With all of the technology currently available and being used by different teams, it’s easy to get overwhelmed and feel like you’re falling behind. Do competitors with a larger budget have an advantage if they’re using the latest products that are cost-prohibitive to smaller programs? Ultimately this depends on the individuals implementing the technology and analyzing the data. Without the right person in this position, the technology can actually cause more problems than it solves. What’s more, research continues to be published demonstrating the effectiveness of cost-free monitoring strategies that require 0 budget and can be implemented by any team at any time. Two recent studies demonstrate this nicely and are summarized below.
- In a new study published ahead of print in the International Journal of Sports Physiology and Performance, perceived measures of recovery were compared to sophisticated heart rate measures (e.g., exercise heart rate, post-exercise heart rate recovery and post-exercise heart rate variability) for reflecting training load in elite soccer players. Training load on match day was substantially higher (600 au) compared to the loads on preceding and on subsequent days throughout the week. Perceived measures of fatigue sleep quality and muscle soreness followed the same trend as training load while there were no significant changes in HR measures. This indicates that perceived measures acquired via basic wellness questionnaire may be more useful than HR-derived recovery status markers for reflecting training status in athletes.
- In another new study published ahead of print in the Journal of Sport Sciences, a group of researchers tracked individual perceived training load (sRPE) and heart rate data from training sessions throughout a longitudinal training period. The aim was to determine if sRPE correlated with heart rate data from training sessions over time in elite male soccer players. The results showed that the changes in sRPE demonstrated a very large correlation between the changes in heart rate based training load (r = 0.75). The correlations remained strong when grouping the athletes by position (r values ranging from 0.70 – 0.84). This suggests that sRPE values provide similar information to heart rate based training load.
The results of these studies, among others, highlight the fact that big budgets with the latest fancy technology likely are not necessary to put together an effective monitoring protocol with your athletes. Self-reported (i.e., subjective) measures of recovery, fatigue, soreness and sleep quality can provide a solid indication of the athletes training status at it evolves throughout training. In addition, sRPE (sRPE = RPE X duration of session in minutes) appears to be a very suitable marker for tracking changes in training load, when compared to HR devices.
References:
Kelly, D. M., Strudwick, A. J., Atkinson, G., Drust, B., & Gregson, W. (2016). The within-participant correlation between perception of effort and heart rate-based estimations of training load in elite soccer players. Journal of Sports Sciences, In Press.
Thorpe, R. T., Strudwick, A. J., Buchheit, M., Atkinson, G., Drust, B., & Gregson, W. (2016). The tracking of morning fatigue status across in-season training weeks in elite soccer players. International Journal of Sports Physiology and Performance. In Press.
