TGG Live: Big Data 2020
Written by Training Ground Guru — November 20, 2020
OUR Big Data event, which examines how top teams are using data science, is back for a second year.
In November 2019, more than 150 delegates from 16 Premier League clubs and seven countries attended our first Big Data event at Emirates Old Trafford in Manchester.
This year, for obvious reasons, we’re taking the event online - but there won't be any less insights because of that. Data science is probably THE biggest growth area in football, yet it remains one of the least understood.
Our speakers will explain how they're using data science and how it's impacting overall coaching, recruitment and leadership at their organisations.
This all-day event will be on Tuesday December 15th via Zoom. Place are limited and you can buy tickets HERE.
A recording will be made available to ticket holders after the event.
Speakers
Professor Geir Jordet has conducted extensive research on performing under pressure, the cognitive and perceptual underpinnings of decision making and talent development. He is regarded as THE world authority on scanning - namely what a player perceives before receiving the ball.
Ed Sulley is Director of Customer Solutions for Hudl and one of the most experienced leaders in the analysis industry. Prior to joining Hudl he spent more than 11 years with Manchester City, including a spell as their Head of Research and Innovation. He also worked for Bolton Wanderers for seven years.
Austin Fuller worked as a performance analyst for the Rugby Football Union for six-and-a-half years before becoming Analysis and Insights Lead for the Football Association in April 2015. He is now Manager of Customer Solutions for Hudl.
Paul Neilson has almost two decades' experience working in sports performance and technology and has seen the boom in data science at first hand. He is now working as a consultant for French start-up SkillCorner, which generates tracking data from broadcast footage.
Paul Power is a senior artificial intelligence manager at Stats Perform. He applies machine learning techniques to tracking and event data to create new models that capture tactical behaviour.