def pullplayergl(rawjson=None,inurl='',outloc='',outcsv=None,stem=''):
if rawjson is None:
r=h.pulldown(inurl=inurl,outfile=outfile)
else:
r=rawjson
if 'copyright' in r:
print(r['copyright'])
dfgamelog=json_normalize(r['stats'][0]['splits'])
modnames={}
modnames.update(batchrename(dfgamelog.keys(),['playerstats'],stem='p.',oldstem='stat.'))
dfgamelog=polish(dfgamelog,
renamecat=['team','game'],
indexvar=['gameid'],
morerename=modnames,
stem=stem)
if outcsv is not None:
dfgamelog.to_csv(path_or_buf=outcsv+'.csv',encoding='utf-8')
return(dfgamelog)
def schedulesingleseason(outloc,apiurl,season):
thisurl=apiurl+'/schedule?startDate='+repr(season)[0:4]+'-07-01&endDate='+repr(season)[4:8]+'-06-30'
r=h.pulldown(inurl=thisurl)
# format data and create the index
df = pd.io.json.json_normalize(r['dates'],['games'])
df.rename(index=str, columns={'gamePk': 'gameid'},inplace=True)
df.set_index('gameid',inplace=True)
# get team information in there
df2=h.flatten(df,'teams',stem='t.')
dfa=h.flatten(df2,'t.away',stem='a.')
dfa2=h.flatten(dfa,'a.leagueRecord',stem='a.lr.')
dfh=h.flatten(df2,'t.home',stem='h.')
dfh2=h.flatten(dfh,'h.leagueRecord',stem='h.lr.')
df=df.join([dfa,dfa2,dfh,dfh2], how='outer')
df.drop(columns=['teams','h.leagueRecord','a.leagueRecord'],inplace=True)
# get venue information
dfv=h.flatten(df,'venue',stem='v.')
df=df.join(dfv,how='outer')
df.drop(columns=['venue'],inplace=True)
# drop content and status since they are not useful
df.drop(columns=['content','status'],inplace=True)
return(df)
def pullteamstats(rawjson=None,inurl='',outloc='',outcsv=None,stem=''):
if rawjson is None:
r=h.pulldown(inurl=inurl,outfile=outfile)
else:
r=rawjson
if 'copyright' in r:
print(r['copyright'])
#####################################################
# pull team metadata
dfteam=json_normalize(r['teams'])
dfteam=polish(dfteam,
renamecat=['franchise','venue','conference','division','team2'],
indexvar=['teamid'],
morerename={'id':'teamid'},
dropvars=['teamStats','franchid2'],
stem=stem)
#####################################################
# pull team stats
r1=deepdivewithindex(r,['teams','ij','teamStats','ij'],['teams','ij','id'],ii=0)
rn=[{
#'teamid':rr['stickyindex'],
'type':rr['type']['displayName'],
'n':rr['splits'][0]['stat'],
'team':rr['splits'][0]['team'],
}
for rr in r1]
rrank=[{
#'teamid':rr['stickyindex'],
'type':rr['type']['displayName'],
'rank':rr['splits'][1]['stat'],
'team':rr['splits'][1]['team']
}
for rr in r1]
# convert ranks into integers
for rr in rrank:
for k in rr['rank']:
rr['rank'][k]=int(rr['rank'][k][:-2])
# switch to dataframe
dfn=json_normalize(rn)
dfrank=json_normalize(rrank)
dfteam=polish(dfn,renamecat=['team'],indexvar=['teamid'],stem=stem)
dfrank=polish(dfrank,renamecat=['team'],indexvar=['teamid'],stem=stem)
if outcsv is not None:
dfteam.to_csv(path_or_buf=outcsv+'_team.csv',encoding='utf-8')
dfn.to_csv(path_or_buf=outcsv+'_n.csv',encoding='utf-8')
dfrank.to_csv(path_or_buf=outcsv+'_rank.csv',encoding='utf-8')
return(dfteam,dfn,dfrank)
def pulllivefeed(rawjson=None,inurl='',outloc='',outcsv=None,stem=''): if rawjson is None: r=h.pulldown(inurl=inurl,outfile=outfile) else: r=rawjson if 'copyright' in r: print(r['copyright']) dfoff,dfplayers,dfteams,dfcoaches,dfplindex=pullboxscore(rawjson=r['liveData']['boxscore'],outcsv=outcsv) return(dfoff,dfplayers,dfteams,dfcoaches,dfplindex)
def multiplayergamestats2(games, apiurl, outloc=''):
gamestatlist = []
for gameid in games:
if outloc == '':
outds = ''
else:
outds = outloc + '/boxscore' + repr(gameid)
thisurl = apiurl + '/game/' + repr(gameid) + '/boxscore'
r = h.pulldown(inurl=thisurl, outfile=outds)
c = fillstats(r)
gamestatlist.append(c)
gamestats = pd.concat(gamestatlist,
keys=games,
names=['gameid', 'teamid', 'personid'],
sort=True)
return (gamestats)
def pullschedule(rawjson=None,inurl='',outloc='',outcsv=None,stem=''):
if rawjson is None:
r=h.pulldown(inurl=inurl,outfile=outfile)
else:
r=rawjson
if 'copyright' in r:
print(r['copyright'])
#####################################################
# pull query metadata, level 0
dfmeta0=json_normalize(r)
dfmeta0.drop(columns=['dates','copyright'],inplace=True)
#####################################################
# pull query metadata, level 1
dfmeta1=json_normalize(r['dates'])
dfmeta1.drop(columns=['games','events','matches'],inplace=True)
#####################################################
# pull game data
rr=deepdivewithindex(r,['dates','ij','games'],['dates','ij','date'],ii=0)
dfgames=json_normalize(rr)
# more extensive renaming due to the depth of the json
modnames={'stickyindex':'date','teams.home.score':'h.score','teams.away.score':'a.score'}
modnames.update(batchrename(dfgames.keys(),['team','leaguerecord'],stem='h.',oldstem='teams.home.'))
modnames.update(batchrename(dfgames.keys(),['team','leaguerecord'],stem='a.',oldstem='teams.away.'))
dfgames=polish(dfgames,
renamecat=['venue','game'],
indexvar=['gameid'],
morerename=modnames,
stem=stem)
if outcsv is not None:
dfmeta0.to_csv(path_or_buf=outcsv+'_meta0.csv',encoding='utf-8')
dfmeta1.to_csv(path_or_buf=outcsv+'_meta1.csv',encoding='utf-8')
dfgames.to_csv(path_or_buf=outcsv+'_games.csv',encoding='utf-8')
return(dfmeta0,dfmeta1,dfgames)
def pullplayergoals(rawjson=None,inurl='',outloc='',outcsv=None,stem=''): if rawjson is None: r=h.pulldown(inurl=inurl,outfile=outfile) else: r=rawjson if 'copyright' in r: print(r['copyright']) dfgoals=json_normalize(r['stats'][0]['splits'][0]) dfgoals=polish(dfgoals, renamecat=['playergoals'], indexvar=['season'], stem=stem) if outcsv is not None: dfgoals.to_csv(path_or_buf=outcsv+'.csv',encoding='utf-8') return(dfgoals)
def pullrosters(rawjson=None, inurl='', outloc='', outcsv=None, stem=''):
if rawjson is None:
r = h.pulldown(inurl=inurl, outfile=outfile)
else:
r = rawjson
if 'copyright' in r:
print(r['copyright'])
#####################################################
# pull team metadata
dfteam = json_normalize(r['teams'])
# move to standardized short names
#renamedict=batchrename(dfteam.keys(),
# ['franchise','venue','conference','division','team2'],
# stem=stem)
#dfteam.rename(columns=renamedict,inplace=True)
#dfteam.rename(columns={'id':'teamid','roster.link':'r.link'},inplace=True)
# there are two columns with franchise ID; drop one of them
#dfteam.drop(columns=['roster.roster','franchid2'],inplace=True)
# add the primary key
#dfteam.set_index(['teamid'],inplace=True)
dfteam = polish(
dfteam,
renamecat=['franchise', 'venue', 'conference', 'division', 'team2'],
indexvar=['teamid'],
morerename={
'id': 'teamid',
'roster.link': 'r.link'
},
dropvars=['roster.roster', 'franchid2'],
stem=stem)
return (dfteam)
def pullplayer(rawjson=None,inurl='',outloc='',outcsv=None,stem=''):
if rawjson is None:
r=h.pulldown(inurl=inurl,outfile=outfile)
else:
r=rawjson
if 'copyright' in r:
print(r['copyright'])
dfplayer=json_normalize(r['people'])
dfplayer=polish(dfplayer,
renamecat=['team','position'],
indexvar=['personid'],
morerename={'id':'personid'},
stem=stem)
if outcsv is not None:
dfplayer.to_csv(path_or_buf=outcsv+'.csv',encoding='utf-8')
return(dfplayer)
def pullteams(rawjson=None,inurl='',outloc='',outcsv=None,stem=''):
if rawjson is None:
r=h.pulldown(inurl=inurl,outfile=outfile)
else:
r=rawjson
if 'copyright' in r:
print(r['copyright'])
df=json_normalize(r['teams'])
df=polish(df,
renamecat=['franchise','venue','conference','division','team2'],
indexvar=['teamid'],
morerename={'id':'teamid'},
dropvars=['franchid2'],
stem=stem)
# write to csv if requested
if outcsv is not None:
df.to_csv(path_or_buf=outcsv+'.csv',encoding='utf-8')
return(df)
def pullteams(rawjson=None, inurl='', outloc='', outcsv=None, stem=''):
if rawjson is None:
r = h.pulldown(inurl=inurl, outfile=outfile)
else:
r = rawjson
if 'copyright' in r:
print(r['copyright'])
df = json_normalize(r['teams'])
df = polish(
df,
renamecat=['franchise', 'venue', 'conference', 'division', 'team2'],
indexvar=['teamid'],
morerename={'id': 'teamid'},
dropvars=['franchid2'],
stem=stem)
# move to standardized short names
#renamedict=batchrename(df.keys(),
# ['franchise','venue','conference','division','team2'],
# stem=stem)
#df.rename(columns=renamedict,inplace=True)
#df.rename(columns={'id':'teamid'},inplace=True)
# there are two columns with franchise ID; drop one of them
#df.drop(columns=['franchid2'],inplace=True)
# add the primary key
#df.set_index(['teamid'],inplace=True)
# write to csv if requested
if outcsv is not None:
df.to_csv(path_or_buf=outcsv + '.csv', encoding='utf-8')
return (df)
def playergamelog(outloc, apiurl, sptuples=[], seasons=[], peopleids=[]):
# this iterates through tuples. If tuples don't
# already exist in sptuples, create sptuples from
# seasons and peopleids
if sptuples == []:
for season in seasons:
for personid in peopleids:
sptuples.append((season, personid))
# iterate through the season x personid tuples to
# pull data
indextuples = []
pgllist = []
for (season, personid) in sptuples:
thisurl = apiurl + '/people/' + repr(
personid) + '/stats?stats=gameLog&season=' + repr(season)
r = h.pulldown(inurl=thisurl)
if r['stats'][0]['splits'] != []:
df = pd.io.json.json_normalize(r['stats'][0]['splits'])
df.rename(index=str,
columns={'game.gamePk': 'gameid'},
inplace=True)
df.set_index('gameid', inplace=True)
indextuples.append((season, personid))
pgllist.append(df)
print(indextuples)
pgls = pd.concat(pgllist,
keys=indextuples,
names=['season', 'personid', 'gameid'],
sort=True)
return (pgls)
def pullrosters(rawjson=None,inurl='',outloc='',outcsv=None,stem=''):
if rawjson is None:
r=h.pulldown(inurl=inurl,outfile=outfile)
else:
r=rawjson
if 'copyright' in r:
print(r['copyright'])
#####################################################
# pull team metadata
dfteam=json_normalize(r['teams'])
dfteam=polish(dfteam,
renamecat=['franchise','venue','conference','division','team2'],
indexvar=['teamid'],
morerename={'id':'teamid','roster.link':'r.link'},
dropvars=['roster.roster','franchid2'],
stem=stem)
#####################################################
# pull roster data
rlist=deepdivewithindex(r,['teams','ij','roster',u'roster','ij'],['teams','ij','id'],ii=0)
roster=json_normalize(rlist)
roster=polish(roster,
renamecat=['player','position'],
indexvar=['teamid','personid'],
morerename={'stickyindex':'teamid'},
stem=stem)
if outcsv is not None:
dfteam.to_csv(path_or_buf=outcsv+'_team.csv',encoding='utf-8')
roster.to_csv(path_or_buf=outcsv+'_roster.csv',encoding='utf-8')
return(dfteam,roster)
def multiplayergamestats(apiurl, outloc, season):
gameid = int(repr(season)[0:4] + '020001')
games = []
gamestatlist = []
success = 1
while success == 1:
if gameid % 20 == 0:
print('reached ' + repr(gameid))
if gameid % 100 == 0:
tock = gameid % 10000
tick = tock - 100
print(tick, tock)
gamestats = pd.concat(gamestatlist[tick:(tock + 1)],
keys=games[tick:(tock + 1)],
names=['gameid', 'teamid', 'personid'],
sort=True)
gamestats[gamestats['person.primaryPosition.code'] == 'G'].to_csv(
path_or_buf=outloc + '/goalie' + repr(gameid) + '.csv',
encoding='utf-8')
gamestats[gamestats['person.primaryPosition.code'] != 'G'].to_csv(
path_or_buf=outloc + '/skater' + repr(gameid) + '.csv',
encoding='utf-8')
print('successful export at ' + repr(gameid))
thisurl = apiurl + '/game/' + repr(gameid) + '/boxscore'
r = h.pulldown(inurl=thisurl)
if 'message' in r:
success = 0
break
else:
c = fillstats(r)
gamestatlist.append(c)
games.append(gameid)
gameid = gameid + 1
print('exited loop at ' + repr(gameid))
# cleanup
gamestats = pd.concat(gamestatlist[tock + 1:],
keys=games[tock + 1:],
names=['gameid', 'teamid', 'personid'],
sort=True)
gamestats[gamestats['person.primaryPosition.code'] == 'G'].to_csv(
path_or_buf=outloc + '/goalie' + repr(season) + '.csv',
encoding='utf-8')
gamestats[gamestats['person.primaryPosition.code'] != 'G'].to_csv(
path_or_buf=outloc + '/skater' + repr(season) + '.csv',
encoding='utf-8')
# overall datasets
gamestats = pd.concat(gamestatlist,
keys=games,
names=['gameid', 'teamid', 'personid'],
sort=True)
gamestats[gamestats['person.primaryPosition.code'] == 'G'].to_csv(
path_or_buf=outloc + '/goalie' + repr(season) + '.csv',
encoding='utf-8')
gamestats[gamestats['person.primaryPosition.code'] != 'G'].to_csv(
path_or_buf=outloc + '/skater' + repr(season) + '.csv',
encoding='utf-8')
return (gamestats)
def pullteamstats(rawjson=None, inurl='', outloc='', outcsv=None, stem=''):
if rawjson is None:
r = h.pulldown(inurl=inurl, outfile=outfile)
else:
r = rawjson
if 'copyright' in r:
print(r['copyright'])
#####################################################
# pull team metadata
dfteam = json_normalize(r['teams'])
# move to standardized short names
#renamedict=batchrename(dfteam.keys(),
# ['franchise','venue','conference','division','team2'],
# stem=stem)
#dfteam.rename(columns=renamedict,inplace=True)
#dfteam.rename(columns={'id':'teamid'},inplace=True)
# there are two columns with franchise ID; drop one of them
#dfteam.drop(columns=['teamStats','franchid2'],inplace=True)
# add the primary key
#dfteam.set_index(['teamid'],inplace=True)
dfteam = polish(
dfteam,
renamecat=['franchise', 'venue', 'conference', 'division', 'team2'],
indexvar=['teamid'],
morerename={'id': 'teamid'},
dropvars=['teamStats', 'franchid2'],
stem=stem)
#####################################################
# pull team stats
r1 = deepdivewithindex(r, ['teams', 'ij', 'teamStats', 'ij'],
['teams', 'ij', 'id'],
ii=0)
rn = [
{
#'teamid':rr['stickyindex'],
'type': rr['type']['displayName'],
'n': rr['splits'][0]['stat'],
'team': rr['splits'][0]['team'],
} for rr in r1
]
rrank = [
{
#'teamid':rr['stickyindex'],
'type': rr['type']['displayName'],
'rank': rr['splits'][1]['stat'],
'team': rr['splits'][1]['team']
} for rr in r1
]
# convert ranks into integers
for rr in rrank:
for k in rr['rank']:
rr['rank'][k] = int(rr['rank'][k][:-2])
# switch to dataframe
dfn = json_normalize(rn)
dfrank = json_normalize(rrank)
print(dfn.dtypes)
# there are two columns with team ID; drop one of them
#dfn.drop(columns=['team.id'],inplace=True)
#dfrank.drop(columns=['team.id'],inplace=True)
# add the primary key
#dfn.set_index(['teamid'],inplace=True)
#dfrank.set_index(['teamid'],inplace=True)
# move to standardized short names
#renamedict=batchrename(dfn.keys(),['team'],stem=stem)
#dfn.rename(columns=renamedict,inplace=True)
#dfrank.rename(columns=renamedict,inplace=True)
dfteam = polish(dfn, renamecat=['team'], indexvar=['teamid'], stem=stem)
dfrank = polish(dfn, renamecat=['team'], indexvar=['teamid'], stem=stem)
if outcsv is not None:
dfteam.to_csv(path_or_buf=outcsv + '_team.csv', encoding='utf-8')
dfn.to_csv(path_or_buf=outcsv + '_n.csv', encoding='utf-8')
dfrank.to_csv(path_or_buf=outcsv + '_rank.csv', encoding='utf-8')
return (dfteam, dfn, dfrank)
def teamrosterpull(season, apiurl, outds):
thisurl = apiurl + '/teams/?expand=team.roster&season=' + repr(season)
r = h.pulldown(thisurl, outds)
return (r)
def playerdata(outloc,
apiurl,
sptuples=[],
seasons=[],
peopleids=[],
reporttype=['a'],
handle='playerdata',
inc=50):
# tracking, since this can be a long-running program
counter = 0
tick = time.time()
# this iterates through tuples. If tuples don't
# already exist in sptuples, create sptuples from
# seasons and peopleids
if sptuples == []:
for season in seasons:
for personid in peopleids:
sptuples.append((season, personid))
# iterate through the season x personid tuples to
# pull data
indextuples = []
dictlist = []
for (season, personid) in sptuples:
# for a given person and season, all the different
# queries are combined into one dictionary
combined = {}
# first, a pointer whether there is any data
dataexist = True
# generic statsSingleSeason gets triggered as 'a'
if 'a' in reporttype:
thisurl = apiurl + '/people/' + repr(
personid) + '/stats?stats=statsSingleSeason&season=' + repr(
season)
r = h.pulldown(inurl=thisurl)
if r['stats'][0]['splits'] == []:
dataexist = False
else:
combined.update(r['stats'][0]['splits'][0]['stat'])
# home-and-away-level data gets triggered as 'ha'
if 'ha' in reporttype:
thisurl = apiurl + '/people/' + repr(
personid) + '/stats?stats=homeAndAway&season=' + repr(season)
r = h.pulldown(inurl=thisurl)
splits = r['stats'][0]['splits']
for s in splits:
if s['isHome'] == True:
modifier = 'h.'
else:
modifier = 'a.'
for metric in s['stat']:
combined[modifier + metric] = s['stat'][metric]
# win/loss/overtime loss-level data gets triggered as 'wl'
if 'wl' in reporttype:
thisurl = apiurl + '/people/' + repr(
personid) + '/stats?stats=winLoss&season=' + repr(season)
r = h.pulldown(inurl=thisurl)
splits = r['stats'][0]['splits']
for s in splits:
if s['isOT'] == False and s['isWin'] == True:
modifier = 'w.'
elif s['isOT'] == False and s['isWin'] == False:
modifier = 'l.'
elif s['isOT'] == True and s['isWin'] == False:
modifier = 'ot.'
for metric in s['stat']:
combined[modifier + metric] = s['stat'][metric]
# add the record
if len(combined) > 0:
indextuples.append((season, personid))
dictlist.append(combined)
# tracking
counter = counter + 1
tock = time.time()
if counter % inc == 0:
print('Reached ' + repr(counter) + ' after ' + repr(tock - tick) +
' seconds')
playerindex = pd.MultiIndex.from_tuples(indextuples,
names=['season', 'personid'])
df = pd.DataFrame(dictlist, index=playerindex, copy=True)
return (df)
def pullboxscore(rawjson=None,inurl='',outloc='',outcsv=None,stem=''):
if rawjson is None:
r=h.pulldown(inurl=inurl,outfile=outfile)
else:
r=rawjson
if 'copyright' in r:
print(r['copyright'])
#####################################################
# Pull officials data
dfoff=json_normalize(r['officials'])
#####################################################
# Pull player data
hp=demote(r['teams']['home']['players'],newname='personidtxt')
ap=demote(r['teams']['away']['players'],newname='personidtxt')
hp.extend(ap)
dfplayers=json_normalize(hp)
# deal with variables that are duplicated between players
# and goalies
dfplayers['p.assists']=dfplayers['stats.skaterStats.assists'].combine_first(dfplayers['stats.goalieStats.assists'])
dfplayers['p.goals']=dfplayers['stats.skaterStats.goals'].combine_first(dfplayers['stats.goalieStats.goals'])
dfplayers['p.shots']=dfplayers['stats.skaterStats.shots'].combine_first(dfplayers['stats.goalieStats.shots'])
dfplayers['p.pim']=dfplayers['stats.skaterStats.penaltyMinutes'].combine_first(dfplayers['stats.goalieStats.pim'])
dfplayers['p.toi']=dfplayers['stats.skaterStats.timeOnIce'].combine_first(dfplayers['stats.goalieStats.timeOnIce'])
dfplayers.drop(columns=['stats.skaterStats.assists',
'stats.skaterStats.penaltyMinutes',
'stats.skaterStats.timeOnIce',
'stats.skaterStats.shots',
'stats.skaterStats.goals',
'stats.goalieStats.assists',
'stats.goalieStats.pim',
'stats.goalieStats.timeOnIce',
'stats.goalieStats.shots',
'stats.goalieStats.goals'],inplace=True)
# person.primaryPosition,person.currentTeam, position, player stats
modnames={}
modnames.update(batchrename(dfplayers.keys(),['team','position'],stem='',oldstem='person.'))
modnames.update(batchrename(dfplayers.keys(),['playerstats'],stem='p.',oldstem='stats.skaterStats.'))
modnames.update(batchrename(dfplayers.keys(),['playerstats'],stem='p.',oldstem='stats.goalieStats.'))
# polish player data
dfplayers=polish(dfplayers,
renamecat=['player','position'],
indexvar=['personid'],
morerename=modnames,
stem=stem)
#####################################################
# Pull team data
rt=[r['teams']['home']]
rt.append(r['teams']['away'])
dfteams=json_normalize(rt)
# playerstats for the game
modnames=batchrename(dfteams.keys(),['playerstats'],stem='t.',oldstem='teamStats.teamSkaterStats.')
# attributes to drop
dropnames=[x for x in dfteams.columns if x[0:7]=='players']
dropnames.extend(['coaches','goalies','onIce','onIcePlus','penaltyBox','scratches','skaters'])
# polish player data
dfteams=polish(dfteams,
renamecat=['team'],
indexvar=['teamid'],
morerename=modnames,
dropvars=dropnames,
stem=stem)
#####################################################
# Pull coaches
coaches=[]
coaches=r['teams']['home']['coaches']
coaches.extend(r['teams']['away']['coaches'])
dfcoaches=json_normalize(coaches)
# polish player data
dfcoaches=polish(dfcoaches,
renamecat=['player','position'],
stem=stem)
#####################################################
# Pull player index -- just playerid, team, and role
# for role in [skater,goalie,scratch]
playerindex=[]
for team in ['home','away']:
teamid=r['teams'][team]['team']['id']
for playertype in ['goalies','skaters','scratches']:
for p in r['teams'][team][playertype]:
for x in r['teams'][team][playertype]:
xval={'personid':x,'playertype':playertype,'teamid':teamid}
playerindex.append(xval)
dfplindex=json_normalize(playerindex)
dfplindex.set_index(['personid'],inplace=True)
#####################################################
# write data to csv if requested
if outcsv is not None:
dfoff.to_csv(path_or_buf=outcsv+'_officials.csv',encoding='utf-8')
dfplayers.to_csv(path_or_buf=outcsv+'_players.csv',encoding='utf-8')
dfteams.to_csv(path_or_buf=outcsv+'_teams.csv',encoding='utf-8')
dfcoaches.to_csv(path_or_buf=outcsv+'_coaches.csv',encoding='utf-8')
dfplindex.to_csv(path_or_buf=outcsv+'_plindex.csv',encoding='utf-8')
return(dfoff,dfplayers,dfteams,dfcoaches,dfplindex)