Sprint intervals: can clusters make them better?

Interval training is a popular training mode across most sports because physiological conditioning is relevant to most sports! Interval training is effective because it allows athletes to experience high levels of physiological stress while working at high power outputs but without excessive accumulation of fatigue. Different types of interval training can be used to accomplish different types of goals, and one popular type of interval training is what’s known as sprint interval training. It consists of very brief periods of very intense work interspersed with short rest periods, leading to improvements in power output, aerobic fitness, as well as anaerobic fitness.

Cluster training

Sprint interval training is both effective and efficient, but coaches, athletes, and researchers are always looking to make training more effective and more efficient - and that’s where cluster training comes in. Cluster training is a strategy used in resistance training where very short breaks are introduced within a set to allow for higher power outputs and better maintenance of performance throughout the set. This strategy has proven successful at sustaining performance during sets, as well as improving training adaptations. Since resistance training and sprint interval training are both focused on challenging athletes with high intensities, could the same strategy be applied to sprint interval training? Fortunately, some smart researchers thought so, and they have put together a study to find out!

New research

A group of international sports scientists sought to discover the impact of cluster training when applied to sprint interval training⁽¹⁾. They wanted to see how clustered sprint interval training on a bike influenced the physiological challenge of a sprint interval session, as well as how clustering the intervals affected power outputs during the sets. The researchers recruited twelve recreationally trained subjects who had a VO2max (maximum oxygen uptake capacity) of around 54.0mls/kg/min. While not highly trained, these were fit individuals with a background of seven years of training, training five times per week, and performing at least two to four endurance training sessions each week.

Study protocol

The subjects visited the laboratory on five occasions. The first visit was a familiarization session during which baseline anthropometric data was taken, and the subjects were fitted to the exercise bike. During the second visit, the subjects performed a graded exercise test to determine their VO2max, the peak power output during the graded exercise test, as well as maximal heart rates. Throughout the testing, gas exchange data and heart rate data were collected. Beyond calculating VO2max, the gas exchange data was used to calculate the respiratory compensation point. This is the point at which there is a significant increase in ventilation (breathing) rate, indicating a much larger contribution of anaerobic metabolism (ie metabolism without oxygen and where lactate begins to accumulate) to power output.

During the last three visits, the subjects performed in a random order three different variations of a sprint interval training protocol:

·       Cycling as fast as possible against a resistive load equivalent to 7.5% of body mass. The subjects performed 4 repetitions of 30-second intervals, with a 240-second rest period between intervals.

·       The second protocol was the same as above except that instead of a continuous 30-second repetition, they performed 2 x 15-second work intervals with a 15-second break between the 2 x 15-second efforts. Also, rather than a 240-second rest period between intervals, a 225-second break was used to ensure that the total rest interval was the same across all protocols.

·       The third protocol involved breaking the 30-second repetition into 3 x 10-second efforts with 10-second breaks, followed by a 220-second break between intervals (again keeping total rest the same).

In summary, all subjects performed 120 seconds of work and 720 seconds of rest during each protocol (see figure 1), with the three above protocols performed in a randomized order. Throughout each interval protocol, the total work and the mechanical power outputs were measured. The researchers determined the highest power output achieved during each work effort, the average power output during each work effort, the minimum power output during each effort, and the fatigue index. The fatigue index was calculated by comparing the maximum power output and the minimum power output, expressed as a percentage.

Figure 1: Experimental protocol