Effects of Flying Start Distances on the FVP

NEW Ph.D. Project: Effects of Flying Start Distances on the FVP

During 2020, I started collaborating with Jason Vescovi on the short sprints modeling, which resulted in development of the shorts R package (published on CRAN) as well as the recent publication in Frontiers and a published preprint (for which we are still finding peer-review home).

Although my previous Ph.D. Project is Velocity-based Training (I have published first paper of the Ph.D. project), on which I am still working by preparing another R package, and a large preprint, I have decided that switching my Ph.D. thesis to sprint modeling is a “better option”. A better option in a way that it is simpler to be done, and in my opinion more impactful to the real-world practices. Just yesterday I have successfully defended the public Ph.D. project and it is accepted by the University of Belgrade.

The paper that Jason Vescovi and myself published in Frontiers showed, retrospectively, that there are differences in estimated force-velocity profile (FVP) parameters if different (in our opinion: improved) model definitions are used. Paper reviewers were rightfully complaining that we need a validation study. And this is exactly what we intend to do now.

In the video presentation below you can find what problem with FVP estimation using timing gates we are trying to solve by utilizing novel model definitions. We plan to do one simulation study and one multi-center, pre-registered study in a hope of confirming the benefits of using FVP estimation with different model definitions.

Using the shorts package, we are able to simulate and explore expected (theoretical) effects. This in turn helps us prepare the analysis in advance (i.e. preregistration), as well as using simulation for the statistical power analysis.

In the video below I am walking you through the R Shiny dashboard/simulator which you can also use to explore the FVP estimation issues using timing gates.

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I am a physical preparation coach from Belgrade, Serbia, grew up in Pula, Croatia (which I consider my home town). I was involved in physical preparation of professional, amateur and recreational athletes of various ages in sports such as basketball, soccer, volleyball, martial arts and tennis. Read More »
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Welcome to Complementary Training Community! Forums NEW Ph.D. Project: Effects of Flying Start Distances on the FVP

This topic contains 2 replies, has 2 voices, and was last updated by  Mladen Jovanovic 5 days, 22 hours ago.

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  • 15/09/2021 at 07:31 #33670

    Great stuff Mladen. I see a few approaches using GPS data to calculate these variables (MSS, MAC, Pmax) from the work of Morin & Samozino. Can you use {shorts} to do this?

    19/10/2021 at 19:27 #33978

    Hi Mitch,

    Yes and no. If you have single intentional max sprint data using GPS, then yes. It would be same as the radar (time and velocity). If you have bunch of data points over weeks of data (i.e., instant acceleration and velocity), then you will need to filter the maxes (crop the low acceleration data) and/or use the quantile regression. Think JB explained this in the blog post

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