Training Load: Improved Performance Versus Injury
Individuals strive to improve their physical performance by adjusting their training load, the frequency, duration, and intensity. The aim is to increase the training load enough to improve physical fitness and performance but not to increase training load so high as to result in worse performance or repetitive-use injury.
A common practice has been to use the 10% rule to safely progress training load. The 10% rule is to progress the current week’s training load no more than 10% above the training load of the previous week. Research has questioned the validity of the 10% rule suggesting that increases in training load above 10% and up to 30% more load than the previous week can be tolerated.
Tim Gabbett from University of Brisbane has proposed an interesting approach to optimizing training load to improve performance and avoid injury. He recommends the concept of “acute: chronic load ratio”. This ratio describes the acute training load (e.g. most recent week’s training load) to the chronic training load (preceding four-week rolling average of acute training load). What is unique is that he recommends referencing the change or increase relative to the preceding four-week average, not the preceding week alone.
For example, if the average number of meters swum for the previous four weeks was 8600 meters/week, and the current week was 10,000 meters swum – dividing the chronic load 8,600 meters by the current week of 10,000 meters the ratio is 1.16. According to the work of Gabbett, the ideal ratio is around 1, this is “in the sweet spot”. If the chronic load is high (four-week rolling average) the individual has developed fitness. If the acute load is low (most recent week) the individual is experiencing minimal fatigue. The individual is well prepared and likely experiencing a positive training response – improved performance.
If the ratios of acute load to chronic load (fitness relative to fatigue) is greater than 1.5, then there is increased risk of injury and/or falling off of performance.
The relative fitness level is going to be relatively low at the beginning of a season or after an injury which inhibits training. This is time progression of training load needs to be conservative, closer to the 10% level rule.
If the ratio of acute load to chronic load is below 0.8, then the individual is under training. Being under-trained may increase risk of injury. In this scenario, the training load needs to be increased.
There are a variety of measures of training load. There are a variety of methods of measuring training load. Examples from training diaries are time, distance, intensity, level of perceived exertion of effort. Cycling has power output devices such as: SRM cycling Power Meters and PowerTap cycling pedals. Time motion analysis systems that use global positioning system tracking can provide a wealth of data. Performance testing such as time trials, jump test, and strength testing can be used to measure training load. Heart rate has been used to measure and monitor training load, such as threshold level for a given work load, and Training Impulse – TRIMP
For the purposes of using the acute training load chronic training load ratio, actual measurements from systems identified above can be used or the units can be converted to arbitrary units to determine relative ratio.
Commercial wearable monitoring devices are becoming more available and prepackaged programs on how to progress training load may be included. Click here for a great summary of latest models and features on the market. The question arises on what principal does the application use to recommend progression of the training load. It may use the standard 10% rule based on the proceeding week. Consider customizing the program to use the concept of acute relative to chronic training load.
A less expensive system approach is to use a spreadsheet applying the concept of ratio of acute training load (current week) relative to chronic training load (rolling average of preceding four weeks) described by Gabbett.
There is a relationship between high training load and injury. Having a high level of fitness provides protection against injury. The ratio of acute recent training load relative to the preceding chronic training load is a better predictor of injury than acute or chronic loads in isolation. The ratio of acute recent training load relative to the preceding chronic training load can be used to optimize training to improve performance.