In this engaging discussion, former professional volleyball player Abby Bertics, sports data analyst James Tozer, and Google DeepMind's Petar Veličković delve into the transformative impact of AI on sports. They explore how AI is revolutionizing strategies in basketball and soccer, enhancing player recruitment and game tactics. The guests share insights on predicting injuries, analyzing player interactions using graph neural networks, and the challenges AI faces in capturing the complexities of human performance on the field.
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Michael Jordan's Inefficient Shots
Michael Jordan's mid-range jump shots in basketball were deemed inefficient by AI analysis.
Stepping back for a three-pointer offered the same likelihood of success with an extra point.
insights INSIGHT
The Rise of the Three-Pointer
AI-driven analysis revealed that three-point shots in basketball, despite lower accuracy, offer a higher point potential.
This insight revolutionized basketball strategy, prioritizing three-pointers and smaller players.
question_answer ANECDOTE
Data-Driven Rugby Victory
James Tozer, while at The Economist, consulted for England's rugby team, applying data analysis.
Three years later, England beat New Zealand, partially using insights from Tozer's Economist article.
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The book tells the story of the Oakland Athletics' 2002 season, where General Manager Billy Beane and his assistant Paul DePodesta used advanced statistical analysis, known as sabermetrics, to assemble a competitive team despite a limited budget. The approach, pioneered by Bill James, focused on metrics such as on-base percentage and slugging percentage rather than traditional measures like batting average and runs batted in. This data-driven strategy allowed the Athletics to compete with teams having much larger payrolls, like the New York Yankees, and achieve significant success, including a 20-game winning streak and a playoff appearance[2][3][5].
Data has transformed sport in recent decades—from identifying the best place to shoot from in basketball and football, to helping recruit the perfect baseball player. The new age of AI, which can utilise vast amounts of data on players, promises even deeper insights. Teams are experimenting with AI tools that can help pick the best players and prepare the best tactics for individual matches. Perhaps one day these models may even be able to predict injuries. AI models could transform sport—and the experiments with games could also inform the future of AI itself.
Host: Alok Jha, The Economist’s science and technology editor. Contributors: The Economist’sAbby Bertics; James Tozer of Prospect Sporting Insights; Patrick Lucey of Stats Perform; Petar Veličković of Google DeepMind.