AI case study

SūmerSportsSports analytics

Managing 200TB of player data required heavy manual oversight. Now, serverless pipelines let scientists deploy models themselves.

Published

Key results

Insight Delivery Time
1 min
Data Processing Growth
3x

Result highlights

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The story

Context

A sports analytics startup helping NFL and college football teams make multimillion-dollar roster decisions by processing up to 200 terabytes of sensor, scouting, and financial data per season.

Challenge

Early infrastructure relied on a disorganized patchwork of cloud services and open-source tools that struggled to scale with the massive influx of...

Solution
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Scope & timeline

  • Model delivery time cut from 3 months to 4 weeks
  • 60 active internal users on the platform

Quotes

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The company

SūmerSports logo

SūmerSports

sumersports.com

SumerSports is a sports analytics company that provides a data-driven platform to help professional and collegiate sports teams make informed roster decisions within salary cap constraints.

LocationPalm Beach, Florida, United States
Employees51-250
Founded2022

The vendor

Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.

IndustrySoftware & Platforms
LocationSan Francisco, California, United States
Employees10K-50K
Founded2013

Use case

SūmerSports's Sports analytics is part of this use case:

AI Infrastructure
78 case studies(+112% YoY)
Proven impact?
LowModerateVery Strong
3.5Moderate
3.5Moderatewithin Product Engineering

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