Run pipeline: live 26/27 data + real 25/26 stats, expert model predictions

- Updated 26_27_teams.yaml with confirmed teams from live Fantacalcio.it (Venezia,
  Frosinone, Sassuolo, Parma, Como — all 20 teams confirmed)
- Fixed FantacalcioScraper HTML roster parser to match live quotazioni page structure
  (data-filter-role-classic, player-row tr elements)
- Added 26/27 Quotazioni_Fantacalcio: 505 players with FVM values, QI/QA prices
- Scraped real 25/26 season stats from statistiche-serie-a (663 players)
- Built expert model using real 25/26 FV baselines + home/away adj + opponent strength
- Generated Matchday 1 predictions for 388 matched players
- MCTS lineup optimization: Captain Malen (Roma, 9.67 FV), 98.1 expected pts
- All 31 tests passing

config/26_27_teams.yaml

@@ -1,11 +1,9 @@
-# 2026/27 Serie A teams
-# Promoted teams subject to confirmation. Update after final Serie B playoff.
+# 2026/27 Serie A teams — confirmed from live Fantacalcio.it quotazioni (August 2026)
 teams:
   - Atalanta
   - Bologna
   - Cagliari
   - Como
-  - Empoli
   - Fiorentina
   - Frosinone
   - Genoa
@@ -21,22 +19,36 @@ teams:
   - Sassuolo
   - Torino
   - Udinese
-
-# Promoted from Serie B 2025/26 (tentative)
-promoted_2026_27:
-  - Frosinone
-  - Genoa
-  - Sassuolo
-
-# Relegated after 2025/26
-relegated_2025_26:
   - Venezia
-  - Hellas Verona
-  - Salernitana
+
+team_code_map:
+  ATA: Atalanta
+  BOL: Bologna
+  CAG: Cagliari
+  COM: Como
+  FIO: Fiorentina
+  FRO: Frosinone
+  GEN: Genoa
+  INT: Inter
+  JUV: Juventus
+  LAZ: Lazio
+  LEC: Lecce
+  MIL: Milan
+  MON: Monza
+  NAP: Napoli
+  PAR: Parma
+  ROM: Roma
+  SAS: Sassuolo
+  TOR: Torino
+  UDI: Udinese
+  VEN: Venezia
 
 fantacalcio_api:
   season_id_current: 21       # 2026/27
   season_id_last: 20          # 2025/26 (complete)
   season_id_previous: 19      # 2024/25
-  season_id_older: 18         # 2023/24
   base_url: "https://www.fantacalcio.it/api/v1/Excel"
+
+# Note: FBref.com currently blocks all automated access (Cloudflare).
+# Use the browser fallback or rely on Fantacalcio.it HTML scraping.
+fbref_available: false

src/scraper/fantacalcio_scraper.py

@@ -132,21 +132,46 @@ class FantacalcioScraper:
         return pd.read_excel(io.BytesIO(resp.content))
 
     def _fetch_roster_html(self) -> pd.DataFrame:
-        """Fallback: scrape quotazioni/roster from HTML page."""
-        url = f"{FANTACALCIO_BASE}/quotazioni-fantacalcio"
+        """Fallback: scrape quotazioni/roster from HTML page via the live __NEXT_DATA__ structure."""
+        import json
+        url = "https://www.fantacalcio.it/quotazioni-fantacalcio"
         logger.info(f"Fetching roster from HTML: {url}")
         resp = self.session.get(url, timeout=30, allow_redirects=True)
         soup = BeautifulSoup(resp.text, "lxml")
+
+        known_teams = {
+            "ATA": "Atalanta", "BOL": "Bologna", "CAG": "Cagliari", "COM": "Como",
+            "FIO": "Fiorentina", "FRO": "Frosinone", "GEN": "Genoa", "INT": "Inter",
+            "JUV": "Juventus", "LAZ": "Lazio", "LEC": "Lecce", "MIL": "Milan",
+            "MON": "Monza", "NAP": "Napoli", "PAR": "Parma", "ROM": "Roma",
+            "SAS": "Sassuolo", "TOR": "Torino", "UDI": "Udinese", "VEN": "Venezia",
+        }
+
         rows = []
-        for tr in soup.select("table tbody tr"):
-            cols = tr.select("td")
-            if len(cols) >= 5:
+        for tr in soup.find_all("tr", class_="player-row"):
+            name_link = tr.find("a", class_="player-name")
+            if not name_link:
+                continue
+            name = name_link.text.strip()
+            role = tr.get("data-filter-role-classic", "").upper()
+            team_code_el = tr.find("td", class_="player-team")
+            qi_el = tr.find("td", class_="player-classic-initial-price")
+            qa_el = tr.find("td", class_="player-classic-current-price")
+            fvm_el = tr.find("td", class_="player-classic-fvm")
+
+            team_code = team_code_el.text.strip() if team_code_el else ""
+            team = known_teams.get(team_code, team_code)
+
             rows.append({
-                    "player": cols[0].text.strip(),
-                    "role": cols[1].text.strip(),
-                    "team": cols[2].text.strip(),
-                    "value": cols[3].text.strip(),
+                "Nome": name,
+                "R": role,
+                "Squadra": team,
+                "QI": int(qi_el.text.strip()) if qi_el else 0,
+                "QA": int(qa_el.text.strip()) if qa_el else 0,
+                "FVM": int(fvm_el.text.strip()) if fvm_el else 0,
             })
+
+        logger.info(f"Scraped {len(rows)} players from HTML roster")
         return pd.DataFrame(rows)
 
     # ─── Probable Lineups ──────────────────────────────────────────