first (part 2: other directories)

2026-04-16 15:11:25 +03:00
parent 7814e0bc6b
commit 2f0b85a0c7
203 changed files with 59989 additions and 0 deletions
@@ -0,0 +1,131 @@
+"""
+Expert Recommendation Engine (Senior Level)
+============================================
+Evaluates ALL markets, classifies by risk, and ensures NO "empty" recommendations.
+Prioritizes user safety by clearly labeling risk levels.
+"""
+
+from dataclasses import dataclass, field
+from typing import List, Optional, Any, Dict
+from .base_calculator import BaseCalculator, CalculationContext
+from .match_result_calculator import MatchResultPrediction
+from .over_under_calculator import OverUnderPrediction
+from .risk_assessor import RiskAnalysis
+
+
+@dataclass
+class ExpertPick:
+    market_type: str
+    pick: str
+    probability: float
+    confidence: float
+    odds: float
+    edge: float  # Expected value percentage
+    
+    # Risk Classification
+    risk_level: str  # SAFE, MEDIUM, RISKY, SURPRISE
+    reasoning: str   # Why this pick? (e.g., "High xG support", "Value detected")
+
+@dataclass
+class ExpertResult:
+    main_pick: ExpertPick
+    safe_alternative: Optional[ExpertPick]
+    value_picks: List[ExpertPick]
+    surprise_picks: List[ExpertPick]
+    market_summary: Dict[str, float] # {market: probability}
+
+
+class ExpertRecommender(BaseCalculator):
+    def calculate(self,
+                  ctx: CalculationContext,
+                  ms_res: MatchResultPrediction,
+                  ou_res: OverUnderPrediction,
+                  risk: RiskAnalysis) -> ExpertResult:
+
+        odds_data = ctx.odds_data
+        all_picks: List[ExpertPick] = []
+
+        # ─── 1. Helper to Evaluate Pick ───
+        def evaluate(market: str, pick: str, prob: float, odd_key: str):
+            odd_val = float(odds_data.get(odd_key, 0))
+            # If odd is missing/low, estimate it via probability (Kelly-ish estimation)
+            if odd_val <= 1.01:
+                odd_val = round(1.0 / (prob + 0.05), 2) # Conservative estimation
+                reasoning = "Derived (No market odd)"
+            else:
+                reasoning = "Market Confirmed"
+
+            implied = 1.0 / odd_val
+            edge = (prob - implied) * 100
+
+            # ─── Risk Classification ───
+            if prob >= 0.75 and odd_val <= 1.45:
+                level = "SAFE"
+            elif edge > 5.0:
+                level = "VALUE"
+            elif odd_val >= 2.50 and prob >= 0.35:
+                level = "SURPRISE"
+            else:
+                level = "MEDIUM"
+
+            all_picks.append(ExpertPick(
+                market_type=market, pick=pick, probability=prob,
+                confidence=prob * 100, odds=odd_val, edge=edge,
+                risk_level=level, reasoning=reasoning
+            ))
+
+        # ─── 2. Evaluate All Major Markets ───
+        # MS
+        evaluate("MS", ms_res.ms_pick, 
+                 ms_res.ms_home_prob if ms_res.ms_pick == "1" else (ms_res.ms_away_prob if ms_res.ms_pick == "2" else ms_res.ms_draw_prob),
+                 f"ms_{ms_res.ms_pick.lower()}")
+        
+        # Double Chance
+        evaluate("DC", ms_res.dc_pick,
+                 ms_res.dc_1x_prob if ms_res.dc_pick == "1X" else (ms_res.dc_x2_prob if ms_res.dc_pick == "X2" else ms_res.dc_12_prob),
+                 f"dc_{ms_res.dc_pick.lower()}")
+
+        # OU25
+        evaluate("OU25", ou_res.ou25_pick,
+                 ou_res.over_25_prob if "Üst" in ou_res.ou25_pick else ou_res.under_25_prob,
+                 "ou25_o" if "Üst" in ou_res.ou25_pick else "ou25_u")
+
+        # BTTS
+        evaluate("BTTS", ou_res.btts_pick,
+                 ou_res.btts_yes_prob if "Var" in ou_res.btts_pick else ou_res.btts_no_prob,
+                 "btts_y" if "Var" in ou_res.btts_pick else "btts_n")
+
+        # OU15
+        evaluate("OU15", ou_res.ou15_pick,
+                 ou_res.over_15_prob if "Üst" in ou_res.ou15_pick else ou_res.under_15_prob,
+                 "ou15_o" if "Üst" in ou_res.ou15_pick else "ou15_u")
+
+        # ─── 3. Sort and Select ───
+        # Sort by a mix of Confidence and Edge
+        all_picks.sort(key=lambda p: (p.probability * 0.6) + (max(0, p.edge/100) * 0.4), reverse=True)
+
+        main = all_picks[0]
+        
+        # Find Safe Alternative (if main isn't Safe)
+        safe_alt = next((p for p in all_picks if p.risk_level == "SAFE"), None)
+        if safe_alt == main: safe_alt = None
+
+        value_picks = [p for p in all_picks if p.risk_level == "VALUE" and p != main]
+        surprise_picks = [p for p in all_picks if p.risk_level == "SURPRISE"]
+
+        # Market Summary for UI
+        market_summary = {
+            "MS_Home": ms_res.ms_home_prob,
+            "MS_Draw": ms_res.ms_draw_prob,
+            "MS_Away": ms_res.ms_away_prob,
+            "OU25_Over": ou_res.over_25_prob,
+            "BTTS_Yes": ou_res.btts_yes_prob
+        }
+
+        return ExpertResult(
+            main_pick=main,
+            safe_alternative=safe_alt,
+            value_picks=value_picks,
+            surprise_picks=surprise_picks,
+            market_summary=market_summary
+        )