Gemini Sports Analytics: what we're building and why
Professional and collegiate sports organizations have mountains of athlete data that isn’t being actioned because the tech talent can’t keep up with demand and the non-technical folks don’t have the relevant skills.
We’re building a software platform that solves that problem.
Nearly every team on the planet is rapidly scaling up their R&D departments, yet there is a clear need to complement that work by filtering the questions which all teams have. The vast majority can be handled by empowering non-technical people with AutoML and more. That clears space for data science teams to focus on solving the most complex and high impact questions.
Without industry solutions, non-technical stakeholders teach themselves how to code or else switch off from engaging with data altogether. The frustrations of waiting on manual/human processes and not being able to meaningfully interact with the data themselves are clear.
This motivated me to design a no-code, predictive intelligence platform which enables non-technical executives to create complex data queries on their own in order to more efficiently draft & sign better players, choose effective tactics and maximize talent to win more games.
With a hyperfocus on user-experience and data pipelines which enable actionable insights to be applied to daily processes, the engineering of our platform is guided by 3 tenets:
Seamless API frameworks prioritizing the most common data sources in sports and best-in-class warehousing resources
Easy, flexible modelling and rapid prototyping enabled by simplified data preparation
Over-index on design and usability to ensure everything is super easy and intuitive
As a non-technical founder with deep operator experience, it brings me enormous excitement to solve this problem as it’s long overdue.
With the dozens of sports industry colleagues that have already helped us design our platform, I simply feel like the conductor of an orchestra that is ready to play beautiful music.