Episode 95: [Value Boost] Building Models That Work While Millions Are Watching

Episode 95: [Value Boost] Building Models That Work While Millions Are Watching

From Value Driven Data Science by Dr Genevieve Hayes

February 25, 2026 · 12 min · Episode 95

About this episode

The episode discusses the challenges of building effective models in high-pressure situations, specifically during the Cricket World Cup.

Building a model for an academic paper is one thing. Building a model that has to work perfectly during the Cricket World Cup with millions watching is something else entirely. There's no room for the kind of errors that might be acceptable in research settings or even standard business applications. In this Value Boost episode, Prof. Steve Stern joins Dr. Genevieve Hayes to share practical lessons from deploying the Duckworth-Lewis-Stern method in high-pressure, real-time environments where mistakes have global consequences. You'll learn: Why model simplicity matters more than you think [02:04] The two types of errors you need to understand [03:21] How to test models for extreme situations [05:50] The balance between confidence and humility [07:37] Guest Bio Prof. Steve Stern is a Professor of Data Science at Bond University, and is the official custodian of the Duckworth-Lewis-Stern (DLS) cricket scoring system. Links Contact Steve at Bond University Connect with Genevieve on LinkedIn Be among the first to hear about the release of each new podcast episode by signing up HERE

People in this episode

Host: Dr Genevieve Hayes

Guest: Prof. Steve Stern

Topics covered

  • model building
  • data science
  • real-time environments
  • sports analytics
  • error management

Keywords

  • model simplicity
  • Duckworth-Lewis-Stern
  • data science
  • real-time modeling
  • error types

Mentioned in this episode

Organizations: Bond University

Books & works: Duckworth-Lewis-Stern method

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