Calculate Acute:Chronic Workload Ratios to Monitor Training Load

Context

There are many wearable GPS products available which players wear during training to track objective training measures such as distance travelled, maximum speed and time spent in different speed zones. Teamworks AMS integrates with many of these third party vendors to sync athletes data to their AMS site using an API. Click here to learn more about the integrations available through AMS.

The metrics gathered from these GPS systems can in turn be used to calculate training load. Training load monitoring is a common practice which can assist in identifying whether players are coping with a training program to minimize the risk of overtraining and subsequent injury or illness. Essentially, training load is the product of training intensity and duration.

One way to monitor training load is through the calculate of acute and chronic training load for an individual. Generally, acute training load (ATL) refers to the total training load for an individual in the last 7 days and chronic training load (CTL) refers to the average training load in the last 28 days. Training load in the last 28 days is an indicator of a players' “fitness” while load in the last 7 days can indicate the amount of “fatigue” an athletes is currently experiencing. From these values, an acute:chronic workload ratio (ACWR) can be calculated, which may provide an indication of readiness to perform.

For example, Athlete A’s total weekly training load for the past four weeks is as follows:

Week 1 = 1000 units

Week 2 = 1200 units

Week 3 = 1500 units

Week 4 (current week) = 2000 units

As a result, Athlete A’s load metrics are:

ATL: 2000 (i.e. the total load for the current week)

CTL: 1425 (i.e. the mean of the four weekly totals)

ACWR: 1.40 (i.e. 2000 divided by 1425)

ACWR values can be interpreted using the following key:

< 0.80 (under training and higher relative injury risk)

80 – 1.30 (optimal workload and lowest relative injury risk; the safe zone)

> 1.50 (overloading and highest relative injury risk)

In the example above, ACWR has been calculated as:

ATL / CTL

However, recent literature suggests that this calculation may underestimate ACWR by including ATL in the CTL value (for more information, refer to Windt and Gabbett's (2019) editorial piece on ACWR and mathematical coupling). An alternative is to remove the additional weighting that ATL may have on the ratio by calculating CTL as the average of the three weeks leading up to the latest week, so as not to include the ATL.

As a result, Athlete A’s uncoupled load metrics would be:

ATL: 2000 (i.e. the total load for the current week)

CTL: 1233 (i.e. the mean of the weekly totals for weeks 1, 2 and 3)

ACWR: 1.62 (i.e. 2000 divided by 1425)

Regardless of the calculation used, ACWR may be useful in monitoring training load over time. If you have further questions, talk to your Product Success Manager.

Goals

This tutorial will take you through the process of calculating ACWR in a GPS event form to monitor an athletes' training load.

Outcomes

1. Calculate ACWR using history calculations and simple calculations within an event form.
2. Use time series chart widgets in the dashboard builder to visualize ACWR over time.

Outcome 1: Calculate ACWR in an event form

1. Create a history calculation for one of your GPS metrics to calculate ATL. The calculation for ATL in AMS is:

   historicalmean(Historical Value, GPS Value)

   where Value is the field that you are calculating ATL for. In this tutorial, we have used the Total Distance (m) field.

   Adjust the Date Restriction section in the sidebar to only include data from the last 7 days.

   

2. Duplicate or create a new history calculation for CTL. The calculation for CTL in AMS is:

   historicalmean(Historical Value, Value)

   where Value is the field that you are calculating CTL for. For this tutorial use the Total Distance (m) field.

   Adjust the Date Restriction section in the sidebar to only include data from the last 28 days.

   

3. Add a calculation for ACWR. As noted at the start of this tutorial, ACWR can be calculated using a couple of different methods. We will use the traditional calculation here:

   ATL / CTL

   

Outcome 2: Visualize ACWR over time using the dashboard builder

1. In the Dashboard builder, create a new dashboard or open an existing dashboard.
2. Ensure that the GPS event form is a data source in the dashboard.
3. Create a new time series chart using the Add Widget button.
   1. In the Data section, select the appropriate data source and apply data filters if required (e.g. if there is a select box widget in the dashboard to filter for an individual).
   2. In the Series section, name the series ACWR and select the appropriate data source, field and data filters (if applicable). Set the aggregation to most recent and set the type as a line chart.

      

   3. In the Regions section, add three regions colored orange, green and red.

   The orange region will cover the ACWR range of 0 to 0.8.

   The green region will cover the ACWR range of 0.8 to 1.3.

   The red region will cover the ACWR range of 1.3 and above.

   

   The resulting chart will display the players' ACWR over a period of time. Use the colored regions to identify when the players' current training load indicates that they are under- or over-training and have an increased risk of injury or overload.

   

Test your workflow

• Ensure that your role has permission to view the event form in the main interface.
• Enter some test data for a period of time into the GPS training data event form against an account.
• Check that the ATL, CTL and ACWR fields are calculated correctly in reports.
• Load the dashboard and check that the data is displayed correctly. If there are athlete or date selectors in the dashboard, check that the values change when you adjust the selected options.