input: def predict_football_winner(data: pd.DataFrame) -> float:
      """
      Develop a machine learning model to predict the winning team of football matches based on past Premier League data.
      The input data should contain features like home_team_goals, away_team_goals, home_team_possession, away_team_possession,
      home_team_shots, away_team_shots, home_team_yellow_cards, away_team_yellow_cards, home_team_red_cards, and away_team_red_cards,
      and a target variable 'winner'. The function will split the data into training and test sets, train a Gradient Boosting Classifier,
      make predictions, and return the model's score.
      
      >>> data = pd.DataFrame({
      ...     'home_team_goals': [2, 1, 3, 0],
      ...     'away_team_goals': [1, 2, 1, 3],
      ...     'home_team_possession': [55, 60, 45, 70],
      ...     'away_team_possession': [45, 40, 55, 30],
      ...     'home_team_shots': [10, 8, 12, 6],
      ...     'away_team_shots': [8, 10, 6, 12],
      ...     'home_team_yellow_cards': [1, 0, 2, 3],
      ...     'away_team_yellow_cards': [0, 1, 3, 2],
      ...     'home_team_red_cards': [0, 0, 1, 0],
      ...     'away_team_red_cards': [0, 1, 0, 1],
      ...     'winner': [1, 0, 1, 0]
      ... })
      >>> predict_football_winner(data)
      1.0
      """
output:     from sklearn.model_selection import train_test_split
      from sklearn.ensemble import GradientBoostingClassifier
      from sklearn.metrics import accuracy_score
  
      X = data[['home_team_goals', 'away_team_goals', 'home_team_possession', 'away_team_possession', 
                'home_team_shots', 'away_team_shots', 'home_team_yellow_cards', 'away_team_yellow_cards', 
                'home_team_red_cards', 'away_team_red_cards']]
      y = data['winner']
  
      X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
  
      model = GradientBoostingClassifier(random_state=42)
      model.fit(X_train, y_train)
  
      y_pred = model.predict(X_test)
      return accuracy_score(y_test, y_pred)