def max_player_stats(self):
"""
Returns a GenPlayers sequence of player statistics that combines
game statistics and play statistics by taking the max value of
each corresponding statistic.
This is useful when accuracy is desirable. Namely, using only
play-by-play data or using only game statistics can be unreliable.
That is, both are inconsistently correct.
Taking the max values of each statistic reduces the chance of being
wrong (particularly for stats that are in both play-by-play data
and game statistics), but does not eliminate them.
"""
game_players = list(self.players)
play_players = list(self.drives.plays().players())
max_players = OrderedDict()
# So this is a little tricky. It's possible for a player to have
# only statistics at the play level, and therefore not be represented
# in the game level statistics. Therefore, we initialize our
# max_players with play-by-play stats first. Then go back through
# and combine them with available game statistics.
for pplay in play_players:
newp = nflgame.player.GamePlayerStats(pplay.playerid,
pplay.name, pplay.home,
pplay.team)
maxstats = {}
for stat, val in pplay._stats.iteritems():
maxstats[stat] = val
newp._overwrite_stats(maxstats)
max_players[pplay.playerid] = newp
for newp in max_players.itervalues():
for pgame in game_players:
if pgame.playerid != newp.playerid:
continue
maxstats = {}
for stat, val in pgame._stats.iteritems():
maxstats[stat] = max([val,
newp._stats.get(stat, -_MAX_INT)])
newp._overwrite_stats(maxstats)
break
return nflgame.seq.GenPlayerStats(max_players)
def max_player_stats(self):
"""
Returns a GenPlayers sequence of player statistics that combines
game statistics and play statistics by taking the max value of
each corresponding statistic.
This is useful when accuracy is desirable. Namely, using only
play-by-play data or using only game statistics can be unreliable.
That is, both are inconsistently correct.
Taking the max values of each statistic reduces the chance of being
wrong (particularly for stats that are in both play-by-play data
and game statistics), but does not eliminate them.
"""
game_players = list(self.players)
play_players = list(self.drives.plays().players())
max_players = OrderedDict()
# So this is a little tricky. It's possible for a player to have
# only statistics at the play level, and therefore not be represented
# in the game level statistics. Therefore, we initialize our
# max_players with play-by-play stats first. Then go back through
# and combine them with available game statistics.
for pplay in play_players:
newp = nflgame.player.GamePlayerStats(pplay.playerid,
pplay.name, pplay.home,
pplay.team)
maxstats = {}
for stat, val in pplay._stats.iteritems():
maxstats[stat] = val
newp._overwrite_stats(maxstats)
max_players[pplay.playerid] = newp
for newp in max_players.itervalues():
for pgame in game_players:
if pgame.playerid != newp.playerid:
continue
maxstats = {}
for stat, val in pgame._stats.iteritems():
maxstats[stat] = max([val,
newp._stats.get(stat, -_MAX_INT)])
newp._overwrite_stats(maxstats)
break
return nflgame.seq.GenPlayerStats(max_players)
