Merge pull request 'complete app' (#3) from dev into main

Reviewed-on: #3

.env.example

@@ -0,0 +1,25 @@
+# ==============================================================================
+# NBA Analytics Environment Configuration
+# ==============================================================================
+
+# ------------------------------------------------------------------------------
+# 1. PostgreSQL Source Connection (Required for pipeline extraction)
+# ------------------------------------------------------------------------------
+POSTGRES_URL=postgresql://username:password@host:5432/nba_source_db
+
+# ------------------------------------------------------------------------------
+# 2. Cloudflare R2 / S3-Compatible Object Storage (Required for DB sync & CI/CD)
+# ------------------------------------------------------------------------------
+# Cloudflare R2 endpoint format: https://<ACCOUNT_ID>.r2.cloudflarestorage.com
+S3_ENDPOINT_URL=https://<ACCOUNT_ID>.r2.cloudflarestorage.com
+S3_BUCKET_NAME=nba-analytics
+S3_ACCESS_KEY_ID=your_r2_access_key_id
+S3_SECRET_ACCESS_KEY=your_r2_secret_access_key
+S3_REGION=auto
+S3_DB_KEY=dbt_nba.duckdb
+
+# ------------------------------------------------------------------------------
+# 3. dbt CLI Configuration (Allows running `uv run dbt ...` directly from root)
+# ------------------------------------------------------------------------------
+DBT_PROJECT_DIR=dbt_nba
+DBT_PROFILES_DIR=dbt_nba

.gitea/workflows/pipeline.yaml

@@ -0,0 +1,42 @@
+name: NBA Data Pipeline
+
+on:
+  schedule:
+    - cron: '0 6 * * *'
+  workflow_dispatch:
+
+jobs:
+  build-and-sync:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Code
+        uses: actions/checkout@v4
+
+      - name: Setup uv
+        uses: astral-sh/setup-uv@v4
+        with:
+          version: "latest"
+
+      - name: Install DuckDB CLI
+        run: |
+          curl -fsSL https://github.com/duckdb/duckdb/releases/latest/download/duckdb_cli-linux-amd64.zip -o duckdb.zip
+          unzip -o duckdb.zip
+          sudo mv duckdb /usr/local/bin/
+          rm -f duckdb.zip
+
+      - name: Install gettext (envsubst)
+        run: |
+          sudo apt-get update && sudo apt-get install -y gettext-base
+
+      - name: Run ETL Pipeline & Upload to Cloudflare R2
+        env:
+          POSTGRES_URL: ${{ secrets.POSTGRES_URL }}
+          S3_ENDPOINT_URL: ${{ secrets.S3_ENDPOINT_URL }}
+          S3_BUCKET_NAME: ${{ secrets.S3_BUCKET_NAME }}
+          S3_ACCESS_KEY_ID: ${{ secrets.S3_ACCESS_KEY_ID }}
+          S3_SECRET_ACCESS_KEY: ${{ secrets.S3_SECRET_ACCESS_KEY }}
+          S3_REGION: ${{ secrets.S3_REGION || 'auto' }}
+          S3_DB_KEY: ${{ secrets.S3_DB_KEY || 'dbt_nba.duckdb' }}
+        run: |
+          chmod +x ./scripts/pipeline.sh ./scripts/db_storage.py
+          ./scripts/pipeline.sh

.gitignore

@@ -176,3 +176,22 @@ cython_debug/
 
 .docs
 docs
+
+# Database files (stored in S3 / Cloudflare R2, not in Git)
+*.duckdb
+*.duckdb.wal
+*.duckdb.tmp
+
+# dbt artifacts
+dbt_nba/target/
+dbt_nba/dbt_packages/
+dbt_nba/logs/
+
+# Environments & secrets
+.env
+.env.*
+!.env.example
+
+AGENTS.md
+.agents
+.claude

dbt_nba/.gitignore

@@ -0,0 +1,4 @@
+
+target/
+dbt_packages/
+logs/

dbt_nba/.user.yml

@@ -0,0 +1 @@
+id: 428675f2-8539-4353-aae8-d37a4d91a7f7

dbt_nba/README.md

@@ -0,0 +1,15 @@
+Welcome to your new dbt project!
+
+### Using the starter project
+
+Try running the following commands:
+- dbt run
+- dbt test
+
+
+### Resources:
+- Learn more about dbt [in the docs](https://docs.getdbt.com/docs/introduction)
+- Check out [Discourse](https://discourse.getdbt.com/) for commonly asked questions and answers
+- Join the [chat](https://community.getdbt.com/) on Slack for live discussions and support
+- Find [dbt events](https://events.getdbt.com) near you
+- Check out [the blog](https://blog.getdbt.com/) for the latest news on dbt's development and best practices

dbt_nba/dbt_project.yml

@@ -0,0 +1,65 @@
+name: 'dbt_nba'
+version: '1.0.0'
+config-version: 2
+
+profile: 'dbt_nba'
+
+model-paths: ["models"]
+analysis-paths: ["analyses"]
+test-paths: ["tests"]
+seed-paths: ["seeds"]
+macro-paths: ["macros"]
+snapshot-paths: ["snapshots"]
+
+clean-targets:
+  - "target"
+  - "dbt_packages"
+
+models:
+  dbt_nba:
+    +materialized: view
+
+    staging:
+      +materialized: view
+      +schema: staging
+      +tags: ['staging']
+
+    intermediate:
+      +materialized: table
+      +schema: intermediate
+      +tags: ['intermediate']
+
+    marts:
+      +materialized: table
+      +schema: marts
+      +tags: ['marts']
+
+      dimensions:
+        +materialized: table
+        +tags: ['dimension']
+
+      facts:
+        +materialized: incremental
+        +tags: ['fact']
+
+tests:
+  dbt_nba:
+    +severity: warn
+    +store_failures: true
+    +schema: test_results
+
+seeds:
+  dbt_nba:
+    +schema: seeds
+
+vars:
+  start_date: '2002-10-01'
+  end_date: '2025-11-10'
+  min_games_played: 10
+  min_minutes_per_game: 15
+  clutch_time_minutes: 5
+  close_game_margin: 5
+  regular_season_start_month: 10
+  regular_season_end_month: 4
+  playoff_start_month: 4
+  playoff_end_month: 6

dbt_nba/models/intermediate/_int_models.yml

@@ -0,0 +1,58 @@
+---
+version: 2
+models:
+  - name: int_player_performance
+    description: "Unified model containing basic and advanced stats for each player in every game. Grain: one row per player per game."
+    tests:
+      - dbt_utils.unique_combination_of_columns:
+          combination_of_columns:
+            - game_id
+            - player_id
+    columns:
+      - name: game_id
+        tests:
+          - not_null
+      - name: player_id
+        tests:
+          - not_null
+
+  - name: int_team_performance
+    description: "Unified model containing basic and advanced stats for each team in every game. Grain: one row per team per game."
+    tests:
+      - dbt_utils.unique_combination_of_columns:
+          combination_of_columns:
+            - game_id
+            - team
+    columns:
+      - name: game_id
+        tests:
+          - not_null
+      - name: team
+        tests:
+          - not_null
+
+  - name: int_games_enriched
+    description: "Game-level model enriched with detailed performance stats for both the home and visitor teams. Grain: one row per game."
+    columns:
+      - name: game_id
+        tests:
+          - unique
+          - not_null
+
+  - name: int_player_shots_enriched
+    description: >
+      Unified shot-level dataset combining field goal attempts (from shot charts)
+      with free throw attempts (derived from stg_player_game_basic_stats).
+      Grain: one row per shot attempt (FG or FT).
+    columns:
+      - name: shot_id
+        tests:
+          - not_null
+      - name: player_id
+        tests:
+          - not_null
+      - name: shot_source
+        tests:
+          - not_null
+          - accepted_values:
+              values: ['shot_chart', 'box_score_ft']

dbt_nba/models/intermediate/int_games_enriched.sql

@@ -0,0 +1,81 @@
+{{
+    config(
+        materialized='table',
+        schema='intermediate',
+        tags=["intermediate"]
+    )
+}}
+
+WITH games AS (
+    SELECT
+        g.*,
+        home_map.team_abbr AS home_team_abbr,
+        visitor_map.team_abbr AS visitor_team_abbr,
+        winning_map.team_abbr AS winning_team_abbr
+    FROM {{ ref('stg_games') }} AS g
+    LEFT JOIN {{ ref('team_maps') }} AS home_map ON g.home_team = home_map.full_name
+    LEFT JOIN {{ ref('team_maps') }} AS visitor_map ON g.visitor_team = visitor_map.full_name
+    LEFT JOIN {{ ref('team_maps') }} AS winning_map ON g.winning_team = winning_map.full_name
+    WHERE (g.season_start_year >= home_map.start_year AND g.season_start_year < home_map.end_year)
+    AND (g.season_start_year >= visitor_map.start_year AND g.season_start_year < visitor_map.end_year)
+    AND (g.season_start_year >= winning_map.start_year AND g.season_start_year < winning_map.end_year)
+),
+
+arena_locations AS (
+    SELECT arena_name, arena_city
+    FROM (
+        SELECT
+            arena_name,
+            city AS arena_city,
+            ROW_NUMBER() OVER (PARTITION BY arena_name ORDER BY city) as rn
+        FROM {{ ref('arena_maps') }}
+    ) AS sub
+    WHERE rn = 1
+),
+
+team_performance AS (
+    SELECT * FROM {{ ref('int_team_performance') }}
+),
+
+final AS (
+    SELECT
+        g.game_id,
+        g.game_date,
+        g.season_start_year,
+        g.is_playoff,
+        g.arena,
+        al.arena_city,
+        g.home_team_abbr AS home_team,
+        g.visitor_team_abbr AS visitor_team,
+        g.winning_team_abbr AS winning_team,
+        g.home_points,
+        g.visitor_points,
+        g.point_differential,
+        g.total_points,
+        g.is_overtime,
+        home_stats.offensive_rating AS home_offensive_rating,
+        home_stats.defensive_rating AS home_defensive_rating,
+        home_stats.net_rating AS home_net_rating,
+        home_stats.pace AS home_pace,
+        home_stats.effective_fg_pct AS home_effective_fg_pct,
+        home_stats.turnover_rate AS home_turnover_rate,
+        home_stats.offensive_tier AS home_offensive_tier,
+        home_stats.defensive_tier AS home_defensive_tier,
+        visitor_stats.offensive_rating AS visitor_offensive_rating,
+        visitor_stats.defensive_rating AS visitor_defensive_rating,
+        visitor_stats.net_rating AS visitor_net_rating,
+        visitor_stats.pace AS visitor_pace,
+        visitor_stats.effective_fg_pct AS visitor_effective_fg_pct,
+        visitor_stats.turnover_rate AS visitor_turnover_rate,
+        visitor_stats.offensive_tier AS visitor_offensive_tier,
+        visitor_stats.defensive_tier AS visitor_defensive_tier,
+        (home_stats.pace + visitor_stats.pace) / 2 AS matchup_pace
+    FROM games g
+    LEFT JOIN arena_locations al ON g.arena = al.arena_name
+    LEFT JOIN team_performance AS home_stats
+        ON g.game_id = home_stats.game_id AND g.home_team_abbr = home_stats.team
+    LEFT JOIN team_performance AS visitor_stats
+        ON g.game_id = visitor_stats.game_id AND g.visitor_team_abbr = visitor_stats.team
+)
+
+SELECT * FROM final

dbt_nba/models/intermediate/int_player_performance.sql

@@ -0,0 +1,97 @@
+{{
+    config(
+        materialized='table',
+        schema='intermediate',
+        tags=["intermediate"]
+    )
+}}
+
+WITH basic_stats AS (
+    SELECT
+        s.*,
+        map.team_abbr AS team_conformed
+    FROM {{ ref('stg_player_game_basic_stats') }} AS s
+    LEFT JOIN {{ ref('team_maps') }} AS map
+        ON s.team = map.team_abbr
+    LEFT JOIN {{ ref('stg_games') }} AS g
+        ON s.game_id = g.game_id
+    WHERE did_play = TRUE
+    AND (g.season_start_year >= map.start_year AND g.season_start_year < map.end_year)
+),
+
+adv_stats AS (
+    SELECT
+        s.*,
+        map.team_abbr AS team_conformed
+    FROM {{ ref('stg_player_game_adv_stats_extended') }} AS s
+    LEFT JOIN {{ ref('team_maps') }} AS map
+        ON s.team = map.team_abbr
+    LEFT JOIN {{ ref('stg_games') }} AS g
+        ON s.game_id = g.game_id
+    WHERE (g.season_start_year >= map.start_year AND g.season_start_year < map.end_year)
+),
+
+games AS (
+    SELECT
+        g.game_id,
+        g.game_date,
+        g.season_start_year,
+        g.is_playoff,
+        home_map.team_abbr AS home_team_abbr,
+        winning_map.team_abbr AS winning_team_abbr
+    FROM {{ ref('stg_games') }} g
+    LEFT JOIN {{ ref('team_maps') }} AS home_map ON g.home_team = home_map.full_name
+    LEFT JOIN {{ ref('team_maps') }} AS winning_map ON g.winning_team = winning_map.full_name
+    WHERE (g.season_start_year >= home_map.start_year AND g.season_start_year < home_map.end_year)
+    AND (g.season_start_year >= winning_map.start_year AND g.season_start_year < winning_map.end_year)
+),
+
+final AS (
+    SELECT
+        b.game_id,
+        b.player_id,
+        b.player_name,
+        b.team_conformed AS team,
+        g.game_date,
+        g.season_start_year,
+        g.is_playoff,
+        CASE WHEN b.team_conformed = g.winning_team_abbr THEN 'W' ELSE 'L' END AS game_result,
+        CASE WHEN b.team_conformed = g.home_team_abbr THEN 'HOME' ELSE 'AWAY' END AS team_location,
+        b.minutes_played,
+        b.points,
+        b.assists,
+        b.total_rebounds,
+        b.steals,
+        b.blocks,
+        b.turnovers,
+        b.plus_minus,
+        a.net_rating,
+        a.box_plus_minus,
+        b.field_goals_made,
+        b.field_goals_attempted,
+        b.field_goal_pct,
+        b.three_pointers_made,
+        b.three_pointers_attempted,
+        b.three_point_pct,
+        a.true_shooting_pct,
+        a.effective_fg_pct,
+        a.usage_pct,
+        a.offensive_rating,
+        a.defensive_rating,
+        a.usage_tier,
+        a.impact_tier,
+        a.shooting_efficiency_tier,
+        a.minutes_based_role,
+        b.is_double_double,
+        b.is_triple_double,
+        a.is_versatile,
+        a.is_defensive_specialist,
+        a.is_three_and_d
+    FROM basic_stats AS b
+    LEFT JOIN adv_stats AS a
+        ON b.game_id = a.game_id AND b.player_id = a.player_id
+    LEFT JOIN games AS g
+        ON b.game_id = g.game_id
+)
+
+SELECT * FROM final

dbt_nba/models/intermediate/int_player_shots_enriched.sql

@@ -0,0 +1,214 @@
+{{
+    config(
+        materialized='table',
+        schema='intermediate',
+        tags=["intermediate"]
+    )
+}}
+
+WITH shot_charts AS (
+    SELECT * FROM {{ ref('stg_player_shot_charts') }}
+),
+
+games AS (
+    SELECT
+        g.game_id,
+        g.game_date,
+        g.season_start_year,
+        g.is_playoff,
+        g.arena,
+        g.home_points,
+        g.visitor_points,
+        g.point_differential,
+        g.is_overtime,
+        home_map.team_abbr AS home_team_abbr,
+        visitor_map.team_abbr AS visitor_team_abbr,
+        winning_map.team_abbr AS winning_team_abbr
+    FROM {{ ref('stg_games') }} AS g
+    LEFT JOIN {{ ref('team_maps') }} AS home_map ON g.home_team = home_map.full_name
+    LEFT JOIN {{ ref('team_maps') }} AS visitor_map ON g.visitor_team = visitor_map.full_name
+    LEFT JOIN {{ ref('team_maps') }} AS winning_map ON g.winning_team = winning_map.full_name
+    WHERE (g.season_start_year >= home_map.start_year AND g.season_start_year < home_map.end_year)
+      AND (g.season_start_year >= visitor_map.start_year AND g.season_start_year < visitor_map.end_year)
+      AND (g.season_start_year >= winning_map.start_year AND g.season_start_year < winning_map.end_year)
+),
+
+shots_conformed AS (
+    SELECT
+        sc.*,
+        COALESCE(tm.team_abbr, sc.team_abbr_raw) AS team_conformed,
+        COALESCE(opp.team_abbr, sc.opponent_abbr_raw) AS opponent_conformed
+    FROM shot_charts AS sc
+    LEFT JOIN {{ ref('team_maps') }} AS tm
+        ON sc.team_abbr_raw = tm.team_abbr
+        AND sc.season_start_year >= tm.start_year
+        AND sc.season_start_year < tm.end_year
+    LEFT JOIN {{ ref('team_maps') }} AS opp
+        ON sc.opponent_abbr_raw = opp.team_abbr
+        AND sc.season_start_year >= opp.start_year
+        AND sc.season_start_year < opp.end_year
+),
+
+shots_with_game AS (
+    SELECT
+        sc.*,
+        g.game_id,
+        g.is_playoff,
+        g.arena,
+        g.is_overtime AS game_had_overtime,
+        CASE
+            WHEN sc.team_conformed = g.home_team_abbr THEN 'HOME'
+            WHEN sc.team_conformed = g.visitor_team_abbr THEN 'AWAY'
+            ELSE NULL
+        END AS team_location,
+        CASE
+            WHEN sc.team_conformed = g.winning_team_abbr THEN 'W'
+            ELSE 'L'
+        END AS game_result
+    FROM shots_conformed AS sc
+    LEFT JOIN games AS g
+        ON CAST(sc.game_date AS DATE) = CAST(g.game_date AS DATE)
+        AND (
+            (sc.team_conformed = g.home_team_abbr AND sc.opponent_conformed = g.visitor_team_abbr)
+            OR
+            (sc.team_conformed = g.visitor_team_abbr AND sc.opponent_conformed = g.home_team_abbr)
+        )
+),
+
+fg_shots AS (
+    SELECT
+        shot_id,
+        game_id,
+        player_id,
+        team_conformed AS team,
+        opponent_conformed AS opponent,
+        game_date,
+        game_date_raw,
+        season_start_year,
+        is_playoff,
+        team_location,
+        game_result,
+        game_had_overtime,
+        quarter_raw,
+        quarter_number,
+        is_overtime_shot,
+        time_remaining_raw,
+        seconds_remaining_in_quarter,
+        shot_x_coordinate,
+        shot_y_coordinate,
+        is_made,
+        shot_made_flag,
+        shot_missed_flag,
+        shot_type_raw,
+        shot_point_value,
+        is_three_pointer,
+        is_free_throw,
+        distance_ft,
+        shot_distance_zone,
+        points_generated,
+        team_had_lead,
+        team_score_at_shot,
+        opponent_score_at_shot,
+        score_margin_at_shot,
+        is_clutch_shot,
+        CASE WHEN game_id IS NOT NULL THEN TRUE ELSE FALSE END AS has_game_match,
+        'shot_chart' AS shot_source,
+        created_at,
+        updated_at,
+        dbt_loaded_at
+    FROM shots_with_game
+),
+
+-- Free throw expansion using DuckDB's generate_series + UNNEST
+matched_player_games AS (
+    SELECT DISTINCT
+        game_id, player_id, team, opponent, game_date, game_date_raw,
+        season_start_year, is_playoff, team_location, game_result, game_had_overtime
+    FROM fg_shots
+    WHERE has_game_match = TRUE
+),
+
+ft_source AS (
+    SELECT
+        mpg.*,
+        bs.free_throws_made,
+        bs.free_throws_attempted
+    FROM matched_player_games AS mpg
+    INNER JOIN {{ ref('stg_player_game_basic_stats') }} AS bs
+        ON mpg.game_id = bs.game_id AND mpg.player_id = bs.player_id
+    WHERE bs.did_play = TRUE AND bs.free_throws_attempted > 0
+),
+
+ft_made_expanded AS (
+    SELECT ft.*, n.n AS ft_seq, TRUE AS ft_is_made
+    FROM ft_source AS ft
+    CROSS JOIN LATERAL (SELECT UNNEST(generate_series(1, GREATEST(ft.free_throws_made, 0))) AS n) AS n
+    WHERE ft.free_throws_made > 0
+),
+
+ft_missed_expanded AS (
+    SELECT ft.*, n.n AS ft_seq, FALSE AS ft_is_made
+    FROM ft_source AS ft
+    CROSS JOIN LATERAL (SELECT UNNEST(generate_series(1, GREATEST(ft.free_throws_attempted - ft.free_throws_made, 0))) AS n) AS n
+    WHERE ft.free_throws_attempted > ft.free_throws_made
+),
+
+ft_shots AS (
+    SELECT
+        -(ABS(hash(
+            ft.game_id || '|' || ft.player_id || '|FT_'
+            || CASE WHEN ft.ft_is_made THEN 'MADE' ELSE 'MISS' END
+            || '|' || CAST(ft.ft_seq AS TEXT)
+        )) % 9223372036854775807 + 1) AS shot_id,
+        ft.game_id,
+        ft.player_id,
+        ft.team,
+        ft.opponent,
+        ft.game_date,
+        ft.game_date_raw,
+        ft.season_start_year,
+        ft.is_playoff,
+        ft.team_location,
+        ft.game_result,
+        ft.game_had_overtime,
+        'Free Throw' AS quarter_raw,
+        0 AS quarter_number,
+        FALSE AS is_overtime_shot,
+        NULL AS time_remaining_raw,
+        NULL::INT AS seconds_remaining_in_quarter,
+        NULL::BIGINT AS shot_x_coordinate,
+        NULL::BIGINT AS shot_y_coordinate,
+        ft.ft_is_made AS is_made,
+        CASE WHEN ft.ft_is_made THEN 1 ELSE 0 END AS shot_made_flag,
+        CASE WHEN ft.ft_is_made THEN 0 ELSE 1 END AS shot_missed_flag,
+        'free-throw' AS shot_type_raw,
+        1 AS shot_point_value,
+        FALSE AS is_three_pointer,
+        TRUE AS is_free_throw,
+        15 AS distance_ft,
+        'Free Throw (15 ft)' AS shot_distance_zone,
+        CASE WHEN ft.ft_is_made THEN 1 ELSE 0 END AS points_generated,
+        NULL::BOOLEAN AS team_had_lead,
+        NULL::BIGINT AS team_score_at_shot,
+        NULL::BIGINT AS opponent_score_at_shot,
+        NULL::INT AS score_margin_at_shot,
+        FALSE AS is_clutch_shot,
+        TRUE AS has_game_match,
+        'box_score_ft' AS shot_source,
+        CURRENT_TIMESTAMP AS created_at,
+        CURRENT_TIMESTAMP AS updated_at,
+        CURRENT_TIMESTAMP AS dbt_loaded_at
+    FROM (
+        SELECT * FROM ft_made_expanded
+        UNION ALL
+        SELECT * FROM ft_missed_expanded
+    ) AS ft
+),
+
+final AS (
+    SELECT * FROM fg_shots
+    UNION ALL
+    SELECT * FROM ft_shots
+)
+
+SELECT * FROM final

dbt_nba/models/intermediate/int_team_performance.sql

@@ -0,0 +1,85 @@
+{{
+    config(
+        materialized='table',
+        schema='intermediate',
+        tags=["intermediate"]
+    )
+}}
+
+WITH basic_stats AS (
+    SELECT
+        s.*,
+        map.team_abbr AS team_conformed
+    FROM {{ ref('stg_team_game_basic_stats') }} AS s
+    LEFT JOIN {{ ref('team_maps') }} AS map
+        ON s.team = map.team_abbr
+    LEFT JOIN {{ ref('stg_games') }} AS g
+        ON s.game_id = g.game_id
+    WHERE (g.season_start_year >= map.start_year AND g.season_start_year < map.end_year)
+),
+
+adv_stats AS (
+    SELECT
+        s.*,
+        map.team_abbr AS team_conformed
+    FROM {{ ref('stg_team_game_adv_stats') }} AS s
+    LEFT JOIN {{ ref('team_maps') }} AS map
+        ON s.team = map.team_abbr
+    LEFT JOIN {{ ref('stg_games') }} AS g
+        ON s.game_id = g.game_id
+    WHERE (g.season_start_year >= map.start_year AND g.season_start_year < map.end_year)
+),
+
+games AS (
+    SELECT
+        g.game_id,
+        g.game_date,
+        g.season_start_year,
+        g.is_playoff,
+        home_map.team_abbr AS home_team_abbr,
+        visitor_map.team_abbr AS visitor_team_abbr,
+        winning_map.team_abbr AS winning_team_abbr
+    FROM {{ ref('stg_games') }} g
+    LEFT JOIN {{ ref('team_maps') }} AS home_map ON g.home_team = home_map.full_name
+    LEFT JOIN {{ ref('team_maps') }} AS visitor_map ON g.visitor_team = visitor_map.full_name
+    LEFT JOIN {{ ref('team_maps') }} AS winning_map ON g.winning_team = winning_map.full_name
+    WHERE (g.season_start_year >= home_map.start_year AND g.season_start_year < home_map.end_year)
+    AND (g.season_start_year >= visitor_map.start_year AND g.season_start_year < visitor_map.end_year)
+    AND (g.season_start_year >= winning_map.start_year AND g.season_start_year < winning_map.end_year)
+),
+
+final AS (
+    SELECT
+        b.game_id,
+        b.team_conformed AS team,
+        g.game_date,
+        g.season_start_year,
+        g.is_playoff,
+        CASE WHEN b.team_conformed = g.winning_team_abbr THEN 'W' ELSE 'L' END AS game_result,
+        CASE
+            WHEN b.team_conformed = g.home_team_abbr THEN g.visitor_team_abbr
+            ELSE g.home_team_abbr
+        END AS opponent_team,
+        b.points,
+        a.offensive_rating,
+        a.defensive_rating,
+        a.net_rating,
+        b.pace,
+        b.effective_fg_pct,
+        b.turnover_rate,
+        b.offensive_rebound_rate,
+        b.free_throw_rate,
+        a.offensive_tier,
+        a.defensive_tier,
+        a.shot_selection_style,
+        a.ball_movement_style,
+        a.ball_security_tier,
+        a.defensive_activity
+    FROM basic_stats AS b
+    LEFT JOIN adv_stats AS a
+        ON b.game_id = a.game_id AND b.team_conformed = a.team_conformed
+    LEFT JOIN games AS g
+        ON b.game_id = g.game_id
+)
+
+SELECT * FROM final

dbt_nba/models/marts/dimensions/dim_arenas.sql

@@ -0,0 +1,21 @@
+{{
+    config(
+        materialized='table',
+        schema='marts',
+        tags=["dimension"]
+    )
+}}
+
+WITH source AS (
+    SELECT arena_name, city, state_or_country, location
+    FROM {{ ref('arena_mappings') }}
+)
+
+SELECT
+    {{ dbt_utils.generate_surrogate_key(['arena_name', 'city']) }} AS arena_key,
+    arena_name,
+    city AS arena_city,
+    state_or_country AS arena_state_or_country,
+    location AS arena_location
+FROM source
+ORDER BY arena_name, arena_city

dbt_nba/models/marts/dimensions/dim_dates.sql

@@ -0,0 +1,44 @@
+{{
+    config(
+        materialized='table',
+        schema='marts',
+        tags=["dimension"]
+    )
+}}
+
+{% set start_date_query %}
+select min(game_date)::date from {{ ref('stg_games') }}
+{% endset %}
+{% set start_date = dbt_utils.get_single_value(start_date_query) %}
+
+{% set end_date_query %}
+select max(game_date)::date from {{ ref('stg_games') }}
+{% endset %}
+{% set end_date = dbt_utils.get_single_value(end_date_query) %}
+
+WITH date_spine AS (
+    SELECT UNNEST(generate_series(
+        '{{ start_date }}'::date,
+        '{{ end_date }}'::date,
+        INTERVAL '1 day'
+    ))::date AS date_day
+)
+
+SELECT
+    CAST(strftime(date_day, '%Y%m%d') AS INTEGER) AS date_key,
+    date_day AS full_date,
+    EXTRACT(YEAR FROM date_day)::int AS year,
+    EXTRACT(QUARTER FROM date_day)::int AS quarter_of_year,
+    EXTRACT(MONTH FROM date_day)::int AS month_of_year,
+    strftime(date_day, '%B') AS month_name,
+    EXTRACT(DAY FROM date_day)::int AS day_of_month,
+    EXTRACT(ISODOW FROM date_day)::int AS day_of_week,
+    strftime(date_day, '%A') AS day_of_week_name,
+    EXTRACT(DOY FROM date_day)::int AS day_of_year,
+    EXTRACT(WEEK FROM date_day)::int AS week_of_year,
+    CASE
+        WHEN EXTRACT(ISODOW FROM date_day) IN (6, 7) THEN true
+        ELSE false
+    END AS is_weekend
+FROM date_spine
+ORDER BY full_date

dbt_nba/models/marts/dimensions/dim_player_game_archetypes.sql

@@ -0,0 +1,36 @@
+{{
+    config(
+        materialized='table',
+        schema='marts',
+        tags=["dimension"]
+    )
+}}
+
+WITH distinct_archetypes AS (
+    SELECT DISTINCT
+        usage_tier,
+        impact_tier,
+        shooting_efficiency_tier,
+        minutes_based_role,
+        is_double_double,
+        is_triple_double,
+        is_versatile,
+        is_defensive_specialist,
+        is_three_and_d
+    FROM {{ ref('int_player_performance') }}
+)
+
+SELECT
+    {{ dbt_utils.generate_surrogate_key([
+        'usage_tier',
+        'impact_tier',
+        'shooting_efficiency_tier',
+        'minutes_based_role',
+        'is_double_double',
+        'is_triple_double',
+        'is_versatile',
+        'is_defensive_specialist',
+        'is_three_and_d'
+    ]) }} AS archetype_key,
+    *
+FROM distinct_archetypes

dbt_nba/models/marts/dimensions/dim_players.sql

@@ -0,0 +1,26 @@
+{{
+    config(
+        materialized='table',
+        schema='marts',
+        tags=["dimension"]
+    )
+}}
+
+WITH player_game_stats AS (
+    SELECT
+        stats.player_id,
+        stats.player_name,
+        games.game_date,
+        ROW_NUMBER() OVER (PARTITION BY stats.player_id ORDER BY games.game_date DESC) as rn
+    FROM {{ ref('stg_player_game_basic_stats') }} AS stats
+    LEFT JOIN {{ ref('stg_games') }} AS games
+        ON stats.game_id = games.game_id
+)
+
+SELECT
+    {{ dbt_utils.generate_surrogate_key(['player_id']) }} AS player_key,
+    player_id,
+    player_name
+FROM player_game_stats
+WHERE rn = 1
+ORDER BY player_name

dbt_nba/models/marts/dimensions/dim_seasons.sql

@@ -0,0 +1,19 @@
+{{
+    config(
+        materialized='table',
+        schema='marts',
+        tags=["dimension"]
+    )
+}}
+
+WITH all_seasons AS (
+    SELECT DISTINCT season_start_year
+    FROM {{ ref('int_games_enriched') }}
+)
+
+SELECT
+    {{ dbt_utils.generate_surrogate_key(['season_start_year']) }} AS season_key,
+    season_start_year,
+    season_start_year || '-' || SUBSTR(CAST(season_start_year + 1 AS VARCHAR), 3, 2) AS season_display
+FROM all_seasons
+ORDER BY season_start_year

dbt_nba/models/marts/dimensions/dim_shot_zones.sql

@@ -0,0 +1,32 @@
+{{
+    config(
+        materialized='table',
+        schema='marts',
+        tags=["dimension"]
+    )
+}}
+
+WITH zones AS (
+    SELECT * FROM (
+        VALUES
+            ('At Rim (0-3 ft)',           0,  3,  1, 'Paint',      'Interior',    'Field Goal'),
+            ('Short Range (4-10 ft)',     4,  10, 2, 'Paint',      'Interior',    'Field Goal'),
+            ('Mid Range (11-16 ft)',      11, 16, 3, 'Mid Range',  'Mid Range',   'Field Goal'),
+            ('Long Mid Range (17-23 ft)', 17, 23, 4, 'Mid Range',  'Mid Range',   'Field Goal'),
+            ('Three Point (24-27 ft)',    24, 27, 5, 'Perimeter',  'Three Point', 'Field Goal'),
+            ('Deep Three (28+ ft)',       28, 50, 6, 'Perimeter',  'Three Point', 'Field Goal'),
+            ('Free Throw (15 ft)',        15, 15, 7, 'Free Throw', 'Free Throw',  'Free Throw')
+    ) AS t(shot_distance_zone, min_distance_ft, max_distance_ft, zone_order, zone_group, zone_category, shot_class)
+)
+
+SELECT
+    {{ dbt_utils.generate_surrogate_key(['shot_distance_zone']) }} AS shot_zone_key,
+    shot_distance_zone,
+    min_distance_ft,
+    max_distance_ft,
+    zone_order,
+    zone_group,
+    zone_category,
+    shot_class
+FROM zones
+ORDER BY zone_order

dbt_nba/models/marts/dimensions/dim_teams.sql

@@ -0,0 +1,19 @@
+{{
+    config(
+        materialized='table',
+        schema='marts',
+        tags=["dimension"]
+    )
+}}
+
+WITH team_mappings AS (
+    SELECT team_abbr, full_name
+    FROM {{ ref('team_maps') }}
+)
+
+SELECT
+    {{ dbt_utils.generate_surrogate_key(['team_abbr']) }} AS team_key,
+    team_abbr,
+    full_name AS team_full_name
+FROM team_mappings
+ORDER BY team_abbr

dbt_nba/models/marts/facts/fct_game_results.sql

@@ -0,0 +1,50 @@
+{{
+    config(
+        materialized='incremental',
+        schema='marts',
+        unique_key='game_key',
+        tags=["fact"]
+    )
+}}
+
+WITH games_enriched AS (
+    SELECT *
+    FROM {{ ref('int_games_enriched') }}
+    {% if is_incremental() %}
+    WHERE game_date >= (SELECT MAX(game_date) FROM {{ this }}) - INTERVAL '30 days'
+    {% endif %}
+)
+
+SELECT
+    {{ dbt_utils.generate_surrogate_key(['ge.game_id']) }} AS game_key,
+    d.date_key,
+    s.season_key,
+    a.arena_key,
+    home_team.team_key AS home_team_key,
+    visitor_team.team_key AS visitor_team_key,
+    winning_team.team_key AS winning_team_key,
+    ge.game_id,
+    ge.home_points,
+    ge.visitor_points,
+    ge.point_differential,
+    ge.total_points,
+    ge.is_playoff,
+    ge.is_overtime,
+    CASE WHEN ge.home_points > ge.visitor_points THEN TRUE ELSE FALSE END AS is_home_team_winner,
+    ge.home_net_rating,
+    ge.visitor_net_rating,
+    ge.matchup_pace,
+    CASE
+        WHEN ge.point_differential <= 5 THEN 'Clutch Game'
+        WHEN ge.point_differential <= 10 THEN 'Competitive'
+        WHEN ge.point_differential <= 20 THEN 'Decisive'
+        ELSE 'Blowout'
+    END AS game_competitiveness_tier,
+    CAST(ge.game_date AS DATE) AS game_date
+FROM games_enriched AS ge
+LEFT JOIN {{ ref('dim_dates') }} AS d ON CAST(ge.game_date AS DATE) = d.full_date
+LEFT JOIN {{ ref('dim_seasons') }} AS s ON ge.season_start_year = s.season_start_year
+LEFT JOIN {{ ref('dim_arenas') }} AS a ON ge.arena = a.arena_name AND ge.arena_city = a.arena_city
+LEFT JOIN {{ ref('dim_teams') }} AS home_team ON ge.home_team = home_team.team_abbr
+LEFT JOIN {{ ref('dim_teams') }} AS visitor_team ON ge.visitor_team = visitor_team.team_abbr
+LEFT JOIN {{ ref('dim_teams') }} AS winning_team ON ge.winning_team = winning_team.team_abbr

dbt_nba/models/marts/facts/fct_player_game_shooting.sql

@@ -0,0 +1,175 @@
+{{
+    config(
+        materialized='incremental',
+        schema='marts',
+        unique_key='player_game_shooting_key',
+        tags=["fact"]
+    )
+}}
+
+WITH shots AS (
+    SELECT *
+    FROM {{ ref('int_player_shots_enriched') }}
+    WHERE has_game_match = TRUE
+    {% if is_incremental() %}
+      AND game_date >= (SELECT MAX(game_date) FROM {{ this }}) - INTERVAL '30 days'
+    {% endif %}
+),
+
+game_agg AS (
+    SELECT
+        game_id, player_id, team, opponent,
+        MIN(game_date) AS game_date,
+        MIN(season_start_year) AS season_start_year,
+        BOOL_OR(is_playoff) AS is_playoff,
+        MIN(team_location) AS team_location,
+        MIN(game_result) AS game_result,
+
+        SUM(points_generated) AS total_points,
+        COUNT(*) AS total_shot_attempts,
+        SUM(shot_made_flag) AS total_shots_made,
+
+        COUNT(*) FILTER (WHERE shot_source = 'shot_chart') AS fg_attempts,
+        SUM(shot_made_flag) FILTER (WHERE shot_source = 'shot_chart') AS fg_makes,
+        CASE WHEN COUNT(*) FILTER (WHERE shot_source = 'shot_chart') > 0
+            THEN SUM(shot_made_flag) FILTER (WHERE shot_source = 'shot_chart')::DECIMAL
+                 / COUNT(*) FILTER (WHERE shot_source = 'shot_chart')::DECIMAL
+            ELSE 0
+        END AS fg_pct,
+        SUM(points_generated) FILTER (WHERE shot_source = 'shot_chart') AS fg_points,
+
+        COUNT(*) FILTER (WHERE shot_source = 'box_score_ft') AS ft_attempts,
+        SUM(shot_made_flag) FILTER (WHERE shot_source = 'box_score_ft') AS ft_makes,
+        CASE WHEN COUNT(*) FILTER (WHERE shot_source = 'box_score_ft') > 0
+            THEN SUM(shot_made_flag) FILTER (WHERE shot_source = 'box_score_ft')::DECIMAL
+                 / COUNT(*) FILTER (WHERE shot_source = 'box_score_ft')::DECIMAL
+            ELSE 0
+        END AS ft_pct,
+        SUM(points_generated) FILTER (WHERE shot_source = 'box_score_ft') AS ft_points,
+
+        COUNT(*) FILTER (WHERE is_three_pointer = FALSE AND shot_source = 'shot_chart') AS two_point_attempts,
+        SUM(shot_made_flag) FILTER (WHERE is_three_pointer = FALSE AND shot_source = 'shot_chart') AS two_point_makes,
+        CASE WHEN COUNT(*) FILTER (WHERE is_three_pointer = FALSE AND shot_source = 'shot_chart') > 0
+            THEN SUM(shot_made_flag) FILTER (WHERE is_three_pointer = FALSE AND shot_source = 'shot_chart')::DECIMAL
+                 / COUNT(*) FILTER (WHERE is_three_pointer = FALSE AND shot_source = 'shot_chart')::DECIMAL
+            ELSE 0
+        END AS two_point_fg_pct,
+
+        COUNT(*) FILTER (WHERE is_three_pointer = TRUE) AS three_point_attempts,
+        SUM(shot_made_flag) FILTER (WHERE is_three_pointer = TRUE) AS three_point_makes,
+        CASE WHEN COUNT(*) FILTER (WHERE is_three_pointer = TRUE) > 0
+            THEN SUM(shot_made_flag) FILTER (WHERE is_three_pointer = TRUE)::DECIMAL
+                 / COUNT(*) FILTER (WHERE is_three_pointer = TRUE)::DECIMAL
+            ELSE 0
+        END AS three_point_fg_pct,
+
+        COUNT(*) FILTER (WHERE shot_distance_zone = 'At Rim (0-3 ft)') AS at_rim_attempts,
+        SUM(shot_made_flag) FILTER (WHERE shot_distance_zone = 'At Rim (0-3 ft)') AS at_rim_makes,
+        CASE WHEN COUNT(*) FILTER (WHERE shot_distance_zone = 'At Rim (0-3 ft)') > 0
+            THEN SUM(shot_made_flag) FILTER (WHERE shot_distance_zone = 'At Rim (0-3 ft)')::DECIMAL
+                 / COUNT(*) FILTER (WHERE shot_distance_zone = 'At Rim (0-3 ft)')::DECIMAL
+            ELSE 0
+        END AS at_rim_fg_pct,
+
+        COUNT(*) FILTER (WHERE is_clutch_shot = TRUE) AS clutch_fg_attempts,
+        SUM(shot_made_flag) FILTER (WHERE is_clutch_shot = TRUE) AS clutch_fg_makes,
+        CASE WHEN COUNT(*) FILTER (WHERE is_clutch_shot = TRUE) > 0
+            THEN SUM(shot_made_flag) FILTER (WHERE is_clutch_shot = TRUE)::DECIMAL
+                 / COUNT(*) FILTER (WHERE is_clutch_shot = TRUE)::DECIMAL
+            ELSE 0
+        END AS clutch_fg_pct,
+
+        CASE WHEN COUNT(*) FILTER (WHERE shot_source = 'shot_chart') > 0
+            THEN COUNT(*) FILTER (WHERE is_three_pointer = TRUE)::DECIMAL
+                 / COUNT(*) FILTER (WHERE shot_source = 'shot_chart')::DECIMAL
+            ELSE 0
+        END AS three_point_rate,
+
+        CASE WHEN COUNT(*) FILTER (WHERE shot_source = 'shot_chart') > 0
+            THEN COUNT(*) FILTER (WHERE shot_distance_zone = 'At Rim (0-3 ft)')::DECIMAL
+                 / COUNT(*) FILTER (WHERE shot_source = 'shot_chart')::DECIMAL
+            ELSE 0
+        END AS at_rim_rate,
+
+        CASE WHEN COUNT(*) FILTER (WHERE shot_source = 'shot_chart') > 0
+            THEN COUNT(*) FILTER (WHERE shot_distance_zone IN ('Mid Range (11-16 ft)', 'Long Mid Range (17-23 ft)'))::DECIMAL
+                 / COUNT(*) FILTER (WHERE shot_source = 'shot_chart')::DECIMAL
+            ELSE 0
+        END AS mid_range_rate,
+
+        AVG(distance_ft) FILTER (WHERE shot_source = 'shot_chart') AS avg_fg_distance_ft,
+
+        CASE WHEN (
+                COUNT(*) FILTER (WHERE shot_source = 'shot_chart')
+                + 0.44 * COUNT(*) FILTER (WHERE shot_source = 'box_score_ft')
+            ) > 0
+            THEN SUM(points_generated)::DECIMAL / (
+                2.0 * (
+                    COUNT(*) FILTER (WHERE shot_source = 'shot_chart')
+                    + 0.44 * COUNT(*) FILTER (WHERE shot_source = 'box_score_ft')
+                )
+            )
+            ELSE 0
+        END AS true_shooting_pct
+
+    FROM shots
+    GROUP BY game_id, player_id, team, opponent
+),
+
+final AS (
+    SELECT
+        {{ dbt_utils.generate_surrogate_key(['ga.game_id', 'ga.player_id']) }} AS player_game_shooting_key,
+        p.player_key,
+        t.team_key,
+        opp_t.team_key AS opponent_key,
+        d.date_key,
+        s.season_key,
+        ga.game_id,
+        ga.is_playoff,
+        ga.team_location,
+        ga.game_result,
+        ga.total_points,
+        ga.total_shot_attempts,
+        ga.total_shots_made,
+        ga.fg_attempts,
+        ga.fg_makes,
+        ga.fg_pct,
+        ga.fg_points,
+        ga.ft_attempts,
+        ga.ft_makes,
+        ga.ft_pct,
+        ga.ft_points,
+        ga.true_shooting_pct,
+        ga.two_point_attempts,
+        ga.two_point_makes,
+        ga.two_point_fg_pct,
+        ga.three_point_attempts,
+        ga.three_point_makes,
+        ga.three_point_fg_pct,
+        ga.at_rim_attempts,
+        ga.at_rim_makes,
+        ga.at_rim_fg_pct,
+        ga.clutch_fg_attempts,
+        ga.clutch_fg_makes,
+        ga.clutch_fg_pct,
+        ga.three_point_rate,
+        ga.at_rim_rate,
+        ga.mid_range_rate,
+        ga.avg_fg_distance_ft,
+        CASE
+            WHEN ga.three_point_rate >= 0.50 THEN 'Perimeter Heavy'
+            WHEN ga.at_rim_rate >= 0.50 THEN 'Rim Attacker'
+            WHEN ga.mid_range_rate >= 0.40 THEN 'Mid Range Heavy'
+            WHEN ga.three_point_rate >= 0.35 AND ga.at_rim_rate >= 0.30 THEN 'Modern (Rim & Three)'
+            ELSE 'Balanced'
+        END AS shot_profile_type,
+        CAST(ga.game_date AS DATE) AS game_date
+    FROM game_agg AS ga
+    LEFT JOIN {{ ref('dim_players') }} AS p ON ga.player_id = p.player_id
+    LEFT JOIN {{ ref('dim_teams') }} AS t ON ga.team = t.team_abbr
+    LEFT JOIN {{ ref('dim_teams') }} AS opp_t ON ga.opponent = opp_t.team_abbr
+    LEFT JOIN {{ ref('dim_dates') }} AS d ON CAST(ga.game_date AS DATE) = d.full_date
+    LEFT JOIN {{ ref('dim_seasons') }} AS s ON ga.season_start_year = s.season_start_year
+)
+
+SELECT * FROM final

dbt_nba/models/marts/facts/fct_player_game_stats.sql

@@ -0,0 +1,71 @@
+{{
+    config(
+        materialized='incremental',
+        schema='marts',
+        unique_key='player_game_key',
+        tags=["fact"]
+    )
+}}
+
+WITH player_performance AS (
+    SELECT * FROM {{ ref('int_player_performance') }}
+),
+
+game_details AS (
+    SELECT game_id, arena AS arena_name, arena_city
+    FROM {{ ref('int_games_enriched') }}
+),
+
+final AS (
+    SELECT
+        {{ dbt_utils.generate_surrogate_key(['pp.game_id', 'pp.player_id']) }} AS player_game_key,
+        p.player_key,
+        t.team_key,
+        d.date_key,
+        s.season_key,
+        a.arena_key,
+        arch.archetype_key,
+        pp.game_id,
+        pp.minutes_played,
+        pp.points,
+        pp.assists,
+        pp.total_rebounds,
+        pp.steals,
+        pp.blocks,
+        pp.turnovers,
+        pp.plus_minus,
+        pp.net_rating,
+        pp.box_plus_minus,
+        pp.field_goals_made,
+        pp.field_goals_attempted,
+        pp.three_pointers_made,
+        pp.three_pointers_attempted,
+        pp.true_shooting_pct,
+        pp.effective_fg_pct,
+        pp.usage_pct,
+        pp.offensive_rating,
+        pp.defensive_rating,
+        CAST(pp.game_date AS DATE) AS game_date
+    FROM player_performance AS pp
+    LEFT JOIN game_details AS gd ON pp.game_id = gd.game_id
+    LEFT JOIN {{ ref('dim_player_game_archetypes') }} AS arch
+        ON pp.usage_tier = arch.usage_tier
+        AND pp.impact_tier = arch.impact_tier
+        AND pp.shooting_efficiency_tier = arch.shooting_efficiency_tier
+        AND pp.minutes_based_role = arch.minutes_based_role
+        AND pp.is_double_double = arch.is_double_double
+        AND pp.is_triple_double = arch.is_triple_double
+        AND pp.is_versatile = arch.is_versatile
+        AND pp.is_defensive_specialist = arch.is_defensive_specialist
+        AND pp.is_three_and_d = arch.is_three_and_d
+    LEFT JOIN {{ ref('dim_players') }} AS p ON pp.player_id = p.player_id
+    LEFT JOIN {{ ref('dim_teams') }} AS t ON pp.team = t.team_abbr
+    LEFT JOIN {{ ref('dim_dates') }} AS d ON CAST(pp.game_date AS DATE) = d.full_date
+    LEFT JOIN {{ ref('dim_seasons') }} AS s ON pp.season_start_year = s.season_start_year
+    LEFT JOIN {{ ref('dim_arenas') }} AS a ON gd.arena_name = a.arena_name AND gd.arena_city = a.arena_city
+    {% if is_incremental() %}
+    WHERE pp.game_date >= (SELECT MAX(game_date) FROM {{ this }}) - INTERVAL '30 days'
+    {% endif %}
+)
+
+SELECT * FROM final

dbt_nba/models/marts/facts/fct_player_shots.sql

@@ -0,0 +1,62 @@
+{{
+    config(
+        materialized='incremental',
+        schema='marts',
+        unique_key='shot_key',
+        tags=["fact"]
+    )
+}}
+
+WITH shots_enriched AS (
+    SELECT *
+    FROM {{ ref('int_player_shots_enriched') }}
+    WHERE has_game_match = TRUE
+    {% if is_incremental() %}
+      AND game_date >= (SELECT MAX(game_date) FROM {{ this }}) - INTERVAL '30 days'
+    {% endif %}
+),
+
+final AS (
+    SELECT
+        {{ dbt_utils.generate_surrogate_key(['se.shot_id', 'se.shot_source']) }} AS shot_key,
+        p.player_key,
+        t.team_key,
+        opp_t.team_key AS opponent_key,
+        d.date_key,
+        s.season_key,
+        se.game_id,
+        se.shot_id,
+        se.shot_source,
+        se.is_playoff,
+        se.team_location,
+        se.game_result,
+        se.quarter_number,
+        se.is_overtime_shot,
+        se.seconds_remaining_in_quarter,
+        se.shot_x_coordinate,
+        se.shot_y_coordinate,
+        se.is_made,
+        se.shot_made_flag,
+        se.shot_missed_flag,
+        se.shot_type_raw AS shot_type,
+        se.shot_point_value,
+        se.is_three_pointer,
+        se.is_free_throw,
+        se.distance_ft,
+        se.shot_distance_zone,
+        se.points_generated,
+        se.team_had_lead,
+        se.team_score_at_shot,
+        se.opponent_score_at_shot,
+        se.score_margin_at_shot,
+        se.is_clutch_shot,
+        CAST(se.game_date AS DATE) AS game_date
+    FROM shots_enriched AS se
+    LEFT JOIN {{ ref('dim_players') }} AS p ON se.player_id = p.player_id
+    LEFT JOIN {{ ref('dim_teams') }} AS t ON se.team = t.team_abbr
+    LEFT JOIN {{ ref('dim_teams') }} AS opp_t ON se.opponent = opp_t.team_abbr
+    LEFT JOIN {{ ref('dim_dates') }} AS d ON CAST(se.game_date AS DATE) = d.full_date
+    LEFT JOIN {{ ref('dim_seasons') }} AS s ON se.season_start_year = s.season_start_year
+)
+
+SELECT * FROM final

dbt_nba/models/marts/facts/fct_quarter_scoring.sql

@@ -0,0 +1,57 @@
+{{
+    config(
+        materialized='incremental',
+        schema='marts',
+        unique_key='quarter_scoring_key',
+        tags=["fact"]
+    )
+}}
+
+WITH games AS (
+    SELECT game_id, game_date, season_start_year
+    FROM {{ ref('int_games_enriched') }}
+    {% if is_incremental() %}
+    WHERE game_date >= (SELECT MAX(game_date) FROM {{ this }}) - INTERVAL '30 days'
+    {% endif %}
+),
+
+unpivoted_scores AS (
+    {{ dbt_utils.unpivot(
+        relation=ref('stg_line_scores'),
+        cast_to='INTEGER',
+        exclude=['game_id', 'team', 'total_points', 'first_half_points', 'second_half_points', 'regulation_points', 'overtime_points', 'had_ot1', 'had_ot2', 'had_ot3', 'q2_momentum', 'q3_momentum', 'q4_momentum', 'max_quarter_score', 'min_quarter_score', 'best_quarter', 'created_at', 'updated_at', 'dbt_loaded_at'],
+        field_name='period_name',
+        value_name='points_scored'
+    ) }}
+    WHERE game_id IN (SELECT game_id FROM games)
+),
+
+final AS (
+    SELECT
+        {{ dbt_utils.generate_surrogate_key(['team_scores.game_id', 'team_map.team_abbr', 'team_scores.period_name']) }} AS quarter_scoring_key,
+        d.date_key,
+        s.season_key,
+        t.team_key,
+        opp.team_key AS opponent_key,
+        team_scores.game_id,
+        REPLACE(UPPER(team_scores.period_name), '_POINTS', '') AS period,
+        team_scores.points_scored,
+        opponent_scores.points_scored AS opponent_points_scored,
+        (team_scores.points_scored - opponent_scores.points_scored) AS period_point_differential,
+        CAST(g.game_date AS DATE) AS game_date
+    FROM unpivoted_scores AS team_scores
+    INNER JOIN unpivoted_scores AS opponent_scores
+        ON team_scores.game_id = opponent_scores.game_id
+        AND team_scores.period_name = opponent_scores.period_name
+        AND team_scores.team != opponent_scores.team
+    INNER JOIN games AS g ON team_scores.game_id = g.game_id
+    LEFT JOIN {{ ref('team_maps') }} AS team_map ON team_scores.team = team_map.team_abbr
+    LEFT JOIN {{ ref('team_maps') }} AS opponent_map ON opponent_scores.team = opponent_map.team_abbr
+    LEFT JOIN {{ ref('dim_teams') }} AS t ON team_map.team_abbr = t.team_abbr
+    LEFT JOIN {{ ref('dim_teams') }} AS opp ON opponent_map.team_abbr = opp.team_abbr
+    LEFT JOIN {{ ref('dim_dates') }} AS d ON CAST(g.game_date AS DATE) = d.full_date
+    LEFT JOIN {{ ref('dim_seasons') }} AS s ON g.season_start_year = s.season_start_year
+    WHERE team_scores.points_scored IS NOT NULL
+)
+
+SELECT * FROM final

dbt_nba/models/marts/facts/fct_team_game_stats.sql

@@ -0,0 +1,54 @@
+{{
+    config(
+        materialized='incremental',
+        schema='marts',
+        tags=["fact"],
+        unique_key='team_game_key'
+    )
+}}
+
+WITH team_performance AS (
+    SELECT * FROM {{ ref('int_team_performance') }}
+),
+
+game_details AS (
+    SELECT
+        game_id, game_date, season_start_year,
+        home_team, visitor_team, arena AS arena_name, arena_city
+    FROM {{ ref('int_games_enriched') }}
+),
+
+final AS (
+    SELECT
+        {{ dbt_utils.generate_surrogate_key(['tp.game_id', 'tp.team']) }} AS team_game_key,
+        t.team_key,
+        d.date_key,
+        s.season_key,
+        a.arena_key,
+        opp.team_key AS opponent_key,
+        tp.game_id,
+        (tp.team = gd.home_team) AS is_home_team,
+        tp.points,
+        tp.offensive_rating,
+        tp.defensive_rating,
+        tp.net_rating,
+        tp.pace,
+        tp.effective_fg_pct,
+        tp.turnover_rate,
+        tp.offensive_tier,
+        tp.defensive_tier,
+        CAST(gd.game_date AS DATE) AS game_date
+    FROM team_performance AS tp
+    LEFT JOIN game_details AS gd ON tp.game_id = gd.game_id
+    LEFT JOIN {{ ref('dim_teams') }} AS t ON tp.team = t.team_abbr
+    LEFT JOIN {{ ref('dim_teams') }} AS opp
+        ON CASE WHEN tp.team = gd.home_team THEN gd.visitor_team ELSE gd.home_team END = opp.team_abbr
+    LEFT JOIN {{ ref('dim_dates') }} AS d ON CAST(gd.game_date AS DATE) = d.full_date
+    LEFT JOIN {{ ref('dim_seasons') }} AS s ON gd.season_start_year = s.season_start_year
+    LEFT JOIN {{ ref('dim_arenas') }} AS a ON gd.arena_name = a.arena_name AND gd.arena_city = a.arena_city
+    {% if is_incremental() %}
+    WHERE gd.game_date >= (SELECT MAX(game_date) FROM {{ this }}) - INTERVAL '30 days'
+    {% endif %}
+)
+
+SELECT * FROM final

dbt_nba/models/schema.yml

@@ -0,0 +1,129 @@
+version: 2
+
+sources:
+  - name: raw_nba
+    description: Raw NBA data in DuckDB
+    schema: main
+    tables:
+      - name: games
+        description: Core game information including scores, teams, and venues
+        columns:
+          - name: game_id
+            tests:
+              - unique
+              - not_null
+      - name: line_scores
+        description: Quarter-by-quarter scoring breakdown
+        columns:
+          - name: game_id
+            tests:
+              - not_null
+      - name: player_game_basic_stats
+        description: Basic player statistics for each game
+        columns:
+          - name: game_id
+            tests:
+              - not_null
+          - name: player_id
+            tests:
+              - not_null
+      - name: player_game_adv_stats
+        description: Advanced player statistics for each game
+        columns:
+          - name: game_id
+            tests:
+              - not_null
+          - name: player_id
+            tests:
+              - not_null
+      - name: team_game_basic_stats
+        description: Basic team statistics for each game
+        columns:
+          - name: game_id
+            tests:
+              - not_null
+          - name: team
+            tests:
+              - not_null
+      - name: team_game_adv_stats
+        description: Advanced team statistics for each game
+        columns:
+          - name: game_id
+            tests:
+              - not_null
+          - name: team
+            tests:
+              - not_null
+      - name: player_shot_charts
+        description: Individual shot-level data from NBA player shot charts
+        columns:
+          - name: id
+            tests:
+              - unique
+              - not_null
+
+models:
+  - name: stg_games
+    description: Staged games data with cleaned fields and derived metrics
+    columns:
+      - name: game_id
+        tests:
+          - unique
+          - not_null
+
+  - name: stg_line_scores
+    description: Staged quarter-by-quarter scoring with momentum metrics
+    columns:
+      - name: game_id
+        tests:
+          - not_null
+
+  - name: stg_player_game_basic_stats
+    description: Staged player basic stats with calculated metrics
+    columns:
+      - name: game_id
+        tests:
+          - not_null
+      - name: player_id
+        tests:
+          - not_null
+
+  - name: stg_player_game_adv_stats
+    description: Staged player advanced stats with performance tiers
+    columns:
+      - name: game_id
+        tests:
+          - not_null
+      - name: player_id
+        tests:
+          - not_null
+
+  - name: stg_player_game_adv_stats_extended
+    description: Extended player advanced stats with dynamic per-season tiering
+    columns:
+      - name: game_id
+        tests:
+          - not_null
+      - name: player_id
+        tests:
+          - not_null
+
+  - name: stg_team_game_basic_stats
+    description: Staged team basic stats with four factors
+    columns:
+      - name: game_id
+        tests:
+          - not_null
+      - name: team
+        tests:
+          - not_null
+
+  - name: stg_team_game_adv_stats
+    description: Staged team advanced stats with play style indicators
+    columns:
+      - name: game_id
+        tests:
+          - not_null
+      - name: team
+        tests:
+          - not_null

dbt_nba/models/staging/stg_games.sql

@@ -0,0 +1,82 @@
+{{
+    config(
+        materialized='view',
+        schema='staging'
+    )
+}}
+
+WITH overtime_games AS (
+    SELECT
+        game_id,
+        MAX(CASE WHEN overtime_points > 0 THEN 1 ELSE 0 END) AS had_overtime
+    FROM {{ ref('stg_line_scores') }}
+    GROUP BY 1
+),
+
+source_data AS (
+    SELECT * FROM {{ source('raw_nba', 'games') }}
+    WHERE deleted_at IS NULL
+),
+
+cleaned AS (
+    SELECT
+        g.game_id,
+        g.home_team,
+        g.visitor_team,
+        g.date AS game_date,
+        EXTRACT(YEAR FROM g.date) AS season_year,
+        CASE
+            WHEN EXTRACT(MONTH FROM g.date) >= 10 THEN EXTRACT(YEAR FROM g.date)
+            ELSE EXTRACT(YEAR FROM g.date) - 1
+        END AS season_start_year,
+        EXTRACT(MONTH FROM g.date) AS game_month,
+        EXTRACT(DAY FROM g.date) AS game_day,
+        strftime(g.date, '%A') AS game_day_of_week,
+        g.is_playoff,
+        g.start_time_et,
+        CASE
+            WHEN g.start_time_et LIKE '%7:%p%' OR g.start_time_et LIKE '%8:%p%' THEN 'Prime Time'
+            WHEN g.start_time_et LIKE '%12:%p%' OR g.start_time_et LIKE '%1:%p%'
+                OR g.start_time_et LIKE '%2:%p%' OR g.start_time_et LIKE '%3:%p%' THEN 'Afternoon'
+            ELSE 'Late Night'
+        END AS game_time_slot,
+        g.arena,
+        g.home_pts AS home_points,
+        g.visitor_pts AS visitor_points,
+        CASE
+            WHEN g.home_pts > g.visitor_pts THEN g.home_team
+            WHEN g.visitor_pts > g.home_pts THEN g.visitor_team
+            ELSE NULL
+        END AS winning_team,
+        CASE
+            WHEN g.home_pts < g.visitor_pts THEN g.home_team
+            WHEN g.visitor_pts < g.home_pts THEN g.visitor_team
+            ELSE NULL
+        END AS losing_team,
+        CASE
+            WHEN g.home_pts > g.visitor_pts THEN 'HOME'
+            WHEN g.visitor_pts > g.home_pts THEN 'AWAY'
+            ELSE NULL
+        END AS winner_location,
+        ABS(g.home_pts - g.visitor_pts) AS point_differential,
+        g.home_pts + g.visitor_pts AS total_points,
+        g.game_duration,
+        CASE
+            WHEN ot.had_overtime = 1 THEN TRUE
+            ELSE FALSE
+        END AS is_overtime,
+        g.box_score_url,
+        g.created_at,
+        g.updated_at,
+        CURRENT_TIMESTAMP AS dbt_loaded_at
+    FROM source_data AS g
+    LEFT JOIN overtime_games AS ot
+        ON g.game_id = ot.game_id
+    WHERE
+        g.game_id IS NOT NULL
+        AND g.date IS NOT NULL
+        AND g.home_team IS NOT NULL
+        AND g.visitor_team IS NOT NULL
+)
+
+SELECT * FROM cleaned

dbt_nba/models/staging/stg_line_scores.sql

@@ -0,0 +1,51 @@
+{{
+    config(
+        materialized='view',
+        schema='staging'
+    )
+}}
+
+WITH source_data AS (
+    SELECT *
+    FROM {{ source('raw_nba', 'line_scores') }}
+    WHERE deleted_at IS NULL
+),
+
+cleaned_and_transformed AS (
+    SELECT
+        game_id,
+        team,
+        COALESCE(q1, 0) AS q1_points,
+        COALESCE(q2, 0) AS q2_points,
+        COALESCE(q3, 0) AS q3_points,
+        COALESCE(q4, 0) AS q4_points,
+        COALESCE(ot1, 0) AS ot1_points,
+        COALESCE(ot2, 0) AS ot2_points,
+        COALESCE(ot3, 0) AS ot3_points,
+        total AS total_points,
+        COALESCE(q1, 0) + COALESCE(q2, 0) AS first_half_points,
+        COALESCE(q3, 0) + COALESCE(q4, 0) AS second_half_points,
+        COALESCE(q1, 0) + COALESCE(q2, 0) + COALESCE(q3, 0) + COALESCE(q4, 0) AS regulation_points,
+        COALESCE(ot1, 0) + COALESCE(ot2, 0) + COALESCE(ot3, 0) AS overtime_points,
+        COALESCE(ot1, 0) > 0 AS had_ot1,
+        COALESCE(ot2, 0) > 0 AS had_ot2,
+        COALESCE(ot3, 0) > 0 AS had_ot3,
+        COALESCE(q2, 0) - COALESCE(q1, 0) AS q2_momentum,
+        COALESCE(q3, 0) - COALESCE(q2, 0) AS q3_momentum,
+        COALESCE(q4, 0) - COALESCE(q3, 0) AS q4_momentum,
+        GREATEST(COALESCE(q1, 0), COALESCE(q2, 0), COALESCE(q3, 0), COALESCE(q4, 0)) AS max_quarter_score,
+        LEAST(COALESCE(q1, 0), COALESCE(q2, 0), COALESCE(q3, 0), COALESCE(q4, 0)) AS min_quarter_score,
+        CASE
+            WHEN GREATEST(COALESCE(q1, 0), COALESCE(q2, 0), COALESCE(q3, 0), COALESCE(q4, 0)) = COALESCE(q1, 0) THEN 'Q1'
+            WHEN GREATEST(COALESCE(q1, 0), COALESCE(q2, 0), COALESCE(q3, 0), COALESCE(q4, 0)) = COALESCE(q2, 0) THEN 'Q2'
+            WHEN GREATEST(COALESCE(q1, 0), COALESCE(q2, 0), COALESCE(q3, 0), COALESCE(q4, 0)) = COALESCE(q3, 0) THEN 'Q3'
+            ELSE 'Q4'
+        END AS best_quarter,
+        created_at,
+        updated_at,
+        CURRENT_TIMESTAMP AS dbt_loaded_at
+    FROM source_data
+    WHERE game_id IS NOT NULL AND team IS NOT NULL
+)
+
+SELECT * FROM cleaned_and_transformed

dbt_nba/models/staging/stg_player_game_adv_stats.sql

@@ -0,0 +1,106 @@
+{{
+    config(
+        materialized='view',
+        schema='staging'
+    )
+}}
+
+WITH source_data AS (
+    SELECT * FROM {{ source('raw_nba', 'player_game_adv_stats') }}
+    WHERE deleted_at IS NULL
+),
+
+with_minutes AS (
+    SELECT
+        *,
+        CASE
+            WHEN mp IS NOT NULL AND mp != '' AND mp LIKE '%:%' THEN
+                CAST(SPLIT_PART(mp, ':', 1) AS DECIMAL) +
+                (CAST(SPLIT_PART(mp, ':', 2) AS DECIMAL) / 60.0)
+            WHEN mp IS NOT NULL AND mp != '' THEN CAST(mp AS DECIMAL)
+            ELSE 0
+        END AS minutes_played_calc
+    FROM source_data
+),
+
+cleaned AS (
+    SELECT
+        game_id,
+        player_id,
+        team,
+        player_name,
+        mp AS minutes_played_str,
+        minutes_played_calc AS minutes_played,
+        COALESCE(ts_percent, 0) AS true_shooting_pct,
+        COALESCE(efg_percent, 0) AS effective_fg_pct,
+        COALESCE(three_p_ar, 0) AS three_point_attempt_rate,
+        COALESCE(f_tr, 0) AS free_throw_rate,
+        COALESCE(orb_percent, 0) AS offensive_rebound_pct,
+        COALESCE(drb_percent, 0) AS defensive_rebound_pct,
+        COALESCE(trb_percent, 0) AS total_rebound_pct,
+        COALESCE(ast_percent, 0) AS assist_pct,
+        COALESCE(stl_percent, 0) AS steal_pct,
+        COALESCE(blk_percent, 0) AS block_pct,
+        COALESCE(tov_percent, 0) AS turnover_pct,
+        COALESCE(usg_percent, 0) AS usage_pct,
+        COALESCE(o_rtg, 0) AS offensive_rating,
+        COALESCE(d_rtg, 0) AS defensive_rating,
+        COALESCE(bpm, 0) AS box_plus_minus,
+        COALESCE(o_rtg, 0) - COALESCE(d_rtg, 0) AS net_rating,
+        CASE
+            WHEN minutes_played_calc < 5 THEN 'Insufficient Minutes'
+            WHEN COALESCE(ts_percent, 0) >= 0.60 THEN 'Elite'
+            WHEN COALESCE(ts_percent, 0) >= 0.55 THEN 'Good'
+            WHEN COALESCE(ts_percent, 0) >= 0.50 THEN 'Average'
+            ELSE 'Below Average'
+        END AS shooting_efficiency_tier,
+        CASE
+            WHEN minutes_played_calc < 5 THEN 'Garbage Time'
+            WHEN minutes_played_calc < 15 THEN 'Limited Minutes'
+            WHEN (minutes_played_calc >= 30 AND COALESCE(usg_percent, 0) >= 22) OR
+                 (minutes_played_calc >= 25 AND COALESCE(usg_percent, 0) >= 25) THEN 'Primary Option'
+            WHEN minutes_played_calc >= 20 AND COALESCE(usg_percent, 0) >= 20 THEN 'Secondary Option'
+            WHEN minutes_played_calc >= 15 THEN 'Role Player'
+            ELSE 'Limited Minutes'
+        END AS usage_tier,
+        CASE
+            WHEN minutes_played_calc < 5 THEN 'Insufficient Minutes'
+            WHEN COALESCE(bpm, 0) >= 10 THEN 'Elite Impact'
+            WHEN COALESCE(bpm, 0) >= 5 THEN 'High Impact'
+            WHEN COALESCE(bpm, 0) >= 0 THEN 'Positive Impact'
+            WHEN COALESCE(bpm, 0) >= -5 THEN 'Negative Impact'
+            ELSE 'Very Negative Impact'
+        END AS impact_tier,
+        CASE
+            WHEN minutes_played_calc >= 32 THEN 'Starter/Key Player'
+            WHEN minutes_played_calc >= 20 THEN 'Rotation Player'
+            WHEN minutes_played_calc >= 10 THEN 'Bench Player'
+            WHEN minutes_played_calc >= 5 THEN 'Deep Bench'
+            ELSE 'Garbage Time'
+        END AS minutes_based_role,
+        CASE
+            WHEN minutes_played_calc >= 15
+                AND COALESCE(ast_percent, 0) >= 20
+                AND COALESCE(trb_percent, 0) >= 15 THEN TRUE
+            ELSE FALSE
+        END AS is_versatile,
+        CASE
+            WHEN minutes_played_calc >= 15
+                AND (COALESCE(stl_percent, 0) >= 2.5 OR COALESCE(blk_percent, 0) >= 4)
+                AND COALESCE(d_rtg, 0) < 105 THEN TRUE
+            ELSE FALSE
+        END AS is_defensive_specialist,
+        CASE
+            WHEN minutes_played_calc >= 15
+                AND COALESCE(three_p_ar, 0) >= 0.4
+                AND COALESCE(d_rtg, 0) < 110 THEN TRUE
+            ELSE FALSE
+        END AS is_three_and_d,
+        created_at,
+        updated_at,
+        CURRENT_TIMESTAMP AS dbt_loaded_at
+    FROM with_minutes
+    WHERE game_id IS NOT NULL AND player_id IS NOT NULL
+)
+
+SELECT * FROM cleaned

dbt_nba/models/staging/stg_player_game_adv_stats_extended.sql

@@ -0,0 +1,169 @@
+{{
+    config(
+        materialized='table',
+        schema='staging',
+        tags=["staging"]
+    )
+}}
+
+{% set minutes_insufficient = 5 %}
+
+WITH source_data AS (
+    SELECT * FROM {{ source('raw_nba', 'player_game_adv_stats') }}
+    WHERE deleted_at IS NULL
+),
+
+games AS (
+    SELECT game_id, season_start_year
+    FROM {{ ref('stg_games') }}
+),
+
+with_minutes AS (
+    SELECT
+        sd.*,
+        g.season_start_year,
+        CASE
+            WHEN sd.mp IS NOT NULL AND sd.mp != '' AND sd.mp LIKE '%:%' THEN
+                CAST(SPLIT_PART(sd.mp, ':', 1) AS DECIMAL)
+                + (CAST(SPLIT_PART(sd.mp, ':', 2) AS DECIMAL) / 60.0)
+            WHEN sd.mp IS NOT NULL AND sd.mp != '' AND regexp_matches(sd.mp, '^[0-9\.]+$') THEN
+                CAST(sd.mp AS DECIMAL)
+            ELSE 0
+        END AS minutes_played
+    FROM source_data AS sd
+    LEFT JOIN games AS g ON sd.game_id = g.game_id
+),
+
+season_thresholds AS (
+    SELECT * FROM {{ ref('stg_season_thresholds') }}
+),
+
+cleaned AS (
+    SELECT
+        wm.game_id,
+        wm.player_id,
+        wm.team,
+        wm.player_name,
+        wm.mp AS minutes_played_str,
+        wm.minutes_played,
+        COALESCE(wm.ts_percent, 0) AS true_shooting_pct,
+        COALESCE(wm.efg_percent, 0) AS effective_fg_pct,
+        COALESCE(wm.three_p_ar, 0) AS three_point_attempt_rate,
+        COALESCE(wm.f_tr, 0) AS free_throw_rate,
+        COALESCE(wm.orb_percent, 0) AS offensive_rebound_pct,
+        COALESCE(wm.drb_percent, 0) AS defensive_rebound_pct,
+        COALESCE(wm.trb_percent, 0) AS total_rebound_pct,
+        COALESCE(wm.ast_percent, 0) AS assist_pct,
+        COALESCE(wm.stl_percent, 0) AS steal_pct,
+        COALESCE(wm.blk_percent, 0) AS block_pct,
+        COALESCE(wm.tov_percent, 0) AS turnover_pct,
+        COALESCE(wm.usg_percent, 0) AS usage_pct,
+        COALESCE(wm.o_rtg, 0) AS offensive_rating,
+        COALESCE(wm.d_rtg, 0) AS defensive_rating,
+        COALESCE(wm.bpm, 0) AS box_plus_minus,
+        COALESCE(wm.o_rtg, 0) - COALESCE(wm.d_rtg, 0) AS net_rating,
+
+        -- Minutes-based role
+        CASE
+            WHEN wm.minutes_played >= t.min_p95 THEN 'Elite Minutes (Top 5%)'
+            WHEN wm.minutes_played >= t.min_p90 THEN 'Elite Minutes (Top 10%)'
+            WHEN wm.minutes_played >= t.min_q3 THEN 'Starter'
+            WHEN wm.minutes_played >= t.min_median THEN 'Key Rotation'
+            WHEN wm.minutes_played >= t.min_q1 THEN 'Regular Rotation'
+            WHEN wm.minutes_played >= t.min_p5 THEN 'Deep Bench'
+            WHEN wm.minutes_played >= {{ minutes_insufficient }} THEN 'Garbage Time'
+            ELSE 'Insufficient Minutes'
+        END AS minutes_based_role,
+
+        CASE
+            WHEN wm.minutes_played < {{ minutes_insufficient }} THEN 'Insufficient'
+            WHEN wm.minutes_played < t.min_q1 THEN 'Q1'
+            WHEN wm.minutes_played < t.min_median THEN 'Q2'
+            WHEN wm.minutes_played < t.min_q3 THEN 'Q3'
+            ELSE 'Q4'
+        END AS minutes_quartile,
+
+        -- Usage Tier
+        CASE
+            WHEN wm.minutes_played < {{ minutes_insufficient }} THEN 'Insufficient Minutes'
+            WHEN COALESCE(wm.usg_percent, 0) >= t.usg_p90
+                AND wm.minutes_played >= t.min_q1 THEN 'Heliocentric Option'
+            WHEN COALESCE(wm.usg_percent, 0) >= t.usg_q3
+                AND wm.minutes_played >= t.min_q3 THEN 'Primary Option'
+            WHEN COALESCE(wm.usg_percent, 0) >= t.usg_median
+                AND wm.minutes_played >= t.min_median THEN 'Secondary Option'
+            WHEN COALESCE(wm.usg_percent, 0) >= t.usg_q1
+                AND wm.minutes_played >= t.min_q1 THEN 'Role Player'
+            WHEN wm.minutes_played >= t.min_q1
+                AND COALESCE(wm.usg_percent, 0) >= t.usg_p5 THEN 'Connector/Specialist'
+            WHEN wm.minutes_played >= t.min_p5 THEN 'Low Usage Player'
+            ELSE 'Limited Role'
+        END AS usage_tier,
+
+        CASE
+            WHEN COALESCE(wm.usg_percent, 0) < t.usg_q1 THEN 'Q1'
+            WHEN COALESCE(wm.usg_percent, 0) < t.usg_median THEN 'Q2'
+            WHEN COALESCE(wm.usg_percent, 0) < t.usg_q3 THEN 'Q3'
+            ELSE 'Q4'
+        END AS usage_quartile,
+
+        -- Impact Tier
+        CASE
+            WHEN wm.minutes_played < {{ minutes_insufficient }} THEN 'Insufficient Minutes'
+            WHEN COALESCE(wm.bpm, 0) >= t.bpm_p90 THEN 'Elite Impact'
+            WHEN COALESCE(wm.bpm, 0) >= t.bpm_q3 THEN 'High Impact'
+            WHEN COALESCE(wm.bpm, 0) >= t.bpm_median THEN 'Positive Impact'
+            WHEN COALESCE(wm.bpm, 0) >= t.bpm_q1 THEN 'Neutral Impact'
+            WHEN COALESCE(wm.bpm, 0) >= t.bpm_p5 THEN 'Negative Impact'
+            ELSE 'Very Negative Impact'
+        END AS impact_tier,
+
+        CASE
+            WHEN COALESCE(wm.bpm, 0) < t.bpm_q1 THEN 'Q1'
+            WHEN COALESCE(wm.bpm, 0) < t.bpm_median THEN 'Q2'
+            WHEN COALESCE(wm.bpm, 0) < t.bpm_q3 THEN 'Q3'
+            ELSE 'Q4'
+        END AS bpm_quartile,
+
+        -- Shooting efficiency tier
+        CASE
+            WHEN wm.minutes_played < {{ minutes_insufficient }} THEN 'Insufficient Minutes'
+            WHEN COALESCE(wm.ts_percent, 0) >= t.ts_q3 THEN 'Elite'
+            WHEN COALESCE(wm.ts_percent, 0) >= t.ts_median THEN 'Good'
+            WHEN COALESCE(wm.ts_percent, 0) >= t.ts_q1 THEN 'Average'
+            ELSE 'Below Average'
+        END AS shooting_efficiency_tier,
+
+        -- Boolean flags
+        wm.minutes_played >= t.min_p90 AS is_extreme_minutes,
+        wm.minutes_played >= t.min_q3 AS is_starter_minutes,
+        wm.minutes_played >= t.min_q1 AS is_meaningful_minutes,
+
+        wm.minutes_played >= t.min_q1
+            AND COALESCE(wm.ast_percent, 0) >= 20
+            AND COALESCE(wm.trb_percent, 0) >= 13 AS is_versatile,
+
+        wm.minutes_played >= t.min_q1
+            AND (COALESCE(wm.stl_percent, 0) >= 2.5 OR COALESCE(wm.blk_percent, 0) >= 3)
+            AND COALESCE(wm.d_rtg, 0) <= 110 AS is_defensive_specialist,
+
+        wm.minutes_played >= t.min_q1
+            AND COALESCE(wm.three_p_ar, 0) >= 0.4
+            AND COALESCE(wm.d_rtg, 0) <= 110 AS is_three_and_d,
+
+        COALESCE(wm.usg_percent, 0) >= t.usg_p90 AS is_extreme_usage,
+        COALESCE(wm.usg_percent, 0) >= t.usg_q3 AS is_high_usage,
+        COALESCE(wm.bpm, 0) >= t.bpm_p90 AS is_elite_impact,
+        COALESCE(wm.bpm, 0) >= t.bpm_q3 AS is_positive_impact,
+
+        wm.created_at,
+        wm.updated_at,
+        CURRENT_TIMESTAMP AS dbt_loaded_at
+
+    FROM with_minutes AS wm
+    LEFT JOIN season_thresholds AS t
+        ON wm.season_start_year = t.season_start_year
+    WHERE wm.game_id IS NOT NULL AND wm.player_id IS NOT NULL
+)
+
+SELECT * FROM cleaned

dbt_nba/models/staging/stg_player_game_basic_stats.sql

@@ -0,0 +1,93 @@
+{{
+    config(
+        materialized='view',
+        schema='staging'
+    )
+}}
+
+WITH source_data AS (
+    SELECT * FROM {{ source('raw_nba', 'player_game_basic_stats') }}
+    WHERE deleted_at IS NULL
+),
+
+cleaned AS (
+    SELECT
+        game_id,
+        player_id,
+        team,
+        player_name,
+        COALESCE(status, 'Unknown') AS player_status,
+        CASE WHEN status = 'Played' THEN TRUE ELSE FALSE END AS did_play,
+        mp AS minutes_played_str,
+        CAST(
+            CASE
+                WHEN mp IS NOT NULL AND mp != '' AND mp LIKE '%:%' THEN
+                    CAST(SPLIT_PART(mp, ':', 1) AS DECIMAL) +
+                    (CAST(SPLIT_PART(mp, ':', 2) AS DECIMAL) / 60.0)
+                WHEN mp IS NOT NULL AND mp != '' THEN CAST(mp AS DECIMAL)
+                ELSE 0
+            END AS DECIMAL(10, 2)) AS minutes_played,
+        COALESCE(fg, 0) AS field_goals_made,
+        COALESCE(fga, 0) AS field_goals_attempted,
+        COALESCE(fg_percent, 0) AS field_goal_pct,
+        COALESCE(three_p, 0) AS three_pointers_made,
+        COALESCE(three_pa, 0) AS three_pointers_attempted,
+        COALESCE(three_p_percent, 0) AS three_point_pct,
+        COALESCE(ft, 0) AS free_throws_made,
+        COALESCE(fta, 0) AS free_throws_attempted,
+        COALESCE(ft_percent, 0) AS free_throw_pct,
+        COALESCE(orb, 0) AS offensive_rebounds,
+        COALESCE(drb, 0) AS defensive_rebounds,
+        COALESCE(trb, 0) AS total_rebounds,
+        COALESCE(ast, 0) AS assists,
+        COALESCE(stl, 0) AS steals,
+        COALESCE(blk, 0) AS blocks,
+        COALESCE(tov, 0) AS turnovers,
+        COALESCE(pf, 0) AS personal_fouls,
+        COALESCE(pts, 0) AS points,
+        COALESCE(gm_sc, 0) AS game_score,
+        COALESCE(plus_minus, 0) AS plus_minus,
+        COALESCE(fg, 0) - COALESCE(three_p, 0) AS two_pointers_made,
+        COALESCE(fga, 0) - COALESCE(three_pa, 0) AS two_pointers_attempted,
+        CASE
+            WHEN (COALESCE(fga, 0) - COALESCE(three_pa, 0)) > 0 THEN
+                CAST(COALESCE(fg, 0) - COALESCE(three_p, 0) AS DECIMAL) /
+                CAST(COALESCE(fga, 0) - COALESCE(three_pa, 0) AS DECIMAL)
+            ELSE 0
+        END AS two_point_pct,
+        CASE
+            WHEN COALESCE(fga, 0) > 0 THEN
+                CAST(COALESCE(pts, 0) AS DECIMAL) / CAST(COALESCE(fga, 0) AS DECIMAL)
+            ELSE 0
+        END AS points_per_shot,
+        CASE
+            WHEN (
+                (CASE WHEN COALESCE(pts, 0) >= 10 THEN 1 ELSE 0 END) +
+                (CASE WHEN COALESCE(trb, 0) >= 10 THEN 1 ELSE 0 END) +
+                (CASE WHEN COALESCE(ast, 0) >= 10 THEN 1 ELSE 0 END) +
+                (CASE WHEN COALESCE(stl, 0) >= 10 THEN 1 ELSE 0 END) +
+                (CASE WHEN COALESCE(blk, 0) >= 10 THEN 1 ELSE 0 END)
+            ) >= 2 THEN TRUE ELSE FALSE
+        END AS is_double_double,
+        CASE
+            WHEN (
+                (CASE WHEN COALESCE(pts, 0) >= 10 THEN 1 ELSE 0 END) +
+                (CASE WHEN COALESCE(trb, 0) >= 10 THEN 1 ELSE 0 END) +
+                (CASE WHEN COALESCE(ast, 0) >= 10 THEN 1 ELSE 0 END) +
+                (CASE WHEN COALESCE(stl, 0) >= 10 THEN 1 ELSE 0 END) +
+                (CASE WHEN COALESCE(blk, 0) >= 10 THEN 1 ELSE 0 END)
+            ) >= 3 THEN TRUE ELSE FALSE
+        END AS is_triple_double,
+        CASE
+            WHEN mp IS NOT NULL AND mp LIKE '%:%' AND
+                 CAST(SPLIT_PART(mp, ':', 1) AS DECIMAL) >= 20 THEN TRUE
+            ELSE FALSE
+        END AS likely_starter,
+        created_at,
+        updated_at,
+        CURRENT_TIMESTAMP AS dbt_loaded_at
+    FROM source_data
+    WHERE game_id IS NOT NULL AND player_id IS NOT NULL
+)
+
+SELECT * FROM cleaned

dbt_nba/models/staging/stg_player_shot_charts.sql

@@ -0,0 +1,105 @@
+{{
+    config(
+        materialized='view',
+        schema='staging'
+    )
+}}
+
+WITH source_data AS (
+    SELECT *
+    FROM {{ source('raw_nba', 'player_shot_charts') }}
+    WHERE deleted_at IS NULL
+),
+
+cleaned AS (
+    SELECT
+        id AS shot_id,
+        player_id,
+        season AS season_year,
+        CASE
+            WHEN date IS NOT NULL AND date != '' THEN
+                strptime(TRIM(date), '%b %d,%Y')::DATE
+            ELSE NULL
+        END AS game_date,
+        date AS game_date_raw,
+        CASE
+            WHEN date IS NOT NULL AND date != '' THEN
+                CASE
+                    WHEN EXTRACT(MONTH FROM strptime(TRIM(date), '%b %d,%Y')::DATE) >= 10
+                        THEN EXTRACT(YEAR FROM strptime(TRIM(date), '%b %d,%Y')::DATE)::INT
+                    ELSE EXTRACT(YEAR FROM strptime(TRIM(date), '%b %d,%Y')::DATE)::INT - 1
+                END
+            ELSE NULL
+        END AS season_start_year,
+        qtr AS quarter_raw,
+        CASE
+            WHEN qtr LIKE '1st%' THEN 1
+            WHEN qtr LIKE '2nd%' THEN 2
+            WHEN qtr LIKE '3rd%' THEN 3
+            WHEN qtr LIKE '4th%' THEN 4
+            WHEN qtr ILIKE '%OT%' THEN 5
+            ELSE NULL
+        END AS quarter_number,
+        CASE WHEN qtr ILIKE '%OT%' THEN TRUE ELSE FALSE END AS is_overtime_shot,
+        time_remaining AS time_remaining_raw,
+        CASE
+            WHEN time_remaining IS NOT NULL AND time_remaining LIKE '%:%' THEN
+                CAST(SPLIT_PART(time_remaining, ':', 1) AS INT) * 60
+                + CAST(SPLIT_PART(time_remaining, ':', 2) AS INT)
+            ELSE NULL
+        END AS seconds_remaining_in_quarter,
+        top AS shot_y_coordinate,
+        "left" AS shot_x_coordinate,
+        COALESCE(result, FALSE) AS is_made,
+        CASE WHEN COALESCE(result, FALSE) = TRUE THEN 1 ELSE 0 END AS shot_made_flag,
+        CASE WHEN COALESCE(result, FALSE) = FALSE THEN 1 ELSE 0 END AS shot_missed_flag,
+        shot_type AS shot_type_raw,
+        CASE
+            WHEN shot_type = '3-pointer' THEN 3
+            WHEN shot_type = '2-pointer' THEN 2
+            ELSE NULL
+        END AS shot_point_value,
+        CASE WHEN shot_type = '3-pointer' THEN TRUE ELSE FALSE END AS is_three_pointer,
+        FALSE AS is_free_throw,
+        COALESCE(distance_ft, 0) AS distance_ft,
+        CASE
+            WHEN COALESCE(distance_ft, 0) <= 3 THEN 'At Rim (0-3 ft)'
+            WHEN COALESCE(distance_ft, 0) <= 10 THEN 'Short Range (4-10 ft)'
+            WHEN COALESCE(distance_ft, 0) <= 16 THEN 'Mid Range (11-16 ft)'
+            WHEN COALESCE(distance_ft, 0) <= 23 THEN 'Long Mid Range (17-23 ft)'
+            WHEN COALESCE(distance_ft, 0) <= 27 THEN 'Three Point (24-27 ft)'
+            ELSE 'Deep Three (28+ ft)'
+        END AS shot_distance_zone,
+        COALESCE(lead, FALSE) AS team_had_lead,
+        COALESCE(team_score, 0) AS team_score_at_shot,
+        COALESCE(opponent_team_score, 0) AS opponent_score_at_shot,
+        COALESCE(team_score, 0) - COALESCE(opponent_team_score, 0) AS score_margin_at_shot,
+        CASE
+            WHEN qtr LIKE '4th%'
+                AND time_remaining IS NOT NULL
+                AND time_remaining LIKE '%:%'
+                AND (CAST(SPLIT_PART(time_remaining, ':', 1) AS INT) * 60
+                     + CAST(SPLIT_PART(time_remaining, ':', 2) AS INT)) <= 300
+                AND ABS(COALESCE(team_score, 0) - COALESCE(opponent_team_score, 0)) <= 5
+            THEN TRUE
+            ELSE FALSE
+        END AS is_clutch_shot,
+        team AS team_abbr_raw,
+        opponent AS opponent_abbr_raw,
+        CASE
+            WHEN COALESCE(result, FALSE) = TRUE THEN
+                CASE
+                    WHEN shot_type = '3-pointer' THEN 3
+                    WHEN shot_type = '2-pointer' THEN 2
+                    ELSE 0
+                END
+            ELSE 0
+        END AS points_generated,
+        created_at,
+        updated_at,
+        CURRENT_TIMESTAMP AS dbt_loaded_at
+    FROM source_data
+    WHERE id IS NOT NULL AND player_id IS NOT NULL AND date IS NOT NULL AND team IS NOT NULL
+)
+
+SELECT * FROM cleaned

dbt_nba/models/staging/stg_season_thresholds.sql

@@ -0,0 +1,59 @@
+{{
+    config(
+        materialized='table',
+        schema='staging',
+        tags=["staging"]
+    )
+}}
+
+WITH player_stats AS (
+    SELECT
+        g.season_start_year,
+        CASE
+            WHEN s.mp IS NOT NULL AND s.mp != '' AND s.mp LIKE '%:%' THEN
+                CAST(SPLIT_PART(s.mp, ':', 1) AS DECIMAL)
+                + (CAST(SPLIT_PART(s.mp, ':', 2) AS DECIMAL) / 60.0)
+            WHEN s.mp IS NOT NULL AND s.mp != '' AND regexp_matches(s.mp, '^[0-9\.]+$') THEN
+                CAST(s.mp AS DECIMAL)
+            ELSE 0
+        END AS minutes_played,
+        COALESCE(s.usg_percent, 0) AS usage_pct,
+        COALESCE(s.bpm, 0) AS bpm,
+        COALESCE(s.ts_percent, 0) AS ts_pct
+    FROM {{ source('raw_nba', 'player_game_adv_stats') }} AS s
+    INNER JOIN {{ ref('stg_games') }} AS g
+        ON s.game_id = g.game_id
+    WHERE s.deleted_at IS NULL
+      AND s.game_id IS NOT NULL
+      AND s.player_id IS NOT NULL
+)
+
+SELECT
+    season_start_year,
+    PERCENTILE_CONT(0.05) WITHIN GROUP (ORDER BY minutes_played) AS min_p5,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY minutes_played) AS min_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY minutes_played) AS min_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY minutes_played) AS min_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY minutes_played) AS min_p90,
+    PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY minutes_played) AS min_p95,
+    PERCENTILE_CONT(0.05) WITHIN GROUP (ORDER BY usage_pct) AS usg_p5,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY usage_pct) AS usg_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY usage_pct) AS usg_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY usage_pct) AS usg_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY usage_pct) AS usg_p90,
+    PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY usage_pct) AS usg_p95,
+    PERCENTILE_CONT(0.05) WITHIN GROUP (ORDER BY bpm) AS bpm_p5,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY bpm) AS bpm_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY bpm) AS bpm_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY bpm) AS bpm_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY bpm) AS bpm_p90,
+    PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY bpm) AS bpm_p95,
+    PERCENTILE_CONT(0.05) WITHIN GROUP (ORDER BY ts_pct) AS ts_p5,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY ts_pct) AS ts_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY ts_pct) AS ts_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY ts_pct) AS ts_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY ts_pct) AS ts_p90,
+    PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY ts_pct) AS ts_p95
+FROM player_stats
+GROUP BY season_start_year
+ORDER BY season_start_year

dbt_nba/models/staging/stg_team_game_adv_stats.sql

@@ -0,0 +1,102 @@
+{{
+    config(
+        materialized='table',
+        schema='staging',
+        tags=["staging"]
+    )
+}}
+
+WITH source_data AS (
+    SELECT * FROM {{ source('raw_nba', 'team_game_adv_stats') }}
+    WHERE deleted_at IS NULL
+),
+
+games AS (
+    SELECT game_id, season_start_year
+    FROM {{ ref('stg_games') }}
+),
+
+team_season_thresholds AS (
+    SELECT * FROM {{ ref('stg_team_season_thresholds') }}
+),
+
+cleaned AS (
+    SELECT
+        sd.game_id,
+        sd.team,
+        COALESCE(sd.mp, 240) AS minutes_played,
+        COALESCE(sd.ts_percent, 0) AS true_shooting_pct,
+        COALESCE(sd.efg_percent, 0) AS effective_fg_pct,
+        COALESCE(sd.three_p_ar, 0) AS three_point_attempt_rate,
+        COALESCE(sd.f_tr, 0) AS free_throw_rate,
+        COALESCE(sd.orb_percent, 0) AS offensive_rebound_pct,
+        COALESCE(sd.drb_percent, 0) AS defensive_rebound_pct,
+        COALESCE(sd.trb_percent, 0) AS total_rebound_pct,
+        COALESCE(sd.ast_percent, 0) AS assist_pct,
+        COALESCE(sd.stl_percent, 0) AS steal_pct,
+        COALESCE(sd.blk_percent, 0) AS block_pct,
+        COALESCE(sd.tov_percent, 0) AS turnover_pct,
+        COALESCE(sd.usg_percent, 100) AS usage_pct,
+        COALESCE(sd.o_rtg, 0) AS offensive_rating,
+        COALESCE(sd.d_rtg, 0) AS defensive_rating,
+        COALESCE(sd.o_rtg, 0) - COALESCE(sd.d_rtg, 0) AS net_rating,
+
+        CASE
+            WHEN COALESCE(sd.o_rtg, 0) >= t.ortg_p90 THEN 'Elite Offense'
+            WHEN COALESCE(sd.o_rtg, 0) >= t.ortg_q3 THEN 'Above Average Offense'
+            WHEN COALESCE(sd.o_rtg, 0) >= t.ortg_q1 THEN 'Average Offense'
+            WHEN COALESCE(sd.o_rtg, 0) >= t.ortg_p10 THEN 'Below Average Offense'
+            ELSE 'Poor Offense'
+        END AS offensive_tier,
+
+        CASE
+            WHEN COALESCE(sd.d_rtg, 0) <= t.drtg_p10 THEN 'Elite Defense'
+            WHEN COALESCE(sd.d_rtg, 0) <= t.drtg_q1 THEN 'Above Average Defense'
+            WHEN COALESCE(sd.d_rtg, 0) <= t.drtg_q3 THEN 'Average Defense'
+            WHEN COALESCE(sd.d_rtg, 0) <= t.drtg_p90 THEN 'Below Average Defense'
+            ELSE 'Poor Defense'
+        END AS defensive_tier,
+
+        CASE
+            WHEN COALESCE(sd.three_p_ar, 0) >= t.tpar_p90 THEN 'Three Point Heavy'
+            WHEN COALESCE(sd.three_p_ar, 0) >= t.tpar_q3 THEN 'Three Point Leaning'
+            WHEN COALESCE(sd.three_p_ar, 0) >= t.tpar_q1 THEN 'Balanced'
+            WHEN COALESCE(sd.three_p_ar, 0) >= t.tpar_p10 THEN 'Inside Leaning'
+            ELSE 'Inside Focused'
+        END AS shot_selection_style,
+
+        CASE
+            WHEN COALESCE(sd.ast_percent, 0) >= t.ast_p90 THEN 'Elite Ball Movement'
+            WHEN COALESCE(sd.ast_percent, 0) >= t.ast_q3 THEN 'High Ball Movement'
+            WHEN COALESCE(sd.ast_percent, 0) >= t.ast_q1 THEN 'Average Ball Movement'
+            WHEN COALESCE(sd.ast_percent, 0) >= t.ast_p10 THEN 'Low Ball Movement'
+            ELSE 'Isolation Heavy'
+        END AS ball_movement_style,
+
+        CASE
+            WHEN COALESCE(sd.tov_percent, 0) <= t.tov_p10 THEN 'Elite Ball Security'
+            WHEN COALESCE(sd.tov_percent, 0) <= t.tov_q1 THEN 'Above Average Ball Security'
+            WHEN COALESCE(sd.tov_percent, 0) <= t.tov_q3 THEN 'Average Ball Security'
+            WHEN COALESCE(sd.tov_percent, 0) <= t.tov_p90 THEN 'Below Average Ball Security'
+            ELSE 'Poor Ball Security'
+        END AS ball_security_tier,
+
+        CASE
+            WHEN (COALESCE(sd.stl_percent, 0) + COALESCE(sd.blk_percent, 0)) >= t.stl_blk_p90 THEN 'Elite Defensive Activity'
+            WHEN (COALESCE(sd.stl_percent, 0) + COALESCE(sd.blk_percent, 0)) >= t.stl_blk_q3 THEN 'High Defensive Activity'
+            WHEN (COALESCE(sd.stl_percent, 0) + COALESCE(sd.blk_percent, 0)) >= t.stl_blk_q1 THEN 'Average Defensive Activity'
+            WHEN (COALESCE(sd.stl_percent, 0) + COALESCE(sd.blk_percent, 0)) >= t.stl_blk_p10 THEN 'Low Defensive Activity'
+            ELSE 'Passive Defense'
+        END AS defensive_activity,
+
+        sd.created_at,
+        sd.updated_at,
+        CURRENT_TIMESTAMP AS dbt_loaded_at
+
+    FROM source_data AS sd
+    LEFT JOIN games AS g ON sd.game_id = g.game_id
+    LEFT JOIN team_season_thresholds AS t ON g.season_start_year = t.season_start_year
+    WHERE sd.game_id IS NOT NULL AND sd.team IS NOT NULL
+)
+
+SELECT * FROM cleaned

dbt_nba/models/staging/stg_team_game_basic_stats.sql

@@ -0,0 +1,92 @@
+{{
+    config(
+        materialized='view',
+        schema='staging'
+    )
+}}
+
+WITH source_data AS (
+    SELECT * FROM {{ source('raw_nba', 'team_game_basic_stats') }}
+    WHERE deleted_at IS NULL
+),
+
+cleaned AS (
+    SELECT
+        game_id,
+        team,
+        COALESCE(mp, 240) AS minutes_played,
+        COALESCE(fg, 0) AS field_goals_made,
+        COALESCE(fga, 0) AS field_goals_attempted,
+        COALESCE(fg_percent, 0) AS field_goal_pct,
+        COALESCE(three_p, 0) AS three_pointers_made,
+        COALESCE(three_pa, 0) AS three_pointers_attempted,
+        COALESCE(three_p_percent, 0) AS three_point_pct,
+        COALESCE(ft, 0) AS free_throws_made,
+        COALESCE(fta, 0) AS free_throws_attempted,
+        COALESCE(ft_percent, 0) AS free_throw_pct,
+        COALESCE(orb, 0) AS offensive_rebounds,
+        COALESCE(drb, 0) AS defensive_rebounds,
+        COALESCE(trb, 0) AS total_rebounds,
+        COALESCE(ast, 0) AS assists,
+        COALESCE(stl, 0) AS steals,
+        COALESCE(blk, 0) AS blocks,
+        COALESCE(tov, 0) AS turnovers,
+        COALESCE(pf, 0) AS personal_fouls,
+        COALESCE(pts, 0) AS points,
+        COALESCE(fg, 0) - COALESCE(three_p, 0) AS two_pointers_made,
+        COALESCE(fga, 0) - COALESCE(three_pa, 0) AS two_pointers_attempted,
+        CASE
+            WHEN (COALESCE(fga, 0) - COALESCE(three_pa, 0)) > 0 THEN
+                CAST(COALESCE(fg, 0) - COALESCE(three_p, 0) AS DECIMAL) /
+                CAST(COALESCE(fga, 0) - COALESCE(three_pa, 0) AS DECIMAL)
+            ELSE 0
+        END AS two_point_pct,
+        COALESCE(fga, 0) + 0.44 * COALESCE(fta, 0) - COALESCE(orb, 0) + COALESCE(tov, 0) AS possessions_estimate,
+        CASE
+            WHEN COALESCE(mp, 240) > 0 THEN
+                (COALESCE(fga, 0) + 0.44 * COALESCE(fta, 0) - COALESCE(orb, 0) + COALESCE(tov, 0)) * 48.0 / (COALESCE(mp, 240) / 5.0)
+            ELSE 0
+        END AS pace,
+        CASE
+            WHEN COALESCE(fga, 0) > 0 THEN
+                CAST(COALESCE(fg, 0) + 0.5 * COALESCE(three_p, 0) AS DECIMAL) / CAST(COALESCE(fga, 0) AS DECIMAL)
+            ELSE 0
+        END AS effective_fg_pct,
+        CASE
+            WHEN (COALESCE(fga, 0) + 0.44 * COALESCE(fta, 0) + COALESCE(tov, 0)) > 0 THEN
+                CAST(COALESCE(tov, 0) AS DECIMAL) / CAST(COALESCE(fga, 0) + 0.44 * COALESCE(fta, 0) + COALESCE(tov, 0) AS DECIMAL)
+            ELSE 0
+        END AS turnover_rate,
+        CASE
+            WHEN (COALESCE(orb, 0) + COALESCE(drb, 0)) > 0 THEN
+                CAST(COALESCE(orb, 0) AS DECIMAL) / CAST(COALESCE(orb, 0) + COALESCE(drb, 0) AS DECIMAL)
+            ELSE 0
+        END AS offensive_rebound_rate,
+        CASE
+            WHEN COALESCE(fga, 0) > 0 THEN
+                CAST(COALESCE(fta, 0) AS DECIMAL) / CAST(COALESCE(fga, 0) AS DECIMAL)
+            ELSE 0
+        END AS free_throw_rate,
+        CASE
+            WHEN COALESCE(tov, 0) > 0 THEN
+                CAST(COALESCE(ast, 0) AS DECIMAL) / CAST(COALESCE(tov, 0) AS DECIMAL)
+            ELSE 0
+        END AS ast_to_tov_ratio,
+        CASE
+            WHEN (COALESCE(fga, 0) + 0.44 * COALESCE(fta, 0) - COALESCE(orb, 0) + COALESCE(tov, 0)) > 0 THEN
+                CAST(COALESCE(pts, 0) AS DECIMAL) / CAST(COALESCE(fga, 0) + 0.44 * COALESCE(fta, 0) - COALESCE(orb, 0) + COALESCE(tov, 0) AS DECIMAL)
+            ELSE 0
+        END AS points_per_possession,
+        CASE
+            WHEN COALESCE(fga, 0) > 0 THEN
+                CAST(COALESCE(three_pa, 0) AS DECIMAL) / CAST(COALESCE(fga, 0) AS DECIMAL)
+            ELSE 0
+        END AS three_point_rate,
+        created_at,
+        updated_at,
+        CURRENT_TIMESTAMP AS dbt_loaded_at
+    FROM source_data
+    WHERE game_id IS NOT NULL AND team IS NOT NULL
+)
+
+SELECT * FROM cleaned

dbt_nba/models/staging/stg_team_season_thresholds.sql

@@ -0,0 +1,84 @@
+{{
+    config(
+        materialized='table',
+        schema='staging',
+        tags=["staging"]
+    )
+}}
+
+WITH team_stats AS (
+    SELECT
+        g.season_start_year,
+        COALESCE(s.o_rtg, 0) AS offensive_rating,
+        COALESCE(s.d_rtg, 0) AS defensive_rating,
+        COALESCE(s.three_p_ar, 0) AS three_point_attempt_rate,
+        COALESCE(s.ast_percent, 0) AS assist_pct,
+        COALESCE(s.orb_percent, 0) AS offensive_rebound_pct,
+        COALESCE(s.drb_percent, 0) AS defensive_rebound_pct,
+        COALESCE(s.tov_percent, 0) AS turnover_pct,
+        COALESCE(s.stl_percent, 0) + COALESCE(s.blk_percent, 0) AS stl_blk_combined,
+        COALESCE(s.ts_percent, 0) AS true_shooting_pct,
+        COALESCE(s.f_tr, 0) AS free_throw_rate
+    FROM {{ source('raw_nba', 'team_game_adv_stats') }} AS s
+    INNER JOIN {{ ref('stg_games') }} AS g
+        ON s.game_id = g.game_id
+    WHERE s.deleted_at IS NULL
+      AND s.game_id IS NOT NULL
+      AND s.team IS NOT NULL
+)
+
+SELECT
+    season_start_year,
+    PERCENTILE_CONT(0.10) WITHIN GROUP (ORDER BY offensive_rating) AS ortg_p10,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY offensive_rating) AS ortg_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY offensive_rating) AS ortg_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY offensive_rating) AS ortg_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY offensive_rating) AS ortg_p90,
+    PERCENTILE_CONT(0.10) WITHIN GROUP (ORDER BY defensive_rating) AS drtg_p10,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY defensive_rating) AS drtg_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY defensive_rating) AS drtg_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY defensive_rating) AS drtg_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY defensive_rating) AS drtg_p90,
+    PERCENTILE_CONT(0.10) WITHIN GROUP (ORDER BY three_point_attempt_rate) AS tpar_p10,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY three_point_attempt_rate) AS tpar_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY three_point_attempt_rate) AS tpar_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY three_point_attempt_rate) AS tpar_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY three_point_attempt_rate) AS tpar_p90,
+    PERCENTILE_CONT(0.10) WITHIN GROUP (ORDER BY assist_pct) AS ast_p10,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY assist_pct) AS ast_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY assist_pct) AS ast_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY assist_pct) AS ast_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY assist_pct) AS ast_p90,
+    PERCENTILE_CONT(0.10) WITHIN GROUP (ORDER BY offensive_rebound_pct) AS orb_p10,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY offensive_rebound_pct) AS orb_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY offensive_rebound_pct) AS orb_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY offensive_rebound_pct) AS orb_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY offensive_rebound_pct) AS orb_p90,
+    PERCENTILE_CONT(0.10) WITHIN GROUP (ORDER BY defensive_rebound_pct) AS drb_p10,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY defensive_rebound_pct) AS drb_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY defensive_rebound_pct) AS drb_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY defensive_rebound_pct) AS drb_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY defensive_rebound_pct) AS drb_p90,
+    PERCENTILE_CONT(0.10) WITHIN GROUP (ORDER BY turnover_pct) AS tov_p10,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY turnover_pct) AS tov_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY turnover_pct) AS tov_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY turnover_pct) AS tov_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY turnover_pct) AS tov_p90,
+    PERCENTILE_CONT(0.10) WITHIN GROUP (ORDER BY stl_blk_combined) AS stl_blk_p10,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY stl_blk_combined) AS stl_blk_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY stl_blk_combined) AS stl_blk_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY stl_blk_combined) AS stl_blk_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY stl_blk_combined) AS stl_blk_p90,
+    PERCENTILE_CONT(0.10) WITHIN GROUP (ORDER BY true_shooting_pct) AS ts_p10,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY true_shooting_pct) AS ts_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY true_shooting_pct) AS ts_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY true_shooting_pct) AS ts_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY true_shooting_pct) AS ts_p90,
+    PERCENTILE_CONT(0.10) WITHIN GROUP (ORDER BY free_throw_rate) AS ftr_p10,
+    PERCENTILE_CONT(0.25) WITHIN GROUP (ORDER BY free_throw_rate) AS ftr_q1,
+    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY free_throw_rate) AS ftr_median,
+    PERCENTILE_CONT(0.75) WITHIN GROUP (ORDER BY free_throw_rate) AS ftr_q3,
+    PERCENTILE_CONT(0.90) WITHIN GROUP (ORDER BY free_throw_rate) AS ftr_p90
+FROM team_stats
+GROUP BY season_start_year
+ORDER BY season_start_year

dbt_nba/package-lock.yml

@@ -0,0 +1,5 @@
+packages:
+  - name: dbt_utils
+    package: dbt-labs/dbt_utils
+    version: 1.3.1
+sha1_hash: 1b75844a5c14558fe9ae17335b3632c080d6784c

dbt_nba/packages.yml

@@ -0,0 +1,3 @@
+packages:
+  - package: dbt-labs/dbt_utils
+    version: 1.3.1

dbt_nba/profiles.yml

@@ -0,0 +1,6 @@
+dbt_nba:
+  target: dev
+  outputs:
+    dev:
+      type: duckdb
+      path: "{{ env_var('DBT_DUCKDB_PATH', 'data/DB/dbt_nba.duckdb') }}"

dbt_nba/reports/.evidence/customization/.profile.json

@@ -0,0 +1 @@
+{"anonymousId":"8aa41dce-bd0b-40af-96a3-de949fffe712","traits":{"projectCreated":"2026-05-21T05:40:13.247Z"}}

dbt_nba/reports/.evidence/customization/custom-formatting.json

@@ -0,0 +1,4 @@
+{
+  "version": "1.0",
+  "customFormats": []
+}

dbt_nba/reports/.gitignore

@@ -0,0 +1,10 @@
+.evidence/template
+.svelte-kit
+build
+node_modules
+.DS_Store
+static/data
+*.options.yaml
+.vscode/settings.json
+.env
+.evidence/meta

dbt_nba/reports/.npmrc

@@ -0,0 +1,3 @@
+loglevel=error
+audit=false
+fund=false

dbt_nba/reports/.vscode/extensions.json

@@ -0,0 +1,5 @@
+{
+	"recommendations": [
+		"evidence.evidence-vscode"
+	]
+}

dbt_nba/reports/README.md

@@ -0,0 +1,48 @@
+# Evidence Template Project
+
+## Using Codespaces
+
+If you are using this template in Codespaces, click the `Start Evidence` button in the bottom status bar. This will install dependencies and open a preview of your project in your browser - you should get a popup prompting you to open in browser.
+
+Or you can use the following commands to get started:
+
+```bash
+npm install
+npm run sources
+npm run dev -- --host 0.0.0.0
+```
+
+See [the CLI docs](https://docs.evidence.dev/cli/) for more command information.
+
+**Note:** Codespaces is much faster on the Desktop app. After the Codespace has booted, select the hamburger menu → Open in VS Code Desktop.
+
+## Get Started from VS Code
+
+The easiest way to get started is using the [VS Code Extension](https://marketplace.visualstudio.com/items?itemName=Evidence.evidence-vscode):
+
+
+
+1. Install the extension from the VS Code Marketplace
+2. Open the Command Palette (Ctrl/Cmd + Shift + P) and enter `Evidence: New Evidence Project`
+3. Click `Start Evidence` in the bottom status bar
+
+## Get Started using the CLI
+
+```bash
+npx degit evidence-dev/template my-project
+cd my-project 
+npm install 
+npm run sources
+npm run dev 
+```
+
+Check out the docs for [alternative install methods](https://docs.evidence.dev/getting-started/install-evidence) including Docker, Github Codespaces, and alongside dbt.
+
+
+
+## Learning More
+
+- [Docs](https://docs.evidence.dev/)
+- [Github](https://github.com/evidence-dev/evidence)
+- [Slack Community](https://slack.evidence.dev/)
+- [Evidence Home Page](https://www.evidence.dev)

dbt_nba/reports/evidence.config.yaml

@@ -0,0 +1,81 @@
+appearance:
+  default: system
+  switcher: true
+
+theme:
+  colorPalettes:
+    default:
+      light:
+        - "#236aa4"
+        - "#45a1bf"
+        - "#a5cdee"
+        - "#8dacbf"
+        - "#85c7c6"
+        - "#d2c6ac"
+        - "#f4b548"
+        - "#8f3d56"
+        - "#71b9f4"
+        - "#46a485"
+      dark:
+        - "#236aa4"
+        - "#45a1bf"
+        - "#a5cdee"
+        - "#8dacbf"
+        - "#85c7c6"
+        - "#d2c6ac"
+        - "#f4b548"
+        - "#8f3d56"
+        - "#71b9f4"
+        - "#46a485"
+  colorScales:
+    default:
+      light:
+        - "#ADD8E6"
+        - "#00008B"
+      dark:
+        - "#ADD8E6"
+        - "#00008B"
+  colors:
+    primary:
+      light: "#2563eb"
+      dark: "#3b82f6"
+    accent:
+      light: "#c2410c"
+      dark: "#fdba74"
+    base:
+      light: "#ffffff"
+      dark: "#09090b"
+    info:
+      light: "#0284c7"
+      dark: "#38bdf8"
+    positive:
+      light: "#16a34a"
+      dark: "#4ade80"
+    warning:
+      light: "#f8c900"
+      dark: "#fbbf24"
+    negative:
+      light: "#dc2626"
+      dark: "#f87171"
+
+plugins:
+  components:
+    # This loads all of evidence's core charts and UI components
+    # You probably don't want to edit this dependency unless you know what you are doing
+    "@evidence-dev/core-components": {}
+
+  datasources:
+    # You can add additional datasources here by adding npm packages. 
+    # Make to also add them to `package.json`.
+    "@evidence-dev/bigquery": { }
+    "@evidence-dev/csv": { }
+    "@evidence-dev/databricks": { }
+    "@evidence-dev/duckdb": { }
+    "@evidence-dev/mssql": { }
+    "@evidence-dev/mysql": { }
+    "@evidence-dev/postgres": { }
+    "@evidence-dev/source-javascript": { }
+    "@evidence-dev/snowflake": { }
+    "@evidence-dev/sqlite": { }
+    "@evidence-dev/trino": { }
+    "@evidence-dev/motherduck": { }

dbt_nba/reports/package.json

@@ -0,0 +1,41 @@
+{
+  "name": "my-evidence-project",
+  "version": "0.0.1",
+  "scripts": {
+    "build": "evidence build",
+    "build:strict": "evidence build:strict",
+    "dev": "evidence dev --open /",
+    "test": "evidence build",
+    "sources": "evidence sources",
+    "sources:strict": "evidence sources --strict",
+    "preview": "evidence preview"
+  },
+  "engines": {
+    "npm": ">=7.0.0",
+    "node": ">=18.0.0"
+  },
+  "type": "module",
+  "dependencies": {
+    "@evidence-dev/bigquery": "^2.0.12",
+    "@evidence-dev/core-components": "^5.4.2",
+    "@evidence-dev/csv": "^1.0.16",
+    "@evidence-dev/databricks": "^1.0.10",
+    "@evidence-dev/duckdb": "^2.0.1",
+    "@evidence-dev/evidence": "^40.1.8",
+    "@evidence-dev/motherduck": "^1.0.6",
+    "@evidence-dev/mssql": "^1.1.4",
+    "@evidence-dev/mysql": "^1.1.6",
+    "@evidence-dev/postgres": "^1.0.10",
+    "@evidence-dev/snowflake": "^1.2.4",
+    "@evidence-dev/source-javascript": "^0.0.3",
+    "@evidence-dev/sqlite": "^2.0.9",
+    "@evidence-dev/trino": "^1.0.11"
+  },
+  "overrides": {
+    "jsonwebtoken": "9.0.0",
+    "trim@<0.0.3": ">0.0.3",
+    "sqlite3": "5.1.5",
+    "axios": "^1.7.4",
+    "vitest": "^3.2.6"
+  }
+}

dbt_nba/reports/pages/index.md

@@ -0,0 +1,182 @@
+---
+title: NBA Analytics Dashboard
+---
+
+```sql games
+select * from nba.games
+```
+
+```sql season_summary
+select * from nba.season_summary
+```
+
+```sql competitiveness
+select * from nba.competitiveness
+```
+
+```sql home_advantage
+select * from nba.home_advantage
+```
+
+```sql top_scorers
+select * from nba.top_scorers
+```
+
+```sql pace_and_scoring
+select * from nba.pace_and_scoring
+```
+
+```sql team_ratings
+select * from nba.team_ratings
+```
+
+```sql play_styles
+select * from nba.play_styles
+```
+
+```sql player_impact
+select * from nba.player_impact
+```
+
+```sql game_drama
+select * from nba.game_drama
+```
+
+```sql usage_efficiency
+select * from nba.usage_efficiency
+```
+
+# 🏀 NBA Analytics
+
+<BigValue data={season_summary} value=total_games title="Total Games" />
+<BigValue data={season_summary} value=avg_total_points title="Avg Points/Game" />
+<BigValue data={season_summary} value=overtime_games title="OT Games" />
+<BigValue data={season_summary} value=avg_margin title="Avg Margin" />
+
+---
+
+## League Evolution: Pace & Scoring
+
+<LineChart
+  data={pace_and_scoring}
+  x=season
+  y={['avg_total_points', 'avg_pace']}
+  y2=avg_efg_pct
+  title="How the NBA Has Changed: Points, Pace & Efficiency"
+  yAxisTitle="Points / Pace"
+  y2AxisTitle="eFG%"
+/>
+
+## Game Drama Over Time
+
+<AreaChart
+  data={game_drama}
+  x=season
+  y={['clutch_pct', 'blowout_pct', 'ot_pct']}
+  title="% of Games: Clutch (≤5pt margin) vs Blowouts (20+) vs Overtime"
+  yAxisTitle="% of Games"
+/>
+
+---
+
+## Current Season: Team Power Rankings
+
+<BarChart
+  data={team_ratings}
+  x=team
+  y=avg_net_rating
+  title="Net Rating by Team (Current Season)"
+  swapXY=true
+  colorPalette={['#dc2626', '#dc2626', '#dc2626', '#dc2626', '#dc2626', '#f97316', '#f97316', '#f97316', '#f97316', '#f97316', '#6b7280', '#6b7280', '#6b7280', '#6b7280', '#6b7280', '#6b7280', '#6b7280', '#6b7280', '#6b7280', '#6b7280', '#22c55e', '#22c55e', '#22c55e', '#22c55e', '#22c55e', '#16a34a', '#16a34a', '#16a34a', '#16a34a', '#16a34a']}
+/>
+
+<DataTable data={team_ratings} rows=30>
+  <Column id=team title="Team" />
+  <Column id=wins title="W" />
+  <Column id=games title="GP" />
+  <Column id=win_pct title="Win%" />
+  <Column id=avg_off_rating title="ORtg" />
+  <Column id=avg_def_rating title="DRtg" />
+  <Column id=avg_net_rating title="Net" contentType=colorscale colorScale=RdYlGn />
+  <Column id=avg_pace title="Pace" />
+</DataTable>
+
+## Shot Selection Style & Winning
+
+<BarChart
+  data={play_styles}
+  x=shot_selection_style
+  y={['win_pct', 'avg_off_rating']}
+  y2=avg_off_rating
+  title="Does Three-Point Shooting Win Games?"
+  yAxisTitle="Win %"
+  y2AxisTitle="Off Rating"
+/>
+
+---
+
+## Player Impact: Usage vs Efficiency
+
+<ScatterPlot
+  data={usage_efficiency}
+  x=usage
+  y=efficiency
+  size=ppg
+  tooltipTitle=player_name
+  title="Usage Rate vs True Shooting % (bubble size = PPG)"
+  xAxisTitle="Usage Rate %"
+  yAxisTitle="True Shooting %"
+/>
+
+## Top 30 Players by Box Plus/Minus (Current Season)
+
+<DataTable data={player_impact} rows=30>
+  <Column id=player_name title="Player" />
+  <Column id=team title="Team" />
+  <Column id=games title="GP" />
+  <Column id=ppg title="PPG" />
+  <Column id=apg title="APG" />
+  <Column id=rpg title="RPG" />
+  <Column id=avg_bpm title="BPM" contentType=colorscale colorScale=RdYlGn />
+  <Column id=avg_usage title="USG%" />
+  <Column id=ts_pct title="TS%" />
+  <Column id=double_doubles title="DD" />
+  <Column id=triple_doubles title="TD" />
+</DataTable>
+
+<BarChart
+  data={player_impact}
+  x=player_name
+  y=avg_bpm
+  title="Box Plus/Minus Leaders"
+  swapXY=true
+/>
+
+---
+
+## Home Court Advantage Trend
+
+<LineChart
+  data={home_advantage}
+  x=season_display
+  y=home_win_pct
+  title="Home Team Win % by Season"
+  yAxisTitle="Win %"
+  yMin=40
+  yMax=70
+  markers=true
+/>
+
+## Recent Games
+
+<DataTable data={games} rows=20>
+  <Column id=game_date title="Date" />
+  <Column id=home_team title="Home" />
+  <Column id=visitor_team title="Away" />
+  <Column id=home_points title="H Pts" />
+  <Column id=visitor_points title="A Pts" />
+  <Column id=winning_team title="Winner" />
+  <Column id=point_differential title="Margin" />
+  <Column id=game_competitiveness_tier title="Type" />
+  <Column id=is_overtime title="OT" />
+</DataTable>

dbt_nba/reports/sources/nba/competitiveness.sql

@@ -0,0 +1,6 @@
+select
+  game_competitiveness_tier,
+  count(*) as games
+from main_marts.fct_game_results
+group by game_competitiveness_tier
+order by games desc

dbt_nba/reports/sources/nba/connection.yaml

@@ -0,0 +1,4 @@
+name: nba
+type: duckdb
+options:
+  filename: dbt_nba.duckdb

dbt_nba/reports/sources/nba/game_drama.sql

@@ -0,0 +1,8 @@
+select
+  season_start_year || '-' || substr(cast(season_start_year + 1 as varchar), 3, 2) as season,
+  round(100.0 * sum(case when is_overtime then 1 else 0 end) / count(*), 1) as ot_pct,
+  round(100.0 * sum(case when point_differential <= 5 then 1 else 0 end) / count(*), 1) as clutch_pct,
+  round(100.0 * sum(case when point_differential >= 20 then 1 else 0 end) / count(*), 1) as blowout_pct
+from main_intermediate.int_games_enriched
+group by season_start_year
+order by season_start_year

dbt_nba/reports/sources/nba/games.sql

@@ -0,0 +1,18 @@
+select
+  g.game_date,
+  g.home_points,
+  g.visitor_points,
+  g.total_points,
+  g.point_differential,
+  g.is_overtime,
+  g.is_playoff,
+  g.game_competitiveness_tier,
+  g.is_home_team_winner,
+  ht.team_abbr as home_team,
+  vt.team_abbr as visitor_team,
+  wt.team_abbr as winning_team
+from main_marts.fct_game_results g
+left join main_marts.dim_teams ht on g.home_team_key = ht.team_key
+left join main_marts.dim_teams vt on g.visitor_team_key = vt.team_key
+left join main_marts.dim_teams wt on g.winning_team_key = wt.team_key
+order by g.game_date desc

dbt_nba/reports/sources/nba/home_advantage.sql

@@ -0,0 +1,9 @@
+select
+  s.season_display,
+  count(*) as total_games,
+  sum(case when g.is_home_team_winner then 1 else 0 end) as home_wins,
+  round(100.0 * sum(case when g.is_home_team_winner then 1 else 0 end) / count(*), 1) as home_win_pct
+from main_marts.fct_game_results g
+left join main_marts.dim_seasons s on g.season_key = s.season_key
+group by s.season_display
+order by s.season_display

dbt_nba/reports/sources/nba/pace_and_scoring.sql

@@ -0,0 +1,10 @@
+select
+  season_start_year || '-' || substr(cast(season_start_year + 1 as varchar), 3, 2) as season,
+  round(avg(matchup_pace), 1) as avg_pace,
+  round(avg(total_points), 1) as avg_total_points,
+  round(avg(home_effective_fg_pct + visitor_effective_fg_pct) / 2 * 100, 1) as avg_efg_pct,
+  round(avg(point_differential), 1) as avg_margin,
+  count(*) as games
+from main_intermediate.int_games_enriched
+group by season_start_year
+order by season_start_year

dbt_nba/reports/sources/nba/play_styles.sql

@@ -0,0 +1,9 @@
+select
+  shot_selection_style,
+  count(*) as games,
+  round(avg(case when game_result = 'W' then 1.0 else 0.0 end) * 100, 1) as win_pct,
+  round(avg(offensive_rating), 1) as avg_off_rating
+from main_intermediate.int_team_performance
+where season_start_year = (select max(season_start_year) from main_intermediate.int_team_performance)
+group by shot_selection_style
+order by avg_off_rating desc

dbt_nba/reports/sources/nba/player_impact.sql

@@ -0,0 +1,20 @@
+select
+  player_name,
+  team,
+  count(*) as games,
+  round(avg(points), 1) as ppg,
+  round(avg(assists), 1) as apg,
+  round(avg(total_rebounds), 1) as rpg,
+  round(avg(box_plus_minus), 2) as avg_bpm,
+  round(avg(usage_pct), 1) as avg_usage,
+  round(avg(true_shooting_pct) * 100, 1) as ts_pct,
+  round(avg(net_rating), 1) as avg_net_rating,
+  sum(case when is_double_double then 1 else 0 end) as double_doubles,
+  sum(case when is_triple_double then 1 else 0 end) as triple_doubles
+from main_intermediate.int_player_performance
+where season_start_year = (select max(season_start_year) from main_intermediate.int_player_performance)
+  and minutes_played >= 20
+group by player_name, team
+having count(*) >= 20
+order by avg_bpm desc
+limit 30

dbt_nba/reports/sources/nba/season_summary.sql

@@ -0,0 +1,11 @@
+select
+  s.season_display,
+  count(*) as total_games,
+  sum(case when g.is_overtime then 1 else 0 end) as overtime_games,
+  sum(case when g.is_playoff then 1 else 0 end) as playoff_games,
+  round(avg(g.total_points), 1) as avg_total_points,
+  round(avg(g.point_differential), 1) as avg_margin
+from main_marts.fct_game_results g
+left join main_marts.dim_seasons s on g.season_key = s.season_key
+group by s.season_display
+order by s.season_display desc

dbt_nba/reports/sources/nba/team_ratings.sql

@@ -0,0 +1,14 @@
+select
+  team,
+  count(*) as games,
+  sum(case when game_result = 'W' then 1 else 0 end) as wins,
+  round(100.0 * sum(case when game_result = 'W' then 1 else 0 end) / count(*), 1) as win_pct,
+  round(avg(offensive_rating), 1) as avg_off_rating,
+  round(avg(defensive_rating), 1) as avg_def_rating,
+  round(avg(net_rating), 1) as avg_net_rating,
+  round(avg(pace), 1) as avg_pace,
+  round(avg(effective_fg_pct) * 100, 1) as avg_efg_pct
+from main_intermediate.int_team_performance
+where season_start_year = (select max(season_start_year) from main_intermediate.int_team_performance)
+group by team
+order by avg_net_rating desc

dbt_nba/reports/sources/nba/top_scorers.sql

@@ -0,0 +1,13 @@
+select
+  p.player_name,
+  count(*) as games_played,
+  round(avg(ps.points), 1) as ppg,
+  round(avg(ps.total_rebounds), 1) as rpg,
+  round(avg(ps.assists), 1) as apg,
+  round(avg(ps.true_shooting_pct) * 100, 1) as ts_pct
+from main_marts.fct_player_game_stats ps
+left join main_marts.dim_players p on ps.player_key = p.player_key
+group by p.player_name
+having count(*) >= 50
+order by ppg desc
+limit 20

dbt_nba/reports/sources/nba/usage_efficiency.sql

@@ -0,0 +1,13 @@
+select
+  player_name,
+  team,
+  count(*) as games,
+  round(avg(usage_pct), 1) as usage,
+  round(avg(true_shooting_pct) * 100, 1) as efficiency,
+  round(avg(points), 1) as ppg
+from main_intermediate.int_player_performance
+where season_start_year = (select max(season_start_year) from main_intermediate.int_player_performance)
+  and minutes_played >= 20
+group by player_name, team
+having count(*) >= 20
+order by usage desc

dbt_nba/seeds/arena_mappings.csv

@@ -0,0 +1,97 @@
+arena_name,city,state_or_country,location
+ARCO Arena (II),Sacramento,California,North Natomas
+AT&T Center,San Antonio,Texas,East Side
+AccorHotels Arena,Paris,France,Bercy
+Air Canada Centre,Toronto,Ontario,Harbourfront
+Alamodome,San Antonio,Texas,Downtown
+Amalie Arena,Tampa,Florida,Channelside
+America West Arena,Phoenix,Arizona,Downtown
+American Airlines Center,Dallas,Texas,Victory Park
+AmericanAirlines Arena,Miami,Florida,Waterfront
+Amway Arena,Orlando,Florida,Downtown
+Amway Center,Orlando,Florida,Parramore
+BMO Harris Bradley Center,Milwaukee,Wisconsin,Downtown
+Ball Arena,Denver,Colorado,Central Platte Valley
+Bankers Life Fieldhouse,Indianapolis,Indiana,Downtown
+Barclays Center,Brooklyn,New York,Atlantic Yards
+Bradley Center,Milwaukee,Wisconsin,Downtown
+Capital One Arena,Washington,D.C.,Penn Quarter
+Charlotte Bobcats Arena,Charlotte,North Carolina,Uptown
+Charlotte Coliseum,Charlotte,North Carolina,Southwest Charlotte
+Chase Center,San Francisco,California,Mission Bay
+Chesapeake Energy Arena,Oklahoma City,Oklahoma,Downtown
+Compaq Center,Houston,Texas,Greenway Plaza
+Conseco Fieldhouse,Indianapolis,Indiana,Downtown
+Continental Airlines Arena,East Rutherford,New Jersey,Meadowlands
+Crypto.com Arena,Los Angeles,California,South Park
+Delta Center,Salt Lake City,Utah,Downtown
+EnergySolutions Arena,Salt Lake City,Utah,Downtown
+FTX Arena,Miami,Florida,Waterfront
+FedEx Forum,Memphis,Tennessee,Downtown
+FedExForum,Memphis,Tennessee,Downtown
+First Union Center,Philadelphia,Pennsylvania,South Philadelphia
+Fiserv Forum,Milwaukee,Wisconsin,Deer District
+FleetCenter,Boston,Massachusetts,West End
+Footprint Center,Phoenix,Arizona,Downtown
+Ford Center,Oklahoma City,Oklahoma,Downtown
+Frost Bank Center,San Antonio,Texas,East Side
+Gainbridge Fieldhouse,Indianapolis,Indiana,Downtown
+Golden 1 Center,Sacramento,California,Downtown Commons
+Gund Arena,Cleveland,Ohio,Gateway District
+Intuit Dome,Inglewood,California,Hollywood Park
+Izod Center,East Rutherford,New Jersey,Meadowlands
+Kaseya Center,Miami,Florida,Waterfront
+KeyArena at Seattle Center,Seattle,Washington,Seattle Center
+Kia Center,Orlando,Florida,Parramore
+LLoyd Noble Center,Norman,Oklahoma,University of Oklahoma
+Little Caesars Arena,Detroit,Michigan,Midtown
+MCI Center,Washington,D.C.,Penn Quarter
+Madison Square Garden (IV),New York,New York,Midtown Manhattan
+Mexico City Arena,Mexico City,Mexico,Azcapotzalco
+Moda Center,Portland,Oregon,Lloyd District
+Moody Center,Austin,Texas,University of Texas
+Mortgage Matchup Center,Cleveland,Ohio,Gateway District
+New Orleans Arena,New Orleans,Louisiana,Central Business District
+Oakland Arena,Oakland,California,Coliseum Complex
+Oklahoma City Arena,Oklahoma City,Oklahoma,Downtown
+Oracle Arena,Oakland,California,Coliseum Complex
+Paycom Center,Oklahoma City,Oklahoma,Downtown
+Pepsi Center,Denver,Colorado,Central Platte Valley
+Pete Maravich Assembly Center,Baton Rouge,Louisiana,LSU Campus
+Philips Arena,Atlanta,Georgia,Downtown
+Phoenix Suns Arena,Phoenix,Arizona,Downtown
+Power Balance Pavilion,Sacramento,California,North Natomas
+Prudential Center,Newark,New Jersey,Downtown
+Pyramid Arena,Memphis,Tennessee,Downtown
+Quicken Loans Arena,Cleveland,Ohio,Gateway District
+Rocket Arena,Houston,Texas,Greenway Plaza
+Rocket Mortgage Fieldhouse,Cleveland,Ohio,Gateway District
+Rose Garden Arena,Portland,Oregon,Lloyd District
+SBC Center,San Antonio,Texas,East Side
+STAPLES Center,Los Angeles,California,South Park
+Saitama Super Arena,Saitama,Japan,Chūō-ku
+Scotiabank Arena,Toronto,Ontario,Harbourfront
+Sleep Train Arena,Sacramento,California,North Natomas
+Smoothie King Center,New Orleans,Louisiana,Central Business District
+Spectrum Center,Charlotte,North Carolina,Uptown
+State Farm Arena,Atlanta,Georgia,Downtown
+T-Mobile Arena,Las Vegas,Nevada,Paradise
+TD Banknorth Garden,Boston,Massachusetts,West End
+TD Garden,Boston,Massachusetts,West End
+TD Waterhouse Centre,Orlando,Florida,Downtown
+Talking Stick Resort Arena,Phoenix,Arizona,Downtown
+Target Center,Minneapolis,Minnesota,Warehouse District
+The Arena in Oakland,Oakland,California,Coliseum Complex
+The O2 Arena,London,England,Greenwich Peninsula
+The Palace of Auburn Hills,Auburn Hills,Michigan,Auburn Hills
+Time Warner Cable Arena,Charlotte,North Carolina,Uptown
+Toyota Center,Houston,Texas,Downtown
+US Airways Center,Phoenix,Arizona,Downtown
+UW–Milwaukee Panther Arena,Milwaukee,Wisconsin,Downtown
+United Center,Chicago,Illinois,Near West Side
+Verizon Center,Washington,D.C.,Penn Quarter
+Vivint Arena,Salt Lake City,Utah,Downtown
+Vivint Smart Home Arena,Salt Lake City,Utah,Downtown
+Wachovia Center,Philadelphia,Pennsylvania,South Philadelphia
+Wells Fargo Center,Philadelphia,Pennsylvania,South Philadelphia
+Xfinity Mobile Arena,Manchester,New Hampshire,Downtown

dbt_nba/seeds/arena_maps.csv

@@ -0,0 +1,97 @@
+arena_name,city,state_or_country,location,start_date,end_date
+ARCO Arena (II),Sacramento,California,North Natomas,1988-11-08,2016-10-30
+AT&T Center,San Antonio,Texas,East Side,2006-01-01,2023-09-21
+AccorHotels Arena,Paris,France,Bercy (12th arrondissement),2015-10-01,2020-06-01
+Air Canada Centre,Toronto,Ontario,Downtown/Harbourfront,1999-02-20,2018-06-30
+Alamodome,San Antonio,Texas,Downtown,1993-05-15,2026-06-30
+Amalie Arena,Tampa,Florida,Channelside,1996-10-20,2026-06-30
+America West Arena,Phoenix,Arizona,Downtown,1992-06-06,2006-09-30
+American Airlines Center,Dallas,Texas,Victory Park,2001-07-17,2026-06-30
+AmericanAirlines Arena,Miami,Florida,Downtown/Biscayne Bay,1999-12-31,2021-06-01
+Amway Arena,Orlando,Florida,Downtown,1989-01-29,2010-10-01
+Amway Center,Orlando,Florida,Downtown,2010-10-01,2023-12-19
+BMO Harris Bradley Center,Milwaukee,Wisconsin,Downtown,2012-05-21,2018-09-17
+Ball Arena,Denver,Colorado,Central Platte Valley/LoDo,2020-10-22,2026-06-30
+Bankers Life Fieldhouse,Indianapolis,Indiana,Downtown,2011-12-01,2021-09-26
+Barclays Center,Brooklyn,New York,Downtown Brooklyn/Prospect Heights,2012-09-21,2026-06-30
+Bradley Center,Milwaukee,Wisconsin,Downtown,1988-10-01,2012-05-20
+Capital One Arena,Washington,District of Columbia,Chinatown/Penn Quarter,2017-08-09,2026-06-30
+Charlotte Bobcats Arena,Charlotte,North Carolina,Uptown (First Ward),2005-10-21,2008-08-01
+Charlotte Coliseum,Charlotte,North Carolina,Tyvola Road,1988-08-11,2005-10-26
+Chase Center,San Francisco,California,Mission Bay,2019-09-06,2026-06-30
+Chesapeake Energy Arena,Oklahoma City,Oklahoma,Downtown,2011-01-01,2021-04-01
+Compaq Center,Houston,Texas,Greenway Plaza,1998-01-01,2003-10-01
+Conseco Fieldhouse,Indianapolis,Indiana,Downtown,1999-11-06,2011-11-30
+Continental Airlines Arena,East Rutherford,New Jersey,Meadowlands Sports Complex,1996-01-04,2007-06-30
+Crypto.com Arena,Los Angeles,California,South Park/Downtown,2021-12-25,2026-06-30
+Delta Center,Salt Lake City,Utah,West Downtown,1991-10-04,2026-06-30
+EnergySolutions Arena,Salt Lake City,Utah,West Downtown,2006-11-20,2015-10-25
+FTX Arena,Miami,Florida,Downtown/Biscayne Bay,2021-06-01,2023-01-01
+FedEx Forum,Memphis,Tennessee,Downtown (near Beale Street),2004-09-06,2026-06-30
+FedExForum,Memphis,Tennessee,Downtown (near Beale Street),2004-09-06,2026-06-30
+First Union Center,Philadelphia,Pennsylvania,South Philadelphia Sports Complex,1998-09-01,2003-06-30
+Fiserv Forum,Milwaukee,Wisconsin,Deer District/Downtown,2018-08-26,2026-06-30
+FleetCenter,Boston,Massachusetts,West End,1995-09-30,2005-06-30
+Footprint Center,Phoenix,Arizona,Downtown,2021-07-16,2025-02-17
+Ford Center,Oklahoma City,Oklahoma,Downtown,2002-06-08,2010-12-31
+Frost Bank Center,San Antonio,Texas,East Side,2023-09-22,2026-06-30
+Gainbridge Fieldhouse,Indianapolis,Indiana,Downtown,2021-09-27,2026-06-30
+Golden 1 Center,Sacramento,California,Downtown Commons (DoCo),2016-10-04,2026-06-30
+Gund Arena,Cleveland,Ohio,Gateway District/Downtown,1994-10-01,2005-08-01
+Intuit Dome,Inglewood,California,Hollywood Park,2024-08-15,2026-06-30
+Izod Center,East Rutherford,New Jersey,Meadowlands Sports Complex,2007-07-01,2015-01-15
+Kaseya Center,Miami,Florida,Downtown/Biscayne Bay,2023-04-01,2026-06-30
+KeyArena at Seattle Center,Seattle,Washington,Seattle Center/Lower Queen Anne,1995-10-26,2008-04-13
+Kia Center,Orlando,Florida,Downtown,2023-12-20,2026-06-30
+LLoyd Noble Center,Norman,Oklahoma,University of Oklahoma Campus,1975-11-01,2026-06-30
+Little Caesars Arena,Detroit,Michigan,Midtown/District Detroit,2017-09-05,2026-06-30
+MCI Center,Washington,District of Columbia,Chinatown/Penn Quarter,1997-12-02,2006-02-28
+Madison Square Garden (IV),New York,New York,Midtown Manhattan (Penn Station),1968-02-11,2026-06-30
+Mexico City Arena,Mexico City,Mexico,Azcapotzalco,2012-02-25,2026-06-30
+Moda Center,Portland,Oregon,Rose Quarter/Lloyd District,2013-08-13,2026-06-30
+Moody Center,Austin,Texas,UT Campus,2022-04-20,2026-06-30
+Mortgage Matchup Center,Phoenix,Arizona,Downtown,2025-10-02,2026-06-30
+New Orleans Arena,New Orleans,Louisiana,Central Business District,1999-10-01,2014-02-04
+Oakland Arena,Oakland,California,Coliseum Industrial,2019-06-14,2026-06-30
+Oklahoma City Arena,Oklahoma City,Oklahoma,Downtown,2010-01-01,2010-12-31
+Oracle Arena,Oakland,California,Coliseum Industrial,2006-10-20,2019-06-13
+Paycom Center,Oklahoma City,Oklahoma,Downtown,2021-07-27,2026-06-30
+Pepsi Center,Denver,Colorado,Central Platte Valley/LoDo,1999-10-01,2020-10-21
+Pete Maravich Assembly Center,Baton Rouge,Louisiana,LSU Campus,1972-01-15,2026-06-30
+Philips Arena,Atlanta,Georgia,Centennial Olympic Park District,1999-09-01,2018-08-28
+Phoenix Suns Arena,Phoenix,Arizona,Downtown,2020-11-01,2021-07-15
+Power Balance Pavilion,Sacramento,California,North Natomas,2011-03-01,2012-12-31
+Prudential Center,Newark,New Jersey,Downtown Newark,2007-10-25,2026-06-30
+Pyramid Arena,Memphis,Tennessee,Downtown (Riverfront),1991-11-09,2004-12-31
+Quicken Loans Arena,Cleveland,Ohio,Gateway District/Downtown,2005-08-01,2019-03-31
+Rocket Arena,Cleveland,Ohio,Gateway District/Downtown,2025-02-18,2026-06-30
+Rocket Mortgage Fieldhouse,Cleveland,Ohio,Gateway District/Downtown,2019-04-01,2025-02-17
+Rose Garden Arena,Portland,Oregon,Rose Quarter/Lloyd District,1995-10-12,2013-08-12
+SBC Center,San Antonio,Texas,East Side,2002-10-18,2005-12-31
+STAPLES Center,Los Angeles,California,South Park/Downtown,1999-10-17,2021-12-24
+Saitama Super Arena,Saitama,Japan,Chuo-ku/Shin-Toshin,2000-09-01,2026-06-30
+Scotiabank Arena,Toronto,Ontario,Downtown/Harbourfront,2018-07-01,2026-06-30
+Sleep Train Arena,Sacramento,California,North Natomas,2013-01-01,2016-10-30
+Smoothie King Center,New Orleans,Louisiana,Central Business District,2014-02-05,2026-06-30
+Spectrum Center,Charlotte,North Carolina,Uptown (First Ward),2016-08-17,2026-06-30
+State Farm Arena,Atlanta,Georgia,Centennial Olympic Park District,2018-08-29,2026-06-30
+T-Mobile Arena,Las Vegas,Nevada,Las Vegas Strip,2016-04-06,2026-06-30
+TD Banknorth Garden,Boston,Massachusetts,West End,2005-07-01,2009-07-15
+TD Garden,Boston,Massachusetts,West End,2009-07-16,2026-06-30
+TD Waterhouse Centre,Orlando,Florida,Downtown,1999-10-01,2002-12-31
+Talking Stick Resort Arena,Phoenix,Arizona,Downtown,2015-09-01,2020-10-31
+Target Center,Minneapolis,Minnesota,Warehouse District/North Loop,1990-10-16,2026-06-30
+The Arena in Oakland,Oakland,California,Coliseum Industrial,1997-10-01,2004-12-31
+The O2 Arena,London,United Kingdom,Greenwich Peninsula,2007-06-24,2026-06-30
+The Palace of Auburn Hills,Auburn Hills,Michigan,Auburn Hills (I-75 corridor),1988-10-01,2017-10-12
+Time Warner Cable Arena,Charlotte,North Carolina,Uptown (First Ward),2008-08-01,2016-08-16
+Toyota Center,Houston,Texas,Downtown/East Downtown,2003-10-06,2026-06-30
+US Airways Center,Phoenix,Arizona,Downtown,2006-10-01,2015-08-31
+UW–Milwaukee Panther Arena,Milwaukee,Wisconsin,Downtown,1950-08-04,2026-06-30
+United Center,Chicago,Illinois,Near West Side,1994-08-18,2026-06-30
+Verizon Center,Washington,District of Columbia,Chinatown/Penn Quarter,2006-03-01,2017-08-08
+Vivint Arena,Salt Lake City,Utah,West Downtown,2020-01-01,2023-06-30
+Vivint Smart Home Arena,Salt Lake City,Utah,West Downtown,2015-10-26,2019-12-31
+Wachovia Center,Philadelphia,Pennsylvania,South Philadelphia Sports Complex,2003-07-01,2010-06-30
+Wells Fargo Center,Philadelphia,Pennsylvania,South Philadelphia Sports Complex,2010-07-01,2025-08-31
+Xfinity Mobile Arena,Philadelphia,Pennsylvania,South Philadelphia Sports Complex,2025-09-01,2026-06-30

dbt_nba/seeds/team_abbreviation_mappings.csv

@@ -0,0 +1,41 @@
+source_abbr,team_abbr
+ATL,ATL
+BOS,BOS
+BKN,BKN
+NJN,BKN
+BRK,BKN
+CHA,CHA
+CHH,CHA
+CHO,CHA
+CHI,CHI
+CLE,CLE
+DAL,DAL
+DEN,DEN
+DET,DET
+GSW,GSW
+HOU,HOU
+IND,IND
+LAC,LAC
+LAL,LAL
+MEM,MEM
+MIA,MIA
+MIL,MIL
+MIN,MIN
+NOP,NOP
+NOH,NOP
+NOK,NOP
+NYK,NYK
+OKC,OKC
+SEA,OKC
+ORL,ORL
+PHI,PHI
+PHX,PHX
+PHO,PHX
+POR,POR
+SAC,SAC
+SAS,SAS
+TOR,TOR
+UTA,UTA
+WAS,WAS
+VAN,MEM
+SDC,LAC

dbt_nba/seeds/team_mappings.csv

@@ -0,0 +1,36 @@
+team_abbr,full_name
+ATL,Atlanta Hawks
+BOS,Boston Celtics
+BKN,Brooklyn Nets
+BKN,New Jersey Nets
+CHA,Charlotte Hornets
+CHA,Charlotte Bobcats
+CHI,Chicago Bulls
+CLE,Cleveland Cavaliers
+DAL,Dallas Mavericks
+DEN,Denver Nuggets
+DET,Detroit Pistons
+GSW,Golden State Warriors
+HOU,Houston Rockets
+IND,Indiana Pacers
+LAC,Los Angeles Clippers
+LAL,Los Angeles Lakers
+MEM,Memphis Grizzlies
+MIA,Miami Heat
+MIL,Milwaukee Bucks
+MIN,Minnesota Timberwolves
+NOP,New Orleans Pelicans
+NOP,New Orleans Hornets
+NOP,New Orleans/Oklahoma City Hornets
+NYK,New York Knicks
+OKC,Oklahoma City Thunder
+OKC,Seattle SuperSonics
+ORL,Orlando Magic
+PHI,Philadelphia 76ers
+PHX,Phoenix Suns
+POR,Portland Trail Blazers
+SAC,Sacramento Kings
+SAS,San Antonio Spurs
+TOR,Toronto Raptors
+UTA,Utah Jazz
+WAS,Washington Wizards

dbt_nba/seeds/team_maps.csv

@@ -0,0 +1,39 @@
+team_abbr,full_name,start_year,end_year,is_current,source,notes
+ATL,Atlanta Hawks,1968,2026,TRUE,all,No changes since 1968
+BOS,Boston Celtics,1946,2026,TRUE,all,No changes since 1946
+BRK,Brooklyn Nets,2012,2026,TRUE,bref,Basketball-Reference abbreviation for Brooklyn
+CHA,Charlotte Bobcats,2004,2014,FALSE,bref,Renamed to Hornets in 2014; ESPN/NBA.com also use CHA for current Hornets
+CHH,Charlotte Hornets,1988,2002,FALSE,bref,Original Hornets; relocated to New Orleans after 2001-02
+CHI,Chicago Bulls,1966,2026,TRUE,all,No changes since 1966
+CHO,Charlotte Hornets,2014,2026,TRUE,bref,Basketball-Reference abbreviation; reclaimed original Hornets history
+CLE,Cleveland Cavaliers,1970,2026,TRUE,all,No changes since 1970
+DAL,Dallas Mavericks,1980,2026,TRUE,all,Expansion team 1980-81 season
+DEN,Denver Nuggets,1976,2026,TRUE,all,Joined NBA in 1976 from ABA
+DET,Detroit Pistons,1957,2026,TRUE,all,In Detroit since 1957
+GSW,Golden State Warriors,1971,2026,TRUE,all,Name changed from San Francisco Warriors in 1971
+HOU,Houston Rockets,1971,2026,TRUE,all,Moved from San Diego in 1971
+IND,Indiana Pacers,1976,2026,TRUE,all,Joined NBA in 1976 from ABA
+LAC,Los Angeles Clippers,1984,2026,TRUE,all,Relocated from San Diego
+LAL,Los Angeles Lakers,1960,2026,TRUE,all,Moved from Minneapolis in 1960
+MEM,Memphis Grizzlies,2001,2026,TRUE,all,Relocated from Vancouver
+MIA,Miami Heat,1988,2026,TRUE,all,Expansion team 1988-89 season
+MIL,Milwaukee Bucks,1968,2026,TRUE,all,No changes since 1968
+MIN,Minnesota Timberwolves,1989,2026,TRUE,all,Expansion team 1989-90 season
+NJN,New Jersey Nets,1977,2012,FALSE,all,Moved to Brooklyn after 2011-12 season
+NOH,New Orleans Hornets,2002,2005,FALSE,bref,Relocated from Charlotte; excludes NOK years; renamed Pelicans in 2013
+NOK,New Orleans/Oklahoma City Hornets,2005,2007,FALSE,bref,Hurricane Katrina temporary relocation; split home games
+NOP,New Orleans Pelicans,2013,2026,TRUE,all,Renamed from Hornets
+NYK,New York Knicks,1946,2026,TRUE,all,No changes since 1946
+OKC,Oklahoma City Thunder,2008,2026,TRUE,all,Relocated from Seattle
+ORL,Orlando Magic,1989,2026,TRUE,all,Expansion team 1989-90 season
+PHI,Philadelphia 76ers,1963,2026,TRUE,all,Moved from Syracuse in 1963
+PHO,Phoenix Suns,1968,2026,TRUE,bref,Basketball-Reference abbreviation
+POR,Portland Trail Blazers,1970,2026,TRUE,all,No changes since 1970
+SAC,Sacramento Kings,1985,2026,TRUE,all,Relocated from Kansas City
+SAS,San Antonio Spurs,1976,2026,TRUE,all,Joined NBA in 1976 from ABA
+SDC,San Diego Clippers,1978,1984,FALSE,bref,Moved to Los Angeles after 1983-84 season
+SEA,Seattle SuperSonics,1967,2008,FALSE,all,Relocated to Oklahoma City after 2007-08 season
+TOR,Toronto Raptors,1995,2026,TRUE,all,Expansion team 1995-96 season
+UTA,Utah Jazz,1979,2026,TRUE,all,Moved from New Orleans in 1979
+VAN,Vancouver Grizzlies,1995,2001,FALSE,all,Expansion team 1995-96; relocated to Memphis after 2000-01
+WAS,Washington Wizards,1997,2026,TRUE,all,Renamed from Bullets

dbt_nba/selectors.yml

@@ -0,0 +1,16 @@
+selectors:
+  - name: nba_pipeline
+    description: "Executes the full pipeline: Staging -> Intermediate -> Dimensions -> Facts"
+    default: false
+    definition:
+      union:
+        - method: tag
+          value: staging
+        - method: tag
+          value: intermediate
+        - method: tag
+          value: dimension
+        - method: tag
+          value: fact
+        - method: tag
+          value: marts

pyproject.toml

@@ -0,0 +1,13 @@
+[project]
+name = "dbt-nba"
+version = "1.0.0"
+requires-python = ">=3.11,<3.13"
+dependencies = [
+    "dbt-duckdb",
+    "streamlit>=1.45.1",
+    "duckdb>=1.3.0",
+    "plotly>=6.1.2",
+    "streamlit-echarts>=0.4.0",
+    "boto3>=1.34.0",
+    "python-dotenv>=1.0.0",
+]

scripts/db_storage.py

@@ -0,0 +1,302 @@
+#!/usr/bin/env python3
+"""
+S3/Cloudflare R2 Object Storage utility for DuckDB database management.
+
+Supports:
+- Cloudflare R2 (recommended: zero egress fees)
+- Hetzner S3 Object Storage
+- SeaweedFS / MinIO / AWS S3
+
+Commands:
+  python scripts/db_storage.py status
+  python scripts/db_storage.py upload [--file PATH] [--key KEY]
+  python scripts/db_storage.py download [--force] [--key KEY]
+"""
+
+import argparse
+import hashlib
+import os
+import shutil
+import sys
+import time
+from pathlib import Path
+
+try:
+    from dotenv import load_dotenv
+    # Load .env file from repo root
+    repo_root = Path(__file__).resolve().parent.parent
+    load_dotenv(repo_root / ".env")
+except ImportError:
+    repo_root = Path(__file__).resolve().parent.parent
+
+try:
+    import boto3
+    from boto3.s3.transfer import TransferConfig
+    from botocore.client import Config
+    from botocore.exceptions import ClientError
+except ImportError:
+    print("ERROR: boto3 is not installed. Please run `uv sync` to install dependencies.", file=sys.stderr)
+    sys.exit(1)
+
+# Default Paths
+DEFAULT_LOCAL_DB = repo_root / "data" / "DB" / "dbt_nba.duckdb"
+DEFAULT_REPORTS_DB = repo_root / "dbt_nba" / "reports" / "sources" / "nba" / "dbt_nba.duckdb"
+
+# Tuned TransferConfig for resilient large multipart transfers over HTTPS
+TRANSFER_CONFIG = TransferConfig(
+    multipart_threshold=32 * 1024 * 1024,   # 32 MB
+    max_concurrency=4,                       # 4 concurrent threads
+    multipart_chunksize=32 * 1024 * 1024,   # 32 MB per chunk
+    use_threads=True,
+    num_download_attempts=5,
+)
+
+
+def get_s3_config():
+    """Retrieve S3/R2 configuration from environment variables."""
+    endpoint_url = os.getenv("S3_ENDPOINT_URL") or os.getenv("R2_ENDPOINT_URL")
+    bucket_name = os.getenv("S3_BUCKET_NAME") or os.getenv("R2_BUCKET_NAME")
+    access_key = os.getenv("S3_ACCESS_KEY_ID") or os.getenv("AWS_ACCESS_KEY_ID") or os.getenv("R2_ACCESS_KEY_ID")
+    secret_key = os.getenv("S3_SECRET_ACCESS_KEY") or os.getenv("AWS_SECRET_ACCESS_KEY") or os.getenv("R2_SECRET_ACCESS_KEY")
+    region_name = os.getenv("S3_REGION", "auto")
+    db_key = os.getenv("S3_DB_KEY", "dbt_nba.duckdb")
+
+    missing = []
+    if not endpoint_url:
+        missing.append("S3_ENDPOINT_URL")
+    if not bucket_name:
+        missing.append("S3_BUCKET_NAME")
+    if not access_key:
+        missing.append("S3_ACCESS_KEY_ID")
+    if not secret_key:
+        missing.append("S3_SECRET_ACCESS_KEY")
+
+    if missing:
+        print(f"ERROR: Missing required environment variables in .env: {', '.join(missing)}", file=sys.stderr)
+        print("Please check .env.example for guidance.", file=sys.stderr)
+        sys.exit(1)
+
+    return {
+        "endpoint_url": endpoint_url,
+        "bucket_name": bucket_name,
+        "access_key": access_key,
+        "secret_key": secret_key,
+        "region_name": region_name,
+        "db_key": db_key,
+    }
+
+
+def get_s3_client(config):
+    """Create a boto3 S3 client configured for custom S3/R2 endpoints."""
+    return boto3.client(
+        "s3",
+        endpoint_url=config["endpoint_url"],
+        aws_access_key_id=config["access_key"],
+        aws_secret_access_key=config["secret_key"],
+        region_name=config["region_name"],
+        config=Config(
+            signature_version="s3v4",
+            s3={"addressing_style": "path"},
+            retries={"max_attempts": 5, "mode": "adaptive"},
+        ),
+    )
+
+
+class ProgressPercentage:
+    """Console progress tracker for S3 file transfer."""
+
+    def __init__(self, filename, total_size, action="Transferring"):
+        self._filename = filename
+        self._total_size = float(total_size) if total_size > 0 else 1.0
+        self._seen_so_far = 0
+        self._start_time = time.time()
+        self._action = action
+
+    def __call__(self, bytes_amount):
+        self._seen_so_far += bytes_amount
+        percentage = (self._seen_so_far / self._total_size) * 100
+        elapsed = max(time.time() - self._start_time, 0.001)
+        speed_mb = (self._seen_so_far / (1024 * 1024)) / elapsed
+        mb_seen = self._seen_so_far / (1024 * 1024)
+        mb_total = self._total_size / (1024 * 1024)
+
+        sys.stdout.write(
+            f"\r{self._action} {Path(self._filename).name}: {mb_seen:.1f}/{mb_total:.1f} MB "
+            f"({percentage:5.1f}%) @ {speed_mb:5.1f} MB/s"
+        )
+        sys.stdout.flush()
+        if self._seen_so_far >= self._total_size:
+            sys.stdout.write("\n")
+            sys.stdout.flush()
+
+
+def compute_file_md5(filepath: Path) -> str:
+    """Compute hex MD5 hash of a local file."""
+    hash_md5 = hashlib.md5()
+    with open(filepath, "rb") as f:
+        for chunk in iter(lambda: f.read(1024 * 1024), b""):
+            hash_md5.update(chunk)
+    return hash_md5.hexdigest()
+
+
+def upload_db(file_path: Path = None, key: str = None):
+    """Upload DuckDB file to S3/R2 with auto-retry."""
+    config = get_s3_config()
+    target_file = Path(file_path) if file_path else DEFAULT_LOCAL_DB
+    object_key = key or config["db_key"]
+
+    if not target_file.exists():
+        print(f"ERROR: Local database file not found at {target_file}", file=sys.stderr)
+        sys.exit(1)
+
+    file_size = target_file.stat().st_size
+    print(f"==> Uploading {target_file} ({file_size / (1024*1024):.2f} MB) to s3://{config['bucket_name']}/{object_key}...")
+
+    s3 = get_s3_client(config)
+    max_retries = 3
+
+    for attempt in range(1, max_retries + 1):
+        try:
+            progress = ProgressPercentage(str(target_file), file_size, action="Uploading")
+            s3.upload_file(
+                Filename=str(target_file),
+                Bucket=config["bucket_name"],
+                Key=object_key,
+                Config=TRANSFER_CONFIG,
+                Callback=progress,
+            )
+            print(f"✓ Successfully uploaded {object_key} to {config['bucket_name']}")
+            return
+        except Exception as e:
+            if attempt < max_retries:
+                print(f"\n[Attempt {attempt}/{max_retries}] Upload encountered error ({e}). Retrying in 3s...", file=sys.stderr)
+                time.sleep(3)
+            else:
+                print(f"\nERROR: Failed to upload to S3 after {max_retries} attempts: {e}", file=sys.stderr)
+                sys.exit(1)
+
+
+def download_db(force: bool = False, key: str = None):
+    """Download DuckDB file from S3/R2 to local destinations with auto-retry."""
+    config = get_s3_config()
+    object_key = key or config["db_key"]
+    s3 = get_s3_client(config)
+
+    print(f"==> Checking remote object s3://{config['bucket_name']}/{object_key}...")
+    try:
+        head = s3.head_object(Bucket=config["bucket_name"], Key=object_key)
+    except ClientError as e:
+        print(f"ERROR: Could not find or access remote object {object_key} in {config['bucket_name']}: {e}", file=sys.stderr)
+        sys.exit(1)
+
+    remote_size = head.get("ContentLength", 0)
+    last_modified = head.get("LastModified")
+
+    print(f"    Remote size: {remote_size / (1024*1024):.2f} MB | Last modified: {last_modified}")
+
+    # Check if local file is already identical
+    if not force and DEFAULT_LOCAL_DB.exists() and DEFAULT_LOCAL_DB.stat().st_size == remote_size:
+        # Check if reports db also exists
+        if DEFAULT_REPORTS_DB.exists() and DEFAULT_REPORTS_DB.stat().st_size == remote_size:
+            print("✓ Local database is already up-to-date. Skipping download (use --force to re-download).")
+            return
+
+    # Ensure parent directories exist
+    DEFAULT_LOCAL_DB.parent.mkdir(parents=True, exist_ok=True)
+    DEFAULT_REPORTS_DB.parent.mkdir(parents=True, exist_ok=True)
+
+    temp_file = DEFAULT_LOCAL_DB.with_suffix(".duckdb.tmp")
+    max_retries = 3
+
+    for attempt in range(1, max_retries + 1):
+        try:
+            progress = ProgressPercentage(str(DEFAULT_LOCAL_DB), remote_size, action="Downloading")
+            s3.download_file(
+                Bucket=config["bucket_name"],
+                Key=object_key,
+                Filename=str(temp_file),
+                Config=TRANSFER_CONFIG,
+                Callback=progress,
+            )
+            # Atomically move temp file to main db path
+            shutil.move(str(temp_file), str(DEFAULT_LOCAL_DB))
+            # Copy to reports location as well
+            shutil.copy2(str(DEFAULT_LOCAL_DB), str(DEFAULT_REPORTS_DB))
+            print(f"✓ Downloaded database to:\n  - {DEFAULT_LOCAL_DB}\n  - {DEFAULT_REPORTS_DB}")
+            return
+        except Exception as e:
+            if temp_file.exists():
+                temp_file.unlink()
+            if attempt < max_retries:
+                print(f"\n[Attempt {attempt}/{max_retries}] Download encountered error ({e}). Retrying in 3s...", file=sys.stderr)
+                time.sleep(3)
+            else:
+                print(f"\nERROR: Failed to download from S3 after {max_retries} attempts: {e}", file=sys.stderr)
+                sys.exit(1)
+
+
+def status_db():
+    """Show status of remote and local databases."""
+    config = get_s3_config()
+    object_key = config["db_key"]
+    s3 = get_s3_client(config)
+
+    print("=" * 60)
+    print("Database Storage Status (Cloudflare R2 / S3)")
+    print("=" * 60)
+    print(f"Endpoint: {config['endpoint_url']}")
+    print(f"Bucket:   {config['bucket_name']}")
+    print(f"DB Key:   {object_key}")
+    print("-" * 60)
+
+    try:
+        head = s3.head_object(Bucket=config["bucket_name"], Key=object_key)
+        remote_size = head.get("ContentLength", 0)
+        last_modified = head.get("LastModified")
+        print(f"Remote DB: Exists ({remote_size / (1024*1024):.2f} MB)")
+        print(f"           Last Modified: {last_modified}")
+    except ClientError as e:
+        print(f"Remote DB: NOT FOUND ({e})")
+
+    print("-" * 60)
+    if DEFAULT_LOCAL_DB.exists():
+        print(f"Local DB (Data):    Exists ({DEFAULT_LOCAL_DB.stat().st_size / (1024*1024):.2f} MB) -> {DEFAULT_LOCAL_DB}")
+    else:
+        print(f"Local DB (Data):    Missing -> {DEFAULT_LOCAL_DB}")
+
+    if DEFAULT_REPORTS_DB.exists():
+        print(f"Local DB (Reports): Exists ({DEFAULT_REPORTS_DB.stat().st_size / (1024*1024):.2f} MB) -> {DEFAULT_REPORTS_DB}")
+    else:
+        print(f"Local DB (Reports): Missing -> {DEFAULT_REPORTS_DB}")
+    print("=" * 60)
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Manage NBA DuckDB sync with Cloudflare R2 / S3.")
+    subparsers = parser.add_subparsers(dest="command", required=True)
+
+    # status
+    subparsers.add_parser("status", help="Check remote and local database status")
+
+    # upload
+    upload_parser = subparsers.add_parser("upload", help="Upload local DuckDB to S3/R2")
+    upload_parser.add_argument("--file", help="Path to local .duckdb file (default: data/DB/dbt_nba.duckdb)")
+    upload_parser.add_argument("--key", help="Remote object key (default: from env or dbt_nba.duckdb)")
+
+    # download
+    download_parser = subparsers.add_parser("download", help="Download DuckDB from S3/R2")
+    download_parser.add_argument("--force", action="store_true", help="Force download even if local file matches")
+    download_parser.add_argument("--key", help="Remote object key (default: from env or dbt_nba.duckdb)")
+
+    args = parser.parse_args()
+
+    if args.command == "status":
+        status_db()
+    elif args.command == "upload":
+        upload_db(file_path=args.file, key=args.key)
+    elif args.command == "download":
+        download_db(force=args.force, key=args.key)
+
+
+if __name__ == "__main__":
+    main()

scripts/extract.sql

@@ -0,0 +1,28 @@
+-- Extract source tables from Postgres into DuckDB
+-- Requires: POSTGRES_URL environment variable
+-- Usage: Run via scripts/pipeline.sh (handles variable substitution)
+
+INSTALL postgres;
+LOAD postgres;
+
+ATTACH '${POSTGRES_URL}' AS pg (TYPE POSTGRES, READ_ONLY);
+
+DROP TABLE IF EXISTS main.games;
+DROP TABLE IF EXISTS main.line_scores;
+DROP TABLE IF EXISTS main.player_game_basic_stats;
+DROP TABLE IF EXISTS main.player_game_adv_stats;
+DROP TABLE IF EXISTS main.player_shot_charts;
+DROP TABLE IF EXISTS main.team_game_basic_stats;
+DROP TABLE IF EXISTS main.team_game_adv_stats;
+
+CREATE TABLE main.games AS SELECT * FROM pg.public.games;
+CREATE TABLE main.line_scores AS SELECT * FROM pg.public.line_scores;
+CREATE TABLE main.player_game_basic_stats AS SELECT * FROM pg.public.player_game_basic_stats;
+CREATE TABLE main.player_game_adv_stats AS SELECT * FROM pg.public.player_game_adv_stats;
+CREATE TABLE main.player_shot_charts AS SELECT * FROM pg.public.player_shot_charts;
+CREATE TABLE main.team_game_basic_stats AS SELECT * FROM pg.public.team_game_basic_stats;
+CREATE TABLE main.team_game_adv_stats AS SELECT * FROM pg.public.team_game_adv_stats;
+
+DETACH pg;
+
+SELECT 'Extraction complete' AS status;

scripts/pipeline.sh

@@ -0,0 +1,47 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+REPO_ROOT="$(cd "$(dirname "$0")/.." && pwd)"
+DB_PATH="$REPO_ROOT/data/DB/dbt_nba.duckdb"
+REPORTS_DB="$REPO_ROOT/dbt_nba/reports/sources/nba/dbt_nba.duckdb"
+
+# Load .env if it exists
+if [ -f "$REPO_ROOT/.env" ]; then
+  set -a
+  source "$REPO_ROOT/.env"
+  set +a
+fi
+
+# Check prerequisites
+if [ -z "${POSTGRES_URL:-}" ]; then
+  echo "ERROR: POSTGRES_URL environment variable is not set" >&2
+  echo "Please export POSTGRES_URL or configure it in $REPO_ROOT/.env" >&2
+  exit 1
+fi
+
+echo "==> [1/4] Extracting from Postgres into DuckDB..."
+mkdir -p "$(dirname "$DB_PATH")"
+mkdir -p "$(dirname "$REPORTS_DB")"
+rm -f "$DB_PATH"
+envsubst < "$REPO_ROOT/scripts/extract.sql" | duckdb "$DB_PATH"
+
+echo "==> [2/4] Running dbt build --full-refresh..."
+export DBT_PROJECT_DIR="$REPO_ROOT/dbt_nba"
+export DBT_PROFILES_DIR="$REPO_ROOT/dbt_nba"
+export DBT_DUCKDB_PATH="$DB_PATH"
+
+uv run --project "$REPO_ROOT" dbt deps --project-dir "$DBT_PROJECT_DIR" --profiles-dir "$DBT_PROFILES_DIR"
+uv run --project "$REPO_ROOT" dbt build --full-refresh --project-dir "$DBT_PROJECT_DIR" --profiles-dir "$DBT_PROFILES_DIR"
+
+echo "==> [3/4] Copying database to reports directory..."
+cp "$DB_PATH" "$REPORTS_DB"
+
+echo "==> [4/4] Syncing database artifact to Cloudflare R2 / S3..."
+if [ -n "${S3_ENDPOINT_URL:-}" ] || [ -n "${R2_ENDPOINT_URL:-}" ]; then
+  uv run --project "$REPO_ROOT" python "$REPO_ROOT/scripts/db_storage.py" upload
+  echo "==> Cloudflare R2 upload complete!"
+else
+  echo "==> S3_ENDPOINT_URL not set; skipping remote upload (local DB ready)."
+fi
+
+echo "==> Pipeline complete successfully!"

scripts/run_app.sh

@@ -0,0 +1,41 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+REPO_ROOT="$(cd "$(dirname "$0")/.." && pwd)"
+REPORTS_DB="$REPO_ROOT/dbt_nba/reports/sources/nba/dbt_nba.duckdb"
+DATA_DB="$REPO_ROOT/data/DB/dbt_nba.duckdb"
+
+# Load .env if present
+if [ -f "$REPO_ROOT/.env" ]; then
+  set -a
+  source "$REPO_ROOT/.env"
+  set +a
+fi
+
+FORCE_SYNC=0
+for arg in "$@"; do
+  if [ "$arg" == "--sync" ] || [ "$arg" == "-s" ]; then
+    FORCE_SYNC=1
+  fi
+done
+
+# Check if database is missing or sync requested
+if [ ! -f "$REPORTS_DB" ] || [ "$FORCE_SYNC" -eq 1 ]; then
+  if [ -f "$DATA_DB" ] && [ "$FORCE_SYNC" -eq 0 ]; then
+    echo "==> Copying local database to reports path..."
+    mkdir -p "$(dirname "$REPORTS_DB")"
+    cp "$DATA_DB" "$REPORTS_DB"
+  elif [ -n "${S3_ENDPOINT_URL:-}" ] || [ -n "${R2_ENDPOINT_URL:-}" ]; then
+    echo "==> Local database missing or --sync requested; downloading latest from Cloudflare R2 / S3..."
+    uv run --project "$REPO_ROOT" python "$REPO_ROOT/scripts/db_storage.py" download
+  else
+    echo "ERROR: Local database file not found at $REPORTS_DB." >&2
+    echo "Please either:" >&2
+    echo "  1. Run ./scripts/pipeline.sh to extract and build from Postgres, or" >&2
+    echo "  2. Configure R2 credentials in .env and run: uv run python scripts/db_storage.py download" >&2
+    exit 1
+  fi
+fi
+
+echo "==> Starting Streamlit NBA Analytics Dashboard..."
+uv run --project "$REPO_ROOT" streamlit run "$REPO_ROOT/streamlit_app/app.py"

streamlit_app/.streamlit/config.toml

@@ -0,0 +1,8 @@
+[theme]
+primaryColor = "#3b82f6"
+backgroundColor = "#0e1117"
+secondaryBackgroundColor = "#1e293b"
+textColor = "#f8fafc"
+
+[server]
+maxUploadSize = 5

streamlit_app/requirements.txt

@@ -0,0 +1,4 @@
+streamlit>=1.55.0
+duckdb==1.3.0
+plotly==6.1.2
+streamlit-echarts>=0.4.0