Developed by Dr. W. Jack Rejeski, the Rejeski Feeling Scale is a subjective measure of how an individual feels during or after a physical activity. It is a simple yet powerful tool that allows athletes to express their emotions and perceptions, providing valuable insights into the psychological impact of their training. The scale ranges from -5 to +5, with negative values indicating negative emotions (e.g., fatigue, stress) and positive values representing positive emotions (e.g., enjoyment, exhilaration).
SELFLOOPS has integrated the Feeling Scale on the website and smartphone applications.
VAMS is a psychological assessment tool designed to gauge an individual’s mood state. Unlike traditional mood questionnaires that rely on fixed responses, VAMS uses a visual approach. It typically consists of a series of lines or sliders marked with contrasting mood states at each end (e.g., happy vs. sad, energized vs. tired). Athletes indicate their current mood by marking a point on the line that best represents their feeling.
SELFLOOPS has integrated the Visual Analogue Mood Scales (VAMS) on the website and smartphone applications.
The Positive and Negative Affect Schedule (PANAS) is a widely used psychological tool designed to assess an individual’s affective or emotional states. It measures two primary dimensions: positive affect (PA) and negative affect (NA). Positive affect refers to the extent to which an individual experiences positive emotions such as joy, enthusiasm, and alertness, while negative affect gauges the presence of negative emotions like fear, anger, and distress.
SELFLOOPS has integrated the Positive and Negative Affect Schedule (PANAS) on the website and smartphone applications.
The I-PANAS-SF, developed by Edmund Thompson, is a shortened, 10-item version of the original PANAS scale. The I-PANAS-SF, like its predecessor, yields two distinct scores: Positive Affect (PA) and Negative Affect (NA). However, the I-PANAS-SF is more concise, featuring a reduced number of items while maintaining its reliability and validity.
The validated scale consists of two 5-item mood scales: one for positive affect (e.g. active, inspired) and one for negative affect (e.g. afraid, nervous). Participants self-report the extent they experienced each mood state, allowing easy snapshot measurements of key attitudinal dimensions.
Unlike lengthier assessments, the brevity of the I-PANAS-SF is particularly advantageous for busy athletes and coaches, allowing for regular assessments without a significant time commitment. This enhancement in efficiency makes I-PANAS-SF a valuable update for those looking to integrate psychological assessments seamlessly into their training routines.
SELFLOOPS has integrated the International Positive and Negative Affect Schedule Short Form (I-PANAS-SF) on the website and smartphone applications.
The Brunel Mood Scale, developed by Dr. Terry Magill and his team at Brunel University, is a psychometric tool designed to assess mood states in athletes. It contains 24 simple mood descriptors like “angry,” “uncertain,” and “miserable.” Athletes self-report on a scale of 0-4 how much they relate to each mood descriptor based on how they feel at the present moment.
The BRUMS measures six identifiable mood factors: tension, depression, anger, vigor, fatigue, and confusion. Athletes rate their feelings on a scale to provide a comprehensive overview of their emotional states.
SELFLOOPS has integrated the Brunel Mood Scale (BRUMS) on the website and smartphone applications.
Endurance athletes and coaches often talk about polarized vs. non-polarized training. But what does this actually mean, and how can you quantify whether a training program is polarized or not? A new metric called the polarization index (PI) aims to provide some clarity.
The polarization index is a simple calculation that looks at the distribution of your training time or distance across three intensity zones:
Zone 1: Low intensity
Zone 2: Medium intensity
Zone 3: High intensity
To determine the PI
PI = log10(((Zone 1 / Zone 2 )* Zone 3) * 100)
If your PI is greater than 2.00, your training distribution is considered polarized. This means the majority of your training volume is spent in Zone 1, with less emphasis on Zones 2 and 3. Non-polarized training distributes volume more evenly across the three zones.
Research has shown that elite endurance athletes tend to follow a polarized training model. Their high volume of low intensity training allows them to absorb the hard workouts and adapt to get stronger. But what PI is ideal? There is no perfect number, as it depends on your specific sport and goals. The PI simply quantifies your polarization.
So in summary, the polarization index is an easy way to calculate whether your training is polarized or not based on time or distance in three intensity zones. It provides an objective measure you can track over time as you refine your training plan for optimal performance. Give it a try!
You can find the PI index in the activity analysis and in the calendar view of the SELFLOOPS website.
Reference
Treff, G., Winkert, K., Sareban, M., Steinacker, J. M., & Sperlich, B. (2019). The Polarization-Index: A Simple Calculation to Distinguish Polarized From Non-polarized Training Intensity Distributions. Frontiers in physiology, 10, 707. https://doi.org/10.3389/fphys.2019.00707
If you are not in a lab, caloric expenditure incurred during your physical endeavors are calculated using formulas. Different applications and devices use their own methods to estimate the calories burned during an activity.
If the device you use calculates the calories burned, we will use the values provided. Otherwise, we will calculate the calories burned using the following approach.
Caloric Estimations from Power Data
With power data, we use the following formula
kcal = kJ / 4.186 / .22
Kilojoules (kJ) emanate from measurements derived from the trainer or power meter.
4.186 kJ = 1 kcal = 1 Calorie Standard assumption of human mechanical efficiency = 22%
Caloric Estimations from Heart Rate Data
When power data is not available, heart rate data is used as alternative for caloric expenditure assessment. We use the following formula to estimate calories burned (from *Keytel et al. (2005)):
Mankcal = ((-55.0969 + (0.6309 x HR) + (0.1988 x W) + (0.2017 x A))/4.184) x 60 x T Womankcal = ((-20.4022 + (0.4472 x HR) – (0.1263 x W) + (0.074 x A))/4.184) x 60 x T
HR = average heart rate (in beats/minute) W = Weight (in KG) A = Age (in years) T = Exercise duration time (in hours)
*Keytel, L. R., Goedecke, J. H., Noakes, T. D., Hiiloskorpi, H., Laukkanen, R., van der Merwe, L., & Lambert, E. V. (2005). Prediction of energy expenditure from heart rate monitoring during submaximal exercise. Journal of Sports Sciences, 23(3), 289–297.
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.
*Banister EW, Calvert TW, Savage MV, Bach TM. A systems model of training for athletic performance. Australian Journal of Sports Medicine. 1975;7:57–61
