The American healthcare system is one of the most innovative in the world. But it’s also riddled with complex challenges, such as access to affordable medications, inefficiency and administrative burdens, and communication barriers between providers. There’s clearly a better way—and at Surescripts, we have a unique sightline into what that may be. In this series, host Melanie Marcus, Chief Marketing Officer of Surescripts, sits down with today’s most inspiring and innovative leaders in healt ...
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continue reading
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Seth Stephens-Davidowitz — Who Makes the NBA? (EP.250)
Manage episode 460148163 series 2631820
Content provided by Jim O'Shaughnessy. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jim O'Shaughnessy or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Seth Stephens-Davidowitz, a data scientist and bestselling author, is known for his brilliant use of data to upend conventional wisdom - often with humorous, surprising, and occasionally shocking results. His latest book, Who Makes the NBA, uses data to interrogate some of basketball’s biggest questions, consistently yielding unexpected insights. Here’s the kicker - he wrote the entire book in just 30 days after discovering Code Interpreter.
Unsurprisingly for a former quant, I had a blast chatting to Seth. Topics discussed include why so many NBA players are called Chris, whether basketball is due for a Moneyball moment, and why so many of us misunderstand the rags-to-riches story.
I hope you enjoy this conversation as much as I did. For the full transcript, episode takeaways, and bucketloads of other goodies designed to make you go, “Hmm, that’s interesting!”, check out our Substack.
Important Links:
Show Notes:
- Author, data scientist… comedian?
- Using Code Interpreter to write a book in 30 days
- The trait that makes it incredibly easy to become an NBA player
- Why the best NBA player in history isn’t who you think it is
- Is basketball due a Moneyball moment?
- Why are so many NBA players named Chris?
- What people get wrong about the rags-to-riches story
- The hidden magic of data storytelling
- Finding your audience
- The danger of glamour
- Keep it simple, stupid
- Why the standard interview sucks
- Doppelgangers & the power of A/B testing
- The overdue revolution in health data
- Why Google should be worried
- Stated vs revealed preferences
- The power of enormous data sets
- Seth as World Emperor
Books Mentioned:
- Who Makes the NBA?: Data-Driven Answers to Basketball's Biggest Questions; by Seth Stephens-Davidowitz
- Don't Trust Your Gut: Using Data to Get What You Really Want in Life; by Seth Stephens-Davidowitz
- Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are; by Seth Stephens-Davidowitz
- What Works on Wall Street: A Guide to the Best-Performing Investment Strategies of All Time; by Jim O’Shaughnessy
270 episodes
Share
Manage episode 460148163 series 2631820
Content provided by Jim O'Shaughnessy. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Jim O'Shaughnessy or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Seth Stephens-Davidowitz, a data scientist and bestselling author, is known for his brilliant use of data to upend conventional wisdom - often with humorous, surprising, and occasionally shocking results. His latest book, Who Makes the NBA, uses data to interrogate some of basketball’s biggest questions, consistently yielding unexpected insights. Here’s the kicker - he wrote the entire book in just 30 days after discovering Code Interpreter.
Unsurprisingly for a former quant, I had a blast chatting to Seth. Topics discussed include why so many NBA players are called Chris, whether basketball is due for a Moneyball moment, and why so many of us misunderstand the rags-to-riches story.
I hope you enjoy this conversation as much as I did. For the full transcript, episode takeaways, and bucketloads of other goodies designed to make you go, “Hmm, that’s interesting!”, check out our Substack.
Important Links:
Show Notes:
- Author, data scientist… comedian?
- Using Code Interpreter to write a book in 30 days
- The trait that makes it incredibly easy to become an NBA player
- Why the best NBA player in history isn’t who you think it is
- Is basketball due a Moneyball moment?
- Why are so many NBA players named Chris?
- What people get wrong about the rags-to-riches story
- The hidden magic of data storytelling
- Finding your audience
- The danger of glamour
- Keep it simple, stupid
- Why the standard interview sucks
- Doppelgangers & the power of A/B testing
- The overdue revolution in health data
- Why Google should be worried
- Stated vs revealed preferences
- The power of enormous data sets
- Seth as World Emperor
Books Mentioned:
- Who Makes the NBA?: Data-Driven Answers to Basketball's Biggest Questions; by Seth Stephens-Davidowitz
- Don't Trust Your Gut: Using Data to Get What You Really Want in Life; by Seth Stephens-Davidowitz
- Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are; by Seth Stephens-Davidowitz
- What Works on Wall Street: A Guide to the Best-Performing Investment Strategies of All Time; by Jim O’Shaughnessy
270 episodes
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Similar to Infinite Loops
The American healthcare system is one of the most innovative in the world. But it’s also riddled with complex challenges, such as access to affordable medications, inefficiency and administrative burdens, and communication barriers between providers. There’s clearly a better way—and at Surescripts, we have a unique sightline into what that may be. In this series, host Melanie Marcus, Chief Marketing Officer of Surescripts, sits down with today’s most inspiring and innovative leaders in healt ...
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continue reading
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continue reading
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