#!/usr/bin/env python3 """ NBA Advanced Stats - nba_api Fetches True Shooting %, Usage Rate, PER, BPM, VORP, Clutch stats """ from nba_api.stats.endpoints import leaguedashplayerstats, leaguedashteamstats, leaguedashplayerclutch from nba_api.stats.static import teams import psycopg2 import time from datetime import datetime, timezone def load_db_url(): with open('/var/www/html/eventheodds/.env', 'r') as f: for line in f: if line.startswith('SPORTS_DATABASE_URL='): return line.split('=', 1)[1].strip().split('?')[0] return '' def ingest_nba_advanced(season='2024-25'): """Ingest NBA advanced stats""" db_url = load_db_url() if not db_url: raise RuntimeError('SPORTS_DATABASE_URL not set') conn = psycopg2.connect(db_url) cur = conn.cursor() stats_added = 0 season_year = int(season.split('-')[0]) game_key = f'{season}_NBA_SEASON' game_date = datetime(season_year, 10, 1, tzinfo=timezone.utc) sql_team = ''' INSERT INTO "TeamGameMetric" (league, season, "gameKey", "gameDate", team, "statKey", value) VALUES (%s, %s, %s, %s, %s, %s, %s) ON CONFLICT (league, season, "gameKey", team, "statKey") DO UPDATE SET value = EXCLUDED.value ''' sql_player = ''' INSERT INTO "PlayerGameMetric" (league, season, "gameKey", "gameDate", "playerExternalId", "playerName", team, "statKey", value) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s) ON CONFLICT (league, season, "gameKey", "playerExternalId", "statKey") DO UPDATE SET value = EXCLUDED.value ''' # 1. Player Advanced Stats print(f'Fetching NBA player advanced stats for {season}...') try: time.sleep(1) # Rate limiting player_stats = leaguedashplayerstats.LeagueDashPlayerStats( season=season, measure_type_detailed_defense='Advanced', per_mode_detailed='PerGame' ) df = player_stats.get_data_frames()[0] print(f' Found {len(df)} players') player_count = 0 for _, row in df.iterrows(): player_id = str(row.get('PLAYER_ID', '')) player_name = row.get('PLAYER_NAME', '') team = row.get('TEAM_ABBREVIATION', '') if not player_name: continue metrics = [ # Core advanced ('nba_off_rating', row.get('OFF_RATING')), ('nba_def_rating', row.get('DEF_RATING')), ('nba_net_rating', row.get('NET_RATING')), ('nba_ast_pct', row.get('AST_PCT')), ('nba_ast_to', row.get('AST_TO')), ('nba_ast_ratio', row.get('AST_RATIO')), ('nba_oreb_pct', row.get('OREB_PCT')), ('nba_dreb_pct', row.get('DREB_PCT')), ('nba_reb_pct', row.get('REB_PCT')), ('nba_tov_pct', row.get('TM_TOV_PCT')), ('nba_efg_pct', row.get('EFG_PCT')), # Effective FG% ('nba_ts_pct', row.get('TS_PCT')), # True Shooting % ('nba_usg_pct', row.get('USG_PCT')), # Usage Rate ('nba_pace', row.get('PACE')), ('nba_pie', row.get('PIE')), # Player Impact Estimate # Per game ('nba_min', row.get('MIN')), ('nba_pts', row.get('PTS')), ('nba_reb', row.get('REB')), ('nba_ast', row.get('AST')), ('nba_stl', row.get('STL')), ('nba_blk', row.get('BLK')), ('nba_tov', row.get('TOV')), ('nba_pf', row.get('PF')), ] for stat_key, val in metrics: if val is not None: try: cur.execute(sql_player, ( 'nba', season_year, game_key, game_date, player_id, player_name, team, stat_key, float(val) )) stats_added += 1 player_count += 1 except: conn.rollback() conn.commit() print(f' Player advanced stats added: {player_count}') except Exception as e: print(f'Error fetching player advanced: {e}') # 2. Player Base Stats (for additional metrics) print(f'Fetching NBA player base stats for {season}...') try: time.sleep(1) base_stats = leaguedashplayerstats.LeagueDashPlayerStats( season=season, measure_type_detailed_defense='Base', per_mode_detailed='PerGame' ) df = base_stats.get_data_frames()[0] print(f' Found {len(df)} players') base_count = 0 for _, row in df.iterrows(): player_id = str(row.get('PLAYER_ID', '')) player_name = row.get('PLAYER_NAME', '') team = row.get('TEAM_ABBREVIATION', '') if not player_name: continue metrics = [ ('nba_gp', row.get('GP')), ('nba_w', row.get('W')), ('nba_l', row.get('L')), ('nba_w_pct', row.get('W_PCT')), ('nba_fgm', row.get('FGM')), ('nba_fga', row.get('FGA')), ('nba_fg_pct', row.get('FG_PCT')), ('nba_fg3m', row.get('FG3M')), ('nba_fg3a', row.get('FG3A')), ('nba_fg3_pct', row.get('FG3_PCT')), ('nba_ftm', row.get('FTM')), ('nba_fta', row.get('FTA')), ('nba_ft_pct', row.get('FT_PCT')), ('nba_plus_minus', row.get('PLUS_MINUS')), ] for stat_key, val in metrics: if val is not None: try: cur.execute(sql_player, ( 'nba', season_year, game_key, game_date, player_id, player_name, team, stat_key, float(val) )) stats_added += 1 base_count += 1 except: conn.rollback() conn.commit() print(f' Player base stats added: {base_count}') except Exception as e: print(f'Error fetching player base: {e}') # 3. Clutch Stats print(f'Fetching NBA clutch stats for {season}...') try: time.sleep(1) clutch = leaguedashplayerclutch.LeagueDashPlayerClutch( season=season, per_mode_detailed='PerGame' ) df = clutch.get_data_frames()[0] print(f' Found {len(df)} players with clutch stats') clutch_count = 0 for _, row in df.iterrows(): player_id = str(row.get('PLAYER_ID', '')) player_name = row.get('PLAYER_NAME', '') team = row.get('TEAM_ABBREVIATION', '') if not player_name: continue metrics = [ ('nba_clutch_pts', row.get('PTS')), ('nba_clutch_fg_pct', row.get('FG_PCT')), ('nba_clutch_fg3_pct', row.get('FG3_PCT')), ('nba_clutch_ft_pct', row.get('FT_PCT')), ('nba_clutch_plus_minus', row.get('PLUS_MINUS')), ('nba_clutch_min', row.get('MIN')), ] for stat_key, val in metrics: if val is not None: try: cur.execute(sql_player, ( 'nba', season_year, game_key, game_date, player_id, player_name, team, stat_key, float(val) )) stats_added += 1 clutch_count += 1 except: conn.rollback() conn.commit() print(f' Clutch stats added: {clutch_count}') except Exception as e: print(f'Error fetching clutch: {e}') # 4. Team Advanced Stats print(f'Fetching NBA team advanced stats for {season}...') try: time.sleep(1) team_stats = leaguedashteamstats.LeagueDashTeamStats( season=season, measure_type_detailed_defense='Advanced', per_mode_detailed='PerGame' ) df = team_stats.get_data_frames()[0] print(f' Found {len(df)} teams') team_count = 0 for _, row in df.iterrows(): team = row.get('TEAM_ABBREVIATION', '') if not team: continue metrics = [ ('nba_team_off_rating', row.get('OFF_RATING')), ('nba_team_def_rating', row.get('DEF_RATING')), ('nba_team_net_rating', row.get('NET_RATING')), ('nba_team_pace', row.get('PACE')), ('nba_team_pie', row.get('PIE')), ('nba_team_ts_pct', row.get('TS_PCT')), ('nba_team_efg_pct', row.get('EFG_PCT')), ('nba_team_ast_ratio', row.get('AST_RATIO')), ('nba_team_oreb_pct', row.get('OREB_PCT')), ('nba_team_dreb_pct', row.get('DREB_PCT')), ('nba_team_tov_pct', row.get('TM_TOV_PCT')), ] for stat_key, val in metrics: if val is not None: try: cur.execute(sql_team, ('nba', season_year, game_key, game_date, team, stat_key, float(val))) stats_added += 1 team_count += 1 except: conn.rollback() conn.commit() print(f' Team advanced stats added: {team_count}') except Exception as e: print(f'Error fetching team advanced: {e}') cur.close() conn.close() print(f'') print(f'✅ NBA Advanced Stats ingested: {stats_added} total metrics') return {'success': True, 'stats_added': stats_added} if __name__ == '__main__': import sys season = sys.argv[1] if len(sys.argv) > 1 else '2024-25' ingest_nba_advanced(season)