diff --git a/retrosheet_data.py b/retrosheet_data.py
index e65b07b..01fa7f8 100644
--- a/retrosheet_data.py
+++ b/retrosheet_data.py
@@ -222,18 +222,22 @@ def get_player_ids(plays: pd.DataFrame, which: Literal['batters', 'pitchers']) -
         r_vs_l = 0 if 'r' not in pa_vl else pa_vl['r']
         r_vs_r = 0 if 'r' not in pa_vr else pa_vr['r']
 
+        # If player ONLY batted from one side (zero PAs from other side), classify as single-handed
         if sum([l_vs_l, l_vs_r]) == 0 and sum([r_vs_l, r_vs_r]) > 0:
             return 'R'
         elif sum([l_vs_l, l_vs_r]) > 0 and sum([r_vs_l, r_vs_r]) == 0:
             return 'L'
-        
-        if sum([l_vs_l, l_vs_r, r_vs_l, r_vs_r]) < 10:
-            if sum([l_vs_l, l_vs_r]) > sum([r_vs_l, r_vs_r]):
-                return 'L'
-            else:
-                return 'R'
-        else:
+
+        # If player batted from both sides (even if limited sample), they're a switch hitter
+        # This correctly identifies switch hitters regardless of total PA count
+        if sum([l_vs_l, l_vs_r]) > 0 and sum([r_vs_l, r_vs_r]) > 0:
             return 'S'
+
+        # Fallback for edge cases (shouldn't reach here in normal flow)
+        if sum([l_vs_l, l_vs_r]) > sum([r_vs_l, r_vs_r]):
+            return 'L'
+        else:
+            return 'R'
     
     def get_pitch_hand(row):
         first_event = plays.drop_duplicates('pitcher_id').loc[plays.pitcher_id == row['key_retro'], 'pitcher_hand']
@@ -1096,8 +1100,15 @@ async def get_or_post_players(bstat_df: pd.DataFrame = None, bat_rat_df: pd.Data
             return mlb_player
 
     def new_player_payload(row, ratings_df: pd.DataFrame):
+        # Append handedness indicator to player name (* for left, # for switch)
+        name_suffix = ''
+        if row.get('bat_hand') == 'L':
+            name_suffix = '*'
+        elif row.get('bat_hand') == 'S':
+            name_suffix = '#'
+
         return {
-            'p_name': f'{row["use_name"]} {row["last_name"]}',
+            'p_name': f'{row["use_name"]} {row["last_name"]}{name_suffix}',
             'cost': f'{ratings_df.loc[row['key_bbref']]["cost"]}',
             'image': f'change-me',
             'mlbclub': CLUB_LIST[row['Tm']],