Monitoring Progress

Development of human performance is never linear. It is heavily dependent on the environment and situation. Therefore it is not enough to have visibility to performance only in laboratory environment.

SmartPaddle enables monitoring the progress in daily training environment. A good practice has been to have

  • periodic profiling:
    more detailed analysis to identify which muscle limits the performance. Most straight forward approach would be to use some of the test series already used in coaching. Alternatively you can consider using 4x25/50m with increasing speed (200RP, 100RP, 50RP, AllOut) to build visibility to the performance on different efforts
  • regular data collection:
    get visibility to the progress of development by collecting data regularly (recommendation weekly). The set for monitoring can be finetuned to fit into weekly program. Either recording some of the recurring training sets, or having a simple 2x50 racepace swim after the warmup on a predefined way of the week.

With this level of detail each of the profiling sessions becomes easier and easier. Both the swimmer and coach will have visibility on transfer of training: what was done and how it impacted the stroke level execution. This will enable optimising the training to balance the quality and quantity.

Based on the learnings it is also possible to finetune the test protocol to improve understanding on the skill level on different conditions:

  • fresh -> the best possible technique
  • effort -> how the technique differentiates in slow and fast swimming
  • normal practice sessions -> this is real skill level which in the end will be visible in the competition

Real merit of progress is the capability to maintain the skill level in normal practices. Each of the swimmers do have their specific survival technique: when they hit their limiting factor, they modify the stroke to meet the targets that have been defined. It is important to appreciate this and ensure that the selection of the survival technique is such that optimizes the learning.

Depending on the need, the data can be analysed in different levels of detail:

  • Stroke level monitoring
    Makes visible the stroke level details and enables comparing to the selected reference stroke
  • Development over time
    makes visible how the parameters have developed over time
  • Power parameter monitoring
    makes visible the swimming dynamics, i.e., changes and differences over the different swimming speed
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