
Working with AI with Matthew Scherer
Pondering AI
Drafts: More Misses Than Hits, Even with Metrics
In basketball drafts, despite extensive evaluations of players’ past performances and physical abilities, teams often miss selecting the best candidates. The high similarity between past roles and current opportunities, coupled with detailed metrics, does not guarantee successful outcomes. Instead, teams frequently overlook the best player available for potential fits, highlighting the inherent unpredictability in talent selection.
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