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Data science, data visualisation and evaluating the effectiveness of a programme with Johann Windt

Data science, data visualisation and evaluating the effectiveness of a programme with Johann Windt

Released Thursday, 22nd September 2022
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Data science, data visualisation and evaluating the effectiveness of a programme with Johann Windt

Data science, data visualisation and evaluating the effectiveness of a programme with Johann Windt

Data science, data visualisation and evaluating the effectiveness of a programme with Johann Windt

Data science, data visualisation and evaluating the effectiveness of a programme with Johann Windt

Thursday, 22nd September 2022
Good episode? Give it some love!
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This week's guest on the Pacey Performance Podcast is Johann Windt. Johann is Head of Performance Data Science at the Vancouver Whitecaps in MLS. He is a strength and conditioning coach turned data scientist and it is this transition which makes Johann such an interesting person to speak to. He is able to speak "coach". He "gets" what happens in the weightroom and on the field and is able to integrate that mindset into his discussions on complex topics.

In this episode he chats with Rob about what data science actually is. It has gained a perception of being a mystical thing that goes on in dark rooms with staff who don't speak to each other. However, when done well its quite the opposite. He speaks about how data science is being used to help every other department at the club answer important questions. "Is this piece of technology valid?" or "what effect is this intervention having on our players?"

He finishes off the conversation by reflecting on his recent article for Sportsmith on data visualisation and explaining the principle of data being "not ugly and efficient".

If you're interested in making the most of the data that you collect with your team, hit play on your chosen podcast player now.

Today's talking points -

  • Where a data scientist fits within an organisation?
  • For those that don’t have a data scientist, what are the minimum data skills required across a sports science department?
  • Technology evaluation and linking research and practice
  • Subjectives evaluations
  • Maximising data quality
  • Evaluating the effectiveness of your interventions
  • Data viz
  • ‘Not ugly’ and ‘efficient’
  • Examples of how you live this daily
  • What you present and how
  • Common data viz mistakes —-failing to contextualize
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