Jesse Paquette leads the development of new features and pipelines that enhance user experience, particularly in the life sciences domain. Prior to Ayasdi, Jesse was a computational biologist at UCSF. He maintains an impressive collection of scar tissue, perpetuated by weekly overdoses of pickup soccer. With the rise of sports data collection companies like Opta Sports and Prozone, professional soccer is rapidly becoming a data-driven sport. Teams are now presented with an overwhelming challenge – they know these data hold the key to understanding playing styles, team success and optimal player performance, but they lack the tools. Ayasdi was founded in 2008 as an offshoot of the Stanford Math Department. Its software platform, Iris, uses Topological Data Analysis (TDA) to identify patterns of similarity between data points (players) over many dimensions (statistics). Recently, Jesse Paquette assisted The Economist magazine in producing a TDA network showing player similarity across two years of the English Premier League (EPL). In this session, Jesse will explain TDA and how it can be used by professional soccer teams to achieve Moneyball-like results from player data. What's GeekdomSF? GeekdomSF is a collaborative space for developers and startups. They provide easy access to great people to scale your idea faster. Learn more or find them on Twitter.