IBM Emerging Technologies’s Darren Shaw and Rosie Likorish take you on a tour of how they used Watson services to determine what makes an individual athlete great.

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Pele or Messi? Ali or Sugar Ray Robinson? Navratilova or Serena Williams? Who is the greatest competitor of all time is a debate that rages across all sports, but an even more intriguing question is “how do you determine what makes a sporting great?”. Is it the number of medals they win? The sportsmanship they show? Or how they come back from defeat?

IBM’s campaign for Wimbledon 2017 involved determining what makes a great Wimbledon champion. The challenge set to Darren Shaw and Rosie Lickorish from IBM’s Emerging Technology group was an exciting one: Could they use Watson services to combine statistics, unstructured data, and fans’ opinions to find out what makes a great athlete?

Darren and Rosie take you on a tour of the project in which they set out the problem and the technologies used and explain what it was like to work with tennis pros, coaches, and journalists on a technology-based project. They talk about the Watson services they used and demonstrate how you can get up and running with your own application using the same Watson services.

Darren Shaw is a technical lead in IBM’s Emerging Technology group. His background is in data analytics and visualisation. He led the development of a cross language social network for a US non-profit organisation and a gamification based prototype for a UK online retailer. Darren leads the development of the cognitive and social media analytics tools for Wimbledon.

Rosie Lickorish is a Software Developer in IBM’s Emerging Technology group. Rosie has worked in a number of roles within IBM, most recently as a Site Reliability Engineer for IBM Containers. Developing the #WhatMakeGreat campaign was her second project in the Emerging Technology group.

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