def getTodaysPlayers():
"""
Returns a list of player IDs belonging to players that played today
:return:
"""
data = scoreboardv2.ScoreboardV2().get_data_frames()[0]
player_ids = []
# print(data.to_string())
# print(list(data))
playing_team_ids = []
home_team_ids = data["HOME_TEAM_ID"].tolist()
# print(home_team_ids)
playing_team_ids += home_team_ids
# print(data.to_string())
away_team_ids = data["VISITOR_TEAM_ID"].tolist()
playing_team_ids += away_team_ids
for team_id in playing_team_ids:
# curr_team = [team for team in getAllNbaTeams()
# if team['id'] == team_id]
current_team_roster = commonteamroster.CommonTeamRoster(
team_id=team_id).get_data_frames()[0]
time.sleep(2)
for index, row in current_team_roster.iterrows():
player_id = row['PLAYER_ID']
player_ids.append(player_id)
print(player_ids)
return player_ids
def add_one_team_to_league_df(team_id, season_end):
team_info = teams.find_team_name_by_id(team_id)
team_name = team_info.get('full_name')
print(team_name + '' + str(team_id))
team_roster = commonteamroster.CommonTeamRoster(
team_id=team_id,
season=season_end).common_team_roster.get_data_frame()
team_df = team_roster[[
'PLAYER_ID', 'TeamID', 'SEASON', 'PLAYER', 'AGE', 'EXP'
]]
team_df = team_df.rename(
columns={
'PLAYER_ID': 'player_id',
'TeamID': 'team_id',
'SEASON': 'season_end',
'PLAYER': 'player_name',
'AGE': 'age',
'EXP': 'exp'
})
team_df['team_name'] = team_name
#league_df = league_df.append(team_df)
conn = pg2.connect(dbname='postgres', host="localhost")
conn.autocommit = True
engine = create_engine(
'postgresql+psycopg2://jacobpress:bocaj29@localhost/wins_contr')
team_df.to_sql('league_rosters',
con=engine,
if_exists='append',
index=False)
conn.close()
def create_roster(season, team, struc):
response = ctr.CommonTeamRoster(season=season, team_id=team)
content = json.loads(response.get_json())
# transform contents into dataframe
results = content['resultSets'][0]
headers = results['headers']
rows = results['rowSet']
team_roster = pd.DataFrame(rows)
team_roster.columns = headers
if struc == 'df':
roster = team_roster
elif struc == 'list':
roster = team_roster['PLAYER'].tolist()
else:
print('\nIncorrect data structure input. Use either "list" or "df".\n')
return roster
def roster(team, season):
team = teams.find_teams_by_full_name(team)
team = team[0]
team = commonteamroster.CommonTeamRoster(team_id=team.get("id"),
season=season)
team = (team.get_data_frames())[0]
return team['PLAYER']
def get_roster_stats():
try:
roster = commonteamroster.CommonTeamRoster(season='2018-19',
team_id=miami_heat_team_id)
roster_stats = roster.get_dict()
return processnbadict(roster_stats['resultSets'][0]) #array []
except Exception as e:
return str(e)
def insert_players(cur, conn, id):
roster = commonteamroster.CommonTeamRoster(team_id=id).get_dict()
player_ids = []
names = []
for player in roster['resultSets'][0]['rowSet']:
if (player[-3] != 'R' and int(player[11]) >= 4):
player_ids.append(player[-1])
names.append(player[3])
for i in range(len(player_ids)):
cur.execute(
'INSERT INTO players (player_id, name, team_id) VALUES (?,?,?)',
(player_ids[i], names[i], id))
conn.commit()
def getRosterFromId(self, my_team_id="1610612744", my_season="2018-19"):
try:
roster_info = commonteamroster.CommonTeamRoster(season=my_season,
team_id=my_team_id)
roster = roster_info.get_dict()
a = roster['resultSets']
b = a[0]
c = b['rowSet']
my_players = []
for player in c:
my_players.append(player[3])
return my_players
except:
raise Exception("Team ID not valid")
async def roster(self, ctx, season_year, *, object_search):
try:
object_row = (sheet.find(object_search).row)
object_column = (sheet.find(object_search).col)
object_id = sheet.cell(object_row, object_column - 1).value
object_id = str(object_id)
team_roster = commonteamroster.CommonTeamRoster(season=season_year,
team_id=object_id)
df_team_roster = team_roster.get_data_frames()
# ID found and roster data found
roster_player_name = df_team_roster[0]['PLAYER'].to_string(
index=False)
jersey_number = df_team_roster[0]['NUM'].to_string(index=False)
player_position = df_team_roster[0]['POSITION'].to_string(
index=False)
# columns converted to strings so that they display in one large column in embedd message
# embedd message limited in that they don't have table functionality and can only take 3 columns before formatting poorly
roster_embed = discord.Embed(
title=(f'{season_year} Roster for the {object_search}'),
colour=discord.Colour(0x0e1cf5))
roster_embed.set_footer(text='gimme help | RIP Kobe')
roster_embed.set_image(
url=
'https://cdn.vox-cdn.com/thumbor/v1jR5XEgcDrnwTq_uSZt4ApiIqg=/1400x1400/filters:format(jpeg)/cdn.vox-cdn.com/uploads/chorus_asset/file/20025173/nba_covid_3_ringer_illo.jpg'
)
roster_embed.set_author(
name=f'Roster for the {season_year} {object_search}')
roster_embed.add_field(name='Players', value=roster_player_name)
roster_embed.add_field(name='Jersey #', value=jersey_number)
roster_embed.add_field(name='Position', value=player_position)
await ctx.send(embed=roster_embed)
# once again, value of variables added to embedded message and sent to chat
except (UnboundLocalError, gspread.exceptions.CellNotFound):
await ctx.send("""
I think you spelled it wrong hombre, make sure you're using this format: `gimme roster Toronto Raptors`.
Also, make sure you're not using shortened versions of names like `Raptors`, `Toronto`, or `TOR`.
""")
def scrapeTeamRosters():
teams = getAllNbaTeams()
# print(teams)
for team in teams:
# print(team)
team_id = team['id']
team_abbrev = team['abbreviation']
time.sleep(5)
current_team_roster = commonteamroster.CommonTeamRoster(
team_id=team_id).get_data_frames()[0]
print(current_team_roster)
filename = '{}datasets/rosters/{}_Roster.csv'.format(
filepath, team_abbrev)
current_team_roster.to_csv(filename, index=None, header=True)
print("finished {}'s roster".format(team_abbrev))
def create_league_team_df():
team_ids = [
1610612737, 1610612738, 1610612751, 1610612766, 1610612741, 1610612739,
1610612742, 1610612743, 1610612765, 1610612744, 1610612745, 1610612754,
1610612746, 1610612747, 1610612763, 1610612748, 1610612749, 1610612750,
1610612740, 1610612752, 1610612760, 1610612753, 1610612755, 1610612756,
1610612757, 1610612758, 1610612759, 1610612761, 1610612762, 1610612764
]
season_end_list = [2019, 2018, 2017, 2016, 2015, 2014]
for season_end in season_end_list:
for team_id in team_ids:
team_info = teams.find_team_name_by_id(team_id)
team_name = team_info.get('full_name')
print(team_name + '' + str(team_id))
team_roster = commonteamroster.CommonTeamRoster(
team_id=team_id,
season=season_end).common_team_roster.get_data_frame()
team_df = team_roster[[
'PLAYER_ID', 'TeamID', 'SEASON', 'PLAYER', 'AGE', 'EXP'
]]
team_df = team_df.rename(
columns={
'PLAYER_ID': 'player_id',
'TeamID': 'team_id',
'SEASON': 'season_end',
'PLAYER': 'player_name',
'AGE': 'age',
'EXP': 'exp'
})
team_df['team_name'] = team_name
#league_df = league_df.append(team_df)
conn = pg2.connect(dbname='postgres', host="localhost")
conn.autocommit = True
engine = create_engine(
'postgresql+psycopg2://jacobpress:bocaj29@localhost/wins_contr'
)
team_df.to_sql('league_rosters',
con=engine,
if_exists='append',
index=False)
conn.close()
sleep(15)
def get_team_common_info(team):
team_info = teaminfocommon.TeamInfoCommon(team).get_data_frames()[0]
team_info2 = teamdetails.TeamDetails(team).get_data_frames()[0]
team_stats = teaminfocommon.TeamInfoCommon(team).get_data_frames()[1]
team_players = teamdetails.TeamDetails(team).get_data_frames()[6]
team_roster_df = commonteamroster.CommonTeamRoster(1610612737).get_data_frames()[0]
player_columns=[{"name": i, "id": i} for i in team_roster_df.columns],
team_roster_df = team_roster_df.loc[team_roster_df['EXP']!="R"]
team_roster = team_roster_df.to_dict(orient='records')
name = team_info['TEAM_NAME'][0]
city = team_info['TEAM_CITY'][0]
team_conf = rank_name(team_info['CONF_RANK'][0]) + ' in ' + team_info['TEAM_CONFERENCE'][0] + " Conference"
team_div = rank_name(team_info['DIV_RANK'][0]) + ' in ' + team_info['TEAM_DIVISION'][0] + ' Division'
firstactive = 'Year Founded: ' + team_info['MIN_YEAR'][0]
lastactive = 'Last Active: ' + team_info['MAX_YEAR'][0]
# manager = 'Manager: ' + team_info2['GENERALMANAGER'][0]
head_coach = 'Head Coach: ' + team_info2['HEADCOACH'][0]
abrv = team_info['TEAM_ABBREVIATION'][0]
team_logo = f'https://stats.nba.com/media/img/teams/logos/{abrv}_logo.svg'
team_pts = str(team_stats['PTS_PG'][0])
team_ast = str(team_stats['AST_PG'][0])
# team_oreb = str(team_info['OREB'][0])
# team_dreb = str(team_info['DREB'][0])
team_reb = str(team_stats['REB_PG'][0])
team_opp_pts = str(team_stats['OPP_PTS_PG'][0])
team_pts_rank = rank_name(team_stats['PTS_RANK'][0])
team_ast_rank = rank_name(team_stats['AST_RANK'][0])
# team_oreb_rank = rank_name(team_info['OREB_RANK'][0])
# team_dreb_rank = rank_name(team_info['DREB_RANK'][0])
team_reb_rank = rank_name(team_stats['REB_RANK'][0])
team_opp_pts_rank = rank_name(team_stats['OPP_PTS_RANK'][0])
# ppg = team_info['PTS_PG'][0]
# rpg = team_info['REB_PG'][0]
# apg = team_info['AST_PG'][0]
return name, city, team_conf, team_div, firstactive, lastactive, head_coach, team_logo, \
team_pts, team_reb, team_ast, team_opp_pts,\
team_pts_rank, team_reb_rank, team_ast_rank,team_opp_pts_rank, team_roster
def run(self, dispatcher, tracker, domain):
last_message = tracker.current_state()['latest_message']['text']
try:
team_id, team_name = get_team_id(last_message)
except Exception as e:
print('Failed to get team information from your input. Error: {}'.
format(e))
try:
team_roster = commonteamroster.CommonTeamRoster(
team_id=team_id).coaches.get_dict()
team_name = team_name.replace('"', '')
dispatcher.utter_message('The coach of the {} is {}'.format(
team_name, json.dumps(team_roster['data'][0][5], indent=4)))
except Exception as e:
print(
'Failed to get roster information with the processed team id. E: {}'
.format(e))
return []
o += 1
p += 1
#getting team IDs given the names seen above
Team1 = [x for x in teams if x['full_name'] == a][0]
Team1_id = Team1['id']
Team2 = [x for x in teams if x['full_name'] == b][0]
Team2_id = Team2['id']
#find games played by a team, to see stats for the team for a given season
Team1_Current = teamgamelog.TeamGameLog(Team1_id).get_data_frames()[0]
Team2_Current = teamgamelog.TeamGameLog(Team2_id).get_data_frames()[0]
#find current roster for each team
Team1_Roster = commonteamroster.CommonTeamRoster(Team1_id).get_data_frames()[0]
Team2_Roster = commonteamroster.CommonTeamRoster(Team2_id).get_data_frames()[0]
#find player ids for everyone on both teams
Team1_PlayerIds = Team1_Roster[['PLAYER_ID']]
Team1_PlayerIds = convert(Team1_PlayerIds, 'PLAYER_ID')
Team2_PlayerIds = Team2_Roster[['PLAYER_ID']]
Team2_PlayerIds = convert(Team2_PlayerIds, 'PLAYER_ID')
#determining the lenght of each team
Team1_length = len(Team1_PlayerIds)
Team2_length = len(Team2_PlayerIds)
#getting info on all the players on each team for how succesfull each player is
Team1_PlayerInfo = []
def get_szn_teammates(tid, szn):
teammates = commonteamroster.CommonTeamRoster(team_id=tid, season=szn)
return [
d['PLAYER_ID']
for d in teammates.get_normalized_dict()['CommonTeamRoster']
]
for player in allPlayers:
if player["full_name"] == "LeBron James":
lebronsID = player["id"]
career = playercareerstats.PlayerCareerStats(player_id='{}'.format(lebronsID))
lebronCareer = career.season_totals_regular_season.get_data_frame()
lebronPlayoffs = career.season_totals_post_season.get_data_frame()
lebron_info = commonplayerinfo.CommonPlayerInfo(player_id="{}".format(lebronsID))
lebron_bio = lebron_info.common_player_info.get_data_frame() #Draft position, hometown, height, weight, etc
allTeams = teams.get_teams() #Team names and IDs
for l in allTeams:
if l["full_name"] == "Los Angeles Lakers":
lakersID = l["id"]
lakersRoster = commonteamroster.CommonTeamRoster(lakersID, season="2019-20")
lakersRosterData = lakersRoster.common_team_roster.get_data_frame()
standings19_20 = leaguestandingsv3.LeagueStandingsV3(season="2019-20")
standings19_20data = standings19_20.get_data_frames()[0] #Can get regular season team stats (WL Record) from this
#%% Basketball-Reference Examples
stevosAdvanced = pd.DataFrame()
for year in range(2000,2020): #Search for the big kiwi in all data
temp = pd.read_excel("./Basketball-Reference/advanced{}.xlsx".format(yearConvert(year)))
for index, row in temp.iterrows():
if "Steven Adams" in row["Player"]:
stevo = row
stevo["Year"] = yearConvert(year)
stevosAdvanced = stevosAdvanced.append(stevo, ignore_index=True)
print("Steven Adams' Advanced Stats:")
with open(path, 'w') as outFile:
outFile.write(",".join(headers) + "\n")
for row in rows:
rowStr = [str(r) for r in row]
outFile.write(",".join(rowStr) + "\n")
# Simple Team info such as location and name
teamDataPath = './data/teams.csv'
if not os.path.exists(teamDataPath):
listOfDicToFile(teams.get_teams(), teamDataPath)
teamsInfo = csvToArrayDic(teamDataPath)
for team in teamsInfo:
rosterPath = './data/' + team['abbreviation'] + '_roster.csv'
print(rosterPath)
if not os.path.exists(rosterPath):
time.sleep(1)
resp = commonteamroster.CommonTeamRoster(team['id'], proxy=False)
rosterDict = resp.common_team_roster.get_dict()
headers = rosterDict['headers']
data = rosterDict['data']
headersAndRowsToCSV(headers, data, rosterPath)
rosterInfo = csvToArrayDic(rosterPath)
gameLogPath = './data/gameLogs.csv'
gameLog = leaguegamelog.LeagueGameLog(proxy=False)
gameLogDict = gameLog.league_game_log.get_dict()
headers = gameLogDict['headers']
data = gameLogDict['data']
headersAndRowsToCSV(headers, data, gameLogPath)
stephen_curry = players.find_player_by_id(201939)
print(stephen_curry['full_name'])
from nba_api.stats.endpoints import commonplayerinfo
# Basic Request
player_info = commonplayerinfo.CommonPlayerInfo(player_id=2544)
lebron_stats = player_info.player_headline_stats.get_dict()
print(lebron_stats['data'])
from nba_api.stats.endpoints import commonteamroster
import json
roster_info = commonteamroster.CommonTeamRoster(season=2017,
team_id=1610612739)
roster_cavs = roster_info.get_dict()
with open('nba.json', 'w') as fp:
json.dump(roster_cavs, fp, indent=3)
a = roster_cavs['resultSets']
b = a[0]
c = b['rowSet']
for player in c:
print(player[3])
from nba_api.stats.endpoints import leagueleaders
league_info = leagueleaders.LeagueLeaders(
from nba_api.stats.static import teams
from nba_api.stats.endpoints import commonteamroster
import os, time
nba_teams = teams.get_teams()
dirtowrite = 'C://Users//mpollard//Documents//GitHub//nba_api//output//'
for team in nba_teams:
roster = commonteamroster.CommonTeamRoster(team_id=team['id'])
roster = roster.get_data_frames()[0]
filename = team['full_name'] + '-roster.csv'
roster.to_csv(os.path.join(dirtowrite, filename))
time.sleep(10)
from nba_api.stats.endpoints import commonplayerinfo, commonteamroster
from nba_api.stats.static import players, teams
import time
import pandas as pd
df = pd.DataFrame(columns=["realname","team"])
year = '1946'
for team in teams.get_teams():
print(team)
for i in range(1945,2018):
team_roster = commonteamroster.CommonTeamRoster(season=str(i)+'-'+str(i+1)[2:],team_id=team['id'])
print(team_roster.common_team_roster.get_dict()['data'])
for player in team_roster.common_team_roster.get_dict()['data']:
df = df.append({'realname':player[3], 'team':team['abbreviation']}, ignore_index=True)
print({'realname':player[3], 'team':team['abbreviation']})
time.sleep(2)
df.drop_duplicates(inplace=True)
df.to_csv('players.csv')
def get_roster(team_abbr):
roster = commonteamroster.CommonTeamRoster(
teams.find_team_by_abbreviation(team_abbr.lower())["id"])
return roster.get_data_frames()[0]
num_to_team = {1610612737:"Atlanta_Hawks",1610612738:"Boston_Celtics", 1610612739:"Cleveland_Cavaliers", 1610612740:"New_Orleans_Pelicans", 1610612741:"Chicago_Bulls", 1610612742: "Dallas_Mavericks",1610612743:"Denver_Nuggets", 1610612744:"Golden_State_Warriors",1610612745:"Houston_Rockets", 1610612746:"Los_Angeles_Clippers", 1610612747: "Los_Angeles_Lakers", 1610612748: "Miami_Heat",1610612750:"Minnesota_Timberwolves", 1610612751:"Brooklyn_Nets", 1610612752:"New_York_Knicks", 1610612753:"Orlando_Magic", 1610612754: "Indiana_Pacers", 1610612755: "Philadelphia_76ers", 1610612756:"Phoenix_Suns", 1610612757:"Portland_Trail_Blazers", 1610612758:"Sacramento_Kings",1610612759:"San_Antonio_Spurs", 1610612760:"Oklahoma_City_Thunder", 1610612749:"Milwaukee_Bucks", 1610612762:"Utah_Jazz", 1610612763:"Menphis_Grizzlies",1610612764:"Washington_Wizards", 1610612765:"Detroit_Pistons", 1610612766:"Charlotte_Hornets", 1610612761:"Toronto_Raptors"}
#get teams
teams_dict = commonteamyears.CommonTeamYears()
teams_dict = teams_dict.team_years.get_dict()
teams = []
for teamNum in range(30):
teams.append(teams_dict["data"][teamNum])
#get rosters
rosters = []
for team in teams:
time.sleep(1)
rosters_dict = commonteamroster.CommonTeamRoster(season="2018-19",team_id=team[1])
rosters_dict = rosters_dict.common_team_roster.get_dict()
rosters.append(rosters_dict["data"])
db = mysql.connector.connect(
host = database.databaseInfo["host"],
user = database.databaseInfo["user"],
passwd = database.databaseInfo["passwd"],
database = database.databaseInfo["database"]
)
cursor = db.cursor()
for team in teams:
sql = "CREATE TABLE IF NOT EXISTS "
sql += str(num_to_team[team[1]]) + "_Roster (teamid INT, playerid INT, playername VARCHAR(255), num INT, position VARCHAR(255), height VARCHAR(255), weight INT, age INT, PRIMARY KEY (playerid))"
cursor.execute(sql)
teamRegularSeasonStandings = {}
for year, standingsData in allRegularSeasonStandings.items():
for index, row in standingsData.iterrows():
if teamInput in row[
"TeamName"]: #Change to teamID == row["TeamID"] to see technical team data (Ex Seattle+OKC has same ID)
teamRegularSeasonStandings[year] = row
teamRegularSeasonWinPercentages = {}
for year, seasonSeries in teamRegularSeasonStandings.items():
teamRegularSeasonWinPercentages[year] = seasonSeries["WinPCT"]
#%% Get the team's roster for every year
teamAllRosters = {}
for year in range(2000, 2020):
time.sleep(2) #Needed to avoid timeouts
teamRoster = commonteamroster.CommonTeamRoster(
teamID, season=yearConvert(year))
teamRosterData = teamRoster.common_team_roster.get_data_frame()
teamAllRosters[yearConvert(year)] = teamRosterData
#%% Get advanced stats for each player on the roster every year
teamAdvancedStats = {}
for year, rosterDF in teamAllRosters.items():
#For that year, make a DataFrame with all Advanced Stats for each player
currentYearDF = pd.DataFrame()
advanced = pd.read_excel(
"./Basketball-Reference/advanced{}.xlsx".format(year))
for advancedIndex, advancedRow in advanced.iterrows():
for rosterIndex, rosterRow in rosterDF.iterrows():
if rosterRow["PLAYER"] in advancedRow["Player"]:
if advancedRow["Tm"] == teamAbbreviation:
# ^^ Removes stats from players not recorded on that team
