Adding latest scores

app.py

@@ -25,7 +25,6 @@ def initialize_files():
         df.to_csv(PREDICTIONS_CSV, index=False)
 
 
-@st.cache_data
 def load_data(file_path):
     """
     Load data from a JSON or CSV file.
@@ -315,25 +314,7 @@ def save_users(users):
         json.dump(users, file, indent=4)
 
 
-def save_match_outcomes(new_outcome):
-    # First, try to load the existing outcomes
-    try:
-        with open(OUTCOMES_JSON, 'r') as file:
-            outcomes = json.load(file)
-    except (FileNotFoundError, json.JSONDecodeError):
-        outcomes = []  # If there's an issue loading, start with an empty list
-
-    # Check if the match_id already exists in outcomes
-    match_index = next((index for (index, d) in enumerate(outcomes) if d["match_id"] == new_outcome["match_id"]), None)
-    
-    if match_index is not None:
-        # If match_id exists, update the existing entry
-        outcomes[match_index] = new_outcome
-    else:
-        # If match_id does not exist, append the new outcome
-        outcomes.append(new_outcome)
-
-    # Finally, save the updated outcomes back to the file
+def save_match_outcomes(outcomes):
     with open(OUTCOMES_JSON, 'w') as file:
         json.dump(outcomes, file, indent=4)
 
@@ -343,42 +324,31 @@ def update_leaderboard_and_outcomes(match_id, winning_team, man_of_the_match):
     predictions = load_predictions(PREDICTIONS_CSV)  # Load existing predictions
     users = load_users(USERS_JSON)  # Load existing user points
 
-    # Update match outcomes
-    match_outcome = next((outcome for outcome in outcomes if outcome['match_id'] == match_id), None)
-    if match_outcome:
-        match_outcome['winning_team'] = winning_team
-        match_outcome['man_of_the_match'] = man_of_the_match
-    else:
-        outcomes.append({
-            "match_id": match_id,
-            "winning_team": winning_team,
-            "man_of_the_match": man_of_the_match
-        })
+    # Directly update or add the match outcome
+    outcome_exists = False
+    for outcome in outcomes:
+        if outcome['match_id'] == match_id:
+            outcome.update({"winning_team": winning_team, "man_of_the_match": man_of_the_match})
+            outcome_exists = True
+            break
+    if not outcome_exists:
+        outcomes.append({"match_id": match_id, "winning_team": winning_team, "man_of_the_match": man_of_the_match})
 
     # Update user points based on prediction accuracy
-    match_predictions = predictions[predictions['match_id'] == match_id]
-    for _, prediction in match_predictions.iterrows():
-        user_name = prediction['user_name']
-        # Initialize user points if not present
-        users[user_name] = users.get(user_name, 0)
-
-        # Points for correct or incorrect team prediction
-        if prediction['predicted_winner'] == winning_team:
-            users[user_name] += 1000  # Correct team prediction
-            # Check for double or nothing bid points
-            users[user_name] += prediction['bid_points'] * 2
-        else:
-            users[user_name] -= 200  # Deduct points for incorrect team prediction
-            users[user_name] -= prediction['bid_points']  # Lose bid points for incorrect prediction
+    for _, prediction in predictions.iterrows():
+        if prediction['match_id'] == match_id:
+            user_name = prediction['user_name']
+            users[user_name] = users.get(user_name, 0)  # Initialize user points if not present
 
-        # Points for correct man of the match prediction
-        if prediction['predicted_motm'] == man_of_the_match:
-            users[user_name] += 200  # Correct man of the match prediction
-            # Bonus for getting both right
+            # Update points based on prediction accuracy
             if prediction['predicted_winner'] == winning_team:
-                users[user_name] += 200
+                users[user_name] += 1000
+                users[user_name] += prediction['bid_points'] * 2
+                if prediction['predicted_motm'] == man_of_the_match:
+                    users[user_name] += 400  # Bonus for both correct predictions
+            else:
+                users[user_name] -= 200 + prediction['bid_points']  # Penalty for wrong team prediction
 
-    # Save updated outcomes and user points
     save_match_outcomes(outcomes)
     save_users(users)
 

match_outcomes.json

@@ -1,7 +1,27 @@
 [
+    {
+        "match_id": "20240322_1",
+        "winning_team": "CSK",
+        "man_of_the_match": "Mustafizur Rahman"
+    },
+    {
+        "match_id": "20240323_2",
+        "winning_team": "PBKS",
+        "man_of_the_match": "Sam Curran"
+    },
     {
         "match_id": "20240323_3",
         "winning_team": "KKR",
         "man_of_the_match": "Andre Russell"
+    },
+    {
+        "match_id": "20240324_4",
+        "winning_team": "RR",
+        "man_of_the_match": "Sanju Samson"
+    },
+    {
+        "match_id": "20240324_5",
+        "winning_team": "GT",
+        "man_of_the_match": "B Sai Sudharsan"
     }
 ]

predictions.csv

@@ -12,7 +12,7 @@ Kichu,20240322_1,CSK,MS Dhoni,500
 Haaris,20240322_1,CSK,MS Dhoni,500
 Rakesh,20240322_1,CSK,MS Dhoni,500
 Megha,20240323_2,DC,Rishabh Pant,200
-Arpit,20240323_2,DC,David Warner,496
+Arpit,20240323_2,DC,David Warner,500
 Sahil,20240323_2,DC,Mitchell Marsh,250
 Sai,20240323_2,DC,Rishabh Pant,200
 Neha,20240323_2,DC,Rishabh Pant,500

users.json

@@ -1,18 +1,17 @@
 {
-    "Archana": 5000,
-    "Arpit": 9704,
-    "Ganesh": 6050,
-    "Haaris": 6500,
-    "Jay": 7000,
-    "Kichu": 7000,
-    "Megha": 5300,
-    "Naveein": 7300,
-    "Neha": 5900,
-    "Praveen": 8000,
-    "Rakesh": 7000,
-    "Sai": 4100,
-    "Sahil": 7750,
+    "Arpit": 11300,
+    "Ganesh": 5750,
+    "Haaris": 6000,
+    "Jay": 6500,
+    "Kishore": 5700,
+    "Megha": 5900,
+    "Naveein": 6300,
+    "Neha": 5600,
+    "Praveen": 9000,
+    "Rakesh": 6500,
+    "Sai": 3100,
+    "Sahil": 6600,
     "Sunil": 4501,
-    "Vaibhav": 6600,
-    "Vinay": 5416
+    "Vaibhav": 5600,
+    "Vinay": 5300
 }