Five projects, one data stack.
Each project builds on the last — shot quality feeds game prediction, which feeds trade value. Start with the foundation and watch the stack compound.
Shot Quality Model
xFGHow much better or worse is a player shooting than expected, given shot difficulty?
An expected field-goal model that accounts for distance, zone, type, game context and defender distance — a calibrated probability for every shot, plus a leaderboard of over- and under-performing shooters.
by location
Game Prediction Engine
PlannedCan we predict game outcomes better than Vegas using team-level efficiency metrics?
Builds directly on the xFG model — team shot quality becomes an input feature. Explores how much pregame data (pace, offensive / defensive rating, rest days, travel) predicts the final score.
Trade Value Predictor
PlannedWhat is a player actually worth in a trade, quantitatively?
Combines on-court production (informed by the shot-quality work), contract data, age curves and positional scarcity into a single tradeable value score. Inspired by Basketball-Reference WAR — but built from scratch.
Play-by-Play Clustering
PlannedWhat types of possessions actually exist, and which teams and players run them most?
Unsupervised clustering on play-by-play sequences to surface possession archetypes — pick-and-roll, isolation, transition. Feeds naturally into both trade value and game prediction.
Draft Class Projection
PlannedWhich college and international prospects translate to NBA production, and why?
Historical draft-class analysis plus a projection model. The capstone — it requires the full data infrastructure built across projects 1 through 4.
Other questions worth chasing.
Pulled out during planning — they didn't fit neatly into the five projects, but they're too good to lose.