Start with View chooser when you know the workflow but not the exact analytics_ object.

Jump to View scouting reports for a one-card explanation of what each analytics view includes and when to trust it.

Go to

when you suspect the fast-break surface is hiding too much detail.

Use Star Reference for exact schema-backed columns after you choose the right view family here.

The all-purpose player-game read: traditional, advanced, misc, hustle, and tracking stats joined with player, team, and game context.

Best when: you want one player-game row with most common context already attached.

A season dossier for player comparison: totals, averages, and per-36/per-48 normalization in one place.

Best when: you are ranking players, building season dashboards, or comparing volume to rate stats.

Team-game stats across traditional, advanced, misc, hustle, and tracking families joined with team and game context.

Best when: you want one team-game row with box-score families already packed together.

Team-season summary that layers season rollups with standings and team context.

Best when: you need quick team snapshots, standings overlays, or year-over-year club comparison.

Opponent scouting summary that condenses team-vs-team outcomes and scoring margins.

Best when: you want rivalry, matchup, or opponent-prep reporting without rebuilding the join yourself.

Game recap surface with game result, both teams via bridge_game_team, and team context.

Best when: you need a schedule view, result dashboard, or quick game recap with both sides.

Clutch stat splits joined with player and team context from fact_player_clutch_detail.

Best when: you are studying pressure-situation performance or ranking clutch-time contributors.

Player dashboard split rows enriched with player identity plus season-overall baselines and deltas for fast context analysis.

Best when: you want quick home/away, rest, month, or win/loss split comparisons without rebuilding the overall baseline join.

Player-vs-player matchup data joined with player identity and team context.

Best when: you need defensive assignment analysis or head-to-head player comparison.

Shot chart detail with league-average zone baselines, player identity, and game context.

Best when: you want shot quality analysis relative to league expectations by zone.

On/off split data combined with season aggregates and player/team identity.

Best when: you are measuring a player's on-court impact via plus/minus and differential metrics.

Draft pick facts joined with career aggregate outcomes and player identity.

Best when: you are evaluating draft class performance, pick value, or prospect-to-career pipelines.

Season-level player and team aggregates providing league-wide baselines and percentile context.

Best when: you need a benchmarking surface for league-wide comparison or percentile ranking.

Team dashboard split rows enriched with team identity plus season-overall baselines and deltas for quick context reads.

Best when: you need team home/away, rest, or month splits compared to the club's overall season line.