In this episode of the Low Man Help podcast, host Marc Campbell interviews Neil Paine, a prominent figure in basketball analytics. We discuss the evolution of analytics in basketball, the intersection of film study and statistical analysis, and the importance of playoff experience in predicting team performance. Neil shares insights from his work on the NBA Forecaster and the challenges of creating accurate predictive models. The conversation emphasizes the need for a balanced approach to analytics, combining both data and qualitative observations to understand player and team performance. We delve into the intricacies of NBA team dynamics, focusing on how matchups can significantly influence game outcomes. We analyze the Memphis Grizzlies' performance metrics, contrasting statistical models with real-world results. The discussion transitions to the RAPTOR metric, exploring its components and effectiveness in evaluating player performance. Finally, we examine Shai Gilgeous-Alexander's (SGA) impact on the court, highlighting the metrics that support his status as a top player in the league. We also explore various aspects of NBA performance, focusing on playoff evaluations, shooting mechanics, and the role of analytics in understanding player effectiveness. We discuss the importance of fear in basketball, particularly how it influences defensive strategies against players like DeMar DeRozan, who, despite his efficiency, may not instill fear in opponents. The dialogue touches on the evolution of NBA offenses, emphasizing the critical role of shooting in creating space and enhancing team performance. 0:01 - 20:13 Neil's Background and the Changing Landscape of Analytics 20:13 - 27:10 Why The Stats Forecast Hates the Grizz (and Marc's Ja Beef) 27:10 - 36:14 RAPTOR's Origins & Who It Got Right 36:14 - 46:40 Is SGA a True Number One Option? 46:40 - 1:01:01 RAPTOR's DeMar DeRozan Love and Quantifying Fear