Table Lineage

This page traces every star schema table back to its source API endpoint(s) and intermediate staging table(s). Think of each block as a half-court possession: the endpoint initiates the action, raw and staging move the ball into structure, and the downstream table finishes the play.

Read each chain from left to right:

Inbound — source endpoint or generated upstream table
Advance — raw_* capture keeps the original feed available
Set — stg_* tables normalize names, types, and validation
Finish — dim_*, fact_*, bridge_*, agg_*, or analytics_* tables receive the final touch

Entry surface

Start with dimensions

Jump to Dimension tables when the downstream issue is about conformed entities like player, team, game, date, or season.

Entry surface

Start with facts

Use Fact tables when the breakage is at player-game, team-game, play-by-play, shot, standings, or matchup grain.

Entry surface

Check bridges or second-side tables

Go to Bridge tables, Derived aggregations, or Analytics views when the dependency chain starts after the first finish.

Generated companion

Leave curated examples for full coverage

Open Generated Lineage Map when you need wider dependency coverage than this page curates.

Source preview

flowchart LR
    A["Inbound
NBA endpoint"] --> B["Outlet pass
raw_*"]
    B --> C["Half-court set
stg_*"]
    C --> D["Paint touch
dim_* / fact_* / bridge_*"]
    D --> E["Kick-out
agg_* / analytics_*"]
    style A fill:#e1f5fe
    style B fill:#fff8e1
…

The diagram is a legend for the detailed chains below: dimensions set the floor, facts capture live possessions, bridges connect secondary actors, and aggregates/views summarize what happened after the shot goes up.

Start with the right possession type

If the downstream table starts with…	Start here	What you will usually learn first
`dim_`	Dimension tables	Which source feeds establish reusable join anchors
`fact_`	Fact tables	The natural grain and primary inbound endpoint family
`bridge_`	Bridge tables	Which secondary actors are attached outside the main fact grain
`agg_`	Derived aggregations	Which star tables are recombined into reusable rollups
`analytics_`	Analytics views	Which facts, aggregates, and dimensions are joined for convenience

Set the floor

Dimension Tables

Dimension tables define the reusable court markings: who played, where, when, and which shared entities the rest of the warehouse joins against.

dim_player

NBA API: CommonPlayerInfo, PlayerIndex
  --> raw_player_info, raw_player_career
    --> stg_player_info, stg_player_career
      --> dim_player (SCD2: DimPlayerTransformer)

Transform: SCD2 with change detection on team_id, position, jersey_number. Generates surrogate key player_sk.

dim_team

NBA API: TeamInfoCommon, TeamDetails
  --> raw_team_info
    --> stg_team_info
      --> dim_team (DimTeamTransformer)

Transform: Direct mapping with franchise metadata enrichment.

dim_game

NBA API: ScoreboardV2, LeagueGameLog, ScheduleLeagueV2
  --> raw_schedule, raw_game_log
    --> stg_schedule, stg_game_log
      --> dim_game (DimGameTransformer)

Transform: Deduplicates games, resolves home/away teams, joins arena data.

dim_season

Generated from: season_year values across staging tables
  --> dim_season (DimSeasonTransformer)

Transform: Builds season dimension from distinct season_year values. Adds year_start, year_end, season_type.

dim_date

Generated from: game_date range across dim_game
  --> dim_date (DimDateTransformer)

Transform: Generates calendar rows for every date in the range. Adds day_of_week, month_name, is_weekend.

dim_official

NBA API: ScoreboardV2 (Officials)
  --> raw_schedule (officials result set)
    --> stg_schedule
      --> dim_official (DimOfficialTransformer)

Transform: Extracts distinct officials from game data.

dim_coach

NBA API: CommonTeamRoster (Coaches)
  --> raw_team_info (coaches result set)
    --> stg_team_info
      --> dim_coach (DimCoachTransformer)

Transform: Extracts coaching staff, classifies head vs assistant.

dim_arena

NBA API: TeamDetails, ScoreboardV2
  --> raw_team_info, raw_schedule
    --> stg_team_info
      --> dim_arena (DimArenaTransformer)

Transform: Extracts distinct arenas, generates surrogate arena_id.

dim_shot_zone

NBA API: ShotChartDetail (zone fields)
  --> raw_shot_chart
    --> stg_shot_chart
      --> dim_shot_zone (DimShotZoneTransformer)

Transform: Extracts distinct (zone_basic, zone_area, zone_range) combinations.

dim_play_event_type

NBA API: PlayByPlayV3 (action_type, sub_type)
  --> raw_play_by_play
    --> stg_play_by_play
      --> dim_play_event_type (DimPlayEventTypeTransformer)

Transform: Extracts distinct action_type/sub_type combinations, classifies field goal attempts.

dim_college

NBA API: CommonPlayerInfo, DraftCombineStats
  --> raw_player_info
    --> stg_player_info
      --> dim_college (DimCollegeTransformer)

Transform: Extracts distinct college names, generates surrogate college_id.

dim_lineup

NBA API: Derived from rotation data
  --> fact_rotation
    --> dim_lineup (via lineup detection logic)

Transform: Identifies 5-player combinations from rotation overlaps. Generates lineup_hash for deduplication.

Live-ball possessions

Fact Tables

Fact tables record the actual action: box scores, play-by-play, matchups, shots, rotations, standings, and draft outcomes at their natural grain.

fact_box_score_player (Traditional)

NBA API: BoxScoreTraditionalV3
  --> raw_box_score_traditional
    --> stg_box_score_traditional
      --> fact_player_game_traditional (FactPlayerGameTraditionalTransformer)

Transform: Filters to player_id IS NOT NULL, selects standard box score columns.

fact_box_score_advanced_player

NBA API: BoxScoreAdvancedV3
  --> raw_box_score_advanced
    --> stg_box_score_advanced
      --> fact_player_game_advanced (FactPlayerGameAdvancedTransformer)

fact_box_score_hustle

NBA API: BoxScoreHustleV2
  --> raw_box_score_hustle
    --> stg_box_score_hustle
      --> fact_player_game_hustle (FactPlayerGameHustleTransformer)

fact_box_score_tracking

NBA API: BoxScorePlayerTrackV3
  --> raw_box_score_tracking
    --> stg_box_score_tracking
      --> fact_player_game_tracking (FactPlayerGameTrackingTransformer)

fact_box_score_defensive

NBA API: BoxScoreMatchupsV3
  --> raw_box_score_matchups
    --> stg_box_score_matchups
      --> fact_box_score_defensive (FactTrackingDefenseTransformer)

fact_box_score_team

NBA API: BoxScoreTraditionalV3 (team result set)
  --> raw_box_score_traditional
    --> stg_box_score_traditional
      --> fact_team_game (FactTeamGameTransformer)

fact_game_result

NBA API: LeagueGameLog, ScoreboardV2
  --> raw_game_log, raw_schedule
    --> stg_game_log, stg_schedule
      --> fact_game_result (FactGameResultTransformer)

fact_play_by_play

NBA API: PlayByPlayV3
  --> raw_play_by_play
    --> stg_play_by_play
      --> fact_play_by_play (FactPlayByPlayTransformer)

fact_shot_chart

NBA API: ShotChartDetail
  --> raw_shot_chart
    --> stg_shot_chart
      --> fact_shot_chart (FactShotChartTransformer)

fact_win_probability

NBA API: WinProbabilityPBP
  --> raw_win_probability
    --> stg_win_probability
      --> fact_win_probability (FactWinProbabilityTransformer)

fact_rotation

NBA API: GameRotation
  --> raw_rotation
    --> stg_rotation
      --> fact_rotation (FactRotationTransformer)

fact_matchup

NBA API: BoxScoreMatchupsV3
  --> raw_box_score_matchups
    --> stg_box_score_matchups
      --> fact_matchup (FactMatchupTransformer)

fact_standings

NBA API: LeagueStandingsV3
  --> raw_standings
    --> stg_standings
      --> fact_standings (FactStandingsTransformer)

fact_draft

NBA API: DraftHistory, DraftCombineStats
  --> raw_draft
    --> stg_draft
      --> fact_draft (FactDraftTransformer)

fact_synergy

NBA API: SynergyPlayTypes
  --> raw_synergy
    --> stg_synergy
      --> fact_synergy (FactSynergyTransformer)

Handoffs and switches

Bridge Tables

Bridge tables connect extra participants to the main event grain when a single row needs more than one player or official attached.

bridge_game_official

NBA API: ScoreboardV2 (Officials)
  --> raw_schedule
    --> stg_schedule
      --> bridge_game_official (BridgeGameOfficialTransformer)

bridge_play_player

NBA API: PlayByPlayV3 (player references)
  --> raw_play_by_play
    --> stg_play_by_play
      --> bridge_play_player (BridgePlayPlayerTransformer)

Second-side actions

Derived Aggregations

Aggregate tables consume star schema tables to produce reusable rollups:

agg_player_season

fact_player_game_traditional + fact_player_game_advanced + dim_game
  --> agg_player_season (AggPlayerSeasonTransformer)

Transform: GROUP BY player_id, team_id, season_year, season_type. Computes totals, averages, and season shooting/rating summaries.

agg_player_rolling

fact_player_game_traditional + dim_game
  --> agg_player_rolling (AggPlayerRollingTransformer)

Transform: Window functions with 5/10/20-game rolling averages ordered by game_date.

agg_team_season

fact_team_game + dim_game
  --> agg_team_season (AggTeamSeasonTransformer)

Transform: GROUP BY team_id, season_year, season_type. Computes season-average box score and shooting splits.

Kick-out reads

Analytics Views

Analytics outputs join facts, aggregates, and dimensions for convenience:

analytics_player_game_complete

fact_player_game_traditional
  + fact_player_game_advanced
  + fact_player_game_misc
  + fact_player_game_hustle
  + fact_player_game_tracking
  + dim_player
  + dim_game
  + dim_team
    --> analytics_player_game_complete (AnalyticsPlayerGameCompleteTransformer)

analytics_player_season_complete

agg_player_season
  + agg_player_season_per36
  + agg_player_season_per48
  + dim_player
  + dim_team
    --> analytics_player_season_complete (AnalyticsPlayerSeasonCompleteTransformer)

analytics_team_season_summary

agg_team_season
  + fact_standings
  + dim_team
    --> analytics_team_season_summary (AnalyticsTeamSeasonSummaryTransformer)

analytics_head_to_head

fact_team_game
  + dim_game
  + dim_team
    --> analytics_head_to_head (AnalyticsHeadToHeadTransformer)

Next replay angle

Next steps from table lineage

Next stop

Slow down to the field that changed

Move to Column Lineage when the table chain is clear but one key or metric still needs a frame-by-frame review.

Next stop

Open the exhaustive dependency board

Use Generated Lineage Map when you need wider coverage than the curated examples on this page.

Next stop

Reconnect the replay to the visual boards

Jump to Pipeline Flow or Endpoint Map when you want the same story told as a stage diagram or source-coverage board instead of a dependency trace.

Table Lineage

Start with dimensions

Start with facts

Check bridges or second-side tables

Leave curated examples for full coverage

Slow down to the field that changed

Open the exhaustive dependency board

Reconnect the replay to the visual boards

Stay in the same possession

Column Lineage

Auto Lineage

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