369 lines
13 KiB
Python
Executable File
369 lines
13 KiB
Python
Executable File
"""
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Referee Engine - V9 Feature
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Hakem profilleri ve maç etki analizi.
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Analiz Edilen Metrikler:
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- Ortalama kart sayısı (sarı/kırmızı)
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- Penaltı verme eğilimi
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- Ev sahibi lehine karar oranı
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- Maç başına toplam gol ortalaması
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"""
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import os
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from typing import Dict, Optional, List
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from dataclasses import dataclass, field
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from datetime import datetime
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try:
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import psycopg2
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from psycopg2.extras import RealDictCursor
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except ImportError:
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psycopg2 = None
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@dataclass
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class RefereeProfile:
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"""Hakem profili"""
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referee_name: str
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matches_count: int = 0
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# Kart istatistikleri
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avg_yellow_cards: float = 0.0
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avg_red_cards: float = 0.0
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total_cards_per_match: float = 0.0
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# Penaltı istatistikleri
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penalty_rate: float = 0.0 # Penaltı verdiği maç oranı
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# Ev sahibi eğilimi
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home_win_rate: float = 0.0
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home_bias: float = 0.0 # -1 (away bias) to +1 (home bias)
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# Gol istatistikleri
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avg_goals_per_match: float = 0.0
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over_25_rate: float = 0.0
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@dataclass
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class RefereeFeatures:
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"""Model için hakem feature'ları"""
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referee_name: str = ""
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referee_matches: int = 0
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referee_avg_yellow: float = 0.0
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referee_avg_red: float = 0.0
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referee_cards_total: float = 0.0
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referee_penalty_rate: float = 0.0
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referee_home_bias: float = 0.0
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referee_avg_goals: float = 0.0
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referee_over25_rate: float = 0.0
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referee_experience: float = 0.0 # 0-1 normalized
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def to_dict(self) -> Dict[str, float]:
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return {
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'referee_matches': float(self.referee_matches),
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'referee_avg_yellow': self.referee_avg_yellow,
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'referee_avg_red': self.referee_avg_red,
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'referee_cards_total': self.referee_cards_total,
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'referee_penalty_rate': self.referee_penalty_rate,
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'referee_home_bias': self.referee_home_bias,
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'referee_avg_goals': self.referee_avg_goals,
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'referee_over25_rate': self.referee_over25_rate,
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'referee_experience': self.referee_experience,
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}
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class RefereeEngine:
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"""
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Hakem analiz motoru.
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Hakemlerin geçmiş maçlarını analiz ederek:
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- Kart eğilimlerini
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- Ev sahibi bias'ını
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- Gol ortalamasını
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hesaplar.
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"""
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# Ana hakem rolü ID'si (genellikle 1 veya "Hakem")
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MAIN_REFEREE_ROLE_ID = 1
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def __init__(self):
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self.conn = None
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self._referee_cache: Dict[str, RefereeProfile] = {}
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self._cache_loaded = False
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def _connect_db(self):
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if psycopg2 is None:
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return None
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try:
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from data.db import get_clean_dsn
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self.conn = psycopg2.connect(get_clean_dsn())
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return self.conn
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except Exception as e:
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print(f"[RefereeEngine] DB connection failed: {e}")
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return None
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def get_conn(self):
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if self.conn is None or self.conn.closed:
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self._connect_db()
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return self.conn
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def _get_main_referee_role_id(self) -> int:
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"""Ana hakem rolü ID'sini bul"""
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conn = self.get_conn()
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if conn is None:
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return self.MAIN_REFEREE_ROLE_ID
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try:
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with conn.cursor() as cur:
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cur.execute("""
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SELECT id FROM official_roles
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WHERE LOWER(name) LIKE '%%hakem%%'
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AND LOWER(name) NOT LIKE '%%yardımcı%%'
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AND LOWER(name) NOT LIKE '%%dördüncü%%'
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LIMIT 1
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""")
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result = cur.fetchone()
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if result:
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return result[0]
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except Exception:
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pass
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return self.MAIN_REFEREE_ROLE_ID
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def get_referee_for_match(self, match_id: str) -> Optional[str]:
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"""Maçın ana hakemini bul"""
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conn = self.get_conn()
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if conn is None:
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return None
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try:
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main_role_id = self._get_main_referee_role_id()
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with conn.cursor() as cur:
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cur.execute("""
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SELECT name FROM match_officials
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WHERE match_id = %s AND role_id = %s
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LIMIT 1
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""", (match_id, main_role_id))
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result = cur.fetchone()
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return result[0] if result else None
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except Exception as e:
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print(f"[RefereeEngine] Error getting referee: {e}")
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return None
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def calculate_referee_profile(self, referee_name: str, league_id: str = None) -> RefereeProfile:
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"""Hakemin maçlarını analiz et. league_id verilirse sadece o ligteki maçları kullanır."""
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# Composite cache key — aynı isim farklı liglerde farklı profil
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cache_key = (referee_name, league_id)
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if cache_key in self._referee_cache:
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return self._referee_cache[cache_key]
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profile = RefereeProfile(referee_name=referee_name)
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conn = self.get_conn()
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if conn is None:
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return profile
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try:
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main_role_id = self._get_main_referee_role_id()
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with conn.cursor(cursor_factory=RealDictCursor) as cur:
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# Bu hakemin yönettiği maçları al (league_id varsa sadece o lig)
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if league_id:
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cur.execute("""
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SELECT m.id, m.score_home, m.score_away, m.home_team_id, m.away_team_id
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FROM matches m
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JOIN match_officials mo ON m.id = mo.match_id
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WHERE mo.name = %s
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AND mo.role_id = %s
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AND m.league_id = %s
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AND m.score_home IS NOT NULL
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AND m.score_away IS NOT NULL
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ORDER BY m.mst_utc DESC
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LIMIT 100
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""", (referee_name, main_role_id, league_id))
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else:
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cur.execute("""
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SELECT m.id, m.score_home, m.score_away, m.home_team_id, m.away_team_id
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FROM matches m
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JOIN match_officials mo ON m.id = mo.match_id
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WHERE mo.name = %s
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AND mo.role_id = %s
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AND m.score_home IS NOT NULL
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AND m.score_away IS NOT NULL
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ORDER BY m.mst_utc DESC
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LIMIT 100
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""", (referee_name, main_role_id))
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matches = cur.fetchall()
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profile.matches_count = len(matches)
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if profile.matches_count == 0:
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return profile
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match_ids = [m['id'] for m in matches]
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# Kart istatistikleri
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cur.execute("""
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SELECT
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COUNT(*) FILTER (WHERE event_subtype ILIKE '%%yellow%%') as yellow_count,
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COUNT(*) FILTER (WHERE event_subtype ILIKE '%%red%%' OR event_subtype ILIKE '%%second%%') as red_count
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FROM match_player_events
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WHERE match_id = ANY(%s) AND event_type = 'card'
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""", (match_ids,))
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card_stats = cur.fetchone()
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if card_stats:
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profile.avg_yellow_cards = (card_stats['yellow_count'] or 0) / profile.matches_count
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profile.avg_red_cards = (card_stats['red_count'] or 0) / profile.matches_count
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profile.total_cards_per_match = profile.avg_yellow_cards + profile.avg_red_cards
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# Penaltı istatistikleri
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cur.execute("""
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SELECT COUNT(DISTINCT match_id) as penalty_matches
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FROM match_player_events
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WHERE match_id = ANY(%s)
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AND event_type = 'goal'
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AND event_subtype ILIKE '%%penaltı%%'
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""", (match_ids,))
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penalty_stats = cur.fetchone()
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if penalty_stats:
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profile.penalty_rate = (penalty_stats['penalty_matches'] or 0) / profile.matches_count
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# Ev sahibi eğilimi ve gol ortalaması
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home_wins = 0
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away_wins = 0
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draws = 0
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total_goals = 0
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over_25_count = 0
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for m in matches:
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goals = (m['score_home'] or 0) + (m['score_away'] or 0)
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total_goals += goals
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if goals > 2.5:
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over_25_count += 1
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if m['score_home'] > m['score_away']:
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home_wins += 1
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elif m['score_home'] < m['score_away']:
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away_wins += 1
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else:
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draws += 1
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profile.avg_goals_per_match = total_goals / profile.matches_count
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profile.over_25_rate = over_25_count / profile.matches_count
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profile.home_win_rate = home_wins / profile.matches_count
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# Home bias: -1 (away favors) to +1 (home favors)
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# Normal lig ortalaması ~%46 ev sahibi, buna göre normalize
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expected_home_rate = 0.46
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profile.home_bias = (profile.home_win_rate - expected_home_rate) * 2
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profile.home_bias = max(-1, min(1, profile.home_bias))
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# Cache'e ekle
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self._referee_cache[cache_key] = profile
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return profile
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except Exception as e:
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print(f"[RefereeEngine] Error calculating profile: {e}")
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return profile
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def get_features(self, match_id: str, league_id: str = None) -> Dict[str, float]:
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"""
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Maç için hakem feature'larını hesapla.
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Args:
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match_id: Maç ID'si
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league_id: Lig ID'si (opsiyonel — isim çakışmalarını önlemek için)
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Returns:
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Hakem feature'ları dict olarak
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"""
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features = RefereeFeatures()
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# Hakemi bul
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referee_name = self.get_referee_for_match(match_id)
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if referee_name is None:
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return features.to_dict()
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features.referee_name = referee_name
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# Profili hesapla (league_id ile scope'lanmış)
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profile = self.calculate_referee_profile(referee_name, league_id=league_id)
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features.referee_matches = profile.matches_count
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features.referee_avg_yellow = profile.avg_yellow_cards
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features.referee_avg_red = profile.avg_red_cards
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features.referee_cards_total = profile.total_cards_per_match
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features.referee_penalty_rate = profile.penalty_rate
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features.referee_home_bias = profile.home_bias
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features.referee_avg_goals = profile.avg_goals_per_match
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features.referee_over25_rate = profile.over_25_rate
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# Deneyim: 50+ maç = 1.0, 0 maç = 0.0
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features.referee_experience = min(profile.matches_count / 50, 1.0)
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return features.to_dict()
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def get_features_by_name(self, referee_name: str, league_id: str = None) -> Dict[str, float]:
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"""
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Hakem ismiyle feature'ları hesapla.
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Args:
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referee_name: Hakem ismi
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league_id: Lig ID'si (opsiyonel — isim çakışmalarını önlemek için)
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Returns:
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Hakem feature'ları dict olarak
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"""
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features = RefereeFeatures()
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if not referee_name:
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return features.to_dict()
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features.referee_name = referee_name
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profile = self.calculate_referee_profile(referee_name, league_id=league_id)
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features.referee_matches = profile.matches_count
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features.referee_avg_yellow = profile.avg_yellow_cards
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features.referee_avg_red = profile.avg_red_cards
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features.referee_cards_total = profile.total_cards_per_match
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features.referee_penalty_rate = profile.penalty_rate
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features.referee_home_bias = profile.home_bias
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features.referee_avg_goals = profile.avg_goals_per_match
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features.referee_over25_rate = profile.over_25_rate
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features.referee_experience = min(profile.matches_count / 50, 1.0)
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return features.to_dict()
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# Singleton instance
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_engine: Optional[RefereeEngine] = None
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def get_referee_engine() -> RefereeEngine:
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"""Singleton referee engine instance döndür"""
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global _engine
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if _engine is None:
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_engine = RefereeEngine()
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return _engine
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if __name__ == "__main__":
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# Test
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engine = get_referee_engine()
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print("\n🧪 Referee Engine Test")
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print("=" * 50)
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# Test with a known referee name
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test_referee = "Cüneyt Çakır"
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features = engine.get_features_by_name(test_referee)
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print(f"\n📊 Hakem: {test_referee}")
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for key, value in features.items():
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print(f" {key}: {value:.3f}")
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