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Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders.

Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader.

Jun 29, 2018

In this, the final show in our AI in Sports series, I’m joined by Stephanie Kovalchik, Research Fellow at Victoria University and Senior Sports Scientist at Tennis Australia.

Stephanie and I had a great conversation about a few of the many interesting projects underway at Tennis Australia. We look at their use of data to develop a player rating system based on ability and probability, as opposed to the current official one which is based on points scored and match results. We then get into some of the interesting products her Game Insight Group is developing, including a win forecasting algorithm, and a statistic that measures a given player’s workload during a match. Stephanie details her paper “Is there a pythagorean theorem for winning in tennis?”, which explores the development and application of a pythagorean theorem for win expectation in tennis. We also take a look at her project to develop a system for classifying “ending” shots, and an emotion tracking system that help shows the link between emotion and performance in tennis.

For the complete show notes, visit

For details on our AI in Sports series, visit