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NBA_Betting_Models

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James McCool commited on Nov 12, 2024

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68d4dce

1 Parent(s): fb1703c

Changed line 524

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app.py +2 -2

app.py CHANGED Viewed

@@ -521,7 +521,7 @@ with tab5:
                                     players_only['poisson_var'] = players_only.apply(calculate_poisson, axis=1)
                                     players_only['10%'] = overall_file.quantile(0.1, axis=1)
                                     players_only['90%'] = overall_file.quantile(0.9, axis=1)
-                                    players_only['Over'] = np_where(overall_file['Prop'] <= 3, players_only['poisson_var'], prop_check[prop_check > 0].count(axis=1)/float(total_sims))
                                     players_only['Imp Over'] = players_only['Player'].map(over_dict)
                                     players_only['Over%'] = players_only[["Over", "Imp Over"]].mean(axis=1)
                                     players_only['Under'] = np_where(overall_file['Prop'] <= 3, 1 - players_only['poisson_var'], prop_check[prop_check < 0].count(axis=1)/float(total_sims))
@@ -667,7 +667,7 @@ with tab5:
                                 players_only['poisson_var'] = players_only.apply(calculate_poisson, axis=1)
                                 players_only['10%'] = overall_file.quantile(0.1, axis=1)
                                 players_only['90%'] = overall_file.quantile(0.9, axis=1)
-                                players_only['Over'] = np_where(overall_file['Prop'] <= 3, players_only['poisson_var'], prop_check[prop_check > 0].count(axis=1)/float(total_sims))
                                 players_only['Imp Over'] = players_only['Player'].map(over_dict)
                                 players_only['Over%'] = players_only[["Over", "Imp Over"]].mean(axis=1)
                                 players_only['Under'] = np_where(overall_file['Prop'] <= 3, 1 - players_only['poisson_var'], prop_check[prop_check < 0].count(axis=1)/float(total_sims))

                                     players_only['poisson_var'] = players_only.apply(calculate_poisson, axis=1)
                                     players_only['10%'] = overall_file.quantile(0.1, axis=1)
                                     players_only['90%'] = overall_file.quantile(0.9, axis=1)
+                                    players_only['Over'] = np_where(players_only['Prop'] <= 3, players_only['poisson_var'], prop_check[prop_check > 0].count(axis=1)/float(total_sims))
                                     players_only['Imp Over'] = players_only['Player'].map(over_dict)
                                     players_only['Over%'] = players_only[["Over", "Imp Over"]].mean(axis=1)
                                     players_only['Under'] = np_where(overall_file['Prop'] <= 3, 1 - players_only['poisson_var'], prop_check[prop_check < 0].count(axis=1)/float(total_sims))
                                 players_only['poisson_var'] = players_only.apply(calculate_poisson, axis=1)
                                 players_only['10%'] = overall_file.quantile(0.1, axis=1)
                                 players_only['90%'] = overall_file.quantile(0.9, axis=1)
+                                players_only['Over'] = np_where(players_only['Prop'] <= 3, players_only['poisson_var'], prop_check[prop_check > 0].count(axis=1)/float(total_sims))
                                 players_only['Imp Over'] = players_only['Player'].map(over_dict)
                                 players_only['Over%'] = players_only[["Over", "Imp Over"]].mean(axis=1)
                                 players_only['Under'] = np_where(overall_file['Prop'] <= 3, 1 - players_only['poisson_var'], prop_check[prop_check < 0].count(axis=1)/float(total_sims))