import numpy as np
from sklearn.metrics import brier_score_loss
import pandas as pd
import random
df = pd.read_csv("samplesubmission_datacompetition.csv")
y_pred = df.HomeWP # this is your probabilistic prediction vector
# the following will include the actual outcome: 1 if home team wins 0 otherwise
# for now we generate a random vector for illustration
y_true = []
for i in range(len(df.HomeWP)):
y_true.append(round(random.uniform(0, 1)))
brier_score_loss(y_true, y_pred)
# when providing everything with 0.5 probability you should get a Brier score of 0.25.
# If your solution is improving over this you are at the right direction