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E524 Sujoy Ganguly, Chief Technology Officer at Sports Info Solutions

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Manage episode 431260619 series 2874110
Contenuto fornito da Alldus International. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Alldus International o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

Today's guest is Sujoy Ganguly, Chief Technology Officer at Sports Info Solutions. SIS was founded on the belief that decision making in sports could be improved and that they could help teams win more games through the use of better data, analytics and technology. That belief has been validated repeatedly since their founding in 2002 as SIS continue to revolutionize the way the game is played on and off the field. It is their mission to enrich and optimize the decision-making process for sports teams, sportsbooks and sports fans.

SIS are proud to become leaders in collecting, analyzing and distributing the deepest data sets and insights to professional sports teams across the MLB, NBA and NFL. The company has evolved to include former professional and collegiate athletes, coaches and scouts, alongside their best in class technology and research analysts. SIS are now doubling down on what’s made them successful by further advancing their data, technology, insights and partners as they drive forward the next innovations in Sports Data and Analytics.

In this episode, Sujoy discusses:

His background from academia to AI and Computer Vision in sport,

How SIS transformed from Baseball Info Solutions to AI-driven analytics,

Using AI to contextualize raw NBA tracking data into detailed game insights,

An insight into how the team processes and deploys sports data with AI,

Why specialized sports data complexity limits model utilization,

Emerging areas from real-time decision-making, injury prevention & granular data analysis,

What makes Sports Info Solutions a great place to work,

Why Data engineering and model reusability are critical for scaling

  continue reading

678 episodi

Artwork
iconCondividi
 
Manage episode 431260619 series 2874110
Contenuto fornito da Alldus International. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Alldus International o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

Today's guest is Sujoy Ganguly, Chief Technology Officer at Sports Info Solutions. SIS was founded on the belief that decision making in sports could be improved and that they could help teams win more games through the use of better data, analytics and technology. That belief has been validated repeatedly since their founding in 2002 as SIS continue to revolutionize the way the game is played on and off the field. It is their mission to enrich and optimize the decision-making process for sports teams, sportsbooks and sports fans.

SIS are proud to become leaders in collecting, analyzing and distributing the deepest data sets and insights to professional sports teams across the MLB, NBA and NFL. The company has evolved to include former professional and collegiate athletes, coaches and scouts, alongside their best in class technology and research analysts. SIS are now doubling down on what’s made them successful by further advancing their data, technology, insights and partners as they drive forward the next innovations in Sports Data and Analytics.

In this episode, Sujoy discusses:

His background from academia to AI and Computer Vision in sport,

How SIS transformed from Baseball Info Solutions to AI-driven analytics,

Using AI to contextualize raw NBA tracking data into detailed game insights,

An insight into how the team processes and deploys sports data with AI,

Why specialized sports data complexity limits model utilization,

Emerging areas from real-time decision-making, injury prevention & granular data analysis,

What makes Sports Info Solutions a great place to work,

Why Data engineering and model reusability are critical for scaling

  continue reading

678 episodi

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