for game in team.games:
p_win = calculate_game_probability(
rating, game.difficulty(location_adjustment))
if game.result == "W":
p = p * p_win
elif game.result == "L":
p = p * (1.0 - p_win)
else:
raise "Unexpected result %s" % game.result
return p
### GET INPUT DATA ###
# Create team objects
team_list_source = "%s/constants/names.txt" % ROOT_PATH
teams = Team.build_teams_from_file(team_list_source)
records_source = "%s/output/standings-week%s.csv" % (ROOT_PATH, CURRENT_WEEK)
with open(records_source) as f:
for line in f:
name, record = line.strip().split(",")
name = translate_ncaa_name(name)
teams[name].record = record
# Create game objects
schedule_root = '%s/output/football/schedules/' % ROOT_PATH
idx = 0
for name, team in teams.items():
team.id = idx
idx += 1
filename_format_name = build_filename_format(name)
CURRENT_WEEK)
sources['performance'] = '%s/output/performance-ratings-week%s.csv' % (
root_path, CURRENT_WEEK)
sources['names'] = '%s/constants/names.txt' % root_path
sources['last_week'] = '%s/output/results-week%s.csv' % (root_path,
CURRENT_WEEK - 1)
sources['conferences'] = '%s/constants/conferences.txt' % root_path
sources['records'] = '%s/output/standings-week%s.csv' % (root_path,
CURRENT_WEEK)
data = {}
for key, sourcefile in sources.items():
with open(sourcefile) as f:
data[key] = list(f)
teams = Team.build_teams_from_file(sources['names'])
conference_flairs = build_conference_flairs(data['conferences'])
dropped_out = Team.set_last_week(data['last_week'], teams)
for data_line in data['power']:
raw_data = read_power_line(data_line)
team = process_power_name(raw_data['name'])
if team in POWER_NAMES:
team = POWER_NAMES[team]
teams[team].set_power_mean(raw_data['mean'])
for data_line in data['performance']:
raw_data = read_performance_line(data_line)
raw_name = raw_data['name']
if raw_name in PERFORMANCE_NAMES:
name = PERFORMANCE_NAMES[raw_name]
