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This method can be combined with other popular sprint profiling methods e.g FV profiling. In fact, the distance time data from timing gates etc can be used to perform FV profiling also. Robin has done some specific validation of this technique:
An important difference is that FV profiling requires a “true” first split time (where timing is initiated by the first movement of the athlete) whereas this is not a requirement of variability profiling (as long as the test set up is consistent, it’s fine). FV profiling calculates the macroscopic external mechanical capabilities of an athlete’s neuromuscular system throughout the acceleration phase of sprinting. In summary the methods are highly compatible as they yield distinct information.
The sprint variability profiling using the timing gates can also, easily, be combined with other data. For example, in a collaborative project at the Irish Institute of Sport, Robin combined the timing gate data with stride length, stride frequency and contact time data from an optojump system (this article was born out of this collaborative project). This extra layer of data can be analysed in a very similar z-score manner helping to identify which athletes might be stride length dominant, which might be stride frequency dominant or which athletes might need to work on longer or shorter contact times.
More data can blur the coaches vision and make everything more difficult to interpret. But I think the z-score analysis presented in the article can help add clarity.