A further consideration to make is that if there is variation in the first set of testing, there will also be variation in the second set of testing, and so the CV needs to be doubled (2CV) to account for the chance of error in both testing periods. For instance, if an athlete’s first performance is lower than their ‘true’ score and their second performance above, one needs to account for this extension of the SD. Thus, 2CV is necessary to ensure the threshold is large enough to account for a real change .
Using Figure 2 as an example, targets can be set, accounting for SWC, CV and 2CV, allowing for the identification of a trivial change, a possibly meaningful change, or a certainly meaningful change, respectively. For instance, data that falls outside of the 2CV range provides a target that would be a certainly meaningful change in performance. However, this target may be unrealistic to reach as it requires the greatest change in performance.
In contrast, the SWC provides an achievable target for athletes as it requires the smallest change in performance, but the change in performance is likely to be trivial. Therefore, there needs to be an appreciation of all three statistics when identifying performance change in athletes. Coaches can use these data to set achievable, but also meaningful targets for their athletes, in which there is consideration for not only the magnitude of change, but also the degree of certainty to which this change is meaningful.