def __make_predictions(self, year_range: Tuple[int, int]) -> None:
predictions = self.data_importer.fetch_prediction_data(
year_range, verbose=self.verbose
)
home_away_df = pivot_team_matches_to_matches(predictions)
for pred in home_away_df.to_dict("records"):
Prediction.update_or_create_from_data(pred)
if self.verbose == 1:
print("\nPredictions saved!")
def __make_predictions(self, year: int, round_number: int) -> None:
predictions = self.data_importer.fetch_prediction_data(
(year, year + 1), round_number=round_number, ml_models=self.ml_models
)
home_away_df = pivot_team_matches_to_matches(predictions)
for pred in home_away_df.to_dict("records"):
Prediction.update_or_create_from_data(pred)
if self.verbose == 1:
print("Predictions saved!\n")
def test_convert_data_to_record(self):
data = fake_prediction_data(self.match, ml_model_name=self.ml_model.name)
home_away_df = pivot_team_matches_to_matches(pd.DataFrame(data))
self.assertEqual(Prediction.objects.count(), 0)
Prediction.update_or_create_from_data(home_away_df.to_dict("records")[0])
self.assertEqual(Prediction.objects.count(), 1)
with self.subTest("when prediction record already exists"):
predicted_margin = 100
home_away_df.loc[:, "home_predicted_margin"] = predicted_margin
home_away_df.loc[:, "away_predicted_margin"] = -predicted_margin
Prediction.update_or_create_from_data(home_away_df.to_dict("records")[0])
self.assertEqual(Prediction.objects.count(), 1)
prediction = Prediction.objects.first()
self.assertEqual(prediction.predicted_margin, predicted_margin)
# Regression tests for bug that caused update_or_create_from_data
# to select wrong team as predicted_winner when predicted margin
# was greater than away team's predicted winning margin
with self.subTest(
"when predicted margins are skewed with large home losing margin"
):
predicted_winning_margin = 100
predicted_losing_margin = -200
home_away_df.loc[:, "home_predicted_margin"] = predicted_losing_margin
home_away_df.loc[:, "away_predicted_margin"] = predicted_winning_margin
Prediction.update_or_create_from_data(home_away_df.to_dict("records")[0])
prediction = Prediction.objects.first()
self.assertEqual(prediction.predicted_margin, 150)
self.assertEqual(
home_away_df["away_team"].iloc[0], prediction.predicted_winner.name
)
with self.subTest(
"when predicted margins are skewed with large away losing margin"
):
predicted_winning_margin = 100
predicted_losing_margin = -200
home_away_df.loc[:, "home_predicted_margin"] = predicted_winning_margin
home_away_df.loc[:, "away_predicted_margin"] = predicted_losing_margin
Prediction.update_or_create_from_data(home_away_df.to_dict("records")[0])
prediction = Prediction.objects.first()
self.assertEqual(prediction.predicted_margin, 150)
self.assertEqual(
home_away_df["home_team"].iloc[0], prediction.predicted_winner.name
)
with self.subTest("when predicted margins are less than 0.5"):
predicted_winning_margin = 0.4
predicted_losing_margin = -0.4
home_away_df.loc[:, "home_predicted_margin"] = predicted_winning_margin
home_away_df.loc[:, "away_predicted_margin"] = predicted_losing_margin
Prediction.update_or_create_from_data(home_away_df.to_dict("records")[0])
prediction = Prediction.objects.first()
self.assertEqual(prediction.predicted_margin, 1)
self.assertEqual(
home_away_df["home_team"].iloc[0], prediction.predicted_winner.name
)