We are happy to announce the new feature that allows seamless synchronization of your Stages Cycling workouts. Now, you can effortlessly transfer all your workout data from Stages Cycling devices and apps to Selfloops, providing you with a comprehensive fitness tracking experience.
Whether you prefer using a Stages bike computer or the Stages smartphone app, you can now have your valuable workout information securely stored on the Selfloops website. Activating this integration is simple. Just follow these steps:
If you have a Stages bike computer or are using the Stages smartphone app, navigate to the “Connections” section in the Stages app.
Look for Selfloops in the list of available connections and select it.
Once selected, you will be redirected to the Selfloops website to log in. In case you don’t have an account yet, you can easily sign up for one there.
Once you have successfully logged in, all your future workouts completed with Stages devices and apps will be automatically synchronized with Selfloops. This means that you no longer have to manually transfer your data between platforms or worry about missing any crucial workout information.
By streamlining the synchronization process, we aim to enhance your fitness journey and provide you with a consolidated overview of your performance. With Selfloops and Stages Cycling working together seamlessly, you can focus on achieving your fitness goals without any hassle.
Sports performance is highly influenced by our daily state of mind and well-being. Each day brings a unique set of circumstances, with some days brimming with energy and others where our mood may not be at its best. Recognizing this, we have introduced a new metric called “Overall Feeling” to enhance our understanding of sports performance and empower coaches and athletes to make improvements.
To include the Overall Feeling metric in an athlete’s calendar, simply navigate to the desired day and click the “+” sign. From there, select “Add Metric” and choose “Overall Feeling.” Additionally, our smartphone apps now offer the convenience of adding this metric on the go. The scale ranges from 1 (Horrible) to 10 (Best), allowing individuals to easily quantify their emotional state.
These metrics can be analyzed within the Health section and the Trends section of the Selfloops website. In the Trends section, users have the ability to correlate the Overall Feeling metric with other valuable indicators, such as the Session RPE (Rate of Perceived Exertion).
The Overall Feeling metric serves as an expression of an athlete’s mood on a specific day. In addition to this, we have also introduced the “How do you feel?” metric within an activity log, focusing on an athlete’s post-workout experience.
While external load, which can be measured through heart rate monitors and bike power meters, provides insight into an athlete’s physical strain, internal load is gauged through the “How do you feel?” metric and the Rate of Perceived Exertion (RPE).
By integrating sports performance metrics like bike power or heart rate with the feeling/mood metric and RPE, coaches and athletes gain a more comprehensive understanding of an athlete’s overall form and fitness level.
It’s important to recognize that our feelings and mood significantly impact our performance. With the inclusion of these metrics, we offer coaches and athletes an additional tool to effectively track, analyze, and optimize sports performance.
Training zones play a crucial role in enabling athletes to target specific types of training. Different days call for different approaches, such as focusing on Zone 2 for easy training sessions or emphasizing intervals with significant variations on other days.
Coaches rely on training zones to analyze workouts and assess whether each session was executed correctly based on the prescribed zone for that particular day.
Setting appropriate zones involves considering individual athlete characteristics. For instance, heart rate zones should be calculated based on factors like the athlete’s maximum heart rate, resting heart rate, and threshold heart rate.
Moreover, training zones should be tailored to the specific activity being performed. Heart rate zones for cycling, for instance, differ from those for swimming, taking into account that maximum heart rate values also vary across different sports.
In SELFLOOPS, we now offer the capability to establish personalized training zones for various sports. Users can specify the number of zones and set lower and upper limits for each zone. Alternatively, Selfloops can automatically determine zone numbers and limits by utilizing the threshold variable.
Ultimately, we provide coaches and athletes with the flexibility to define their training zones, ensuring that subsequent analysis aligns with the specified zones. Simultaneously, when the threshold value is provided, we automatically calculate the training zones and update them accordingly. For example, if the athlete’s threshold value is updated, the training zones are automatically adjusted.
By incorporating training zones effectively, coaches and athletes can fine-tune their training programs and optimize performance outcomes.
The physiological effect of an athlete’s training can be measured in terms of their training load, which quantifies the impact of a workout on the body by considering its intensity and duration. The concept of training load was introduced by Banister et al in 1975 in an article titled “A systems model of training for athletic performance.” *
In SELFLOOPS, the Training Load is calculated after each session and is accompanied by the Effective Power, Intensity, and TRIMP score.
Effective Power is a weighted average power that takes into account ride variability, while Intensity measures how hard a workout was by calculating the ratio between the athlete’s effective power and their FTP. TRIMP is a metric based on heart rate that captures the stress of an activity in a single number and is used to evaluate the effect of training over time.
The training load can be accumulated over multiple sessions. This metric enables the coach to monitor the athlete’s progress and prescribe an effective training program.
At the end of each week in SELFLOOPS you can visualise the accumulated training load, the workout duration, the distance, the TRIMP score and the calories burned.
To find a delicate balance between increasing training load and resting to allow for recovery and adaptation, the athlete and coach must work together. A good training plan includes periods of training mixed with active recovery and tapering sessions. This concept, known as periodization, considers the athlete’s competitions and form.
To monitor the training balance between training and recovery, SELFLOOPS provides the Fitness and Freshness Chart. The chart allows coaches to track an athlete’s fitness, fatigue, and form over time and use these metrics to guide the athlete to achieve their goals.
The Fitness and Freshness chart uses the accumulated Training Load to model the athlete’s form. Training sessions build long-term stress (fitness) or “chronic training load,” which is required to compete. However, they also cause short-term stress or “acute training load” adaptation, which results in fatigue. The balance between short-term and long-term stress determines the athlete’s training balance or “form.”
Training load can be quantified in different ways depending on the data available. Heart rate data can be used to calculate the TRIMP score or the Heart Rate Stress Score (HRSS), which is based on the lactate threshold heart rate. Bike power meter data can be used to calculate the Power Stress Score (PSS), while speed and distance data can be used to calculate the Swimming Stress Score (SSS) and the Running Stress Score (RSS).
Each activity with a stress score causes its own amount of fatigue and fitness, with a higher training load resulting in higher stress provided to the body. The Fitness and Freshness chart uses the activities’ Training Load to model the athlete’s fatigue, fitness, and form over time.
*BanisterEW, CalvertTW, SavageMV, BachTM. A systems model of training for athletic performance. Australian Journal of Sports Medicine. 1975;7:57–61