main

ai-engine/core/engines/odds_predictor.py

@@ -42,7 +42,7 @@ class OddsPrediction:
     third_likely_score: str = "2-1"
     
     # Value bet opportunities
-    value_bets: list = None
+    value_bets: Optional[list] = None
     
     confidence: float = 0.0
     
@@ -84,7 +84,7 @@ class OddsPredictorEngine:
         try:
             self.value_calc = get_value_calculator()
         except Exception:
-            self.value_calc = None
+            self.value_calc = None  # type: ignore[assignment]
         self.default_ms_h = 2.65
         self.default_ms_d = 3.20
         self.default_ms_a = 2.65

ai-engine/core/engines/player_predictor.py

@@ -72,9 +72,9 @@ class PlayerPredictorEngine:
                 match_id: str,
                 home_team_id: str,
                 away_team_id: str,
-                home_lineup: List[str] = None,
-                away_lineup: List[str] = None,
-                sidelined_data: Dict = None) -> PlayerPrediction:
+                home_lineup: Optional[List[str]] = None,
+                away_lineup: Optional[List[str]] = None,
+                sidelined_data: Optional[Dict] = None) -> PlayerPrediction:
         """
         Generate player-based prediction.
         
@@ -134,10 +134,10 @@ class PlayerPredictorEngine:
             lineup_available = False
         
         # Extract features
-        home_goals = features.get("home_goals_last_5", 0)
-        away_goals = features.get("away_goals_last_5", 0)
-        home_key = features.get("home_key_players", 0)
-        away_key = features.get("away_key_players", 0)
+        home_goals = int(features.get("home_goals_last_5", 0))
+        away_goals = int(features.get("away_goals_last_5", 0))
+        home_key = int(features.get("home_key_players", 0))
+        away_key = int(features.get("away_key_players", 0))
         home_assists = features.get("home_assists_last_5", 0)
         away_assists = features.get("away_assists_last_5", 0)
         home_starting = features.get("home_starting_11", 11)
@@ -171,8 +171,8 @@ class PlayerPredictorEngine:
         # Priority: sidelined data (position-weighted) > lineup count (basic)
         if sidelined_data:
             home_impact, away_impact = self.sidelined_analyzer.analyze_match(sidelined_data)
-            home_missing = home_impact.impact_score
-            away_missing = away_impact.impact_score
+            home_missing = min(1.0, max(0.0, home_impact.impact_score))
+            away_missing = min(1.0, max(0.0, away_impact.impact_score))
             sidelined_available = True
         else:
             # Fallback: basic lineup count method
@@ -241,7 +241,7 @@ if __name__ == "__main__":
     print("=" * 50)
     
     pred = engine.predict(
-        match_id=None,
+        match_id="test_match",
         home_team_id="test_home",
         away_team_id="test_away"
     )

ai-engine/core/engines/referee_predictor.py

@@ -78,9 +78,9 @@ class RefereePredictorEngine:
         print("✅ RefereePredictorEngine initialized")
     
     def predict(self,
-                match_id: str = None,
-                referee_name: str = None,
-                league_id: str = None) -> RefereePrediction:
+                match_id: Optional[str] = None,
+                referee_name: Optional[str] = None,
+                league_id: Optional[str] = None) -> RefereePrediction:
         """
         Generate referee-based prediction.
         
@@ -95,21 +95,21 @@ class RefereePredictorEngine:
         
         # Get referee features
         if match_id:
-            features = self.referee_engine.get_features(match_id, league_id=league_id)
+            features = self.referee_engine.get_features(match_id, league_id=league_id or "")
             # Live flows may already have referee_name while match_officials table is sparse.
             # Prefer the richer profile if direct-name lookup has more history.
             if referee_name:
-                name_features = self.referee_engine.get_features_by_name(referee_name, league_id=league_id)
+                name_features = self.referee_engine.get_features_by_name(referee_name, league_id=league_id or "")
                 if (name_features.get("referee_matches", 0) or 0) > (features.get("referee_matches", 0) or 0):
                     features = name_features
         elif referee_name:
-            features = self.referee_engine.get_features_by_name(referee_name, league_id=league_id)
+            features = self.referee_engine.get_features_by_name(referee_name, league_id=league_id or "")
         else:
             # Return default
             return RefereePrediction(confidence=10.0)
         
-        ref_name = features.get("referee_name", "Unknown")
-        matches = features.get("referee_matches", 0)
+        ref_name = str(features.get("referee_name", "Unknown"))
+        matches = int(features.get("referee_matches", 0))
         
         if matches < 5:
             # Not enough data