How to make my nested loops faster in python?

Please, can somebody improve my code, it get the job done, but is very slow.

Every row is match between 2 players, in column "Players" are only the relevant player. I compare a player against the rows before, e.g "Player2" is at index 2, so I only iterate in the rows 0 and 1 My goal is it to find, if a Player has a different "Y in his next match.

df=pd.DataFrame({"Players":["Player1","Player1","Player2","Player1","Player1"],
                 "Win":["Player1","Player4","Player5","Player1","Player6"],
                 "Loss":["Player3","Player1","Player2","Player5","Player1"],
                 "Y": ["B","A","B","B","B"]})


Results=[]
for index, player in enumerate(Players.values, 0):
    Result=[]
    Result.append(0)
    for i in range(df.shape[0]):           
        if index <= df.index.values[i]: #skip the values in the same row
           continue
        if ((player == df.Win.values[i])| (player == df.Loss.values[i])) & (df.Y[index]!=df.Y[i]):  #has previous match a different Y
           Result.append(1)
        elif ((player == df.Win.values[i])| (player == df.Loss.values[i])) & (df.Y[index]==df.Y[i]): #has previous match the same Y       
           Result.append(0)
    Results.append(Result[-1])       

The outpup should look like this:

Results=[0,1,0,1,0]