feat: Add recent performance stability stats (matches/days) to player profile

web/services/stats_service.py

@@ -632,6 +632,72 @@ class StatsService:
         """
         return query_db('l2', sql, [steam_id, limit])
 
+    @staticmethod
+    def get_recent_performance_stats(steam_id):
+        """
+        Calculates Avg Rating and Rating Variance for:
+        - Last 5, 10, 15 matches
+        - Last 5, 10, 15 days
+        """
+        import numpy as np
+        from datetime import datetime, timedelta
+
+        # Fetch all match ratings with timestamps
+        sql = """
+            SELECT m.start_time, mp.rating
+            FROM fact_match_players mp
+            JOIN fact_matches m ON mp.match_id = m.match_id
+            WHERE mp.steam_id_64 = ?
+            ORDER BY m.start_time DESC
+        """
+        rows = query_db('l2', sql, [steam_id])
+        
+        if not rows:
+            return {}
+
+        # Convert to list of dicts
+        matches = [{'time': r['start_time'], 'rating': r['rating'] or 0} for r in rows]
+        
+        stats = {}
+        
+        # 1. Recent N Matches
+        for n in [5, 10, 15]:
+            subset = matches[:n]
+            if not subset:
+                stats[f'last_{n}_matches'] = {'avg': 0, 'var': 0, 'count': 0}
+                continue
+                
+            ratings = [m['rating'] for m in subset]
+            stats[f'last_{n}_matches'] = {
+                'avg': np.mean(ratings),
+                'var': np.var(ratings),
+                'count': len(ratings)
+            }
+
+        # 2. Recent N Days
+        # Use server time or max match time? usually server time 'now' is fine if data is fresh.
+        # But if data is old, 'last 5 days' might be empty. 
+        # User asked for "recent 5/10/15 days", implying calendar days from now.
+        import time
+        now = time.time()
+        
+        for d in [5, 10, 15]:
+            cutoff = now - (d * 24 * 3600)
+            subset = [m for m in matches if m['time'] >= cutoff]
+            
+            if not subset:
+                stats[f'last_{d}_days'] = {'avg': 0, 'var': 0, 'count': 0}
+                continue
+                
+            ratings = [m['rating'] for m in subset]
+            stats[f'last_{d}_days'] = {
+                'avg': np.mean(ratings),
+                'var': np.var(ratings),
+                'count': len(ratings)
+            }
+            
+        return stats
+
     @staticmethod
     def get_roster_stats_distribution(target_steam_id):
         """