chelsea is 66.667% fucked

ucldraw.py

import pandas as pd
import numpy as np
import seaborn as sns
from ipywidgets import interact, RadioButtons as RB

fs = [("Barcelona", "ESP","D"), ("Beşiktaş", "TUR","G"),
      ("Liverpool", "ENG","E"),
      ("City", "ENG","F"), ("Man U", "ENG","A"),
      ("PSG","FRA","B"), ("Roma", "ITA","C"),
      ("Tottenham", "ENG","H")]
sn = [("Basel","SWI","A"), ("Chelsea","ENG","C"),
      ("Juventus","ITA","D"), ("Porto","POR","G"),
      ("Real Madrid","ESP","H"), ("Sevilla","ESP","E"),
      ("Shakhtar","UKR","F"),
      ("Bayern","GER","B")] 

mt = {u[0]: {v[0]: 0 for v in sn} for u in fs}

# can be optimised
N = 10000000
for i in range(N):
    u = fs[np.random.randint(8)]
    v = sn[np.random.randint(8)]
    
    M = 1
    m = N
    
    if u[1]!=v[1] and u[2]!=v[2]:
        mt[u[0]][v[0]] += 1
        if mt[u[0]][v[0]] < m and mt[u[0]][v[0]] > 0:
            m = mt[u[0]][v[0]]
    
for k in mt:
    for j in mt[k]:
        if mt[k][j] == 0:
            mt[k][j] = np.nan

@interact(norm=RB(options=["none", "x", "y"]))
def _p(norm):
    df = pd.DataFrame(mt)
    if norm == "y":
        df = 100*df/df.sum()
        t = "Probability of `y` facing `x`"
    elif norm == "x":
        df = 100*df.apply(lambda x: x/df.sum(axis=1))
        t = "Probability of `x` facing `y`"
    else:
        t = "# simulations"
    ax = sns.heatmap(df, annot=(norm != "none"),
                     vmin=None if norm == "none" else 0,
                     cbar=(norm == "none"), fmt=".1f")
    ax.set_title(t)