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import requests
import polars as pl
import numpy as np
from datetime import datetime
from tqdm import tqdm
from pytz import timezone
import re
from concurrent.futures import ThreadPoolExecutor, as_completed
class MLB_Scrape:
def __init__(self):
# Initialize your class here if needed
pass
def get_sport_id(self):
"""
Retrieves the list of sports from the MLB API and processes it into a Polars DataFrame.
Returns:
- df (pl.DataFrame): A DataFrame containing the sports information.
"""
# Make API call to retrieve sports information
response = requests.get(url='https://statsapi.mlb.com/api/v1/sports').json()
# Convert the JSON response into a Polars DataFrame
df = pl.DataFrame(response['sports'])
return df
def get_sport_id_check(self, sport_id: int = 1):
"""
Checks if the provided sport ID exists in the list of sports retrieved from the MLB API.
Parameters:
- sport_id (int): The sport ID to check. Default is 1.
Returns:
- bool: True if the sport ID exists, False otherwise. If False, prints the available sport IDs.
"""
# Retrieve the list of sports from the MLB API
sport_id_df = self.get_sport_id()
# Check if the provided sport ID exists in the DataFrame
if sport_id not in sport_id_df['id']:
print('Please Select a New Sport ID from the following')
print(sport_id_df)
return False
return True
def get_game_types(self):
"""
Retrieves the different types of MLB games from the MLB API and processes them into a Polars DataFrame.
Returns:
- df (pl.DataFrame): A DataFrame containing the game types information.
"""
# Make API call to retrieve game types information
response = requests.get(url='https://statsapi.mlb.com/api/v1/gameTypes').json()
# Convert the JSON response into a Polars DataFrame
df = pl.DataFrame(response)
return df
def get_schedule(self,
year_input: list = [2024],
sport_id: list = [1],
game_type: list = ['R']):
"""
Retrieves the schedule of baseball games based on the specified parameters.
Parameters:
- year_input (list): A list of years to filter the schedule. Default is [2024].
- sport_id (list): A list of sport IDs to filter the schedule. Default is [1].
- game_type (list): A list of game types to filter the schedule. Default is ['R'].
Returns:
- game_df (pandas.DataFrame): A DataFrame containing the game schedule information, including game ID, date, time, away team, home team, game state, venue ID, and venue name. If the schedule length is 0, it returns a message indicating that different parameters should be selected.
"""
# Type checks
if not isinstance(year_input, list) or not all(isinstance(year, int) for year in year_input):
raise ValueError("year_input must be a list of integers.")
if not isinstance(sport_id, list) or not all(isinstance(sid, int) for sid in sport_id):
raise ValueError("sport_id must be a list of integers.")
if not isinstance(game_type, list) or not all(isinstance(gt, str) for gt in game_type):
raise ValueError("game_type must be a list of strings.")
eastern = timezone('US/Eastern')
# Convert input lists to comma-separated strings
year_input_str = ','.join([str(x) for x in year_input])
sport_id_str = ','.join([str(x) for x in sport_id])
game_type_str = ','.join([str(x) for x in game_type])
# Make API call to retrieve game schedule
game_call = requests.get(url=f'https://statsapi.mlb.com/api/v1/schedule/?sportId={sport_id_str}&gameTypes={game_type_str}&season={year_input_str}&hydrate=lineup,players').json()
try:
# Extract relevant data from the API response
game_list = [item for sublist in [[y.get('gamePk') for y in x['games']] for x in game_call['dates']] for item in sublist]
time_list = [item for sublist in [[y.get('gameDate') for y in x['games']] for x in game_call['dates']] for item in sublist]
date_list = [item for sublist in [[y.get('officialDate') for y in x['games']] for x in game_call['dates']] for item in sublist]
away_team_list = [item for sublist in [[y['teams']['away']['team'].get('name') for y in x['games']] for x in game_call['dates']] for item in sublist]
home_team_list = [item for sublist in [[y['teams']['home']['team'].get('name') for y in x['games']] for x in game_call['dates']] for item in sublist]
state_list = [item for sublist in [[y['status'].get('codedGameState') for y in x['games']] for x in game_call['dates']] for item in sublist]
venue_id = [item for sublist in [[y['venue'].get('id', None) for y in x['games']] for x in game_call['dates']] for item in sublist]
venue_name = [item for sublist in [[y['venue'].get('name') for y in x['games']] for x in game_call['dates']] for item in sublist]
# Create a Polars DataFrame with the extracted data
game_df = pl.DataFrame(data={'game_id': game_list,
'time': time_list,
'date': date_list,
'away': away_team_list,
'home': home_team_list,
'state': state_list,
'venue_id': venue_id,
'venue_name': venue_name})
# Check if the DataFrame is empty
if len(game_df) == 0:
print('Schedule Length of 0, please select different parameters.')
return None
# Convert date and time columns to appropriate formats
game_df = game_df.with_columns(
game_df['date'].str.to_date(),
game_df['time'].str.to_datetime().dt.convert_time_zone(eastern.zone).dt.strftime("%I:%M %p"))
# Remove duplicate games and sort by date
game_df = game_df.unique(subset='game_id').sort('date')
# Check again if the DataFrame is empty after processing
if len(game_df) == 0:
print('Schedule Length of 0, please select different parameters.')
return None
except KeyError:
print('No Data for Selected Parameters')
return None
return game_df
def get_data(self, game_list_input: list):
"""
Retrieves live game data for a list of game IDs in parallel.
Parameters:
- game_list_input (list): A list of game IDs for which to retrieve live data.
Returns:
- data_total (list): A list of JSON responses containing live game data for each game ID.
"""
data_total = []
print('This May Take a While. Progress Bar shows Completion of Data Retrieval.')
def fetch_data(game_id):
r = requests.get(f'https://statsapi.mlb.com/api/v1.1/game/{game_id}/feed/live')
return r.json()
with ThreadPoolExecutor() as executor:
futures = {executor.submit(fetch_data, game_id): game_id for game_id in game_list_input}
for future in tqdm(as_completed(futures), total=len(futures), desc="Processing", unit="iteration"):
data_total.append(future.result())
return data_total
def get_data_df(self, data_list):
"""
Converts a list of game data JSON objects into a Polars DataFrame.
Parameters:
- data_list (list): A list of JSON objects containing game data.
Returns:
- data_df (pl.DataFrame): A DataFrame containing the structured game data.
"""
swing_list = ['X','F','S','D','E','T','W']
whiff_list = ['S','T','W']
print('Converting Data to Dataframe.')
game_id = []
game_date = []
batter_id = []
batter_name = []
batter_hand = []
batter_team = []
batter_team_id = []
pitcher_id = []
pitcher_name = []
pitcher_hand = []
pitcher_team = []
pitcher_team_id = []
play_description = []
play_code = []
in_play = []
is_strike = []
is_swing = []
is_whiff = []
is_out = []
is_ball = []
is_review = []
pitch_type = []
pitch_description = []
strikes = []
balls = []
outs = []
strikes_after = []
balls_after = []
outs_after = []
start_speed = []
end_speed = []
sz_top = []
sz_bot = []
x = []
y = []
ax = []
ay = []
az = []
pfxx = []
pfxz = []
px = []
pz = []
vx0 = []
vy0 = []
vz0 = []
x0 = []
y0 = []
z0 = []
zone = []
type_confidence = []
plate_time = []
extension = []
spin_rate = []
spin_direction = []
vb = []
ivb = []
hb = []
launch_speed = []
launch_angle = []
launch_distance = []
launch_location = []
trajectory = []
hardness = []
hit_x = []
hit_y = []
index_play = []
play_id = []
start_time = []
end_time = []
is_pitch = []
type_type = []
type_ab = []
ab_number = []
event = []
event_type = []
rbi = []
away_score = []
home_score = []
for data in data_list:
try:
for ab_id in range(len(data['liveData']['plays']['allPlays'])):
ab_list = data['liveData']['plays']['allPlays'][ab_id]
for n in range(len(ab_list['playEvents'])):
if ab_list['playEvents'][n]['isPitch'] == True or 'call' in ab_list['playEvents'][n]['details']:
ab_number.append(ab_list['atBatIndex'] if 'atBatIndex' in ab_list else None)
game_id.append(data['gamePk'])
game_date.append(data['gameData']['datetime']['officialDate'])
if 'matchup' in ab_list:
batter_id.append(ab_list['matchup']['batter']['id'] if 'batter' in ab_list['matchup'] else None)
if 'batter' in ab_list['matchup']:
batter_name.append(ab_list['matchup']['batter']['fullName'] if 'fullName' in ab_list['matchup']['batter'] else None)
else:
batter_name.append(None)
batter_hand.append(ab_list['matchup']['batSide']['code'] if 'batSide' in ab_list['matchup'] else None)
pitcher_id.append(ab_list['matchup']['pitcher']['id'] if 'pitcher' in ab_list['matchup'] else None)
if 'pitcher' in ab_list['matchup']:
pitcher_name.append(ab_list['matchup']['pitcher']['fullName'] if 'fullName' in ab_list['matchup']['pitcher'] else None)
else:
pitcher_name.append(None)
pitcher_hand.append(ab_list['matchup']['pitchHand']['code'] if 'pitchHand' in ab_list['matchup'] else None)
if ab_list['about']['isTopInning']:
batter_team.append(data['gameData']['teams']['away']['abbreviation'] if 'away' in data['gameData']['teams'] else None)
batter_team_id.append(data['gameData']['teams']['away']['id'] if 'away' in data['gameData']['teams'] else None)
pitcher_team.append(data['gameData']['teams']['home']['abbreviation'] if 'home' in data['gameData']['teams'] else None)
pitcher_team_id.append(data['gameData']['teams']['home']['id'] if 'home' in data['gameData']['teams'] else None)
else:
batter_team.append(data['gameData']['teams']['home']['abbreviation'] if 'home' in data['gameData']['teams'] else None)
batter_team_id.append(data['gameData']['teams']['home']['id'] if 'home' in data['gameData']['teams'] else None)
pitcher_team.append(data['gameData']['teams']['away']['abbreviation'] if 'away' in data['gameData']['teams'] else None)
pitcher_team_id.append(data['gameData']['teams']['away']['id'] if 'away' in data['gameData']['teams'] else None)
play_description.append(ab_list['playEvents'][n]['details']['description'] if 'description' in ab_list['playEvents'][n]['details'] else None)
play_code.append(ab_list['playEvents'][n]['details']['code'] if 'code' in ab_list['playEvents'][n]['details'] else None)
in_play.append(ab_list['playEvents'][n]['details']['isInPlay'] if 'isInPlay' in ab_list['playEvents'][n]['details'] else None)
is_strike.append(ab_list['playEvents'][n]['details']['isStrike'] if 'isStrike' in ab_list['playEvents'][n]['details'] else None)
if 'details' in ab_list['playEvents'][n]:
is_swing.append(True if ab_list['playEvents'][n]['details']['code'] in swing_list else None)
is_whiff.append(True if ab_list['playEvents'][n]['details']['code'] in whiff_list else None)
else:
is_swing.append(None)
is_whiff.append(None)
is_ball.append(ab_list['playEvents'][n]['details']['isOut'] if 'isOut' in ab_list['playEvents'][n]['details'] else None)
is_review.append(ab_list['playEvents'][n]['details']['hasReview'] if 'hasReview' in ab_list['playEvents'][n]['details'] else None)
pitch_type.append(ab_list['playEvents'][n]['details']['type']['code'] if 'type' in ab_list['playEvents'][n]['details'] else None)
pitch_description.append(ab_list['playEvents'][n]['details']['type']['description'] if 'type' in ab_list['playEvents'][n]['details'] else None)
if ab_list['playEvents'][n]['pitchNumber'] == 1:
strikes.append(0)
balls.append(0)
strikes_after.append(ab_list['playEvents'][n]['count']['strikes'] if 'strikes' in ab_list['playEvents'][n]['count'] else None)
balls_after.append(ab_list['playEvents'][n]['count']['balls'] if 'balls' in ab_list['playEvents'][n]['count'] else None)
outs.append(ab_list['playEvents'][n]['count']['outs'] if 'outs' in ab_list['playEvents'][n]['count'] else None)
outs_after.append(ab_list['playEvents'][n]['count']['outs'] if 'outs' in ab_list['playEvents'][n]['count'] else None)
else:
strikes.append(ab_list['playEvents'][n-1]['count']['strikes'] if 'strikes' in ab_list['playEvents'][n-1]['count'] else None)
balls.append(ab_list['playEvents'][n-1]['count']['balls'] if 'balls' in ab_list['playEvents'][n-1]['count'] else None)
outs.append(ab_list['playEvents'][n-1]['count']['outs'] if 'outs' in ab_list['playEvents'][n-1]['count'] else None)
strikes_after.append(ab_list['playEvents'][n]['count']['strikes'] if 'strikes' in ab_list['playEvents'][n]['count'] else None)
balls_after.append(ab_list['playEvents'][n]['count']['balls'] if 'balls' in ab_list['playEvents'][n]['count'] else None)
outs_after.append(ab_list['playEvents'][n]['count']['outs'] if 'outs' in ab_list['playEvents'][n]['count'] else None)
if 'pitchData' in ab_list['playEvents'][n]:
start_speed.append(ab_list['playEvents'][n]['pitchData']['startSpeed'] if 'startSpeed' in ab_list['playEvents'][n]['pitchData'] else None)
end_speed.append(ab_list['playEvents'][n]['pitchData']['endSpeed'] if 'endSpeed' in ab_list['playEvents'][n]['pitchData'] else None)
sz_top.append(ab_list['playEvents'][n]['pitchData']['strikeZoneTop'] if 'strikeZoneTop' in ab_list['playEvents'][n]['pitchData'] else None)
sz_bot.append(ab_list['playEvents'][n]['pitchData']['strikeZoneBottom'] if 'strikeZoneBottom' in ab_list['playEvents'][n]['pitchData'] else None)
x.append(ab_list['playEvents'][n]['pitchData']['coordinates']['x'] if 'x' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
y.append(ab_list['playEvents'][n]['pitchData']['coordinates']['y'] if 'y' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
ax.append(ab_list['playEvents'][n]['pitchData']['coordinates']['aX'] if 'aX' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
ay.append(ab_list['playEvents'][n]['pitchData']['coordinates']['aY'] if 'aY' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
az.append(ab_list['playEvents'][n]['pitchData']['coordinates']['aZ'] if 'aZ' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
pfxx.append(ab_list['playEvents'][n]['pitchData']['coordinates']['pfxX'] if 'pfxX' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
pfxz.append(ab_list['playEvents'][n]['pitchData']['coordinates']['pfxZ'] if 'pfxZ' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
px.append(ab_list['playEvents'][n]['pitchData']['coordinates']['pX'] if 'pX' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
pz.append(ab_list['playEvents'][n]['pitchData']['coordinates']['pZ'] if 'pZ' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
vx0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['vX0'] if 'vX0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
vy0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['vY0'] if 'vY0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
vz0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['vZ0'] if 'vZ0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
x0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['x0'] if 'x0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
y0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['y0'] if 'y0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
z0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['z0'] if 'z0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else None)
zone.append(ab_list['playEvents'][n]['pitchData']['zone'] if 'zone' in ab_list['playEvents'][n]['pitchData'] else None)
type_confidence.append(ab_list['playEvents'][n]['pitchData']['typeConfidence'] if 'typeConfidence' in ab_list['playEvents'][n]['pitchData'] else None)
plate_time.append(ab_list['playEvents'][n]['pitchData']['plateTime'] if 'plateTime' in ab_list['playEvents'][n]['pitchData'] else None)
extension.append(ab_list['playEvents'][n]['pitchData']['extension'] if 'extension' in ab_list['playEvents'][n]['pitchData'] else None)
if 'breaks' in ab_list['playEvents'][n]['pitchData']:
spin_rate.append(ab_list['playEvents'][n]['pitchData']['breaks']['spinRate'] if 'spinRate' in ab_list['playEvents'][n]['pitchData']['breaks'] else None)
spin_direction.append(ab_list['playEvents'][n]['pitchData']['breaks']['spinDirection'] if 'spinDirection' in ab_list['playEvents'][n]['pitchData']['breaks'] else None)
vb.append(ab_list['playEvents'][n]['pitchData']['breaks']['breakVertical'] if 'breakVertical' in ab_list['playEvents'][n]['pitchData']['breaks'] else None)
ivb.append(ab_list['playEvents'][n]['pitchData']['breaks']['breakVerticalInduced'] if 'breakVerticalInduced' in ab_list['playEvents'][n]['pitchData']['breaks'] else None)
hb.append(ab_list['playEvents'][n]['pitchData']['breaks']['breakHorizontal'] if 'breakHorizontal' in ab_list['playEvents'][n]['pitchData']['breaks'] else None)
else:
start_speed.append(None)
end_speed.append(None)
sz_top.append(None)
sz_bot.append(None)
x.append(None)
y.append(None)
ax.append(None)
ay.append(None)
az.append(None)
pfxx.append(None)
pfxz.append(None)
px.append(None)
pz.append(None)
vx0.append(None)
vy0.append(None)
vz0.append(None)
x0.append(None)
y0.append(None)
z0.append(None)
zone.append(None)
type_confidence.append(None)
plate_time.append(None)
extension.append(None)
spin_rate.append(None)
spin_direction.append(None)
vb.append(None)
ivb.append(None)
hb.append(None)
if 'hitData' in ab_list['playEvents'][n]:
launch_speed.append(ab_list['playEvents'][n]['hitData']['launchSpeed'] if 'launchSpeed' in ab_list['playEvents'][n]['hitData'] else None)
launch_angle.append(ab_list['playEvents'][n]['hitData']['launchAngle'] if 'launchAngle' in ab_list['playEvents'][n]['hitData'] else None)
launch_distance.append(ab_list['playEvents'][n]['hitData']['totalDistance'] if 'totalDistance' in ab_list['playEvents'][n]['hitData'] else None)
launch_location.append(ab_list['playEvents'][n]['hitData']['location'] if 'location' in ab_list['playEvents'][n]['hitData'] else None)
trajectory.append(ab_list['playEvents'][n]['hitData']['trajectory'] if 'trajectory' in ab_list['playEvents'][n]['hitData'] else None)
hardness.append(ab_list['playEvents'][n]['hitData']['hardness'] if 'hardness' in ab_list['playEvents'][n]['hitData'] else None)
hit_x.append(ab_list['playEvents'][n]['hitData']['coordinates']['coordX'] if 'coordX' in ab_list['playEvents'][n]['hitData']['coordinates'] else None)
hit_y.append(ab_list['playEvents'][n]['hitData']['coordinates']['coordY'] if 'coordY' in ab_list['playEvents'][n]['hitData']['coordinates'] else None)
else:
launch_speed.append(None)
launch_angle.append(None)
launch_distance.append(None)
launch_location.append(None)
trajectory.append(None)
hardness.append(None)
hit_x.append(None)
hit_y.append(None)
index_play.append(ab_list['playEvents'][n]['index'] if 'index' in ab_list['playEvents'][n] else None)
play_id.append(ab_list['playEvents'][n]['playId'] if 'playId' in ab_list['playEvents'][n] else None)
start_time.append(ab_list['playEvents'][n]['startTime'] if 'startTime' in ab_list['playEvents'][n] else None)
end_time.append(ab_list['playEvents'][n]['endTime'] if 'endTime' in ab_list['playEvents'][n] else None)
is_pitch.append(ab_list['playEvents'][n]['isPitch'] if 'isPitch' in ab_list['playEvents'][n] else None)
type_type.append(ab_list['playEvents'][n]['type'] if 'type' in ab_list['playEvents'][n] else None)
if n == len(ab_list['playEvents']) - 1 :
type_ab.append(data['liveData']['plays']['allPlays'][ab_id]['result']['type'] if 'type' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
event.append(data['liveData']['plays']['allPlays'][ab_id]['result']['event'] if 'event' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
event_type.append(data['liveData']['plays']['allPlays'][ab_id]['result']['eventType'] if 'eventType' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
rbi.append(data['liveData']['plays']['allPlays'][ab_id]['result']['rbi'] if 'rbi' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
away_score.append(data['liveData']['plays']['allPlays'][ab_id]['result']['awayScore'] if 'awayScore' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
home_score.append(data['liveData']['plays']['allPlays'][ab_id]['result']['homeScore'] if 'homeScore' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
is_out.append(data['liveData']['plays']['allPlays'][ab_id]['result']['isOut'] if 'isOut' in data['liveData']['plays']['allPlays'][ab_id]['result'] else None)
else:
type_ab.append(None)
event.append(None)
event_type.append(None)
rbi.append(None)
away_score.append(None)
home_score.append(None)
is_out.append(None)
elif ab_list['playEvents'][n]['count']['balls'] == 4:
event.append(data['liveData']['plays']['allPlays'][ab_id]['result']['event'])
event_type.append(data['liveData']['plays']['allPlays'][ab_id]['result']['eventType'])
game_id.append(data['gamePk'])
game_date.append(data['gameData']['datetime']['officialDate'])
batter_id.append(ab_list['matchup']['batter']['id'] if 'batter' in ab_list['matchup'] else None)
batter_name.append(ab_list['matchup']['batter']['fullName'] if 'batter' in ab_list['matchup'] else None)
batter_hand.append(ab_list['matchup']['batSide']['code'] if 'batSide' in ab_list['matchup'] else None)
pitcher_id.append(ab_list['matchup']['pitcher']['id'] if 'pitcher' in ab_list['matchup'] else None)
pitcher_name.append(ab_list['matchup']['pitcher']['fullName'] if 'pitcher' in ab_list['matchup'] else None)
pitcher_hand.append(ab_list['matchup']['pitchHand']['code'] if 'pitchHand' in ab_list['matchup'] else None)
if ab_list['about']['isTopInning']:
batter_team.append(data['gameData']['teams']['away']['abbreviation'] if 'away' in data['gameData']['teams'] else None)
batter_team_id.append(data['gameData']['teams']['away']['id'] if 'away' in data['gameData']['teams'] else None)
pitcher_team.append(data['gameData']['teams']['home']['abbreviation'] if 'home' in data['gameData']['teams'] else None)
pitcher_team_id.append(data['gameData']['teams']['away']['id'] if 'away' in data['gameData']['teams'] else None)
else:
batter_team.append(data['gameData']['teams']['home']['abbreviation'] if 'home' in data['gameData']['teams'] else None)
batter_team_id.append(data['gameData']['teams']['home']['id'] if 'home' in data['gameData']['teams'] else None)
pitcher_team.append(data['gameData']['teams']['away']['abbreviation'] if 'away' in data['gameData']['teams'] else None)
pitcher_team_id.append(data['gameData']['teams']['home']['id'] if 'home' in data['gameData']['teams'] else None)
play_description.append(None)
play_code.append(None)
in_play.append(None)
is_strike.append(None)
is_ball.append(None)
is_review.append(None)
pitch_type.append(None)
pitch_description.append(None)
strikes.append(ab_list['playEvents'][n]['count']['balls'] if 'balls' in ab_list['playEvents'][n]['count'] else None)
balls.append(ab_list['playEvents'][n]['count']['strikes'] if 'strikes' in ab_list['playEvents'][n]['count'] else None)
outs.append(ab_list['playEvents'][n]['count']['outs'] if 'outs' in ab_list['playEvents'][n]['count'] else None)
strikes_after.append(ab_list['playEvents'][n]['count']['balls'] if 'balls' in ab_list['playEvents'][n]['count'] else None)
balls_after.append(ab_list['playEvents'][n]['count']['strikes'] if 'strikes' in ab_list['playEvents'][n]['count'] else None)
outs_after.append(ab_list['playEvents'][n]['count']['outs'] if 'outs' in ab_list['playEvents'][n]['count'] else None)
index_play.append(ab_list['playEvents'][n]['index'] if 'index' in ab_list['playEvents'][n] else None)
play_id.append(ab_list['playEvents'][n]['playId'] if 'playId' in ab_list['playEvents'][n] else None)
start_time.append(ab_list['playEvents'][n]['startTime'] if 'startTime' in ab_list['playEvents'][n] else None)
end_time.append(ab_list['playEvents'][n]['endTime'] if 'endTime' in ab_list['playEvents'][n] else None)
is_pitch.append(ab_list['playEvents'][n]['isPitch'] if 'isPitch' in ab_list['playEvents'][n] else None)
type_type.append(ab_list['playEvents'][n]['type'] if 'type' in ab_list['playEvents'][n] else None)
is_swing.append(None)
is_whiff.append(None)
start_speed.append(None)
end_speed.append(None)
sz_top.append(None)
sz_bot.append(None)
x.append(None)
y.append(None)
ax.append(None)
ay.append(None)
az.append(None)
pfxx.append(None)
pfxz.append(None)
px.append(None)
pz.append(None)
vx0.append(None)
vy0.append(None)
vz0.append(None)
x0.append(None)
y0.append(None)
z0.append(None)
zone.append(None)
type_confidence.append(None)
plate_time.append(None)
extension.append(None)
spin_rate.append(None)
spin_direction.append(None)
vb.append(None)
ivb.append(None)
hb.append(None)
launch_speed.append(None)
launch_angle.append(None)
launch_distance.append(None)
launch_location.append(None)
trajectory.append(None)
hardness.append(None)
hit_x.append(None)
hit_y.append(None)
type_ab.append(None)
ab_number.append(None)
rbi.append(None)
away_score.append(None)
home_score.append(None)
is_out.append(None)
except KeyError:
print(f"No Data for Game")
df = pl.DataFrame(data={
'game_id':game_id,
'game_date':game_date,
'batter_id':batter_id,
'batter_name':batter_name,
'batter_hand':batter_hand,
'batter_team':batter_team,
'batter_team_id':batter_team_id,
'pitcher_id':pitcher_id,
'pitcher_name':pitcher_name,
'pitcher_hand':pitcher_hand,
'pitcher_team':pitcher_team,
'pitcher_team_id':pitcher_team_id,
'ab_number':ab_number,
'play_description':play_description,
'play_code':play_code,
'in_play':in_play,
'is_strike':is_strike,
'is_swing':is_swing,
'is_whiff':is_whiff,
'is_out':is_out,
'is_ball':is_ball,
'is_review':is_review,
'pitch_type':pitch_type,
'pitch_description':pitch_description,
'strikes':strikes,
'balls':balls,
'outs':outs,
'strikes_after':strikes_after,
'balls_after':balls_after,
'outs_after':outs_after,
'start_speed':start_speed,
'end_speed':end_speed,
'sz_top':sz_top,
'sz_bot':sz_bot,
'x':x,
'y':y,
'ax':ax,
'ay':ay,
'az':az,
'pfxx':pfxx,
'pfxz':pfxz,
'px':px,
'pz':pz,
'vx0':vx0,
'vy0':vy0,
'vz0':vz0,
'x0':x0,
'y0':y0,
'z0':z0,
'zone':zone,
'type_confidence':type_confidence,
'plate_time':plate_time,
'extension':extension,
'spin_rate':spin_rate,
'spin_direction':spin_direction,
'vb':vb,
'ivb':ivb,
'hb':hb,
'launch_speed':launch_speed,
'launch_angle':launch_angle,
'launch_distance':launch_distance,
'launch_location':launch_location,
'trajectory':trajectory,
'hardness':hardness,
'hit_x':hit_x,
'hit_y':hit_y,
'index_play':index_play,
'play_id':play_id,
'start_time':start_time,
'end_time':end_time,
'is_pitch':is_pitch,
'type_type':type_type,
'type_ab':type_ab,
'event':event,
'event_type':event_type,
'rbi':rbi,
'away_score':away_score,
'home_score':home_score,
},strict=False
)
return df
def get_teams(self):
"""
Retrieves information about MLB teams from the MLB API and processes it into a Polars DataFrame.
Returns:
- mlb_teams_df (pl.DataFrame): A DataFrame containing team information, including team ID, city, name, franchise, abbreviation, parent organization ID, parent organization name, league ID, and league name.
"""
# Make API call to retrieve team information
teams = requests.get(url='https://statsapi.mlb.com/api/v1/teams/').json()
# Extract relevant data from the API response
mlb_teams_city = [x['franchiseName'] if 'franchiseName' in x else None for x in teams['teams']]
mlb_teams_name = [x['teamName'] if 'franchiseName' in x else None for x in teams['teams']]
mlb_teams_franchise = [x['name'] if 'franchiseName' in x else None for x in teams['teams']]
mlb_teams_id = [x['id'] if 'franchiseName' in x else None for x in teams['teams']]
mlb_teams_abb = [x['abbreviation'] if 'franchiseName' in x else None for x in teams['teams']]
mlb_teams_parent_id = [x['parentOrgId'] if 'parentOrgId' in x else None for x in teams['teams']]
mlb_teams_parent = [x['parentOrgName'] if 'parentOrgName' in x else None for x in teams['teams']]
mlb_teams_league_id = [x['league']['id'] if 'id' in x['league'] else None for x in teams['teams']]
mlb_teams_league_name = [x['league']['name'] if 'name' in x['league'] else None for x in teams['teams']]
# Create a Polars DataFrame with the extracted data
mlb_teams_df = pl.DataFrame(data={'team_id': mlb_teams_id,
'city': mlb_teams_franchise,
'name': mlb_teams_name,
'franchise': mlb_teams_franchise,
'abbreviation': mlb_teams_abb,
'parent_org_id': mlb_teams_parent_id,
'parent_org': mlb_teams_parent,
'league_id': mlb_teams_league_id,
'league_name': mlb_teams_league_name
}).unique().drop_nulls(subset=['team_id']).sort('team_id')
# Fill missing parent organization IDs with team IDs
mlb_teams_df = mlb_teams_df.with_columns(
pl.when(pl.col('parent_org_id').is_null())
.then(pl.col('team_id'))
.otherwise(pl.col('parent_org_id'))
.alias('parent_org_id')
)
# Fill missing parent organization names with franchise names
mlb_teams_df = mlb_teams_df.with_columns(
pl.when(pl.col('parent_org').is_null())
.then(pl.col('franchise'))
.otherwise(pl.col('parent_org'))
.alias('parent_org')
)
# Create a dictionary for mapping team IDs to abbreviations
abbreviation_dict = mlb_teams_df.select(['team_id', 'abbreviation']).to_dict(as_series=False)
abbreviation_map = {k: v for k, v in zip(abbreviation_dict['team_id'], abbreviation_dict['abbreviation'])}
# Create a DataFrame for parent organization abbreviations
abbreviation_df = mlb_teams_df.select(['team_id', 'abbreviation']).rename({'team_id': 'parent_org_id', 'abbreviation': 'parent_org_abbreviation'})
# Join the parent organization abbreviations with the main DataFrame
mlb_teams_df = mlb_teams_df.join(abbreviation_df, on='parent_org_id', how='left')
return mlb_teams_df
def get_leagues(self):
"""
Retrieves information about MLB leagues from the MLB API and processes it into a Polars DataFrame.
Returns:
- leagues_df (pl.DataFrame): A DataFrame containing league information, including league ID, league name, league abbreviation, and sport ID.
"""
# Make API call to retrieve league information
leagues = requests.get(url='https://statsapi.mlb.com/api/v1/leagues/').json()
# Extract relevant data from the API response
sport_id = [x['sport']['id'] if 'sport' in x else None for x in leagues['leagues']]
league_id = [x['id'] if 'id' in x else None for x in leagues['leagues']]
league_name = [x['name'] if 'name' in x else None for x in leagues['leagues']]
league_abbreviation = [x['abbreviation'] if 'abbreviation' in x else None for x in leagues['leagues']]
# Create a Polars DataFrame with the extracted data
leagues_df = pl.DataFrame(data={
'league_id': league_id,
'league_name': league_name,
'league_abbreviation': league_abbreviation,
'sport_id': sport_id,
})
return leagues_df
def get_player_games_list(self, player_id: int,
season: int,
start_date: str = None,
end_date: str = None,
sport_id: int = 1,
game_type: list = ['R'],
pitching: bool = True):
"""
Retrieves a list of game IDs for a specific player in a given season.
Parameters:
- player_id (int): The ID of the player.
- season (int): The season year for which to retrieve the game list.
- start_date (str): The start date (YYYY-MM-DD) of the range (default is January 1st of the specified season).
- end_date (str): The end date (YYYY-MM-DD) of the range (default is December 31st of the specified season).
- sport_id (int): The ID of the sport for which to retrieve player data.
- game_type (list): A list of game types to filter the schedule. Default is ['R'].
- pitching (bool): Return pitching games.
Returns:
- player_game_list (list): A list of game IDs in which the player participated during the specified season.
"""
# Set default start and end dates if not provided
if not start_date:
start_date = f'{season}-01-01'
if not end_date:
end_date = f'{season}-12-31'
# Determine the group based on the pitching flag
group = 'pitching' if pitching else 'hitting'
# Validate date format
date_pattern = re.compile(r'^\d{4}-\d{2}-\d{2}$')
if not date_pattern.match(start_date):
raise ValueError(f"start_date {start_date} is not in YYYY-MM-DD format")
if not date_pattern.match(end_date):
raise ValueError(f"end_date {end_date} is not in YYYY-MM-DD format")
# Convert game type list to a comma-separated string
game_type_str = ','.join([str(x) for x in game_type])
# Make API call to retrieve player game logs
response = requests.get(url=f'http://statsapi.mlb.com/api/v1/people/{player_id}?hydrate=stats(group={group},type=gameLog,season={season},startDate={start_date},endDate={end_date},sportId={sport_id},gameType=[{game_type_str}]),hydrations').json()
# Check if stats are available in the response
if 'stats' not in response['people'][0]:
print(f'No {group} games found for player {player_id} in season {season}')
return []
# Extract game IDs from the API response
player_game_list = [x['game']['gamePk'] for x in response['people'][0]['stats'][0]['splits']]
return player_game_list
def get_players(self, sport_id: int, season: int, game_type: list = ['R']):
"""
Retrieves data frame of players in a given league
Parameters:
- sport_id (int): The ID of the sport for which to retrieve player data.
- season (int): The season year for which to retrieve player data.
- game_type (list): A list of game types to filter the players. Default is ['R'].
Returns:
- player_df (pl.DataFrame): A DataFrame containing player information, including player ID, name, position, team, and age.
"""
game_type_str = ','.join([str(x) for x in game_type])
# If game type is 'S', fetch data from a different endpoint
if game_type_str == 'S':
# Fetch pitcher data
pitcher_data = requests.get(f'https://bdfed.stitch.mlbinfra.com/bdfed/stats/player?&env=prod&season={season}&sportId=1&stats=season&group=pitching&gameType=S&limit=1000000&offset=0&sortStat=inningsPitched&order=asc').json()
fullName_list = [x['playerFullName'] for x in pitcher_data['stats']]
firstName_list = [x['playerFirstName'] for x in pitcher_data['stats']]
lastName_list = [x['playerLastName'] for x in pitcher_data['stats']]
id_list = [x['playerId'] for x in pitcher_data['stats']]
position_list = [x['primaryPositionAbbrev'] for x in pitcher_data['stats']]
team_list = [x['teamId'] for x in pitcher_data['stats']]
df_pitcher = pl.DataFrame(data={
'player_id': id_list,
'first_name': firstName_list,
'last_name': lastName_list,
'name': fullName_list,
'position': position_list,
'team': team_list
})
# Fetch batter data
batter_data = requests.get(f'https://bdfed.stitch.mlbinfra.com/bdfed/stats/player?&env=prod&season={season}&sportId=1&stats=season&group=hitting&gameType=S&limit=1000000&offset=0').json()
fullName_list = [x['playerFullName'] for x in batter_data['stats']]
firstName_list = [x['playerFirstName'] for x in batter_data['stats']]
lastName_list = [x['playerLastName'] for x in batter_data['stats']]
id_list = [x['playerId'] for x in batter_data['stats']]
position_list = [x['primaryPositionAbbrev'] for x in batter_data['stats']]
team_list = [x['teamId'] for x in batter_data['stats']]
df_batter = pl.DataFrame(data={
'player_id': id_list,
'first_name': firstName_list,
'last_name': lastName_list,
'name': fullName_list,
'position': position_list,
'team': team_list
})
# Combine pitcher and batter data
df = pl.concat([df_pitcher, df_batter]).unique().drop_nulls(subset=['player_id']).sort('player_id')
else:
# Fetch player data for other game types
player_data = requests.get(url=f'https://statsapi.mlb.com/api/v1/sports/{sport_id}/players?season={season}&gameType=[{game_type_str}]').json()['people']
# Extract relevant data
fullName_list = [x['fullName'] for x in player_data]
firstName_list = [x['firstName'] for x in player_data]
lastName_list = [x['lastName'] for x in player_data]
id_list = [x['id'] for x in player_data]
position_list = [x['primaryPosition']['abbreviation'] if 'primaryPosition' in x else None for x in player_data]
team_list = [x['currentTeam']['id'] if 'currentTeam' in x else None for x in player_data]
weight_list = [x['weight'] if 'weight' in x else None for x in player_data]
height_list = [x['height'] if 'height' in x else None for x in player_data]
age_list = [x['currentAge'] if 'currentAge' in x else None for x in player_data]
birthDate_list = [x['birthDate'] if 'birthDate' in x else None for x in player_data]
df = pl.DataFrame(data={
'player_id': id_list,
'first_name': firstName_list,
'last_name': lastName_list,
'name': fullName_list,
'position': position_list,
'team': team_list,
'weight': weight_list,
'height': height_list,
'age': age_list,
'birthDate': birthDate_list
})
return df |