def METHOD_NAME():
    reward_func = A2C_Reward()
    def scripted_func(game) -> Optional[botbowl.Action]:
        available_action_types = [action_choice.action_type for action_choice in game.get_available_actions()]
        if len(available_action_types) == 1 and len(game.get_available_actions()[0].positions) == 0 and len(game.get_available_actions()[0].players) == 0:
            return botbowl.Action(available_action_types[0])
        if botbowl.ActionType.END_PLAYER_TURN in available_action_types and randint(1, 5) == 2:
            return botbowl.Action(botbowl.ActionType.END_PLAYER_TURN)
        return None
    env = BotBowlEnv(EnvConf(size=1))
    env = ScriptedActionWrapper(env, scripted_func)
    env = RewardWrapper(env, home_reward_func=reward_func)
    rewards = []
    own_tds = []
    opp_tds = []
    for _ in range(10):
        _, _, mask = env.reset()
        done = False
        ep_reward = 0.0
        while not done:
            aa = np.where(mask)[0]
            action_idx = np.random.choice(aa, 1)[0]
            (_, _, mask), reward, done, _ = env.step(action_idx)
            ep_reward += reward
        rewards.append(ep_reward)
        own_tds.append(env.game.state.home_team.state.score)
        opp_tds.append(env.game.state.away_team.state.score)