Modern basketball analytics too often divorces raw numbers from defensive rotations. My pipeline connects Second Spectrum optical coordinates with thousands of tagged possessions, verifying mathematical outliers against actual court leverage.

Every statistical model exists to answer immediate front-office queries: identifying weak-side tag latency, spacing gravity decay, and high-efficiency shot geometry before opponents adjust their defensive schemes.

From Coordinates to Game Theory

Data Ingestion

Spatial Modeling

Video Validation

Extracting raw optical coordinate streams and high-resolution play-by-play events through automated Python pipelines into relational database schemas.

Calculating spacing gravity, rim deterrence vectors, and possession efficiency to isolate true performance value beyond basic box-score totals.

Synchronizing statistical anomalies against wide-angle tactical game tape to isolate repeatable coaching habits from short-term shooting variance.

True efficiency is never abstract. A number that fails to explain an on-court defensive rotation is simply noise on a screen.

Analytical Manifesto, Possession Lab