This leaderboard highlights player decision-making based on my custom Heliocentric Shot Selection statistic — a metric that evaluates the expected value of a shot versus the best available teammate option on the floor. It measures how often players take good, great, bad, or terrible shots based on spatial tracking data.
Note: This leaderboard only includes data from the 2015-16 NBA season.
In this EP Snapshot example, the shooter (triangle) took a shot worth 0.97 expected points (EP), while the best available teammate (square) had an EP of 1.14. According to the Max Teammate EP benchmark, this shot falls into a neutral zone—it's not significantly better to be classified as a great or good decision, but also not low enough to be considered a bad or terrible one. Classifications are based on how the shooter's EP compares to the best available teammate's EP using thresholds defined in the benchmark table (shown in the Heliocentric section under Brian's Portfolio). The Heliocentric Value for this shot is calculated as (0.97 − 1.14) + 0.20 = +0.03, quantifying how much better or worse the decision was relative to the best available option with a buffer for turnovers, shot clock violation, etc.