Season-long projections + 4-3-3 formation default

- 505 players projected across all 38 matchdays (opponent-adjusted, home/away, fatigue)
- Season FV rankings: Douvikas 254, Paz N. 254, Dimarco 251, Martinez L. 245
- 4-3-3 Best XI (league): 2851 FV total with captain Douvikas
- 4-3-3 from Al-Cihred squad: 2562 FV (90% efficiency)
- Dashboard Matchday page: season projection rankings table + 4-3-3 XI
- Dashboard Lineup page: default formation changed to 4-3-3
- Per-matchday granular projections saved
- All 49 tests passing

dashboard/pages/01_matchday.py

@@ -1,17 +1,24 @@
 import sys; from pathlib import Path; _p = Path(__file__).resolve().parent.parent.parent; str(_p) not in sys.path and sys.path.insert(0, str(_p))
 """Page 1 — Matchday Control Room.
 
-KPI row, fixture difficulty heatmap, start/sit table, bump chart.
+KPI row, fixture difficulty heatmap, start/sit table, season-long projections.
 """
 
 import numpy as np
 import pandas as pd
 import streamlit as st
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
 
 from dashboard.warehouse import load_predictions, load_fixtures, load_players, load_lineups, load_votes
 from dashboard.viz.components import inject_css, kpi_card, section, insight, role_chip
 from dashboard.viz.charts import fixture_heatmap, kpi_sparkline, error_violins
-from dashboard.viz.template import PITCH_GREEN, GOLD, RED, SKY, VIOLET, WHITE, TEXT_SECONDARY, ROLE_COLORS, ROLE_ICONS, FANTABETO_TEMPLATE
+from dashboard.viz.template import (
+    PITCH_GREEN, GOLD, RED, SKY, VIOLET, WHITE, TEXT_SECONDARY,
+    ROLE_COLORS, ROLE_ICONS, FANTABETO_TEMPLATE
+)
+
+SEASON_PROJECTIONS = Path(__file__).resolve().parent.parent.parent / "data" / "season_projections_26_27.xlsx"
 
 
 @st.cache_data(ttl=3600)
@@ -168,6 +175,47 @@ def run():
     )
     st.plotly_chart(fig, width="stretch")
 
+    # ── Season Projections ─────────────────────────────────────────────
+    st.divider()
+    section("📅 Season-Long Projections", "4-3-3 starting XI + full season FV rankings.")
+
+    if SEASON_PROJECTIONS.exists():
+        season = pd.read_excel(SEASON_PROJECTIONS)
+
+        # 4-3-3 Best XI
+        s_gk = season[season['role'] == 'P'].nlargest(1, 'total_season_fv')
+        s_def = season[season['role'] == 'D'].nlargest(4, 'total_season_fv')
+        s_mid = season[season['role'] == 'C'].nlargest(3, 'total_season_fv')
+        s_fwd = season[season['role'] == 'A'].nlargest(3, 'total_season_fv')
+        stotal = s_gk['total_season_fv'].sum() + s_def['total_season_fv'].sum() + \
+                 s_mid['total_season_fv'].sum() + s_fwd['total_season_fv'].sum()
+        captain_iron = s_fwd.iloc[0]
+
+        c_season, c_table = st.columns([1, 2])
+        with c_season:
+            st.markdown("**4-3-3 Projected XI (Season)**", unsafe_allow_html=False)
+            st.markdown(f"🧤 {s_gk.iloc[0]['player']} ({s_gk.iloc[0]['team']}) — {s_gk.iloc[0]['total_season_fv']:.0f} FV")
+            for _, d in s_def.iterrows():
+                st.markdown(f"🛡 {d['player']} ({d['team']}) — {d['total_season_fv']:.0f} FV")
+            for _, m in s_mid.iterrows():
+                st.markdown(f"⚙ {m['player']} ({m['team']}) — {m['total_season_fv']:.0f} FV")
+            for _, f in s_fwd.iterrows():
+                st.markdown(f"⚡ {f['player']} ({f['team']}) — {f['total_season_fv']:.0f} FV")
+            st.markdown(f"⭐ Captain: **{captain_iron['player']}** → {stotal + captain_iron['total_season_fv']:.0f} FV")
+            insight(f"Projected season total: {stotal:.0f} FV ({stotal + captain_iron['total_season_fv']:.0f} with captain)")
+
+        with c_table:
+            show = season.nlargest(25, 'total_season_fv')[
+                ['player', 'role', 'team', 'projected_games', 'avg_fv_per_game', 'total_season_fv']
+            ].copy()
+            show.columns = ['Player', 'Role', 'Team', 'Games', 'Avg FV/g', 'Season FV']
+            show['Season FV'] = show['Season FV'].astype(float).round(0).astype(int)
+            show['Avg FV/g'] = show['Avg FV/g'].astype(float).round(2)
+            st.dataframe(show, use_container_width=True, hide_index=True)
+            insight("Season-long FV projections based on 25/26 performance, opponent difficulty, home/away, and fatigue.")
+    else:
+        st.info("Season projections not yet generated. Run the season projector to populate.")
+
 
 if __name__ == "__main__":
     run()