def get_tracking_stats(stat_measure, seasons, season_types, entity_type,
**kwargs):
"""
stat_measure - string, options: 'Drives', 'Defense', 'CatchShoot', 'Passing', 'Possessions', 'PullUpShot', 'Rebounding', 'Efficiency', 'SpeedDistance', 'ElbowTouch', 'PostTouch', 'PaintTouch'
seasons - list, ex season '2019-20'
season_types - list, season types are 'Regular Season' or 'Playoffs'
entity_type - string, 'player' or 'team'
possible kwargs:
date_from - string, optional, format - MM/DD/YYYY
date_to - string, optional, format - MM/DD/YYYY
opponent_team_id - int, optional, default is 0, which gets all teams
returns list of dicts
"""
all_season_stats = []
for season in seasons:
for season_type in season_types:
time.sleep(2)
response_json = get_tracking_response_json_for_stat_measure(
stat_measure, season, season_type, entity_type, **kwargs)
stats = utils.make_array_of_dicts_from_response_json(
response_json, 0)
for stat in stats:
stat['SEASON'] = f'{season} {season_type}'
all_season_stats += stats
return all_season_stats
def test_make_array_of_dicts_from_response_json():
response_json = {
'resultSets': [{'headers': ['header1', 'header2'], 'rowSet': [[1, 2], [3, 4], [4, 5], [2, 1]]}]
}
index = 0
array_of_dicts = utils.make_array_of_dicts_from_response_json(response_json, index)
assert array_of_dicts == [{'header1': 1, 'header2': 2}, {'header1': 3, 'header2': 4}, {'header1': 4, 'header2': 5}, {'header1': 2, 'header2': 1}]
def get_hustle_stats(seasons, season_types, **kwargs):
"""
seasons - list, ex season '2019-20'
season_types - list, season types are 'Regular Season' or 'Playoffs'
possible kwargs:
date_from - string, optional, format - MM/DD/YYYY
date_to - string, optional, format - MM/DD/YYYY
returns list of dicts
"""
all_season_stats = []
for season in seasons:
for season_type in season_types:
time.sleep(2)
response_json = get_hustle_response_json_for_stat_measure(
season, season_type, **kwargs)
stats = utils.make_array_of_dicts_from_response_json(
response_json, 0)
for stat in stats:
stat['SEASON'] = f'{season} {season_type}'
all_season_stats += stats
return all_season_stats
def get_tracking_shot_stats(entity_type, seasons, season_types, **kwargs):
"""
entity_type - string, player, team, opponent
seasons - list, ex season '2019-20'
season_types - list, season types are 'Regular Season' or 'Playoffs'
possible kwargs:
close_def_dists - list, options are: '', '0-2 Feet - Very Tight','2-4 Feet - Tight','4-6 Feet - Open','6+ Feet - Wide Open'
shot_clocks - list, options are: '', '24-22', '22-18 Very Early', '18-15 Early', '15-7 Average', '7-4 Late', '4-0 Very Late', 'ShotClock Off'
shot_dists - list, options are: '', '>=10.0'
touch_times - list, options are: '', 'Touch < 2 Seconds', 'Touch 2-6 Seconds', 'Touch 6+ Seconds'
dribble_ranges - list, options are: '', '0 Dribbles', '1 Dribble', '2 Dribbles', '3-6 Dribbles', '7+ Dribbles'
general_ranges - list, options are: 'Overall', 'Catch and Shoot', 'Pullups', 'Less Than 10 ft'
date_from - string, format - MM/DD/YYYY
date_to - string, format - MM/DD/YYYY
periods - list of ints
location - string, 'Home' or 'Road'
returns list of dicts
"""
all_season_stats = []
for season in seasons:
for season_type in season_types:
season_stats = []
for close_def in kwargs.get('close_def_dists', ['']):
for clock in kwargs.get('shot_clocks', ['']):
for dist in kwargs.get('shot_dists', ['']):
for touch in kwargs.get('touch_times', ['']):
for dribbles in kwargs.get('dribble_ranges', ['']):
for general in kwargs.get(
'general_ranges', ['Overall']):
for period in kwargs.get('periods', ['']):
time.sleep(2)
response_json = get_tracking_shots_response(
entity_type,
season,
season_type,
close_def_dist=close_def,
shot_clock=clock,
shot_dist=dist,
touch_time=touch,
dribbles=dribbles,
general_range=general,
date_from=kwargs.get(
'date_from', ''),
date_to=kwargs.get('date_to', ''),
period=period,
location=kwargs.get(
'location', ''),
)
filter_stats = utils.make_array_of_dicts_from_response_json(
response_json, 0)
season_stats.append(filter_stats)
stats = sum_tracking_shot_totals(entity_type, *season_stats)
entity_id_key = 'PLAYER_ID' if entity_type == 'player' else 'TEAM_ID'
overall_response_json = get_tracking_shots_response(
entity_type,
season,
season_type,
general_range='Overall',
date_from=kwargs.get('date_from', ''),
date_to=kwargs.get('date_to', ''))
overall_stats = utils.make_array_of_dicts_from_response_json(
overall_response_json, 0)
overall_stats_by_entity = {
stat[entity_id_key]: {
'FGA': stat['FGA'],
'FG2A': stat['FG2A'],
'FG3A': stat['FG3A']
}
for stat in overall_stats
}
for stat in stats:
entity_id = stat[entity_id_key]
stat['SEASON'] = f'{season} {season_type}'
stat['OVERALL_FGA'] = overall_stats_by_entity[entity_id]['FGA']
stat['OVERALL_FG2A'] = overall_stats_by_entity[entity_id][
'FG2A']
stat['OVERALL_FG3A'] = overall_stats_by_entity[entity_id][
'FG3A']
stat['FGA_FREQUENCY'] = stat['FGA'] / stat[
'OVERALL_FGA'] if stat['OVERALL_FGA'] != 0 else 0
stat['FG2A_FREQUENCY'] = stat['FG2A'] / stat[
'OVERALL_FGA'] if stat['OVERALL_FGA'] != 0 else 0
stat['FG3A_FREQUENCY'] = stat['FG3A'] / stat[
'OVERALL_FGA'] if stat['OVERALL_FGA'] != 0 else 0
stat['FREQUENCY_OF_FG2A'] = stat['FG2A'] / stat[
'OVERALL_FG2A'] if stat['OVERALL_FG2A'] != 0 else 0
stat['FREQUENCY_OF_FG3A'] = stat['FG3A'] / stat[
'OVERALL_FG3A'] if stat['OVERALL_FG3A'] != 0 else 0
all_season_stats += stats
return all_season_stats
