On the use of isoperformance curves for profiling and identification of training needs. Letter to the editor - Jolly, S. (European Journal of Applied Physiology, 2012)
The recent paper by Fukuda et al. (2011) highlights the use of modelling critical velocity (CV) and anaerobic rowing capacity (ARC), in relation to isoperformance curves, for the purposes of profiling aerobic and anaerobic fitness, and identifying training needs based on profiles. However, the suggestion that CV and ARC values may be used to profile the aerobic and anaerobic fitness of individuals, and to determine training needs, relies on the assumption that the parameters of the distance-time performance relationship clearly represent distinct aerobic and anaerobic physiological capacities, which may be an oversimplification of the interrelated underpinning aerobic and anaerobic physiology (Jones et al. 2010). Also, CV and ARC are also not graphically independent as an increase in the slope of a linear function, may occasion a reduction in the y-intercept (Bishop et al. 1998). This may be one explanation of the fact that intervention studies showing an improvement in one parameter often occasioning an unexpected decrease in the other, for example, following anaerobic swimming training, the value of anaerobic swim capacity actually decreased (MacLaren and Coulson 1999). Morton (2009) highlights that either an increase in CV or ARC could lead to an improvement in performance towards isoperformance curves; so the basis for deciding upon which type of training to focus is important. The authors` comparison of individuals` CV and ARC values with group means is used to suggest a division into training groups based on an need for aerobic or anaerobic training or both (Fukuda et al. 2011). However, it is entirely plausible that this group of athletes is part of a much larger quadrant, and that it might equally be argued that all of the group`s performance could be enhanced by one particular type of training. The somewhat arbitrary division based on group means is also subject to changes in the composition of the group. For example, should the mean CV of the group increase through an improvement in performance, or a change in group members, candidates who were not identified as targets for aerobic training, could rapidly become so. Given that values of CV and ARC are susceptible to both the model used (Hill et al. 2003), and the selected combinations of bouts (Kennedy and Bell 2000), this would suggest that the model and protocol used may affect the degree to which individuals are determined to be deficient in their aerobic or anaerobic capabilities as determined by the distance-time model. Morton (2009) advocates using isoperformance curves to select individuals with similar performance, yet different physiological attributes, yet this emphasises that from a coach`s perspective, it is the performance which is the criterion value for selection. The authors identify that isoperformance curves can be used in optimising the team selection process, yet it is not clear that the use of isoperformance curves would substantially improve upon rowing coaches` use of criterion 2,000-m performance times for selection purposes, particularly given the practical disadvantage of the requirement to perform multiple tests to derive CV and ARC. To conclude, the proposed identification of training needs is based upon the oversimplified assumption that performance measures of CV and ARC directly equate to distinct aerobic and anaerobic physiological capacities, and upon the arbitrary division of aerobic and anaerobic training need based on the mean characteristics of the group. The practical selection of rowers is likely to continue to be based on actual performance, rather than an evaluation of whether the line with the derived parameters of CV and anaerobic rowing capacity passes above, through, or below a point of the criterion distance versus time.