Choosing the right training metric is crucial for effective training. Heart rate (HR), pace, power (measured in watts), and RPE (rate of perceived exertion) are four key metrics, each with its own characteristics and areas of application. But which metric is best for your training?
What Exactly Defines Training Metrics?
Training metrics are based on an individual’s threshold performance—the workload a person can maintain for one hour. This threshold forms the basis for defining personal training zones (Allen & Coggan, 2015). It’s important to note that threshold performance alone doesn’t provide a complete picture of an athlete’s metabolic profile. With a spiroergometry test, training zones can be defined even more precisely in enduco.
Accurate tracking of your current performance data is essential. To get reliable results, a consistent testing method is needed—for example, a standardized performance test provided by enduco. This avoids inconsistencies in personal test results. If the threshold is set too high, the actual training load is underestimated; if too low, it’s overestimated. This has a direct impact on long-term training management. If you’re unsure, feel free to reach out to our support—we’re happy to take a closer look at your profile!
Heart rate, pace, power, and RPE are the most important training metrics. They form the basis for additional values like training load, fatigue level, fitness, and fatigue. Training load helps quantify your workout intensity (internal and external load).
How Training Metrics Differ
Each metric responds differently to training stress:
Heart Rate (HR): HR is an internal metric and is very sensitive to external factors like heat, altitude, nutrition, and hydration. It increases with sustained effort but responds slowly to breaks. It best reflects the actual physical strain on the body.
Pace/Speed: This is an objective metric. Depending on the terrain and surface, pace can vary.
Power (Watts): Power measurement shows real-time objective load. On the bike, power stays relatively constant during a climb but drops near zero on descents.
RPE (Rate of Perceived Exertion): On a scale from 1 to 10, this reflects your subjective effort. It’s an internal metric and behaves similarly to heart rate.
These differences are critical when choosing how to guide and analyse your training:
Fig. 1: Trainingsmetriken und ihr Verhalten während dem Training (Ferrauti, 2020, S. 392)
Which Training Metric Should I Prefer?
Choosing the right metric depends on several factors: your experience and fitness level, ambient temperature, terrain, financial resources, and duration of the session—such as in interval training (Hanakam & Ferrauti, 2020). Heart rate is generally the best metric, assuming it’s measured correctly, as it most accurately reflects physical strain.
Base endurance training: Heart rate is the best choice here to ensure you stay in the aerobic zone and don’t train too intensively without realizing it. It’s also ideal in off-road settings.
Tempo and threshold intervals: Again, heart rate is optimal, as this type of interval should match your metabolic threshold. Because HR reacts to external influences, it offers a better picture of your body’s true load.
High-intensity interval training (HIIT): Power or pace (for running) are better for these. HR lags behind the effort, making it less suitable for short, intense intervals.
If you don’t have access to HR, pace, or power data, it’s even more important to log your perceived exertion after each session in enduco.
Measurement Methods
Heart Rate Measurement: Accuracy depends heavily on the method used (Stössel, 2019). A chest strap provides the most accurate data and is the best option for reliable HR tracking. Wrist sensors can be inaccurate, especially during rapid intensity changes or in cold conditions.
Power Measurement: It’s important to calibrate your power meter before performance testing for precise results. If you use multiple bikes with different power meters, expect different readings between them.
Pace Measurement: GPS accuracy varies by device. Watches with “dual-band GPS” offer better accuracy but are generally more expensive. Occasionally check your pace data stream—outliers can significantly affect your training load calculations.
Why It Makes Sense to Combine Metrics
Each metric has strengths and weaknesses, but they’re closely interconnected. For example, a pace-guided session will always correlate with heart rate. The best training control comes from combining external metrics (pace, power) with internal ones (HR, RPE). This allows for a more complete analysis and more precise training management.
Ultimately, you should always listen to your body—no metric can fully replace your own perception. It’s also important for evaluating whether your training parameters are set correctly, which is why regular performance tests are valuable. Good nutrition before and during training is essential. Sometimes, shortening a session makes sense, especially when training indoors on a trainer or treadmill. The goal isn’t to hit a specific training load but to tailor the training to your needs. enduco will then adjust your plan so you can still reach your goals.
Conclusion
The best training metric depends on various factors. While HR tracking is especially useful in base and tempo training, power and pace are often more accurate for short, intense intervals. Measurement quality is key—a chest strap gives the most reliable HR data. The optimal training control comes from smartly combining all relevant metrics.
Regular monitoring is essential to analyze how athletes respond to training and to make informed decisions about both training and recovery (Halson, 2014). Training load should never be viewed in isolation but always in connection with session duration and time spent in specific intensity zones. In addition to objective data like power and pace, subjective factors like perceived effort play a central role. The relationship between heart rate and performance offers valuable insights into training strain, but it must always be interpreted alongside personal perception.
References
Allen, H., & Coggan, A. (2015). Training and Racing with a Power Meter. Hamburg: spomedis.
Fett, J., Frytz, A., Götz, J. K., Hanakam, F., Hottenrott, L., Kappenstein, J., … & Wiewelhove, T. (2020). Exercise Science for Sport Practice: A Textbook for Study, Training, and Teaching in Sport. A. Ferrauti (Ed.). Springer Spektrum.
Halson, S. L. (2014). Monitoring training load to understand fatigue in athletes. Sports Medicine, 44(Suppl.2), 139–147.
Stössel, S. (2019). Effects of combined endurance and strength training on muscle strength during intensive therapy in pediatric oncology: Results of a randomized controlled study.