What if one of soccer’s most important analytics metrics is missing some of the most dangerous moments in a match?
Recorded live with students from the Wharton Moneyball Academy, Jonathan Pipping, Ph.D. student and member of the Wharton Sports Analytics and Business Initiative Research Team, explains the limitations of expected goals and the development of XG+, a new approach that accounts for both the probability of a shot being taken and the likelihood of it becoming a goal. He discusses how player tracking data can reveal opportunities that traditional XG misses, why creating shooting opportunities may be more predictive than finishing ability, and how advanced metrics could help teams better evaluate player performance and transfer value.
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