polar 2b. Camera vs Polar iOS10 2c. iPhone 7+ vs Polar 2d. Comparison of PPG sensors 3. Camera measurement guidelines 4. Validation paper 5. Android camera vs Chest strap 6. Scosche Rhythm24 7. Apple Watch 8. CorSense 9. Samsung Galaxy App Features 1. Features and Recovery Points 2. Daily advice 3. HRV4Training insights 4. Sleep tracking 5. Training load analysis 6a. Integration with Strava 6b. Integration with TrainingPeaks 6c. Integration with SportTracks 6d. Integration with Genetrainer 6e. Integration with Apple Health 6f. Integration with Todays Plan 7. Acute HRV changes by sport 8. Remote tags in HRV4T Coach 9. VO2max Estimation 10. Acute stressors analysis 11. Training Polarization 12. Lactate Threshold Estimation 13. Functional Threshold Power(FTP) Estimation for cyclists 14. Aerobic Endurance analysis 15. Intervals Analysis 16. Training Planning 17. Integration with Oura 18. Aerobic efficiency and cardiac decoupling Other 1. HRV normal values 2. HRV normalization by HR 3. HRV 101 |