simulate_league.py

import pandas as pd 
import numpy as np
import random
from itertools import combinations

def simulate_naive(n_teams):
  #Simulate a single season'
    scores = np.zeros(n_teams, dtype=int)
    for i, j in combinations(range(n_teams), 2):
      # each pair of teams play twice, each time with 50/50 chance of 
      # either team winning; the winning team gets three points
        scores[i if np.random.rand() < 0.5 else j] += 3
        scores[i if np.random.rand() < 0.5 else j] += 3
      
    return scores

# Simulate across multiple seasons
def perfect_competition(n_teams, n_seasons):
    df = pd.DataFrame({season: simulate_naive(n_teams) for season in range(n_seasons)})
    return df