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AI Analytics Podcast: Episode 17 - Euros Special!

AI Analytics Podcast: Episode 17 - Euros Special!

Dan Kennett is back with Dan Rhodes and Simon Brundish to discuss everything statistical to do with the Euro 2016 tournament. They take a look at the analytics for teams and players and also debunk many of the narratives being developed at the tournament!
AI Analytics Podcast: Episode 16

AI Analytics Podcast: Episode 16

On the latest episode, Dan (@DanKennett) is joined by Will Morgan (@willtgm) and Paul Power from Prozone Sports (@counterattack9) to discuss why Leicester are winning the Premier League. The lads also discuss how Prozone is changing the way we look at defensive analytics and Will's project to use the publicly available event data to provide new ways to look at team quality. Paul's webinars http://prozonesports.stats.com/player-recruitment-using-player-profiling-to-enhance-squad-management/ http://prozonesports.stats.com/game-intelligence-quantifying-movement-intelligence-football/ Will's blog and Statsbomb post on Leicester https://2plus2equals11.com/ http://statsbomb.com/2016/04/leicester-city-need-for-speed/ Paul's book project with David Sumpter http://www.amazon.co.uk/Soccermatics-Mathematical-Adventures-Beautiful-Game/dp/1472924126
AI Analytics Podcast: Episode 15 - Klopp and Spurs

AI Analytics Podcast: Episode 15 - Klopp and Spurs

The analytics pod returns and Dan (@DanKennett) is joined by Andrew Beasley (@BassTunedToRed) and James Yorke (@jair1970) to discuss Klopp and high-flying Spurs ahead of the big Premier League clash at Anfield.
AI Analytic Podcast: Episode 14 - Goalkeeper Special

AI Analytic Podcast: Episode 14 - Goalkeeper Special

Dan Rhodes hosts this goalkeepers special on the AI Analytics podcast with Dan Kennett and Sam Jackson. They cover the following: - A 'state of the nation' on GK analytics (remember the audience is not hard-core analytics so everything needs to be expressed in layman's terms with clear explanations) * what do we know?  * what don't we know?   * what matters in GK analytics? * what are the main sources of bias/noise? * why is it so difficult to get the data that is needed? - Where has Sam J tried to add the debate with his work  * what were the interesting findings in Sam's work?   * could any conclusions be drawn? * where Sam will be taking this work next.   - Case Study of Simon Mignolet (because it's essentially a Liverpool podcast) * how good or bad is he? * context of why he was originally bought (Dan & Dan to do this bit) * where do Liverpool go next?  Who should Liverpool be looking at if they are going to make a change? * where does Simon Mignolet go next? All this and more on the AI Analytics...
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