Refactor statistical calculations in init_team_data function of app.py. Replaced direct calculations for kill, death, assist, and CS projections with apply method for improved readability and performance. This change enhances the clarity of the code and maintains the accuracy of team performance evaluations based on opponent statistics.

app.py

@@ -288,16 +288,16 @@ def init_team_data(team, opponent, win_loss, kill_prediction, death_prediction,
             team_data = player_tables.drop_duplicates(subset = ['playername'])
 
             if win_loss == "Win":
-                team_data['Kill_Proj'] = (team_data['wKill%'] * opp_pos_kills_boost_win.get(team_data['position'], 1)) * kill_prediction
-                team_data['Death_Proj'] = (team_data['wDeath%'] * opp_pos_deaths_boost_win.get(team_data['position'], 1)) * death_prediction
-                team_data['Assist_Proj'] = (team_data['wAssist%'] * opp_pos_assists_boost_win.get(team_data['position'], 1)) * kill_prediction
-                team_data['CS_Proj'] = (team_data['wCS'] * opp_pos_cs_boost_win.get(team_data['position'], 1)) * kill_prediction
+                team_data['Kill_Proj'] = team_data.apply(lambda row: row['wKill%'] * opp_pos_kills_boost_win.get(row['position'], 1), axis=1)
+                team_data['Death_Proj'] = team_data.apply(lambda row: row['wDeath%'] * opp_pos_deaths_boost_win.get(row['position'], 1), axis=1)
+                team_data['Assist_Proj'] = team_data.apply(lambda row: row['wAssist%'] * opp_pos_assists_boost_win.get(row['position'], 1), axis=1)
+                team_data['CS_Proj'] = team_data.apply(lambda row: row['wCS'] * opp_pos_cs_boost_win.get(row['position'], 1), axis=1)
                 team_data = team_data[['playername', 'teamname', 'position', 'Kill_Proj', 'Death_Proj', 'Assist_Proj', 'CS_Proj']]
             else:
-                team_data['Kill_Proj'] = (team_data['lKill%'] * opp_pos_kills_boost_loss.get(team_data['position'], 1)) * kill_prediction
-                team_data['Death_Proj'] = (team_data['lDeath%'] * opp_pos_deaths_boost_loss.get(team_data['position'], 1)) * death_prediction
-                team_data['Assist_Proj'] = (team_data['lAssist%'] * opp_pos_assists_boost_loss.get(team_data['position'], 1)) * kill_prediction
-                team_data['CS_Proj'] = (team_data['lCS'] * opp_pos_cs_boost_loss.get(team_data['position'], 1)) * kill_prediction
+                team_data['Kill_Proj'] = team_data.apply(lambda row: row['lKill%'] * opp_pos_kills_boost_loss.get(row['position'], 1), axis=1)
+                team_data['Death_Proj'] = team_data.apply(lambda row: row['lDeath%'] * opp_pos_deaths_boost_loss.get(row['position'], 1), axis=1)
+                team_data['Assist_Proj'] = team_data.apply(lambda row: row['lAssist%'] * opp_pos_assists_boost_loss.get(row['position'], 1), axis=1)
+                team_data['CS_Proj'] = team_data.apply(lambda row: row['lCS'] * opp_pos_cs_boost_loss.get(row['position'], 1), axis=1)
                 team_data = team_data[['playername', 'teamname', 'position', 'Kill_Proj', 'Death_Proj', 'Assist_Proj', 'CS_Proj']]
         else:
             player_tables = player_tables[['playername', 'teamname', 'position', 'playername_avg_kills_win', 'playername_avg_deaths_win', 'playername_avg_assists_win', 'playername_avg_total_cs_win',
@@ -308,16 +308,16 @@ def init_team_data(team, opponent, win_loss, kill_prediction, death_prediction,
             team_data = player_tables.drop_duplicates(subset = ['playername'])
 
             if win_loss == "Win":
-                team_data['Kill_Proj'] = (team_data['wKill%'] * opp_pos_kills_boost_win.get(team_data['position'], 1))
-                team_data['Death_Proj'] = (team_data['wDeath%'] * opp_pos_deaths_boost_win.get(team_data['position'], 1))
-                team_data['Assist_Proj'] = (team_data['wAssist%'] * opp_pos_assists_boost_win.get(team_data['position'], 1))
-                team_data['CS_Proj'] = (team_data['wCS'] * opp_pos_cs_boost_win.get(team_data['position'], 1))
+                team_data['Kill_Proj'] = team_data.apply(lambda row: row['wKill%'] * opp_pos_kills_boost_win.get(row['position'], 1), axis=1)
+                team_data['Death_Proj'] = team_data.apply(lambda row: row['wDeath%'] * opp_pos_deaths_boost_win.get(row['position'], 1), axis=1)
+                team_data['Assist_Proj'] = team_data.apply(lambda row: row['wAssist%'] * opp_pos_assists_boost_win.get(row['position'], 1), axis=1)
+                team_data['CS_Proj'] = team_data.apply(lambda row: row['wCS'] * opp_pos_cs_boost_win.get(row['position'], 1), axis=1)
                 team_data = team_data[['playername', 'teamname', 'position', 'Kill_Proj', 'Death_Proj', 'Assist_Proj', 'CS_Proj']]
             else:
-                team_data['Kill_Proj'] = (team_data['lKill%'] * opp_pos_kills_boost_loss.get(team_data['position'], 1))
-                team_data['Death_Proj'] = (team_data['lDeath%'] * opp_pos_deaths_boost_loss.get(team_data['position'], 1))
-                team_data['Assist_Proj'] = (team_data['lAssist%'] * opp_pos_assists_boost_loss.get(team_data['position'], 1))
-                team_data['CS_Proj'] = (team_data['lCS'] * opp_pos_cs_boost_loss.get(team_data['position'], 1))
+                team_data['Kill_Proj'] = team_data.apply(lambda row: row['lKill%'] * opp_pos_kills_boost_loss.get(row['position'], 1), axis=1)
+                team_data['Death_Proj'] = team_data.apply(lambda row: row['lDeath%'] * opp_pos_deaths_boost_loss.get(row['position'], 1), axis=1)
+                team_data['Assist_Proj'] = team_data.apply(lambda row: row['lAssist%'] * opp_pos_assists_boost_loss.get(row['position'], 1), axis=1)
+                team_data['CS_Proj'] = team_data.apply(lambda row: row['lCS'] * opp_pos_cs_boost_loss.get(row['position'], 1), axis=1)
                 team_data = team_data[['playername', 'teamname', 'position', 'Kill_Proj', 'Death_Proj', 'Assist_Proj', 'CS_Proj']]
 
         return team_data.dropna().reset_index(drop=True)