Blog post by Marco Altini
It is a common misconception that HRV should track training load, reducing when training load is higher.
In particular, studies looking at the relationship between HRV (and other metrics) with training load over time, look at how these metrics correlate. However, the whole assumption that you should find the metric that “correlates the most” with training load, makes very little sense.
Why? Because you are already measuring training load. What is the point of having another metric that gives you the exact same information? By definition, if a metric is perfectly correlated to training load (positively or negatively), then it is a useless metric.
If HRV had a perfectly negative correlation with training load, It would not add any information to the training and recovery equation. Ironically, these studies would interpret the metric with the highest negative correlation with training load as the best metric (!).
On top of this, HRV is all about individual responses. A non-relationship at the group level does not tell us anything at the individual level. Maybe a few people responded very well and had increased HRV. Other people had a suppression in response to the same load. This is exactly why we monitor.
It makes sense to analyze group-level data in response to acute stressors (see for example our paper here where we look at training, sickness, alcohol intake and the menstrual cycle) However, in the long run, acute and chronic responses differ. As such, a group level analysis does not tell us anything about the individual response.
The notion that increased load should trigger a reduction in HRV is very simplistic. We can have stable or increased HRV when increasing load (a sign of positive adaptation) and decreased HRV with reduced load because of other stressors (travel, work). Check out this blog for more information on HRV trends.
How should we use HRV and training load information then?
If our training load is increasing and our HRV stays within normal or increases, that’s great, it means we are responding well to stress. This is confirmation that we can take the load, maybe even increase it a little more. In general, HRV should not negatively correlate with load.
By measuring your resting physiology first thing in the morning, you can understand how you are responding to training (and other stressors), and use that information as part of your decision-making process.
If you are coping well with stress, HRV will not be decreased.
For more misconceptions about HRV tracking, check out Part 4 of my Ultimate Guide To Heart Rate Variability.
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This blog is curated by
Marco Altini, founder of HRV4Training
The Ultimate Guide to HRV
1: Measurement setup
2: Interpreting your data
3: Case studies and practical examples
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
1. Context & Time of the Day
3. Paced breathing
4. Orthostatic Test
5. Slides HRV overview
6. Normal values and historical data
7. HRV features
1a. Acute Changes in HRV
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
9. Samsung Galaxy
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
1. HRV normal values
2. HRV normalization by HR
3. HRV 101