For (Data) Scientists

Stop wrestling with messy data and get immediate access to rich and clean sport data through our platform. With clean APIs, easy-to-use client libraries and comprehensive documentation – you and your team can focus on meaningful analysis, not data wrangling and IT architecture.

All features that are available to athletes, coaches and developers are also available to data scientists, either via the SweatStack app, the Python client library or via the API.

Ready-to-go JupyterLab Environment

The Python client library includes commands to quickly spin up a JupyterLab environment to start analyzing data. Read more about that here.

Data Ingestion

SweatStack offers several integrations to ingest data from your favourite wearables and training platforms. More integrations are added regularly. Data can also be uploaded manually, or with code using the client library or the API.

The data models are optimized for medium frequency timeseries data (<=1Hz) but we are working on support for higher frequency timeseries data and other types of data. Reach out to us if you have specific data requests.

SweatStack is designed to be data source agnostic (allowing you to analyze data from any source using the same tools) and offers data fusion, merging data from multiple sources into a single data model and allowing you to, for example, combine data from multiple sensors that cannot be recorded on the same device.

Traces

SweatStack allows the user to store manually recorded data (e.g. lactate measurements or RPE values) as "traces". Using data fusion, traces are automatically combined with activity data, giving you 1 convenient interface to all your data.

Longitudinal Analysis

SweatStack not only gives you access to timeseries data on a per activity basis, but also allows you to access timeseries data across multiple activities and across many months (and even years). You can easily query months of data and start analyzing the results within seconds. More info on how to do this can be found in the Python client library documentation.

Data Sharing

Data can be shared with your team members or even a research group with fine-grained access control. And if someone gave you access to their data, all that data is available in the SweatStack app and via the API.

App Marketplace

Quickly develop applications to share your analysis within your organization (or even with the world). Individual apps can be published to the SweatStack app marketplace, where they can be discovered and used by other users.

If you are developing Streamlit apps, the sweatstack library offers a convenient way to authenticate users and access their data. Documentation can be found here.

Pricing

When SweatStack is launched, a free tier will give you access to all features but is limited to 30 days of history. For $20/month, you can create and be part of a team and get unlimited access to the full history of 10 users. By enabling sponsored access, you and your teams get access to the full history of connected users for $1/user/month.

Academic researchers and qualified non-profit organizations are eligible for a free subscription tier. Please contact us at info@sweatstack.no with details about your institution and intended use of SweatStack.

More Features

Info

More features will be announced soon...