Category: Sports Performance

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

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

To correctly receive speed data, you have to set the wheel circumference in the Spark app.

Check the Elite support page for more details about it

Speed value configuration with MyETraining and third party apps

Some bike power pedals are able to measure the left and right side power. They also transmit the power using two different Bluetooth connections. However, to use those pedals with the Selfloops Spark app you need to link those signals so they will transmit their data over a single Bluetooth connection.

If you have Stages pedals, you can use the Stages app to “link” the two sides.

If you have the Favero Assioma pedals you can link them using the Favero app and choosing the Unified Channel L option.

Power smoothing is a feature available in the Selfloops Spark app that is generally used to smooth power values coming from bike power sensors.

Smoothing is generally done by by averaging the last n values coming from the bike power sensor using a moving average formula.

Most power meters measure power throughout the pedal stroke and many high-end smart trainers do something similar. Your power will vary as you are pushing down and pulling up the pedal with each revolution.

If you watch your power in real time – without any smoothing – you will see numbers all over the place. 

Some smart trainers allows you to set Erg mode smoothing.

In the Selfloops Spark, in the Setting section, it is possible to select a smoothing value to avoid this problem.

The Selfloops Spark app is available for Android, iPhone and Apple Watch and support a large variety of Bluetooth sensors.

The app supports the Bluetooth FTMS standard, this means it supports indoor bikes and indoor bike trainers, treadmills, rowers.

It supports the Cycling Power Bluetooth standard, so bike power meters that use this standard are supports (the vast majority).

It supports the Cycling Speed and Cadence Bluetooth standard.

It supports Concept2 machines, including the rowers, bikeErgs, skiErgs that use the PM5 monitor.

It supports heart rate monitors that use the Bluetooth standard.

The Selfloops Spark app does not support ANT+ sensors.

If you have ANT+ sensors, you need to use a bridge device that will allow you to connect the ANT+ sensors to the Selfloops Spark app.

These are the two most popular ANT+ bridges:

1. Cable from North Pole Engineering
2. The Viiiiva heart rate monitor from 4iiii, these are the instructions to use the Viiiiva HRM as a bridge.