Laboratory and field based performance tests are an important element of athlete profiling. These tests allow coaches to identify strengths and weaknesses and design training programmes accordingly. Identifying a meaningful change in performance is therefore a vital factor in this process to track performance change and programme effectiveness. It is important that what change in performance we observe is considered meaningful and not the “noise” of the measure. This “noise” could be because of numerous reasons such as sleep quality, fitness levels, caffeine consumption and many others. With these variations, solely identifying that an athlete has improved their score over a period of time does not provide enough evidence that the change in score is meaningful. This meaningful change can be determined by calculating the smallest worthwhile change (SWC). By calculating the SWC coaches can be confident that they can determine that a real change in performance has occurred over a period of time and not just variation that can be seen in the test.
From reliability analysis the SWC can be calculated. It is determined by multiplying the between subject SD by 0.2, which is the typical effect or by 0.5 which is an alternate effect. Then the typical effort (TE), which is the change in score or difference score for each subject is calculated by dividing the standard deviation of the difference score by root2. For example, if the difference in scores from trial 2 to 1 are 3, -4, 5, 0 and -4, the standard deviation of these scores is 4.1 so the typical error is 4.1/root 2 = 2.9. We then compare the TE to the SWC. If the TE is below the SWC we would rate the test as “good”, we are confident that this test is able to detect meaningful change. If the TE was higher than the SWC then the test would be rated as “marginal” and we would not be confident that real change has occurred.
For example, if a group of athletes performed a CMJ test and the standard deviation for that particular population was 3 cm, the athlete would have to jump 0.6 cm higher to demonstrate a meaningful difference (SWC = 0.2 * 3). However, if the typical error for this population was 1.2 cm, then we would not be confident that real change has occurred as the TE is greater than the SWC. We would then calculate the alternate SWC effect (SWC = 0.5 * 3), which is 1.5 cm. Now the SWC is greater than the TE and we can be confident that any athlete within this population that jump 1.5 cm or higher, that a real change has occurred since the SWC is greater than the TE.
The SWC is a method for coaches to implement as part of their fitness testing procedure as it allows for the determination of meaningful change rather than making decisions based on assumptions. Coaches must be aware of the typical error associated with these tests and it is an important statistic to take into consideration. To provide athletes with the greatest certainty that the change in their performance is real, a combination of the SWC and TE should be used.
Hopkins, W. G. (2004). How to interpret changes in an athletic performance test. Sportscience, 8, 1-7.
Hopkins, W. (2000). Measures of Reliability in Sports Medicine and Science. Sports Medicine, 30, 1-15.
Claire Brady is a Postgraduate Researcher in the Department of Physical Education and Sport Sciences at the University of Limerick. Claire’s current research interests include Strength and Conditioning, Sports Performance, Biomechanics Anatomy and Physiology. Contact Claire via email at Claire.Brady@ul.ie.