Don't know the problem with my minimax algorithm

def minimax_score(board, player): # player will be X for simplicity
    original_player = player
    empty_spots = []
    other_player = None
    if player == 'X':
        other_player = 'O'
    elif player == 'O':
        other_player = 'X'

    for y in range(3): # find all open spots on board
        for x in range(3):
            if board[y][x] == None:
                empty_spots.append([y, x])

    if ttt.get_winner(board) == player:
        return 10
    elif ttt.get_winner(board) == other_player:
        return -10
    elif ttt.get_winner(board) == None and empty_spots == []:
        return 0

    scores = []
    moves = []
    for y in range(3): # find all open spots on board
        for x in range(3):
            if board[y][x] == None:
                moves.append([y, x])            
    for move in moves: # if board state is not terminal
        board[move[0]][move[1]] = player
        if player == 'X':
            player = 'O'
        elif player == 'O':
            player = 'X'
        scores.append(minimax_score(board, player))
        board[move[0]][move[1]] = None 
    player = original_player
    if player == 'X':
        return max(scores)
    elif player == 'O':
        return min(scores)


def minimax_ai(board, player):
    best_move = None
    best_score = None
    moves = []
    for y in range(3): # find all open spots on board
        for x in range(3):
            if board[y][x] == None:
               moves.append([y, x])
    for move in moves:
        new_board = copy.deepcopy(board)
        new_board[move[0]][move[1]] = player
        if player == 'X':
            player = 'O'
        elif player == 'O':
            player = 'X'
        score = minimax_score(new_board, player)
        new_board[move[0]][move[1]] = None
        if best_score is None or score > best_score:
            best_move = [move[1], move[0]]
            best_score = score

    return best_move