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