```json { "table_name": "2018_PRESEASON WEEK 2_plays", "primary_key": "Season,Week,AwayTeam,HomeTeam,DriveNumber,PlayNumberInDrive", "candidates": [ { "rank": 0, "partition_key": "TeamWithPossession", "partition_key_label": "E", "partition_key_reasoning": "TeamWithPossession is the entity whose play-by-play timeline we trace. RPUV=85.50 is excellent for partitioning (32 teams, ~85 plays per team). Top 3 coverage is only 10.60%, indicating good distribution. Semantically, this groups all plays by the team executing them, enabling team-centric analysis of offensive sequences.", "clustering_key": "PlayNumberInDrive", "clustering_key_label": "S", "clustering_key_reasoning": "PlayNumberInDrive is the sequence axis ordering plays within each drive. Monotonicity=0.860 confirms strong sequential ordering. Ranges from 1 to 21, representing the chronological progression of plays within a possession. This orders each team's plays in the sequence they occurred.", "world_line": "TeamWithPossession", "session_column": "DriveNumber", "confidence": "HIGH", "notes": "Primary perspective: team offensive sequences. Each team's plays are grouped together and ordered by their sequence within drives. DriveNumber serves as a natural session boundary within each team's timeline. The composite primary key (Season,Week,AwayTeam,HomeTeam,DriveNumber,PlayNumberInDrive) uniquely identifies each play event." }, { "rank": 1, "partition_key": "derived:concat(AwayTeam,'_vs_',HomeTeam)", "partition_key_label": "E", "partition_key_reasoning": "Game-level perspective: partition by matchup. Each game (AwayTeam vs HomeTeam) would have RPUV of ~171 plays per game (2736 rows / 16 unique matchups). This groups all plays from a single game together, useful for game-specific analysis and replay reconstruction.", "clustering_key": "PlayNumberInDrive", "clustering_key_label": "S", "clustering_key_reasoning": "Within each game, PlayNumberInDrive maintains chronological ordering of plays. Combined with Quarter and DriveNumber context, this reconstructs the game timeline.", "world_line": "derived:concat(AwayTeam,'_vs_',HomeTeam)", "session_column": "DriveNumber", "confidence": "MEDIUM", "notes": "Alternative game-centric perspective. Useful for analyzing complete game narratives, but requires derived key. Less natural than team-based partitioning for most analytical queries." } ] } ```