diff --git a/rlgym/rocket_league/action_parsers/lookup_table_action.py b/rlgym/rocket_league/action_parsers/lookup_table_action.py
index 8e2e2a5..c93d0b4 100644
--- a/rlgym/rocket_league/action_parsers/lookup_table_action.py
+++ b/rlgym/rocket_league/action_parsers/lookup_table_action.py
@@ -1,4 +1,4 @@
-from typing import Dict, Any, Tuple, List
+from typing import Dict, Any, Tuple, List, Union
 
 import numpy as np
 
@@ -6,7 +6,7 @@
 from rlgym.rocket_league.api import GameState
 
 
-class LookupTableAction(ActionParser[AgentID, np.ndarray, np.ndarray, GameState, Tuple[str, int]]):
+class LookupTableAction(ActionParser[AgentID, Union[np.ndarray, int], np.ndarray, GameState, Tuple[str, int]]):
     """
     World-famous discrete action parser which uses a lookup table to reduce the number of possible actions from 1944 to 90
     """
@@ -21,17 +21,12 @@ def get_action_space(self, agent: AgentID) -> Tuple[str, int]:
     def reset(self, agents: List[AgentID], initial_state: GameState, shared_info: Dict[str, Any]) -> None:
         pass
 
-    def parse_actions(self, actions: Dict[AgentID, np.ndarray], state: GameState, shared_info: Dict[str, Any]) -> Dict[AgentID, np.ndarray]:
-        parsed_actions = {}
-        for agent, action in actions.items():
-            # Action can have shape (Ticks, 1) or (Ticks)
-            assert len(action.shape) == 1 or (len(action.shape) == 2 and action.shape[1] == 1)
-
-            if len(action.shape) == 2:
-                action = action.squeeze(1)
-
-            parsed_actions[agent] = self._lookup_table[action]
-
+    def parse_actions(self, actions: Dict[AgentID, Union[np.ndarray, int]], state: GameState, shared_info: Dict[str, Any]) -> Dict[AgentID, np.ndarray]:
+        parsed_actions = {
+            agent: self._lookup_table[action] 
+            for agent, action in actions.items()
+        }
+        
         return parsed_actions
 
     @staticmethod