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Automated Machine Learning: A Game-Changer for Sports

There is an incredible wealth of available data in sports, but capturing and making use of that data in a way that will lead to better outcomes for the team remains a major problem. Factor in long data science time horizons that make it difficult to implement predictive solutions in the space of a season and prohibitive provisioning costs for data science teams, and it’s easy to see why many sports organizations find traditional data science methods to be out of their league.

Enter DataRobot’s automated machine learning platform. This overview will detail exactly how sports organizations are already using this technology to make better decisions, including specific use cases and the challenges most sports organizations face when implementing machine learning initiatives.

This overview will cover:

  • Specific use cases and tangible benefits of predictive analytics
  • The unique challenges of implementing machine learning in sports
  • Why automation is the solution
  • DataRobot's platform makes my work exciting, my job fun, and the results more accurate and timely – it's almost like magic!
    Omair Tariq
    Omair Tariq

    Data Analyst, Symphony Post Acute Network

  • I think we need to take it upon ourselves in the industry to build the predictive models that understand what the needs and wants of our customers are, and go through the whole curation process, become their concierge.
    Oliver Rees
    Oliver Rees

    General Manager – Torque Data at Virgin Australia

  • At LendingTree, we recognize that data is at the core of our business strategy to deliver an exceptional, personalized customer experience. DataRobot transforms the economics of extracting value from this resource.
    Akshay Tandon
    Akshay Tandon

    VP of Strategy Analytics, LendingTree

  • We know part of the science and the heavy lifting are intrinsic to the DataRobot technology. Prior to working with DataRobot, the modeling process was more hands-on. Now, the platform has optimized and automated many of the steps, while still leaving us in full control. Without DataRobot, we would need to add two full-time staffers to replace what DataRobot delivers.
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