def yards_to_go(gid, pid, prechecked_gid=False, prechecked_pid=False):
"""
Finds the distance needed (in yards) to achieve a first down
Parameters
----------
gid: an integer of a game_id
pid: an integer of a play_id
prechecked_gid: a boolean of whether or not the game ID has been checked
before being passed to the function
prechecked_pid: a boolean of whether or not the play ID has been checked
before being passed to the function
Returns
-------
yds_to_go: an integer number of yards needed on a play to achieve
a first down
"""
if not prechecked_gid:
# Validate the game ID
gid = check.game_id(gid)
prechecked_gid = True
if not prechecked_pid:
# Validate the play ID
pid = check.play_id(gid, pid)
prechecked_pid = True
# Load in the plays data
play = load.plays_data(gid, pid, prechecked_gid, prechecked_pid)
# Get the number of yards needed for a first down
yds_to_go = play['yds_to_go'].iloc[0]
return yds_to_go
def line_of_scrimmage(gid, pid, prechecked_gid=False, prechecked_pid=False):
"""
Finds the line of scrimmage for a specified play
Parameters
----------
gid: an integer of a game_id
pid: an integer of a play_id
prechecked_gid: a boolean of whether or not the game ID has been checked
before being passed to the function
prechecked_pid: a boolean of whether or not the play ID has been checked
before being passed to the function
Returns
-------
los: a float of the absolute yardline of the line of scrimmage
"""
if not prechecked_gid:
# Validate the game ID
gid = check.game_id(gid)
prechecked_gid = True
if not prechecked_pid:
# Validate the play ID
pid = check.play_id(gid, pid)
prechecked_pid = True
# Load in the plays data
play = load.plays_data(gid, pid, prechecked_gid, prechecked_pid)
# Get the line of scrimmage
los = play['absolute_yard_line'].iloc[0]
return los
def play_id(gid, pid, prechecked_gid=False):
"""
Checks a play ID exists in the provided dataset. Will prompt until
a valid play ID is provided
Parameters
----------
gid: an integer of a game_id
pid: an integer of a play_id
prechecked_gid: a boolean of whether or not the game ID has been checked
before being passed to the function
Returns
-------
pid: a validated integer of a play_id
"""
if not prechecked_gid:
# Check to make sure the game ID supplied is valid
gid = game_id(gid)
# Load the plays data and get all plays from the supplied game
plays = load.plays_data(gid, prechecked_gid=True)
valid_plays = plays['play_id'].tolist()
play_id_valid = False
while not play_id_valid:
if type(pid) != int:
try:
pid = int(pid)
except:
pass
# If the play is a valid play in the game, break out of the loop
if pid in valid_plays:
play_id_valid = True
# Otherwise, force the player to select a new play
else:
print(f'{pid} is not a valid play ID in this game. Please '
'select a play from the following list:\n')
for i, play in plays.iterrows():
print(f'{play.play_id} -- {play.down_dist_summary}')
pid = int(input('Play ID: '))
return pid
def tracking_and_plays(gid=0,
pid=0,
tracking=pd.DataFrame(),
play=pd.DataFrame()):
"""
Merges play and tracking data together to centralize data source
Parameters
----------
gid: an integer of a game_id
pid: an integer of a play_id
tracking: a dataframe of tracking data that can be used to speed up
data loading
play: a dataframe of play-level data that can be used to speed up data
loading
Returns
-------
tracking_and_plays: a merged dataframe of tracking and play-level data
"""
# If no tracking data is provided...
if tracking.empty:
# If a game ID and play ID are both provided, load the tracking data
# for the play from that game
if gid != 0 and pid != 0:
week = find.game_week(gid)
tracking = load.tracking_data(gid=gid, pid=pid, week=week)
# If a game ID is provided but not a play ID, load all tracking for the
# game
elif gid != 0 and pid == 0:
week = find.game_week(gid)
tracking = load.tracking_data(gid=gid, week=week)
# If a play ID is provided but not a game ID, load all tracking for
# plays with matching play IDs
elif gid == 0 and pid != 0:
tracking = load.tracking_data(pid=pid, week=0)
# If no game ID is provided and no play ID is provided, then load all
# tracking data from all weeks
else:
tracking = load.tracking_data()
# If no play data is provided...
if play.empty:
# If a game ID and play ID are both provided, load the plays data for
# the play from that game
if gid != 0 and pid != 0:
play = load.plays_data(gid=gid, pid=pid)
# If a game ID is provided but not a play ID, load all plays data for
# the game
elif gid != 0 and pid == 0:
play = load.plays_data(gid=gid)
# If a play ID is provided but not a game ID, load all plays data for
# plays with matching play IDs
elif gid == 0 and pid != 0:
play = load.plays_data(pid=pid)
# If no game ID is provided and no play ID is provided, then load all
# plays data
else:
play = load.plays_data()
tracking_and_plays = pd.merge(left=tracking,
right=play,
how='inner',
on=['game_id', 'play_id'])
games_data = load.games_data()[['game_id', 'home', 'away', 'week']]
tracking_and_plays = pd.merge(left=tracking_and_plays,
right=games_data,
how='inner',
on='game_id')
tracking_and_plays['offensive_team'] = \
tracking_and_plays['possession_team']
tracking_and_plays['defensive_team'] = np.where(
tracking_and_plays['offensive_team'] == tracking_and_plays['home'],
tracking_and_plays['away'], tracking_and_plays['home'])
return tracking_and_plays
def plays_and_games(gid=0, home='', away='', prechecked_gid=False):
"""
Merges play and game data together to better illustrate what plays are
being run by which team and against which opponent
Parameters
----------
gid: an integer of a game_id
home: a string representing the home team's team code
away: a string representing the away team's team code
play_info: a dictionary of parameters to use for subsetting. The keys MUST
be columns in the plays data to be used. If not, they will be ignored
prechecked_gid: a boolean of whether or not the game ID has been prechecked
Returns
-------
plays_from_game: a merged dataframe of play and game data
"""
if gid != 0:
# If the game ID is not already checked, check the game ID first
if not prechecked_gid:
gid = check.game_id(gid)
prechecked_gid = True
# If the game ID is not passed, then try to get a game ID based on the home
# and away team. If this yields nothing, then load all games
if home != '' or away != '':
home = check.team_code(home)
away = check.team_code(away)
gid = find.game_id(home, away)
prechecked_gid = True
# Load in plays from the identified game, or from all games if game ID = 0
plays_from_game = load.plays_data(gid=gid, prechecked_gid=prechecked_gid)
# Load in the games data to merge
games_data = load.games_data(
gid, prechecked_gid)[['game_id', 'home', 'away', 'week']]
plays_from_game = pd.merge(left=plays_from_game,
right=games_data,
how='inner',
on='game_id')
plays_from_game['offensive_team'] = plays_from_game['possession_team']
plays_from_game['defensive_team'] = np.where(
plays_from_game['offensive_team'] == plays_from_game['home'],
plays_from_game['away'], plays_from_game['home'])
plays_from_game = plays_from_game[[
'game_id', 'play_id', 'play_description', 'quarter', 'down',
'yds_to_go', 'possession_team', 'play_type', 'yardline_side',
'yardline_number', 'offense_formation', 'personnel_offense',
'defenders_in_box', 'n_pass_rushers', 'personnel_defense',
'type_dropback', 'presnap_away_score', 'presnap_home_score',
'game_clock', 'absolute_yard_line', 'penalty_code', 'penalty_player',
'pass_result', 'offensive_play_result', 'play_result', 'epa',
'is_defensive_pi', 'down_dist_summary', 'home', 'away',
'offensive_team', 'defensive_team', 'week'
]]
return plays_from_game
def play_id(gid=0, home='', away='', play_info={}, prechecked_gid=False):
"""
Finds the play ID of a particular play
Parameters
----------
gid: an integer of a game_id
home: a string representing the home team's team code
away: a string representing the away team's team code
play_info: a dictionary of parameters to use for subsetting. The keys MUST
be columns in the plays data to be used. If not, they will be ignored
prechecked_gid: a boolean of whether or not the game ID has been prechecked
Returns
-------
pid: an integer of a play_id
"""
# Game ID should be the primary lookup tool, so start with loading the
# game's data if this is passed
if gid != 0:
# If the game ID is not already checked, check the game ID first
if not prechecked_gid:
gid = check.game_id(gid)
prechecked_gid = True
# If the game ID is not passed, then try to get a game ID based on the home
# and away team. If this yields nothing, then load all games
if home != '' or away != '':
home = check.team_code(home)
away = check.team_code(away)
gid = game_id(home, away)
prechecked_gid = True
# Load in plays from the identified game, or from all games if game ID = 0
plays_from_game = load.plays_data(gid=gid, prechecked_gid=prechecked_gid)
# Subset by the information about the play in the parameter play_info
if bool(play_info):
for key, val in play_info.items():
# If the desired parameter is not in the columns of the plays data,
# alert user and skip this subsetting parameter
if key not in plays_from_game.columns:
print(f'{key} is not a valid column to use for subsetting as'
' it does not appear in the dataset.')
continue
# If the value passed in the plays_info dictionary is a list, use
# the .isin() method for subsetting
if type(val) == list:
plays_from_game = plays_from_game[
plays_from_game[f'{key}'].isin(val)]
# Otherwise, use the key and value alone
else:
plays_from_game = plays_from_game[plays_from_game[f'{key}'] ==
val]
# If the passed parameters are enough to identify the play, there
# should only be one play ID remaining. Return this value
if len(plays_from_game) == 1:
pid = plays_from_game['play_id'].values[0]
else:
for i, play in plays_from_game.iterrows():
print(f'{play.game_id} -- {play.play_id} -- '
f'{play.down_dist_summary}')
gid = input('Which game ID were you looking for?\nGame ID: ')
pid = input('Which play of the above are you looking for?\nPlay ID: ')
gid = check.game_id(gid)
prechecked_gid = True
pid = check.play_id(gid, pid, prechecked_gid)
return pid