```json { "table_name": "2019_WEEK 6_plays", "primary_key": null, "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=85.54 (28 unique teams, ~85 plays per team) provides good distribution. Top 3 coverage=12.82% shows balanced spread. Semantically, this groups all plays by the team executing them, enabling team-centric play sequence analysis.", "clustering_key": "PlayNumberInDrive", "clustering_key_label": "S", "clustering_key_reasoning": "PlayNumberInDrive is the sequence axis ordering plays within each drive. Monotonicity=0.866 confirms strong sequential ordering. Mean=5.288, range 1-22 shows natural progression through drives. Orders plays chronologically within each team's possessions.", "world_line": "TeamWithPossession", "session_column": "DriveNumber", "confidence": "HIGH", "notes": "Primary perspective: team-centric play sequencing. Each team's plays ordered by their progression through drives. DriveNumber serves as session boundary (each drive is a possession session). Alternative perspectives by game or drive are possible but less natural for play-level event analysis." }, { "rank": 1, "partition_key": "derived:concat(AwayTeam,'_vs_',HomeTeam,'_',Date)", "partition_key_label": "E", "partition_key_reasoning": "Game-level perspective: partition by unique game (AwayTeam+HomeTeam+Date combination). The data shows 3 dates with multiple games. This groups all plays from a single game together. RPUV would be ~2395/~15 games ≈ 160 plays per game, which is reasonable for NFL games.", "clustering_key": "PlayNumberInDrive", "clustering_key_label": "S", "clustering_key_reasoning": "Within each game, PlayNumberInDrive still provides sequential ordering of plays as they occurred. Combined with Quarter and DriveNumber context, this reconstructs game flow chronologically.", "world_line": "derived:concat(AwayTeam,'_vs_',HomeTeam,'_',Date)", "session_column": "DriveNumber", "confidence": "MEDIUM", "notes": "Alternative game-centric perspective. Useful for analyzing complete game narratives. Requires derived key combining AwayTeam, HomeTeam, and Date to uniquely identify each game. Less natural than team perspective but valid for game-level analysis." } ] } ```