predict_cli.py

import pandas as pd
import os
from predict_match import predict_match

def get_available_teams():
    """Return a list of available teams"""
    try:
        team_venue_stats = pd.read_csv('data/processed/team_venue_stats.csv')
        return sorted(team_venue_stats['team'].unique())
    except:
        return [
            "Chennai Super Kings", "Mumbai Indians", "Royal Challengers Bangalore", 
            "Kolkata Knight Riders", "Delhi Capitals", "Sunrisers Hyderabad", 
            "Punjab Kings", "Rajasthan Royals", "Gujarat Titans", "Lucknow Super Giants"
        ]
def get_venues():
    """Return available IPL 2024 venues only"""
    try:
        team_venue_stats = pd.read_csv('data/processed/team_venue_stats.csv')
        # Filter for main venues only - add/remove as needed
        main_venues = [
            "M.A. Chidambaram Stadium, Chepauk",
            "Wankhede Stadium, Mumbai",
            "M. Chinnaswamy Stadium, Bengaluru",
            "Eden Gardens, Kolkata",
            "Arun Jaitley Stadium, Delhi",
            "Rajiv Gandhi International Stadium, Uppal",
            "Punjab Cricket Association Stadium, Mohali",
            "Sawai Mansingh Stadium, Jaipur",
            "Narendra Modi Stadium, Ahmedabad",
            "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cricket Stadium, Lucknow"
        ]
        # Only return venues in our list that exist in the data
        return sorted([v for v in team_venue_stats['venue'].unique() if v in main_venues or any(m in v for m in main_venues)])
    except Exception as e:
        # Fallback to main venues
        return [
            "M.A. Chidambaram Stadium, Chepauk",
            "Wankhede Stadium, Mumbai",
            "M. Chinnaswamy Stadium, Bengaluru",
            "Eden Gardens, Kolkata",
            "Arun Jaitley Stadium, Delhi",
            "Rajiv Gandhi International Stadium, Uppal",
            "Punjab Cricket Association Stadium, Mohali",
            "Sawai Mansingh Stadium, Jaipur",
            "Narendra Modi Stadium, Ahmedabad",
            "Bharat Ratna Shri Atal Bihari Vajpayee Ekana Cricket Stadium, Lucknow"
        ]

def print_menu(options):
    """Print a numbered menu of options"""
    for i, option in enumerate(options, 1):
        print(f"{i}. {option}")

def get_user_choice(prompt, options):
    """Get user choice from a list of options"""
    while True:
        print_menu(options)
        try:
            choice = int(input(prompt))
            if 1 <= choice <= len(options):
                return options[choice-1]
            else:
                print(f"Please enter a number between 1 and {len(options)}.")
        except ValueError:
            print("Please enter a valid number.")

def main():
    """Main function for the prediction CLI"""
    print("=" * 50)
    print("IPL Match Prediction System")
    print("=" * 50)
    
    # Check if model exists
    if not os.path.exists('models/best_model.pkl'):
        print("Error: Model files not found. Please run model_training.py first.")
        return
    
    # Get available teams and venues
    teams = get_available_teams()
    venues = get_venues()
    
    # Select teams
    print("\nSelect the first team:")
    team1 = get_user_choice("Enter team number: ", teams)
    
    remaining_teams = [team for team in teams if team != team1]
    print("\nSelect the second team:")
    team2 = get_user_choice("Enter team number: ", remaining_teams)
    
    # Select venue
    print("\nSelect the venue:")
    venue = get_user_choice("Enter venue number: ", venues)
    
    # Toss information
    print("\nDo you know the toss result?")
    know_toss = get_user_choice("Enter your choice: ", ["Yes", "No"])
    
    toss_winner = None
    toss_decision = None
    
    if know_toss == "Yes":
        print("\nWhich team won the toss?")
        toss_winner = get_user_choice("Enter team: ", [team1, team2])
        
        print("\nWhat did they decide?")
        toss_decision = get_user_choice("Enter decision: ", ["bat", "field"])
    
    # Make prediction
    prediction = predict_match(team1, team2, venue, toss_winner, toss_decision)
    
    if prediction:
        # Display prediction
        print("\n" + "=" * 50)
        print("Match Prediction Results")
        print("=" * 50)
        print(f"Team 1: {prediction['team1']}")
        print(f"Team 2: {prediction['team2']}")
        print(f"Predicted Winner: {prediction['predicted_winner']}")
        print(f"Win Probability: {prediction['win_probability']:.2f}%")
        print(f"Confidence: {prediction['confidence']}")
        
        print(f"\nTeam 1 Win Probability: {prediction['team1_win_probability']:.2f}%")
        print(f"Team 2 Win Probability: {prediction['team2_win_probability']:.2f}%")
        
        print("\nMatch Details:")
        print(f"Venue: {prediction['match_details']['venue']}")
        print(f"Team 1 is Home Team: {'Yes' if prediction['match_details']['team1_is_home'] else 'No'}")
        print(f"Team 1 Recent Form: {prediction['match_details']['team1_recent_form']:.2f}")
        print(f"Team 2 Recent Form: {prediction['match_details']['team2_recent_form']:.2f}")
        print(f"Team 1 H2H Win Rate: {prediction['match_details']['team1_h2h_win_rate']:.2f}")
        print(f"Team 2 H2H Win Rate: {prediction['match_details']['team2_h2h_win_rate']:.2f}")
        
        if prediction['match_details']['toss_winner']:
            print(f"Toss Winner: {prediction['match_details']['toss_winner']}")
            print(f"Toss Decision: {prediction['match_details']['toss_decision']}")

if __name__ == "__main__":
    main()