enhanced

src/player_table.py

@@ -1,20 +1,25 @@
-from constants import PLAYER_NAME_COLUMNS
+from constants import PLAYER_NAME_COLUMNS, ordinal
 
 
 def generate_player_table(df):
-    header = [["Name", "Appearances", "Spent"]]
+    header = [["Player", "Appearances", "Avg. Relative Percentile", "Spent"]]
+
+    player_stats = []
+    for name in PLAYER_NAME_COLUMNS:
+        if name in df.columns:
+            attended = df[df[name] == 1]
+            n = len(attended)
+            if n > 0:
+                avg_rel = attended["Relative Position"].mean()
+                player_stats.append((name, n, avg_rel))
 
-    player_stats = [
-        (name, df[name].sum())
-        for name in df.columns
-        if name in PLAYER_NAME_COLUMNS
-    ]
     player_stats.sort(key=lambda x: x[1], reverse=True)
-    total = sum(n for name, n in player_stats)
-    body = [
-        [name, n, f"£{n * 3:.2f}"]
-        for name, n in player_stats
-    ]
-    footer = [["Total", total, f"£{total * 3:.2f}"]]
+    total = sum(n for _, n, _ in player_stats)
 
-    return (header + body + footer)
+    body = [
+        [name, n, ordinal(round(avg_rel * 100)), f"£{n * 3:.2f}"]
+        for name, n, avg_rel in player_stats
+    ]
+    footer = [["Total", total, "—", f"£{total * 3:.2f}"]]
+
+    return header + body + footer