Within elite sport team environments, sports scientists play a unique role. They’re often the ones responsible for learning insights from the various data sources used to measure athletic readiness and performance in any given organization. They often select the technology used to generate said data and are therefore responsible for setting it up and ensuring the system works.
Because of this technical aspect of the job, many have skills in coding and can build scripts and models using R, Python, or Tableau. As you know, the list could go on, but all this is to say that Sports Science is a multi-faceted position that relies, usually, on multiple pieces of technology.
In this blog we outline some of those key responsibilities and show you how an Athlete Management System can help with things like testing, integrations, data visualization, and sharing your analysis amongst staff.
Smooth Out the Kinks of Testing Days
With athlete testing comes technology. And after you have ensured solid internet connection and attentive athletes, you will have to deal with the data.
This might happen two or three times a year, or you may find yourself testing on a weekly or day-before-game basis. No matter the schedule, the important part is having a smooth, standardized process that keeps you from a long night of manual data entry.
With an Athlete Management System, there are a few ways to go about avoiding this.
One, you can input the data during the testing sessions through a form in real-time, which you can set up to populate a report for analysis later. Or you can benefit from integrated technology, which means the data being produced by whichever testing device you prefer sends the data to the system for you.
Either way, this process is about saving you time from mulling over the exporting and uploading of CSV files and spreadsheets.
The Data Science Side of Things
Technology advancements have forced many in the sports science space to also familiarize themselves with the data science side of things, such as calculated metrics and scripts through R or Python.
We see this a lot and can support such endeavours in two ways.
One, we can actually create a script/calculation for you. Using the metric “sleep quality” as an example, we can write a script that will export a metric from your Kinduct site on a scheduled basis. Outside of the platform we can run further in depth/advanced calculations in R and automatically re-enter the newly calculated metric back into your platform.
Another way is for you to use the open Kinduct API to do this yourself. This way you can bring in any metrics that might be calculated in an internal system, and then push data back into Kinduct on an automated schedule.
Supporting Practicalities of the Job
Open APIs like we mentioned above can come in handy for another part of the job.
Since it’s safe to assume that you are responsible for cleaning and standardizing the data produced by tech such as GPS units or force plates, it may also be safe to assume that having that data relayed to a custom dashboard would be beneficial.
An Athlete Management System like ours is integrated with several technologies and, when set up properly, can save you from spending hours sifting through rows and columns in Excel.
When it comes to visualizing the data, our integration with Tableau means we can do much of the heavy lifting for you when it comes to dashboard building, and really cater the visualizations to your unique needs.
Our goal, in the end, is to make the data available so you can make decisions.