Refactor assist projection calculations in app.py to improve accuracy. Updated the logic for calculating 'Assist_Proj' to scale based on total kills, ensuring projections do not exceed actual performance metrics. This change enhances the integrity of player performance data in both team and player data initialization functions.

app.py

@@ -358,13 +358,17 @@ def init_team_data(game_count, team, opponent, win_loss_settings, kill_predictio
                 if win_loss_settings[game] == "Win":
                     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)
+                    raw_assists = team_data.apply(lambda row: row['wAssist%'] * opp_pos_assists_boost_win.get(row['position'], 1), axis=1) * team_data['Kill_Proj'].sum()
+                    assist_scale = min(1.0, kill_predictions[game] / raw_assists.sum()) if raw_assists.sum() > 0 else 1.0
+                    team_data['Assist_Proj'] = raw_assists * assist_scale
                     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.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)
+                    raw_assists = team_data.apply(lambda row: row['wAssist%'] * opp_pos_assists_boost_win.get(row['position'], 1), axis=1) * team_data['Kill_Proj'].sum()
+                    assist_scale = min(1.0, kill_predictions[game] / raw_assists.sum()) if raw_assists.sum() > 0 else 1.0
+                    team_data['Assist_Proj'] = raw_assists * assist_scale
                     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']]
             
@@ -568,13 +572,17 @@ def init_player_data(game_count, players, opponent, win_loss_settings, kill_pred
                 if win_loss_settings[game] == "Win":
                     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)
+                    raw_assists = team_data.apply(lambda row: row['wAssist%'] * opp_pos_assists_boost_win.get(row['position'], 1), axis=1) * team_data['Kill_Proj'].sum()
+                    assist_scale = min(1.0, kill_predictions[game] / raw_assists.sum()) if raw_assists.sum() > 0 else 1.0
+                    team_data['Assist_Proj'] = raw_assists * assist_scale
                     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.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)
+                    raw_assists = team_data.apply(lambda row: row['wAssist%'] * opp_pos_assists_boost_win.get(row['position'], 1), axis=1) * team_data['Kill_Proj'].sum()
+                    assist_scale = min(1.0, kill_predictions[game] / raw_assists.sum()) if raw_assists.sum() > 0 else 1.0
+                    team_data['Assist_Proj'] = raw_assists * assist_scale
                     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']]