def player_detail(request, pid):
player = Player.objects.get(id=pid)
year = current_season()
games = get_games_(pid, 'all', '', year)
avg_min = games.aggregate(Avg('mp'))
avg_fpts = games.aggregate(Avg('fpts'))
return render(request, 'player_detail.html', locals())
def get_team_games(team):
# get all games for the team last season
players_ = Player.objects.filter(team=team, data_source='FanDuel')
players_ = ['{} {}'.format(ip.first_name, ip.last_name) for ip in players_]
season = current_season()
q = Q(name__in=players_) & \
Q(date__range=[datetime.date(season, SEASON_START_MONTH, SEASON_START_DAY), datetime.date(season+1, SEASON_END_MONTH, SEASON_END_DAY)])
return PlayerGame.objects.filter(q)
def get_win_loss(team):
season = current_season()
q = Q(team=team) & \
Q(date__range=[datetime.date(season, SEASON_START_MONTH, SEASON_START_DAY), datetime.date(season+1, SEASON_END_MONTH, SEASON_END_DAY)])
team_games = PlayerGame.objects.filter(q)
game_results = team_games.values('date', 'game_result').distinct()
wins = game_results.filter(game_result='W').count()
losses = game_results.filter(game_result='L').count()
return wins, losses
def download_game_report(request):
game = request.GET.get('game')
game = Game.objects.get(id=game)
season = current_season()
q = Q(team__in=[game.home_team, game.visit_team]) & \
Q(opp__in=[game.home_team, game.visit_team]) & \
Q(date__range=[datetime.date(season, SEASON_START_MONTH, SEASON_START_DAY), datetime.date(season+1, SEASON_END_MONTH, SEASON_END_DAY)])
qs = PlayerGame.objects.filter(q)
fields = [
f.name for f in PlayerGame._meta.get_fields()
if f.name not in ['id', 'is_new']
]
data = [model_to_dict(entity, fields=fields) for entity in qs]
filename = 'nba_games({}@{}).csv'.format(game.visit_team, game.home_team)
return download_response(fields, data, filename)
def build_player_cache():
# player info -> build cache
players = Player.objects.filter(data_source='FanDuel', play_today=True) \
.order_by('-proj_points')
game_info = {}
for game in Game.objects.all():
game_info[game.home_team] = ''
game_info[game.visit_team] = '@'
for player in players:
games = get_games_(player.id, 'all', '', current_season())
ampg = games.aggregate(Avg('mp'))['mp__avg'] or 0
smpg = games.filter(location=game_info[player.team]).aggregate(
Avg('mp'))['mp__avg'] or 0
afp = games.aggregate(Avg('fpts'))['fpts__avg'] or 0
sfp = games.filter(location=game_info[player.team]).aggregate(
Avg('fpts'))['fpts__avg'] or 0
Player.objects.filter(uid=player.uid).update(
ampg=ampg,
smpg=smpg,
afp=afp,
sfp=sfp,
value=player.salary / 250 + 10)
def get_team_stat(team, loc):
loc_ = '@' if loc == '' else ''
# allowance
season = current_season()
q = Q(opp=team) & Q(location=loc_) & \
Q(date__range=[datetime.date(season, SEASON_START_MONTH, SEASON_START_DAY), datetime.date(season+1, SEASON_END_MONTH, SEASON_END_DAY)])
a_teams = PlayerGame.objects.filter(q)
a_teams_ = a_teams.values('date').annotate(trb=Sum('trb'),
ast=Sum('ast'),
stl=Sum('stl'),
blk=Sum('blk'),
tov=Sum('tov'),
pts=Sum('pts'))
rpg = a_teams_.aggregate(Avg('trb'))['trb__avg'] or 0
apg = a_teams_.aggregate(Avg('ast'))['ast__avg'] or 0
spg = a_teams_.aggregate(Avg('stl'))['stl__avg'] or 0
bpg = a_teams_.aggregate(Avg('blk'))['blk__avg'] or 0
tov = a_teams_.aggregate(Avg('tov'))['tov__avg'] or 0
ppg = a_teams_.aggregate(Avg('pts'))['pts__avg'] or 0
# score
q = Q(team=team) & Q(location=loc) & \
Q(date__range=[datetime.date(season, SEASON_START_MONTH, SEASON_START_DAY), datetime.date(season+1, SEASON_END_MONTH, SEASON_END_DAY)])
s_teams = PlayerGame.objects.filter(q)
s_teams_ = s_teams.values('date').annotate(trb=Sum('trb'),
ast=Sum('ast'),
stl=Sum('stl'),
blk=Sum('blk'),
tov=Sum('tov'),
pts=Sum('pts'))
s_rpg = s_teams_.aggregate(Avg('trb'))['trb__avg'] or 0
s_apg = s_teams_.aggregate(Avg('ast'))['ast__avg'] or 0
s_spg = s_teams_.aggregate(Avg('stl'))['stl__avg'] or 0
s_bpg = s_teams_.aggregate(Avg('blk'))['blk__avg'] or 0
s_tov = s_teams_.aggregate(Avg('tov'))['tov__avg'] or 0
s_ppg = s_teams_.aggregate(Avg('pts'))['pts__avg'] or 0
res = {
'team': team,
'rpg': rpg,
'apg': apg,
'spg': spg,
'bpg': bpg,
'tov': tov,
'ppg': ppg,
'total': rpg + apg + spg + bpg + tov + ppg,
's_rpg': s_rpg,
's_apg': s_apg,
's_spg': s_spg,
's_bpg': s_bpg,
's_tov': s_tov,
's_ppg': s_ppg,
's_total': s_rpg + s_apg + s_spg + s_bpg + s_tov + s_ppg
}
# FPA TM POS
tm_pos = []
# for each distinct match
for ii in a_teams_:
# players (games) in a match
players = a_teams.filter(date=ii['date'])
tm_pos_ = {}
# for each position
for pos in POSITION:
# players in the position of the team
q = Q(position=pos) & Q(data_source='FanDuel')
players_ = Player.objects.filter(Q(team=players[0].team) & q)
players_ = [
'{} {}'.format(ip.first_name, ip.last_name) for ip in players_
]
tm_pos_[pos] = players.filter(name__in=players_).aggregate(
Sum('fpts'))['fpts__sum'] or 0
if tm_pos_['PG'] > 0 and tm_pos_['SG'] > 0:
tm_pos.append(tm_pos_)
print(ii['date'], players[0].team, players[0].opp, players[0].location,
tm_pos_)
for pos in POSITION:
res[pos] = sum(ii[pos]
for ii in tm_pos) / len(tm_pos) if len(tm_pos) else -1
print('-' * 32)
# for FPS TM POS
tm_pos = []
# for each distinct match
for ii in s_teams_:
# players (games) in a match
players = s_teams.filter(date=ii['date'])
tm_pos_ = {}
# for each position
for pos in POSITION:
# players in the position of the team
q = Q(position=pos) & Q(data_source='FanDuel')
players_ = Player.objects.filter(Q(team=players[0].team) & q)
players_ = [
'{} {}'.format(ip.first_name, ip.last_name) for ip in players_
]
tm_pos_[pos] = players.filter(name__in=players_).aggregate(
Sum('fpts'))['fpts__sum'] or 0
if tm_pos_['PG'] > 0 and tm_pos_['SG'] > 0:
tm_pos.append(tm_pos_)
print(ii['date'], players[0].team, players[0].opp, players[0].location,
tm_pos_)
print('-' * 32)
for pos in POSITION:
res['s_' +
pos] = sum(ii[pos]
for ii in tm_pos) / len(tm_pos) if len(tm_pos) else -1
return res