add files

fantasy.py

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+import pandas as pd
+import numpy as np  # Add numpy for generating random data
+from flask import Flask, render_template, request
+from sklearn.ensemble import RandomForestRegressor
+from sklearn.preprocessing import LabelEncoder
+import joblib
+
+app = Flask(__name__)
+
+# Load the preprocessed data
+data = pd.read_csv('static/players_data.csv', index_col='player')  # Set 'player' column as index
+
+# Prepare features and target
+X = data.select_dtypes(include=['float64', 'int64'])  # Only select numeric columns
+y_goals = data['goals']
+y_assists = data['assists']
+
+# Encode categorical variables
+label_encoder = LabelEncoder()
+X.index = label_encoder.fit_transform(X.index)
+
+# Train the models
+model_goals = RandomForestRegressor(n_estimators=100, random_state=42)
+model_goals.fit(X, y_goals)
+
+model_assists = RandomForestRegressor(n_estimators=100, random_state=42)
+model_assists.fit(X, y_assists)
+
+# Save the trained models
+joblib.dump(model_goals, 'goals_prediction_model.pkl')
+joblib.dump(model_assists, 'assists_prediction_model.pkl')
+joblib.dump(label_encoder, 'label_encoder.pkl')
+
+# Get all teams
+all_teams = sorted(data['team'].unique())
+
+def select_best_players(team):
+    # Filter the data for the selected team
+    team_data = data[data['team'] == team]
+
+    # Sort the players based on some criteria (e.g., goals or assists)
+    sorted_players = team_data.sort_values(by=['goals', 'assists'], ascending=False)
+
+    # Select the top 5 players and get their names
+    best_players = sorted_players.index[:5].tolist()
+
+    return best_players
+
+def predict_player_performance(player_stats, model_goals, model_assists):
+    # Ensure proper feature names
+    player_stats.columns = X.columns
+
+    # Make predictions
+    player_stats_values = player_stats.values.reshape(1, -1)  # Reshape the data for prediction
+    predicted_goals = int(model_goals.predict(player_stats_values)[0])
+    predicted_assists = int(model_assists.predict(player_stats_values)[0])
+
+    # Return all predicted stats
+    return predicted_goals, predicted_assists
+
+
+@app.route('/')
+def home():
+    return render_template('index2.html', teams=all_teams)
+
+@app.route('/select_players', methods=['POST'])
+def select_players():
+    team1 = request.form['team1']
+    team2 = request.form['team2']
+
+    best_players_team1 = select_best_players(team1)
+    best_players_team2 = select_best_players(team2)
+
+    return render_template('index2.html', team1=team1, team2=team2, teams=all_teams, best_players_team1=best_players_team1, best_players_team2=best_players_team2)
+
+@app.route('/predict_performance', methods=['POST'])
+def predict_performance():
+    team1 = request.form['team1']
+    team2 = request.form['team2']
+
+    best_players_team1 = select_best_players(team1)
+    best_players_team2 = select_best_players(team2)
+
+    # Load the trained models
+    model_goals = joblib.load('goals_prediction_model.pkl')
+    model_assists = joblib.load('assists_prediction_model.pkl')
+
+    # Generate random player statistics for prediction
+    random_player_stats = pd.DataFrame(np.random.randint(0, 10, size=(len(best_players_team1 + best_players_team2), len(X.columns))), columns=X.columns)
+
+    # Get predicted stats for each player
+    predicted_stats = {}
+    for player, stats in zip(best_players_team1 + best_players_team2, random_player_stats.iterrows()):
+        predicted_goals, predicted_assists = predict_player_performance(stats[1], model_goals, model_assists)
+        predicted_stats[player] = (predicted_goals, predicted_assists)
+
+    return render_template('index2.html', team1=team1, team2=team2, teams=all_teams,
+                           best_players_team1=best_players_team1, best_players_team2=best_players_team2,
+                           predicted_stats=predicted_stats)
+
+if __name__ == '__main__':
+    app.run(debug=True)

requirements.txt

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+gunicorn
+Flask
+pandas
+numpy
+scikit-learn
+joblib

templates/index2.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Fantasy Soccer</title>
+    <!-- <link rel="stylesheet" type="text/css" href="{{ url_for('static', filename='styles.css') }}"> -->
+    <style>
+        body {
+            font-family: Arial, sans-serif;
+            background-color: #f0f0f0;
+            margin: 0;
+            padding: 0;
+        }
+        .container {
+            max-width: 800px;
+            margin: 50px auto;
+            padding: 20px;
+            background-color: #fff;
+            border-radius: 5px;
+            box-shadow: 0 0 10px rgba(0, 0, 0, 0.1);
+        }
+        h1 {
+            text-align: center;
+            color: #333;
+        }
+        form {
+            margin-top: 20px;
+        }
+        .team-select {
+            margin-bottom: 20px;
+        }
+        label {
+            display: block;
+            font-weight: bold;
+            margin-bottom: 5px;
+        }
+        select {
+            width: 100%;
+            padding: 10px;
+            border-radius: 5px;
+            border: 1px solid #ccc;
+        }
+        input[type="submit"] {
+            width: 100%;
+            padding: 10px;
+            border-radius: 5px;
+            border: none;
+            background-color: #4CAF50;
+            color: white;
+            cursor: pointer;
+            font-size: 16px;
+        }
+        input[type="submit"]:hover {
+            background-color: #45a049;
+        }
+        ul {
+            list-style-type: none;
+            padding: 0;
+        }
+        li {
+            margin-bottom: 5px;
+        }
+        table {
+            width: 100%;
+            border-collapse: collapse;
+            margin-top: 20px;
+        }
+        th, td {
+            border: 1px solid #ddd;
+            padding: 8px;
+            text-align: left;
+        }
+        th {
+            background-color: #f2f2f2;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>Fantasy Soccer</h1>
+        <form action="/select_players" method="post">
+            <div class="team-select">
+                <label for="team1">Select Team 1:</label>
+                <select name="team1" id="team1">
+                    {% for team in teams %}
+                        <option value="{{ team }}">{{ team }}</option>
+                    {% endfor %}
+                </select>
+            </div>
+            <div class="team-select">
+                <label for="team2">Select Team 2:</label>
+                <select name="team2" id="team2">
+                    {% for team in teams %}
+                        <option value="{{ team }}">{{ team }}</option>
+                    {% endfor %}
+                </select>
+            </div>
+            <input type="submit" value="Select Players">
+        </form>
+        <!-- Display the selected teams and best players here -->
+        {% if team1 and team2 %}
+            <h2>Team 1: {{ team1 }}</h2>
+            <h3>Best Players:</h3>
+            <ul>
+                {% for player in best_players_team1 %}
+                    <li>{{ player.split('/')[1].split('/')[0].replace('-', ' ') }}</li>
+                {% endfor %}
+            </ul>
+            <h2>Team 2: {{ team2 }}</h2>
+            <h3>Best Players:</h3>
+            <ul>
+                {% for player in best_players_team2 %}
+                    <li>{{ player.split('/')[1].split('/')[0].replace('-', ' ') }}</li>
+                {% endfor %}
+            </ul>
+            <form action="/predict_performance" method="post">
+                <input type="hidden" name="team1" value="{{ team1 }}">
+                <input type="hidden" name="team2" value="{{ team2 }}">
+                <input type="submit" value="Predict Performance">
+            </form>
+        {% endif %}
+        <!-- Prediction results will be displayed here -->
+        {% if predicted_stats %}
+            <h2>Prediction Results</h2>
+            <table>
+                <tr>
+                    <th>Player</th>
+                    <th>Predicted Goals</th>
+                    <th>Predicted Assists</th>
+                </tr>
+                {% for player, stats in predicted_stats.items() %}
+                    <tr>
+                        <td>{{ player.split('/')[1].split('/')[0].replace('-', ' ') }}</td>
+                        <td>{{ stats[0] }}</td>
+                        <td>{{ stats[1] }}</td>
+                    </tr>
+                {% endfor %}
+            </table>
+        {% endif %}
+    </div>
+</body>
+</html>