feat: Feature 1.2 (NBA stats FastAPI service) + Feature 1.4 (database schema)

Feature 1.2: Python FastAPI microservice wrapping nba_api
- GET /stats/season-avg, /stats/last-n, /stats/splits, /players/search
- Redis caching (24hr/1hr/6hr/7day), 0.6s rate limiting, PRA derived stat
- 27 Python tests passing

Feature 1.4: Complete Supabase database schema
- 6 tables: users, picks, scan_sessions, bets, outcomes, performance
- RLS enabled on all tables with auth.uid() policies
- 3 triggers: auto-create user, updated_at, scan count reset
- 37 schema validation tests passing
- Migration SQL ready, pending manual apply (WSL2 DNS blocker)

Total: 92 tests (65 Node.js + 27 Python), all passing

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

nba-service/app/utils/player_map.py

@@ -0,0 +1,50 @@
+from nba_api.stats.static import players
+from app.utils.cache import cache_get, cache_set
+from app.config import PLAYER_SEARCH_TTL
+
+
+def normalize_name(name):
+    return name.strip().lower()
+
+
+def search_players(name):
+    cache_key = f"nba:player:{normalize_name(name)}"
+    cached = cache_get(cache_key)
+    if cached is not None:
+        return cached
+
+    all_players = players.get_players()
+    search_lower = normalize_name(name)
+
+    matches = []
+    for p in all_players:
+        full_name = p["full_name"].lower()
+        if search_lower in full_name:
+            matches.append({
+                "player_id": p["id"],
+                "full_name": p["full_name"],
+                "is_active": p["is_active"],
+            })
+
+    cache_set(cache_key, matches, PLAYER_SEARCH_TTL)
+    return matches
+
+
+def resolve_player(name):
+    """Resolve a player name to a single active player. Returns (player_id, full_name) or raises."""
+    matches = search_players(name)
+    active = [m for m in matches if m["is_active"]]
+
+    if not active:
+        if matches:
+            # Return first inactive match as fallback
+            return matches[0]["player_id"], matches[0]["full_name"]
+        return None, None
+
+    # Prefer exact match
+    search_lower = normalize_name(name)
+    for m in active:
+        if m["full_name"].lower() == search_lower:
+            return m["player_id"], m["full_name"]
+
+    return active[0]["player_id"], active[0]["full_name"]