def show_season_table(db, player, stype, week_range=None, pos=None):
if pos is None:
pos = player.position
_, cur_year, _ = nfldb.current(db)
pstats = []
for year in range(2009, cur_year+1):
qgames = nflcmd.query_games(db, player, year, stype, week_range)
games = qgames.as_games()
if len(games) == 0:
continue
game_stats = map(partial(nflcmd.Game.make, db, player), games)
agg = qgames.sort([]).as_aggregate()
pstats.append(nflcmd.Games(db, year, game_stats, agg[0]))
spec = prefix_season + nflcmd.columns['season'][nflcmd.pcolumns[pos]]
rows = [nflcmd.header_row(spec)]
rows += map(partial(nflcmd.pstat_to_row, spec), pstats)
if len(pstats) > 1:
summary = nfldb.aggregate(pstat._pstat for pstat in pstats)[0]
allrows = nflcmd.Games(db, '-', [], summary)
allrows._fgs = []
for pstat in pstats:
allrows._fgs += pstat.fgs
allrows.games += pstat.games
rows.append(nflcmd.pstat_to_row(spec, allrows))
print(nflcmd.table(rows))
def NOTUSED_recep_yds_per_third_down(db=db):
'''returns most yards/attempt on third down'''
q.game(season_year=2012, season_type='Regular')
q.play(third_down_att=1)
plays = q.as_plays()
aggregated = nfldb.aggregate(plays) # returns a list of PlayPlayer objects.
aggregated = sorted(aggregated, key=lambda p: p.receiving_tar, reverse=True)
for pp in aggregated[0:10]:
name = pp.player
statement = '%s recep yds on 3rd down' % pp.receiving_yds
attempts = 'on %s targets' % pp.receiving_tar
average = '@ %.2f yds/target' % (float(pp.receiving_yds) / float(pp.receiving_tar))
comp_rate = '.recep rate: %.2f' % (100 *(float(pp.receiving_rec) / float(pp.receiving_tar))) + '%'
print name, statement, attempts, average, comp_rate
def most_wr_third_down_yards(db=db, q=q):
q.game(season_year=2012, season_type='Regular')
q.play(third_down_att=1)
plays = q.as_plays()
aggregated = nfldb.aggregate(plays)
aggregated = sorted(aggregated, key=lambda p: p.rushing_att, reverse=True)
for pp in aggregated[0:5]:
name = pp.player
statement = 'rushed for %s yards on 3rd down' % pp.rushing_yds
attempts = 'on %s attempts' % pp.rushing_att
average = '@ %s yds/attempt' % (pp.rushing_yds / pp.rushing_att)
print name, statement, attempts, average
pass
def most_wr_third_down_yards(db=db, q=q):
q.game(season_year=2012, season_type='Regular')
q.play(third_down_att=1)
plays = q.as_plays()
aggregated = nfldb.aggregate(plays)
aggregated = sorted(aggregated, key=lambda p: p.rushing_att, reverse=True)
for pp in aggregated[0:5]:
name = pp.player
statement = 'rushed for %s yards on 3rd down' % pp.rushing_yds
attempts = 'on %s attempts' % pp.rushing_att
average = '@ %s yds/attempt' % (pp.rushing_yds / pp.rushing_att)
print name, statement, attempts, average
pass
def dep_rushing_yds_per_third_down(db=db):
q = nfldb.Query(db)
q.game(season_year=2012, season_type='Regular')
q.play(third_down_att=1)
plays = q.as_plays()
aggregated = nfldb.aggregate(plays)
aggregated = sorted(aggregated, key=lambda p: p.rushing_yds, reverse=True)
for pp in aggregated[0:10]:
name = pp.player
statement = 'rushed for %s yds on 3rd down' % pp.rushing_yds
attempts = 'on %s att' % pp.rushing_att
average = '@ %.2f yds/att' % (float(pp.rushing_yds) / float(pp.rushing_att))
print name, statement, attempts, average
pass
def most_yards_per_third_down(db=db, q=q):
'''returns most yards/attempt on third down'''
q.game(season_year=2012, season_type='Regular')
q.play(third_down_att=1, passing_yds__ne=0)
plays = q.as_plays()
aggregated = nfldb.aggregate(plays) # returns a list of PlayPlayer objects.
aggregated = sorted(aggregated, key=lambda p: p.passing_yds, reverse=True)
for pp in aggregated[0:5]:
#print pp.player, pp.passing_yds, pp.passing_att
name = pp.player
statement = 'threw for %s passing yards on 3rd down' % pp.passing_yds
attempts = 'on %s attempts' % pp.passing_att
average = '@ %s yds/attempt' % (pp.passing_yds / pp.passing_att)
print name, statement, attempts, average
def most_yards_per_third_down(db=db, q=q):
'''returns most yards/attempt on third down'''
q.game(season_year=2012, season_type='Regular')
q.play(third_down_att=1, passing_yds__ne=0)
plays = q.as_plays()
aggregated = nfldb.aggregate(
plays) # returns a list of PlayPlayer objects.
aggregated = sorted(aggregated, key=lambda p: p.passing_yds, reverse=True)
for pp in aggregated[0:5]:
#print pp.player, pp.passing_yds, pp.passing_att
name = pp.player
statement = 'threw for %s passing yards on 3rd down' % pp.passing_yds
attempts = 'on %s attempts' % pp.passing_att
average = '@ %s yds/attempt' % (pp.passing_yds / pp.passing_att)
print name, statement, attempts, average
def dep_rushing_yds_per_third_down(db=db):
q = nfldb.Query(db)
q.game(season_year=2012, season_type='Regular')
q.play(third_down_att=1)
plays = q.as_plays()
aggregated = nfldb.aggregate(plays)
aggregated = sorted(aggregated, key=lambda p: p.rushing_yds, reverse=True)
for pp in aggregated[0:10]:
name = pp.player
statement = 'rushed for %s yds on 3rd down' % pp.rushing_yds
attempts = 'on %s att' % pp.rushing_att
average = '@ %.2f yds/att' % (float(pp.rushing_yds) /
float(pp.rushing_att))
print name, statement, attempts, average
pass
def passing_yds_per_third_down(db=db):
q = nfldb.Query(db)
'''returns most yards/attempt on third down'''
q.game(season_year=2012, season_type='Regular')
q.play(third_down_att=1)
plays = q.as_plays()
aggregated = nfldb.aggregate(plays) # returns a list of PlayPlayer objects.
aggregated = sorted(aggregated, key=lambda p: p.passing_yds, reverse=True)
for pp in aggregated[0:10]:
#print pp.player, pp.passing_yds, pp.passing_att
name = pp.player
statement = 'threw for %s passing yds on 3rd down' % pp.passing_yds
attempts = 'on %s att' % pp.passing_att
average = '@ %.2f yds/att' % (float(pp.passing_yds) / float(pp.passing_att))
comp_rate = '.Comp rate: %.2f' % (100 *(float(pp.passing_cmp) / float(pp.passing_att))) + '%'
print name, statement, attempts, average, comp_rate
def show_game_table(db, player, year, stype, week_range=None, pos=None):
if pos is None:
pos = player.position
games = nflcmd.query_games(db, player, year, stype, week_range).as_games()
pstats = map(partial(nflcmd.Game.make, db, player), games)
spec = prefix_game + nflcmd.columns['game'][nflcmd.pcolumns[pos]]
rows = [nflcmd.header_row(spec)]
rows += map(partial(nflcmd.pstat_to_row, spec), pstats)
if len(pstats) > 1:
summary = nfldb.aggregate(pstat._pstat for pstat in pstats)[0]
allrows = nflcmd.Game(db, None, '-', summary)
allrows._fgs = []
for pstat in pstats:
allrows._fgs += pstat.fgs
rows.append(nflcmd.pstat_to_row(spec, allrows))
print(nflcmd.table(rows))
def NOTUSED_recep_yds_per_third_down(db=db):
'''returns most yards/attempt on third down'''
q.game(season_year=2012, season_type='Regular')
q.play(third_down_att=1)
plays = q.as_plays()
aggregated = nfldb.aggregate(
plays) # returns a list of PlayPlayer objects.
aggregated = sorted(aggregated,
key=lambda p: p.receiving_tar,
reverse=True)
for pp in aggregated[0:10]:
name = pp.player
statement = '%s recep yds on 3rd down' % pp.receiving_yds
attempts = 'on %s targets' % pp.receiving_tar
average = '@ %.2f yds/target' % (float(pp.receiving_yds) /
float(pp.receiving_tar))
comp_rate = '.recep rate: %.2f' % (
100 * (float(pp.receiving_rec) / float(pp.receiving_tar))) + '%'
print name, statement, attempts, average, comp_rate
def passing_yds_per_third_down(db=db):
q = nfldb.Query(db)
'''returns most yards/attempt on third down'''
q.game(season_year=2012, season_type='Regular')
q.play(third_down_att=1)
plays = q.as_plays()
aggregated = nfldb.aggregate(
plays) # returns a list of PlayPlayer objects.
aggregated = sorted(aggregated, key=lambda p: p.passing_yds, reverse=True)
for pp in aggregated[0:10]:
#print pp.player, pp.passing_yds, pp.passing_att
name = pp.player
statement = 'threw for %s passing yds on 3rd down' % pp.passing_yds
attempts = 'on %s att' % pp.passing_att
average = '@ %.2f yds/att' % (float(pp.passing_yds) /
float(pp.passing_att))
comp_rate = '.Comp rate: %.2f' % (
100 * (float(pp.passing_cmp) / float(pp.passing_att))) + '%'
print name, statement, attempts, average, comp_rate
import nfldb
from scoring import Scoring
scorer = Scoring()
db = nfldb.connect()
q = nfldb.Query(db).game(season_year=2013, season_type='Regular')
# get game stats
for game in q.as_games():
print game
print game.week, game.home_team, game.home_score
print game.week, game.away_team, game.away_score
performances = nfldb.aggregate(game.play_players)
for pp in performances:
print pp.player.full_name, pp.player.position, scorer.get_score(pp)
print
