def ceiling_points(self, **kwargs):
"""
Return score variance
"""
if not self._points:
self.get_points()
return MathUtils.max(self._points)
def _season_points(self, **kwargs):
"""
Calculate points for the whole season
"""
if not self._points:
self.get_points()
return MathUtils.sum(self._points)
def floor_points(self, **kwargs):
"""
Return score variance
"""
if not self._points:
self.get_points()
return MathUtils.min(self._points)
def std_dev_points(self, **kwargs):
"""
Return score variance
"""
if not self._points:
self.get_points()
return MathUtils.std(self._points)
def median_points(self, **kwargs):
"""
Return median score
"""
if not self._points:
self.get_points()
return MathUtils.median(self._points)
def get_context_data(self, **kwargs):
context = super(PlayerDetail, self).get_context_data(**kwargs)
player = context['object']
stat_list = player.stats.all()
stat_keys = filter(lambda x: x not in ['50', '51', '52', '53', '54', '55', '56', '57'], stat_list[0].stat_data.keys())
columns = filter(lambda x: x[0] in stat_keys, STATS.items())
stat_headers = [ stat_item[1][0] for stat_item in columns ]
stat_headers.insert(0, 'Week #')
stat_headers.append('Points')
context['stat_headers'] = stat_headers
context['stat_list'] = []
column_lists = { key: [] for key, value in columns }
for stat in stat_list:
if int(player.bye_week) == stat.week_num:
continue
total_points = stat.total_points()
stat_week = []
stat_week.append(stat.week_num)
for key, value in columns:
stat_week.append(stat.stat_data[key])
column_lists[key].append(stat.stat_data[key])
stat_week.append(total_points)
context['stat_list'].append(stat_week)
avg_stats = ['Avg']
for key, value in columns:
avg_str = "%.1f ± %.1f" % (
MathUtils.mean(column_lists[key]),
MathUtils.std(column_lists[key]),
)
avg_stats.append(avg_str)
avg_stats.append(player.mean_points())
context['stat_list'].append(avg_stats)
points = player.get_points()
context['stat_rows'] = [
("Total Points", player._season_points()),
("Geometric Mean", player.gmean_points()),
("Arithmetic Mean", player.mean_points()),
("Std Dev", player.std_dev_points()),
("Median", player.median_points()),
("Floor", player.floor_points()),
("Ceiling", player.ceiling_points()),
("Games Played", player.games_played()),
("Risk Factor", '%.2f%%' % player.risk_factor()),
]
context['page_title'] = '%s %s Detail' % (player.first_name, player.last_name)
return context
def normalize_points(self, **kwargs):
"""
Returns a list of points normalized to 1.0
"""
if not self._points:
self.get_points()
result = MathUtils.normalize(self._points, **kwargs)
return result
def gmean_points(self, **kwargs):
"""
Return the mean score
"""
if not self._points:
self.get_points()
pts = filter(lambda x: x != 0, self.normalize_points())
return MathUtils.gmean(pts)
def get_context_data(self, **kwargs):
context = super(TeamDetail, self).get_context_data(**kwargs)
team = context['object']
weeks = range(1, League.objects.get(league_key=self.kwargs.get('league_key')).current_week + 1)
context['stat_headers'] = ['Week #'] + self.__class__.position_list
context['stat_list'] = []
for week in weeks:
lineup = team.players.filter(roster__week=week)
player_list = [ player
for position in self.__class__.unique_list
for player in team.players.filter(Q(roster__position=position), Q(roster__week=week))
]
stat_week = [ {'week': week} ] + [ {'player': player} for player in player_list ]
points = MathUtils.sum([ roster.player.get_weekly_points(week) for roster in team.roster.filter(week=week).exclude(position='BN')])
lower_stat = [ {'points': 'Total: %.2f' % points} ] + [ {'points': '%.2f' % player.get_weekly_points(week)} for player in player_list ]
context['stat_list'].append(stat_week)
context['stat_list'].append(lower_stat)
return context
