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import requests
import pandas as pd
import numpy as np
from datetime import datetime
from tqdm import tqdm
import time
from pytz import timezone
class MLB_Scrape:
# def __init__(self):
# # Initialize your class here if needed
# pass
def get_sport_id(self):
df = pd.DataFrame(requests.get(url=f'https://statsapi.mlb.com/api/v1/sports').json()['sports']).set_index('id')
return df
def get_sport_id_check(self,sport_id):
sport_id_df = self.get_sport_id()
if sport_id not in sport_id_df.index:
print('Please Select a New Sport ID from the following')
print(sport_id_df)
return False
return True
def get_schedule(self,year_input=2023,
sport_id=1,
start_date='YYYY-MM-DD',
end_date='YYYY-MM-DD',
final=True,
regular=True,
spring=False):
# Get MLB Schedule
if not self.get_sport_id_check(sport_id=sport_id):
return
if regular == True:
game_call = requests.get(url=f'https://statsapi.mlb.com/api/v1/schedule/?sportId={sport_id}&gameTypes=R&season={year_input}&hydrate=lineup,players').json()
print(f'https://statsapi.mlb.com/api/v1/schedule/?sportId={sport_id}&gameTypes=R&season={year_input}&hydrate=lineup,players')
elif spring == True:
print('spring')
game_call = requests.get(url=f'https://statsapi.mlb.com/api/v1/schedule/?sportId={sport_id}&gameTypes=S&season={year_input}&hydrate=lineup,players').json()
print(f'https://statsapi.mlb.com/api/v1/schedule/?sportId={sport_id}&gameTypes=S&season={year_input}&hydrate=lineup,players')
else:
game_call = requests.get(url=f'https://statsapi.mlb.com/api/v1/schedule/?sportId={sport_id}&season={year_input}&hydrate=lineup,players').json()
# Grab data from MLB Schedule (game id, away, home, state)
game_list = [item for sublist in [[y['gamePk'] for y in x['games']] for x in game_call['dates']] for item in sublist]
time_list = [item for sublist in [[y['gameDate'] for y in x['games']] for x in game_call['dates']] for item in sublist]
date_list = [item for sublist in [[y['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']['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']['name'] for y in x['games']] for x in game_call['dates']] for item in sublist]
state_list = [item for sublist in [[y['status']['codedGameState'] for y in x['games']] for x in game_call['dates']] for item in sublist]
venue_id = [item for sublist in [[y['venue']['id'] for y in x['games']] for x in game_call['dates']] for item in sublist]
venue_name = [item for sublist in [[y['venue']['name'] for y in x['games']] for x in game_call['dates']] for item in sublist]
game_df = pd.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})
# game_list = [item for sublist in [[y['gamePk'] for y in x['games']] for x in game_call['dates']] for item in sublist]
# date_list = [item for sublist in [[y['officialDate'] for y in x['games']] for x in game_call['dates']] for item in sublist]
# cancel_list = [item for sublist in [[y['status']['codedGameState'] for y in x['games']] for x in game_call['dates']] for item in sublist]
# game_df = pd.DataFrame(data={'game_id':game_list,'date':date_list,'state':cancel_list})
#game_df = pd.concat([game_df,game_df])
if len(game_df) == 0:
return 'Schedule Length of 0, please select different parameters.'
game_df['date'] = pd.to_datetime(game_df['date']).dt.date
#game_df['time'] = game_df['time'].dt.tz_localize('UTC')
#game_df['time'] = game_df['time'].dt.tz_localize('UTC')
game_df['time'] = pd.to_datetime(game_df['time'])
eastern = timezone('US/Eastern')
game_df['time'] = game_df['time'].dt.tz_convert(eastern)
game_df['time'] = game_df['time'].dt.strftime("%I:%M %p EST")#.dt.time
if not start_date == 'YYYY-MM-DD' or not end_date == 'YYYY-MM-DD':
try:
start_date = datetime.strptime(start_date, "%Y-%m-%d").date()
end_date = datetime.strptime(end_date, "%Y-%m-%d").date()
game_df = game_df[(game_df['date'] >= start_date) & (game_df['date'] <= end_date)]
except ValueError:
return 'Please use YYYY-MM-DD Format for Start and End Dates'
if final:
game_df = game_df[game_df['state'] == 'F'].drop_duplicates(subset='game_id').reset_index(drop=True)
game_df = game_df.drop_duplicates(subset='game_id').reset_index(drop=True)
if len(game_df) == 0:
return 'Schedule Length of 0, please select different parameters.'
return game_df
def get_data(self,game_list_input = [748540]):
data_total = []
#n_count = 0
print('This May Take a While. Progress Bar shows Completion of Data Retrieval.')
for i in tqdm(range(len(game_list_input)), desc="Processing", unit="iteration"):
#for game_id_select in game_list:
# if n_count%50 == 0:
# print(n_count)
r = requests.get(f'https://statsapi.mlb.com/api/v1.1/game/{game_list_input[i]}/feed/live')
data_total.append(r.json())
#n_count = n_count + 1
return data_total
def get_data_df(self,data_list):
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 = []
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 = []
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 = []
#data[0]['liveData']['plays']['allPlays'][32]['playEvents'][-1]['details']['call']['code'] in ['VP']
for data in data_list:
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']:
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 np.nan)
if 'batter' in ab_list['matchup']:
batter_name.append(ab_list['matchup']['batter']['fullName'] if 'fullName' in ab_list['matchup']['batter'] else np.nan)
else:
batter_name.append(np.nan)
batter_hand.append(ab_list['matchup']['batSide']['code'] if 'batSide' in ab_list['matchup'] else np.nan)
pitcher_id.append(ab_list['matchup']['pitcher']['id'] if 'pitcher' in ab_list['matchup'] else np.nan)
if 'pitcher' in ab_list['matchup']:
pitcher_name.append(ab_list['matchup']['pitcher']['fullName'] if 'fullName' in ab_list['matchup']['pitcher'] else np.nan)
else:
pitcher_name.append(np.nan)
#pitcher_name.append(ab_list['matchup']['pitcher']['fullName'] if 'pitcher' in ab_list['matchup'] else np.nan)
pitcher_hand.append(ab_list['matchup']['pitchHand']['code'] if 'pitchHand' in ab_list['matchup'] else np.nan)
# batter_id.append(ab_list['matchup']['batter']['id'] if 'batter' in ab_list['matchup'] else np.nan)
# batter_name.append(ab_list['matchup']['batter']['fullName'] if 'batter' in ab_list['matchup'] else np.nan)
# batter_hand.append(ab_list['matchup']['batSide']['code'] if 'batSide' in ab_list['matchup'] else np.nan)
# pitcher_id.append(ab_list['matchup']['pitcher']['id'] if 'pitcher' in ab_list['matchup'] else np.nan)
# pitcher_name.append(ab_list['matchup']['pitcher']['fullName'] if 'pitcher' in ab_list['matchup'] else np.nan)
# pitcher_hand.append(ab_list['matchup']['pitchHand']['code'] if 'pitchHand' in ab_list['matchup'] else np.nan)
if ab_list['about']['isTopInning']:
batter_team.append(data['gameData']['teams']['away']['abbreviation'] if 'away' in data['gameData']['teams'] else np.nan)
batter_team_id.append(data['gameData']['teams']['away']['id'] if 'away' in data['gameData']['teams'] else np.nan)
pitcher_team.append(data['gameData']['teams']['home']['abbreviation'] if 'home' in data['gameData']['teams'] else np.nan)
pitcher_team_id.append(data['gameData']['teams']['away']['id'] if 'away' in data['gameData']['teams'] else np.nan)
else:
batter_team.append(data['gameData']['teams']['home']['abbreviation'] if 'home' in data['gameData']['teams'] else np.nan)
batter_team_id.append(data['gameData']['teams']['home']['id'] if 'home' in data['gameData']['teams'] else np.nan)
pitcher_team.append(data['gameData']['teams']['away']['abbreviation'] if 'away' in data['gameData']['teams'] else np.nan)
pitcher_team_id.append(data['gameData']['teams']['home']['id'] if 'home' in data['gameData']['teams'] else np.nan)
play_description.append(ab_list['playEvents'][n]['details']['description'] if 'description' in ab_list['playEvents'][n]['details'] else np.nan)
play_code.append(ab_list['playEvents'][n]['details']['code'] if 'code' in ab_list['playEvents'][n]['details'] else np.nan)
in_play.append(ab_list['playEvents'][n]['details']['isInPlay'] if 'isInPlay' in ab_list['playEvents'][n]['details'] else np.nan)
is_strike.append(ab_list['playEvents'][n]['details']['isStrike'] if 'isStrike' in ab_list['playEvents'][n]['details'] else np.nan)
if 'details' in ab_list['playEvents'][n]:
is_swing.append(True if ab_list['playEvents'][n]['details']['code'] in swing_list else np.nan)
is_whiff.append(True if ab_list['playEvents'][n]['details']['code'] in whiff_list else np.nan)
else:
is_swing.append(np.nan)
is_whiff.append(np.nan)
#is_out.append(ab_list['playEvents'][n]['details']['isBall'] if 'isBall' in ab_list['playEvents'][n]['details'] else np.nan)
is_ball.append(ab_list['playEvents'][n]['details']['isOut'] if 'isOut' in ab_list['playEvents'][n]['details'] else np.nan)
is_review.append(ab_list['playEvents'][n]['details']['hasReview'] if 'hasReview' in ab_list['playEvents'][n]['details'] else np.nan)
pitch_type.append(ab_list['playEvents'][n]['details']['type']['code'] if 'type' in ab_list['playEvents'][n]['details'] else np.nan)
pitch_description.append(ab_list['playEvents'][n]['details']['type']['description'] if 'type' in ab_list['playEvents'][n]['details'] else np.nan)
#if ab_list['playEvents'][n]['isPitch'] == True:
if ab_list['playEvents'][n]['pitchNumber'] == 1:
ab_number.append(ab_list['playEvents'][n]['atBatIndex'] if 'atBatIndex' in ab_list['playEvents'][n] else np.nan)
strikes.append(0)
balls.append(0)
outs.append(0)
else:
ab_number.append(ab_list['playEvents'][n]['atBatIndex'] if 'atBatIndex' in ab_list['playEvents'][n] else np.nan)
strikes.append(ab_list['playEvents'][n-1]['count']['strikes'] if 'strikes' in ab_list['playEvents'][n-1]['count'] else np.nan)
balls.append(ab_list['playEvents'][n-1]['count']['balls'] if 'balls' in ab_list['playEvents'][n-1]['count'] else np.nan)
outs.append(ab_list['playEvents'][n-1]['count']['outs'] if 'outs' in ab_list['playEvents'][n-1]['count'] else np.nan)
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 np.nan)
end_speed.append(ab_list['playEvents'][n]['pitchData']['endSpeed'] if 'endSpeed' in ab_list['playEvents'][n]['pitchData'] else np.nan)
sz_top.append(ab_list['playEvents'][n]['pitchData']['strikeZoneTop'] if 'strikeZoneTop' in ab_list['playEvents'][n]['pitchData'] else np.nan)
sz_bot.append(ab_list['playEvents'][n]['pitchData']['strikeZoneBottom'] if 'strikeZoneBottom' in ab_list['playEvents'][n]['pitchData'] else np.nan)
x.append(ab_list['playEvents'][n]['pitchData']['coordinates']['x'] if 'x' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
y.append(ab_list['playEvents'][n]['pitchData']['coordinates']['y'] if 'y' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
ax.append(ab_list['playEvents'][n]['pitchData']['coordinates']['aX'] if 'aX' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
ay.append(ab_list['playEvents'][n]['pitchData']['coordinates']['aY'] if 'aY' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
az.append(ab_list['playEvents'][n]['pitchData']['coordinates']['aZ'] if 'aZ' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
pfxx.append(ab_list['playEvents'][n]['pitchData']['coordinates']['pfxX'] if 'pfxX' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
pfxz.append(ab_list['playEvents'][n]['pitchData']['coordinates']['pfxZ'] if 'pfxZ' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
px.append(ab_list['playEvents'][n]['pitchData']['coordinates']['pX'] if 'pX' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
pz.append(ab_list['playEvents'][n]['pitchData']['coordinates']['pZ'] if 'pZ' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
vx0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['vX0'] if 'vX0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
vy0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['vY0'] if 'vY0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
vz0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['vZ0'] if 'vZ0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
x0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['x0'] if 'x0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
y0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['y0'] if 'y0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
z0.append(ab_list['playEvents'][n]['pitchData']['coordinates']['z0'] if 'z0' in ab_list['playEvents'][n]['pitchData']['coordinates'] else np.nan)
zone.append(ab_list['playEvents'][n]['pitchData']['zone'] if 'zone' in ab_list['playEvents'][n]['pitchData'] else np.nan)
type_confidence.append(ab_list['playEvents'][n]['pitchData']['typeConfidence'] if 'typeConfidence' in ab_list['playEvents'][n]['pitchData'] else np.nan)
plate_time.append(ab_list['playEvents'][n]['pitchData']['plateTime'] if 'plateTime' in ab_list['playEvents'][n]['pitchData'] else np.nan)
extension.append(ab_list['playEvents'][n]['pitchData']['extension'] if 'extension' in ab_list['playEvents'][n]['pitchData'] else np.nan)
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 np.nan)
spin_direction.append(ab_list['playEvents'][n]['pitchData']['breaks']['spinDirection'] if 'spinDirection' in ab_list['playEvents'][n]['pitchData']['breaks'] else np.nan)
ivb.append(ab_list['playEvents'][n]['pitchData']['breaks']['breakVerticalInduced'] if 'breakVerticalInduced' in ab_list['playEvents'][n]['pitchData']['breaks'] else np.nan)
hb.append(ab_list['playEvents'][n]['pitchData']['breaks']['breakHorizontal'] if 'breakHorizontal' in ab_list['playEvents'][n]['pitchData']['breaks'] else np.nan)
else:
start_speed.append(np.nan)
end_speed.append(np.nan)
sz_top.append(np.nan)
sz_bot.append(np.nan)
x.append(np.nan)
y.append(np.nan)
ax.append(np.nan)
ay.append(np.nan)
az.append(np.nan)
pfxx.append(np.nan)
pfxz.append(np.nan)
px.append(np.nan)
pz.append(np.nan)
vx0.append(np.nan)
vy0.append(np.nan)
vz0.append(np.nan)
x0.append(np.nan)
y0.append(np.nan)
z0.append(np.nan)
zone.append(np.nan)
type_confidence.append(np.nan)
plate_time.append(np.nan)
extension.append(np.nan)
spin_rate.append(np.nan)
spin_direction.append(np.nan)
ivb.append(np.nan)
hb.append(np.nan)
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 np.nan)
launch_angle.append(ab_list['playEvents'][n]['hitData']['launchAngle'] if 'launchAngle' in ab_list['playEvents'][n]['hitData'] else np.nan)
launch_distance.append(ab_list['playEvents'][n]['hitData']['totalDistance'] if 'totalDistance' in ab_list['playEvents'][n]['hitData'] else np.nan)
launch_location.append(ab_list['playEvents'][n]['hitData']['location'] if 'location' in ab_list['playEvents'][n]['hitData'] else np.nan)
trajectory.append(ab_list['playEvents'][n]['hitData']['trajectory'] if 'trajectory' in ab_list['playEvents'][n]['hitData'] else np.nan)
hardness.append(ab_list['playEvents'][n]['hitData']['hardness'] if 'hardness' in ab_list['playEvents'][n]['hitData'] else np.nan)
hit_x.append(ab_list['playEvents'][n]['hitData']['coordinates']['coordX'] if 'coordX' in ab_list['playEvents'][n]['hitData']['coordinates'] else np.nan)
hit_y.append(ab_list['playEvents'][n]['hitData']['coordinates']['coordY'] if 'coordY' in ab_list['playEvents'][n]['hitData']['coordinates'] else np.nan)
else:
launch_speed.append(np.nan)
launch_angle.append(np.nan)
launch_distance.append(np.nan)
launch_location.append(np.nan)
trajectory.append(np.nan)
hardness.append(np.nan)
hit_x.append(np.nan)
hit_y.append(np.nan)
index_play.append(ab_list['playEvents'][n]['index'] if 'index' in ab_list['playEvents'][n] else np.nan)
play_id.append(ab_list['playEvents'][n]['playId'] if 'playId' in ab_list['playEvents'][n] else np.nan)
start_time.append(ab_list['playEvents'][n]['startTime'] if 'startTime' in ab_list['playEvents'][n] else np.nan)
end_time.append(ab_list['playEvents'][n]['endTime'] if 'endTime' in ab_list['playEvents'][n] else np.nan)
is_pitch.append(ab_list['playEvents'][n]['isPitch'] if 'isPitch' in ab_list['playEvents'][n] else np.nan)
type_type.append(ab_list['playEvents'][n]['type'] if 'type' in ab_list['playEvents'][n] else np.nan)
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 np.nan)
event.append(data['liveData']['plays']['allPlays'][ab_id]['result']['event'] if 'event' in data['liveData']['plays']['allPlays'][ab_id]['result'] else np.nan)
event_type.append(data['liveData']['plays']['allPlays'][ab_id]['result']['eventType'] if 'eventType' in data['liveData']['plays']['allPlays'][ab_id]['result'] else np.nan)
rbi.append(data['liveData']['plays']['allPlays'][ab_id]['result']['rbi'] if 'rbi' in data['liveData']['plays']['allPlays'][ab_id]['result'] else np.nan)
away_score.append(data['liveData']['plays']['allPlays'][ab_id]['result']['awayScore'] if 'awayScore' in data['liveData']['plays']['allPlays'][ab_id]['result'] else np.nan)
home_score.append(data['liveData']['plays']['allPlays'][ab_id]['result']['homeScore'] if 'homeScore' in data['liveData']['plays']['allPlays'][ab_id]['result'] else np.nan)
is_out.append(data['liveData']['plays']['allPlays'][ab_id]['result']['isOut'] if 'isOut' in data['liveData']['plays']['allPlays'][ab_id]['result'] else np.nan)
else:
type_ab.append(np.nan)
event.append(np.nan)
event_type.append(np.nan)
rbi.append(np.nan)
away_score.append(np.nan)
home_score.append(np.nan)
is_out.append(np.nan)
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 np.nan)
batter_name.append(ab_list['matchup']['batter']['fullName'] if 'batter' in ab_list['matchup'] else np.nan)
batter_hand.append(ab_list['matchup']['batSide']['code'] if 'batSide' in ab_list['matchup'] else np.nan)
pitcher_id.append(ab_list['matchup']['pitcher']['id'] if 'pitcher' in ab_list['matchup'] else np.nan)
pitcher_name.append(ab_list['matchup']['pitcher']['fullName'] if 'pitcher' in ab_list['matchup'] else np.nan)
pitcher_hand.append(ab_list['matchup']['pitchHand']['code'] if 'pitchHand' in ab_list['matchup'] else np.nan)
if ab_list['about']['isTopInning']:
batter_team.append(data['gameData']['teams']['away']['abbreviation'] if 'away' in data['gameData']['teams'] else np.nan)
batter_team_id.append(data['gameData']['teams']['away']['id'] if 'away' in data['gameData']['teams'] else np.nan)
pitcher_team.append(data['gameData']['teams']['home']['abbreviation'] if 'home' in data['gameData']['teams'] else np.nan)
pitcher_team_id.append(data['gameData']['teams']['away']['id'] if 'away' in data['gameData']['teams'] else np.nan)
else:
batter_team.append(data['gameData']['teams']['home']['abbreviation'] if 'home' in data['gameData']['teams'] else np.nan)
batter_team_id.append(data['gameData']['teams']['home']['id'] if 'home' in data['gameData']['teams'] else np.nan)
pitcher_team.append(data['gameData']['teams']['away']['abbreviation'] if 'away' in data['gameData']['teams'] else np.nan)
pitcher_team_id.append(data['gameData']['teams']['home']['id'] if 'home' in data['gameData']['teams'] else np.nan)
play_description.append(np.nan)
play_code.append(np.nan)
in_play.append(np.nan)
is_strike.append(np.nan)
is_ball.append(np.nan)
is_review.append(np.nan)
pitch_type.append(np.nan)
pitch_description.append(np.nan)
strikes.append(ab_list['playEvents'][n]['count']['balls'] if 'balls' in ab_list['playEvents'][n]['count'] else np.nan)
balls.append(ab_list['playEvents'][n]['count']['strikes'] if 'strikes' in ab_list['playEvents'][n]['count'] else np.nan)
outs.append(ab_list['playEvents'][n]['count']['outs'] if 'outs' in ab_list['playEvents'][n]['count'] else np.nan)
index_play.append(ab_list['playEvents'][n]['index'] if 'index' in ab_list['playEvents'][n] else np.nan)
play_id.append(ab_list['playEvents'][n]['playId'] if 'playId' in ab_list['playEvents'][n] else np.nan)
start_time.append(ab_list['playEvents'][n]['startTime'] if 'startTime' in ab_list['playEvents'][n] else np.nan)
end_time.append(ab_list['playEvents'][n]['endTime'] if 'endTime' in ab_list['playEvents'][n] else np.nan)
is_pitch.append(ab_list['playEvents'][n]['isPitch'] if 'isPitch' in ab_list['playEvents'][n] else np.nan)
type_type.append(ab_list['playEvents'][n]['type'] if 'type' in ab_list['playEvents'][n] else np.nan)
is_swing.append(np.nan)
is_whiff.append(np.nan)
start_speed.append(np.nan)
end_speed.append(np.nan)
sz_top.append(np.nan)
sz_bot.append(np.nan)
x.append(np.nan)
y.append(np.nan)
ax.append(np.nan)
ay.append(np.nan)
az.append(np.nan)
pfxx.append(np.nan)
pfxz.append(np.nan)
px.append(np.nan)
pz.append(np.nan)
vx0.append(np.nan)
vy0.append(np.nan)
vz0.append(np.nan)
x0.append(np.nan)
y0.append(np.nan)
z0.append(np.nan)
zone.append(np.nan)
type_confidence.append(np.nan)
plate_time.append(np.nan)
extension.append(np.nan)
spin_rate.append(np.nan)
spin_direction.append(np.nan)
ivb.append(np.nan)
hb.append(np.nan)
launch_speed.append(np.nan)
launch_angle.append(np.nan)
launch_distance.append(np.nan)
launch_location.append(np.nan)
trajectory.append(np.nan)
hardness.append(np.nan)
hit_x.append(np.nan)
hit_y.append(np.nan)
type_ab.append(np.nan)
ab_number.append(np.nan)
rbi.append(np.nan)
away_score.append(np.nan)
home_score.append(np.nan)
is_out.append(np.nan)
print({
'game_id':len(game_id),
'game_date':len(game_date),
'batter_id':len(batter_id),
'batter_name':len(batter_name),
'batter_hand':len(batter_hand),
'batter_team':len(batter_team),
'batter_team_id':len(batter_team_id),
'pitcher_id':len(pitcher_id),
'pitcher_name':len(pitcher_name),
'pitcher_hand':len(pitcher_hand),
'pitcher_team':len(pitcher_team),
'pitcher_team_id':len(pitcher_team_id),
'play_description':len(play_description),
'play_code':len(play_code),
'in_play':len(in_play),
'is_strike':len(is_strike),
'is_swing':len(is_swing),
'is_whiff':len(is_whiff),
'is_out':len(is_out),
'is_ball':len(is_ball),
'is_review':len(is_review),
'pitch_type':len(pitch_type),
'pitch_description':len(pitch_description),
'strikes':len(strikes),
'balls':len(balls),
'outs':len(outs),
'start_speed':len(start_speed),
'end_speed':len(end_speed),
'sz_top':len(sz_top),
'sz_bot':len(sz_bot),
'x':len(x),
'y':len(y),
'ax':len(ax),
'ay':len(ay),
'az':len(az),
'pfxx':len(pfxx),
'pfxz':len(pfxz),
'px':len(px),
'pz':len(pz),
'vx0':len(vx0),
'vy0':len(vy0),
'vz0':len(vz0),
'x0':len(x0),
'y0':len(y0),
'z0':len(z0),
'zone':len(zone),
'type_confidence':len(type_confidence),
'plate_time':len(plate_time),
'extension':len(extension),
'spin_rate':len(spin_rate),
'spin_direction':len(spin_direction),
'ivb':len(ivb),
'hb':len(hb),
'launch_speed':len(launch_speed),
'launch_angle':len(launch_angle),
'launch_distance':len(launch_distance),
'launch_location':len(launch_location),
'trajectory':len(trajectory),
'hardness':len(hardness),
'hit_x':len(hit_x),
'hit_y':len(hit_y),
'index_play':len(index_play),
'play_id':len(play_id),
'start_time':len(start_time),
'end_time':len(end_time),
'is_pitch':len(is_pitch),
'type_type':len(type_type),
'type_ab':len(type_ab),
'event':len(event),
'event_type':len(event_type),
'rbi':len(rbi),
'away_score':len(away_score),
'home_score':len(home_score),
}
)
df = pd.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,
'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,
'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,
'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,
}
)
return df
def get_players(self,sport_id=1):
player_data = requests.get(url=f'https://statsapi.mlb.com/api/v1/sports/{sport_id}/players').json()
#Select relevant data that will help distinguish players from one another
fullName_list = [x['fullName'] for x in player_data['people']]
id_list = [x['id'] for x in player_data['people']]
position_list = [x['primaryPosition']['abbreviation'] for x in player_data['people']]
team_list = [x['currentTeam']['id']for x in player_data['people']]
age_list = [x['currentAge']for x in player_data['people']]
player_df = pd.DataFrame(data={'player_id':id_list,
'name':fullName_list,
'position':position_list,
'team':team_list,
'age':age_list})
return player_df
def get_teams(self):
teams = requests.get(url='https://statsapi.mlb.com/api/v1/teams/').json()
#Select only teams that are at the MLB level
# mlb_teams_city = [x['franchiseName'] for x in teams['teams'] if x['sport']['name'] == 'Major League Baseball']
# mlb_teams_name = [x['teamName'] for x in teams['teams'] if x['sport']['name'] == 'Major League Baseball']
# mlb_teams_franchise = [x['name'] for x in teams['teams'] if x['sport']['name'] == 'Major League Baseball']
# mlb_teams_id = [x['id'] for x in teams['teams'] if x['sport']['name'] == 'Major League Baseball']
# mlb_teams_abb = [x['abbreviation'] for x in teams['teams'] if x['sport']['name'] == 'Major League Baseball']
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 dataframe of all the teams
mlb_teams_df = pd.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
}).drop_duplicates().dropna(subset=['team_id']).reset_index(drop=True).sort_values('team_id')
mlb_teams_df.loc[mlb_teams_df['parent_org_id'].isnull(),'parent_org_id'] = mlb_teams_df.loc[mlb_teams_df['parent_org_id'].isnull(),'team_id']
mlb_teams_df.loc[mlb_teams_df['parent_org'].isnull(),'parent_org'] = mlb_teams_df.loc[mlb_teams_df['parent_org'].isnull(),'franchise']
mlb_teams_df['parent_org_abbreviation'] = mlb_teams_df['parent_org_id'].map(mlb_teams_df.set_index('team_id')['abbreviation'].to_dict())
#mlb_teams_df.loc[mlb_teams_df.franchise.isin(mlb_teams_df.parent_org.unique()),'parent_org'] = mlb_teams_df.loc[mlb_teams_df.franchise.isin(mlb_teams_df.parent_org.unique()),'franchise']
return mlb_teams_df
def get_leagues(self):
leagues = requests.get(url='https://statsapi.mlb.com/api/v1/leagues/').json()
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']]
leagues_df = pd.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=691587):
player_game_list = [x['game']['gamePk'] for x in requests.get(url=f'http://statsapi.mlb.com/api/v1/people/{player_id}?hydrate=stats(type=gameLog,season=2023),hydrations').json()['people'][0]['stats'][0]['splits']]
return player_game_list
def get_team_schedule(self,year=2023,sport_id=1,mlb_team='Toronto Blue Jays'):
if not self.get_sport_id_check(sport_id=sport_id):
print('Please Select a New Sport ID from the following')
print(self.get_sport_id())
return False, False
schedule_df = self.get_schedule(year_input=year,sport_id=sport_id)
teams_df = self.get_teams().merge(self.get_leagues()).merge(self.get_sport_id(),left_on=['sport_id'],right_index=True,suffixes=['','_sport'])
teams_df = teams_df[teams_df['sport_id'] == sport_id]
team_abb_select = teams_df[teams_df['parent_org'] == mlb_team]['abbreviation'].values[0]
team_name_select = teams_df[teams_df['parent_org'] == mlb_team]['franchise'].values[0]
schedule_df = schedule_df[((schedule_df.away == team_name_select) | (schedule_df.home == team_name_select)) & (schedule_df.state == 'F')].reset_index(drop=True)
return schedule_df,teams_df
def get_team_game_data(self,year=2023,sport_id=1,mlb_team='Toronto Blue Jays'):
schedule_df,teams_df = self.get_team_schedule(year=year,sport_id=sport_id,mlb_team=mlb_team)
if not schedule_df:
return
data = self.get_data(schedule_df['game_id'][:])
df = self.get_data_df(data_list = data)
df['mlb_team'] = teams_df[teams_df['parent_org'] == mlb_team]['parent_org_abbreviation'].values[0]
df['level'] = teams_df[teams_df['parent_org'] == mlb_team]['abbreviation_sport'].values[0]
return df
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