def manual_game_analysis(league_data, predictions):
"""
Takes the league_data dictionary and current predictions.
Asks the user to select the home and away teams from the available
teams.
Provides a comparison.
Returns the prediction as a list: [homeTeam, predictedHomeScore, awayTeam, predictedAwayScore]
"""
today = datetime.today()
team_list = []
selection1 = ""
selection2 = ""
team_list_display = []
if league_data == {}:
print(
"You can't run manual game analysis until you have selected the appropriate league(s)."
)
print("Please select a league or import a JSON file first.")
input("\nPress enter to continue")
error = "No leagues loaded" # Response advising why the function failed.
return error
# Build the basic team list (this must be kept for later use)
for team in list_teams(league_data):
team_list.append(team)
# Build a list of teams with their option numbers ready for display
for team in team_list:
team_list_display.append(str(team_list.index(team) + 1) + " " + team)
# Display the newly generated list
cf.custom_pretty_print(team_list_display, 3)
# while homeTeam not in teamList or awayTeam not in teamList:
while not cf.valid_input(selection1, range(1, len(team_list) + 1)):
print("\nSelect home team from the above list:", end=" ")
selection1 = input()
while not cf.valid_input(selection2, range(1, len(team_list) + 1)):
print("\nSelect away team from the above list:", end=" ")
selection2 = input()
home_team = team_list[int(selection1) - 1]
away_team = team_list[int(selection2) - 1]
home_team_league, away_team_league = get_league(home_team, away_team,
league_data)
if home_team_league == away_team_league:
league = home_team_league
else:
league = "(mixed leagues)"
print(home_team + " vs " + away_team)
comparison = compare(home_team, away_team, league_data)
print("\n\nComparison")
print("==========")
print("\nPositive numbers indicate Home team statistic is higher."
" \nNegative numbers indicate Away team statistic is higher.\n")
comparison_index_count = 0
print("Home / Away Game Statistical Differences")
print("========================================")
for stat in ["Played", "Won", "Drew", "Lost", "For", "Against", "Points"]:
print(stat, comparison[0][comparison_index_count], end=" ")
comparison_index_count += 1
print()
for stat in ["Won per Game", "Drew per Game", "Lost per Game"]:
print(stat, comparison[0][comparison_index_count], end=" ")
comparison_index_count += 1
print()
for stat in ["For per Game", "Against per Game", "Points per Game"]:
print(stat, comparison[0][comparison_index_count], end=" ")
comparison_index_count += 1
print("\n\nTotal Game Statistical Differences")
print("==================================")
comparison_index_count = 0
for stat in ["Played", "Won", "Drew", "Lost", "For", "Against", "Points"]:
print(stat, comparison[1][comparison_index_count], end=" ")
comparison_index_count += 1
print()
for stat in ["Won per Game", "Drew per Game", "Lost per Game"]:
print(stat, comparison[1][comparison_index_count], end=" ")
comparison_index_count += 1
print()
for stat in ["For per Game", "Against per Game", "Points per Game"]:
print(stat, comparison[1][comparison_index_count], end=" ")
comparison_index_count += 1
home_team_max_goals = league_data[home_team_league][home_team]["Home"][
"For per Game"] * 2.5
away_team_max_goals = league_data[away_team_league][away_team]["Away"][
"For per Game"] * 2.5
home_team_goals = int(
(league_data[home_team_league][home_team]["Home"]["For per Game"] *
1.25) *
league_data[away_team_league][away_team]["Away"]["Against per Game"])
away_team_goals = int(
(league_data[away_team_league][away_team]["Away"]["For per Game"] *
1.25) *
league_data[home_team_league][home_team]["Home"]["Against per Game"])
if home_team_goals > home_team_max_goals:
home_team_goals = int(home_team_max_goals)
if away_team_goals > away_team_max_goals:
away_team_goals = int(away_team_max_goals)
prediction_goal_separation = abs(home_team_goals - away_team_goals)
total_goals = home_team_goals + away_team_goals
if home_team_goals > 0 and away_team_goals > 0:
both_to_score = "Yes"
else:
both_to_score = "No"
prediction_name = "Home_home_F_A_vs_Away_away_F_A"
prediction_description = "home_team_goals = int((home_team_avg_gpg_f * 1.25) * (away_team_avg_gpg_a) : away_team_goals = int((away_team_avg_gpg_f * 1.25) * (home_team_avg_gpg_a))"
# Save current prediction as a list item
prediction = {
"League": league,
"Date and time": "Manual entry: ",
"Prediction type": prediction_name,
"Home team": home_team,
"Home team prediction": home_team_goals,
"Away team": away_team,
"Away team prediction": away_team_goals,
"Total goalsexpected": total_goals,
"Predicted separation": prediction_goal_separation,
"Both to score": both_to_score,
"date_as_dtobject": today
}
# Flatten league stats for prediction storage and exporting
index = 0
for team in [home_team, away_team]: # Do for each team
if team == home_team: # Used for the prediction keys
h_a_stat_key = "Home Team"
elif team == away_team:
h_a_stat_key = "Away Team"
league = [home_team_league, away_team_league][index]
index += 1
for section in ["Home", "Away",
"Total"]: # Go through each set of stats
for stat in league_data[league][team][
section]: # Add each stat and a descriptive key to the prediction dictionary
prediction[h_a_stat_key + " " + section + " " +
stat] = league_data[league][team][section][stat]
prediction["Description"] = prediction_description
print(
"\n\nPredicted outcome: " + home_team + " " + str(home_team_goals) +
" " + away_team + " " + str(away_team_goals) +
"\n\nFull analysis details can be viewed be exporting the predictions to a file via the 'Reports' menu."
)
# If the prediction is not already in the predictions list, add it.
if prediction not in predictions:
predictions.append(prediction)
return predictions
def test_valid_input2(self):
self.assertIs(valid_input('eggs', ['spam', 'snakes', 'r/programming']),
False)
def test_valid_input3(self):
self.assertIs(valid_input(int('2'), range(1, 10 + 1)), True)
def test_valid_input(self):
self.assertIs(valid_input('eggs', ['eggs', 'spam', 'snakes']), True)