Playbook Board
ER Diagram
Whiteboard view of the nbadb star schema
Entity-Relationship Diagram
This curated page is the whiteboard version of the nbadb star surface: enough structure to see the shape of the warehouse quickly, without losing the grains that matter in analysis.
Whiteboard cue: Start at
dim_game,dim_player, anddim_team, then follow the spokes outward to event-level facts, rollups, and bridges.
Need the exhaustive, source-derived board? Use the companion Auto ER Diagram, which is generated from schema definitions and should not be hand-edited.
Quick navigation
Find the central spine
Start with How to read the board if you need the fastest
route through dim_game, dim_player, and dim_team.
Read by warehouse role
Jump to Schema categories when you care more about table class counts than individual relationships.
Open the full generator-owned board
Use Auto ER Diagram when you need the exhaustive schema inventory rather than curated emphasis.
Leave the whiteboard for SQL planning
Skip to Next steps when the picture is clear and the next move is relationships, schema reference, or lineage.
Use this page when…
| If you need to answer… | Start here |
|---|---|
| “Which dimensions anchor most joins?” | How to read the board |
| “Which relationships are many-to-many or history-aware?” | How to read the board |
| “How many dimensions, facts, bridges, aggregates, and views exist?” | Schema categories |
| “Where is the full schema-derived roster of entities?” | Auto ER Diagram |
The nbadb star schema consists of 17 dimensions, 72 fact tables, and 2 bridge tables.
erDiagram
dim_player {
int player_id PK
string first_name
string last_name
string position
string height
string weight
date birthdate
string country
string school
int draft_year
…How to Read the Board
If the board feels dense on first glance, read it in three laps: start at the conformed spine, fan out into fact neighborhoods, then finish with bridges and history-aware dimensions.
Scan order
- Center first — Find
dim_game,dim_player, anddim_teambefore you read any peripheral table. - Follow the repeated grains — Look for player-game, team-game, play-by-play, and shot-level fact clusters.
- Finish on exceptions — Bridge tables and SCD2 dimensions explain the relationships that do not fit a single-grain path.
| Scan first | What to trace | Why it matters |
|---|---|---|
dim_game, dim_player, dim_team | The busiest join paths | These conformed dimensions sit at the center of most analytical queries |
| Fact clusters | Repeated grains such as player-game, team-game, tracking, and play-by-play | They show how nbadb separates possessions, summaries, and specialty surfaces without collapsing them together |
| Bridge tables | bridge_game_official and bridge_play_player | They capture many-to-many relationships that do not belong to a single fact grain |
| History-aware dimensions | dim_player and dim_team_history | They preserve roster and franchise changes with SCD2 fields instead of overwriting the past |
Schema Categories
| Category | Count | Description |
|---|---|---|
| Dimensions | 17 | Slowly changing reference data |
| Facts | 72 | Event-level transactional data |
| Bridges | 2 | Many-to-many associations |
| Derived | 16 | Pre-aggregated rollups |
| Views | 4 | Denormalized analytics views |
Next steps from ER diagram
Open the generator-owned full roster
Jump to Auto ER Diagram when you need the exhaustive, schema-derived inventory rather than the curated whiteboard view.
Turn structure into join plans
Continue to Relationships or Schema Reference when the next question is how to join this surface safely in SQL.
Trace one table back to the inbound feed
Move to Table Lineage when the diagram has shown where a table sits, but you still need to know which source endpoints and staging tables feed it.
Keep moving
Stay in the same possession
Keep the mental model warm with adjacent pages, section hubs, and search-friendly routes into the same topic cluster.