def impt_stat():
'''Iterates through each statistic's BS Object to get the important
information.
returns a dictionary
'''
# dictionary to hold the stat, mean, and standard deviation
stat_mean_sdev = {}
# builds then iterates through each stat's BS obj
for k, v in build_dict('stat_position.txt').items():
# list to store all important numbers per stat
ind_stat = []
# creates a BS object per stat
statistic = soupy(k)
# position of each important number within BS object list
x = int(v)
# variables to find the next important number
y = x + 1
z = x + 3
# iterates through BS object to append important num to list
for s in statistic:
if x > len(statistic):
break
else:
if k == 'Passes_Intercepted':
ind_stat.append(float(statistic[x]))
x += z
else:
ind_stat.append(float(statistic[x]))
x += y
# determines mean and standard deviation of each statistic
stat_mean = round(mean(ind_stat), 3)
stat_sdev = round(stdev(ind_stat), 3)
# adds stat: (mean, stdev) to the dictionary
stat_mean_sdev[k] = (stat_mean, stat_sdev)
return stat_mean_sdev
def team_stats():
'''
'''
lower_better = [
'3rd_Down_Conversion_Pct_Defense',
'4th_Down_Conversion_Pct_Defense',
'Blocked_Kicks_Allowed',
'Blocked_Punts_Allowed',
'First_Downs_Defense',
'Fumbles_Lost',
'Kickoff_Return_Defense',
'Total_Defense',
'Rushing_Defense',
'Passing_Yards_Allowed',
'Punt_Return_Defense',
'Scoring_Defense',
'Team_Passing_Efficiency_Defense',
'Red_Zone_Defense',
'Passes_Had_Intercepted',
'Tackles_for_Loss_Allowed',
'Sacks_Allowed',
'Turnovers_Lost'
]
# builds then iterates through each stat's BS obj
for k, v in build_dict('stat_position.txt').items():
# creates a BS object per stat
stats = soupy(k)
# position of each important number within BS object list
x = int(v)
a = 1
b = 2
# variables to find the next important number
y = x + 1
z = x + 3
c = 6
# list to hold teams and stats
team_lst = []
stat_lst = []
# iterates through BS object to append important num to list
for s in stats:
if x > len(stats):
break
elif k == 'Passes_Intercepted':
team_lst.append(stats[a])
stat_lst.append(stats[x])
x += z
a += z
else:
team_lst.append(stats[a])
stat_lst.append(stats[x])
x += y
a += y
stand_score = z_score(team_lst, stat_lst)
for key, val in stand_score.items():
val = float(val)
if k in lower_better:
if val < 0:
stand_score[key] = abs(val)
else:
stand_score[key] = (val - (val * 2))
else:
pass
yield stand_score
