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Hai risparmiato centinaia di ore di processi manuali per la previsione del numero di visualizzazioni del gioco utilizzando il motore di flusso di dati automatizzato di Domo.

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Hoops, KenPom, Data, and Madness: The Ultimate NCAA Dashboard

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min read
Friday, March 15, 2024

March Madness never fails to captivate, and true to form, we’re all in again, diving deep into the heart of NCAA Division 1 men’s basketball. Our journey through the tournament is a tradition—one where we indulge in our basketball passion and revel in the brilliance that our community brings to the table.

In years past, we captured four decades of tournament data in Domo and built our beloved Upset Assistant, a tool that shed light on the unpredictable thrill of upsets. (Although, even we didn’t anticipate Saint Peter’s making it to the Elite Eight that year.) 

Our Upset Assistant returned in 2023. But, I learned even the best tools couldn’t shield my bracket from the inevitable bust. It’s a humbling reminder of the unpredictable dance that is March Madness.  

This year, we’re taking a slight detour from the “Jace analysis” to celebrate something special—a dashboard that’s not just a tool but a testament to the vibrant creativity and genius within our community. 

Fellow enthusiast and data wizard Jonathan Pilafas built the March Madness Data Analysis Dashboard in Domo, data compiled by college basketball analyst Ken Pomeroy. The tool opens up a world where every team, every conference, and every corner of the tournament is at your fingertips, ready to explore.  

A few highlights include: 

  • A “Championship DNA” section that identifies teams with the highest likelihood of winning.
  • Visualizations of metrics that have been crucial in past tournaments, like turnover percentage or offensive efficiency vs defensive efficiency.  
  • The ability to export the tool so you can perform your own analysis in the platform you prefer. 

My take? This isn’t just an analytical tool; it’s a new way to experience the basketball saga we all love. Make sure to check out the data yourself! 

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