def getPlayerMostNegativePasses():
#Empty dictionary
players = {}
#Open json with player info
data = openFileJson('./player_info.json')
#For every player
for playerid, playerdata in data.items():
#Initialize count to 0
players[playerid] = 0
#For every yard they passed
for yards in playerdata['PassYards']:
#If they passed for negative yards
if yards != None and yards < 0:
#Increment their count in dictionary
players[playerid] = players[playerid] + 1
#Get most number of negative yards passed
highest_count = players[max(players, key=players.get)]
#Empty list
player_list = []
#For every player in dictionary
for k in players:
#If their count is equal to highest number of negative rushed passed
if players[k] == highest_count:
#Save their name and count
tup = (data[k]['Name'], players[k])
player_list.append(tup)
return player_list
def getAvgNumPlays():
#Initialize counters
count = 0
plays = 0
#Opens file containing file paths from game_data
with open('files.txt') as f:
#Read every file path (for every game)
for line in f:
#Truncates empty character at end of line
line = line[:27]
#Gets file data
data = openFileJson(line)
#Increment number of games
count = count + 1
# pull out the game id and game data
for gameid, gamedata in data.items():
if gameid != 'nextupdate':
# go straight for the drives
for driveid, drivedata in gamedata['drives'].items():
if driveid != 'crntdrv':
#Adds number of plays in game to total
plays = plays + drivedata['numplays']
#Return mean
return round(plays / count)
def getWinLossRatio(team):
#Open json with team info
data = openFileJson('./team_info.json')
#Calculate ratio
ratio = data[team]['wins'] / data[team]['losses']
return ratio
def getTeamMostPenalties():
#Empty list
team = []
#Open json with team info
data = openFileJson('./team_info.json')
#Most amount of penalties out of all teams
most = data[max(data, key=lambda x: data[x]['penalties'])]['penalties']
#For every team
for t, tdata in data.items():
#If they have the most amount of penalties
if tdata['penalties'] == most:
#Save team & number of penalties
tup = (t, most)
team.append(tup)
return team
def getPlayerMostDroppedPasses():
#Empty list
players = []
#Open json with player info
data = openFileJson('./player_info.json')
#Most number of dropped passes
max_val = data[max(
data, key=lambda x: data[x]['DroppedPasses'])]['DroppedPasses']
#For every player
for player, playerdata in data.items():
#If they dropped as many passes as the most dropped
if playerdata['DroppedPasses'] == max_val:
#Save player name and number of dropped passes
tup = (playerdata['Name'], max_val)
players.append(tup)
return players
def getMostMissedFieldGoals():
#Empty list
players = []
#Open json with player info
data = openFileJson('./player_info.json')
#Most number of missed field goals
max_val = data[max(
data, key=lambda x: data[x]['MissedFieldGoals'])]['MissedFieldGoals']
#For every player
for player, playerdata in data.items():
#If they missed as many field goals as the most missed
if playerdata['MissedFieldGoals'] == max_val:
#Save player name & field goals missed
tup = (playerdata['Name'], max_val)
players.append(tup)
return players
def getMostMadeFieldGoals():
#Empty list
players = []
#Open json with player info
data = openFileJson('./player_info.json')
#Set minimum number of field goals to find the most
most = 0
#For every player
for player, playerdata in data.items():
#If the number of made field goals is greater than or equal to previous most
if len(playerdata['MadeFieldGoals']) >= most:
#Update most number of field goals
most = len(playerdata['MadeFieldGoals'])
#Save player name & number of field goals made
tup = (playerdata['Name'], most)
players.append(tup)
#Remove players from list who have less successful field goals than the most number of field goals made
players = list(filter(lambda x: x[1] == most, players))
return players
def getPlayersWithMostTeams():
#Empty list
players = []
#Open json with player info
data = openFileJson('./player_info.json')
#Get player-id with most teams
max_key = max(data, key=lambda x: len(set(data[x]['Teams'])))
#Most number of teams a player has played for
size = len(data[max_key]['Teams'])
#For every player and their data
for playerid, playerdata in data.items():
#If they have played for the most number of teams
if len(playerdata['Teams']) == size:
#Pair their name and number of teams played for
tup = (playerdata['Name'], size)
#And put in list
players.append(tup)
return players
def getHighestWinLossRatio():
#Empty list
teams = []
#Open json with team info
data = openFileJson('./team_info.json')
#Team with best win/loss ratio
max_key = max(data, key=lambda x: data[x]['wins'] / data[x]['losses'])
#Best win/loss ratio
max_wlr = data[max_key]['wins'] / data[max_key]['losses']
#For every team
for t, tdata in data.items():
#Compute win/loss ratio
ratio = tdata['wins'] / tdata['losses']
#If ratio is the highest win/loss ratio
if ratio == max_wlr:
#Save team & ratio
tup = (t, ratio)
teams.append(tup)
return teams
def getLongestFieldGoal():
#Empty list
players = []
#Open json with player info
data = openFileJson('./player_info.json')
#Sets minimum distance for furthest field goal
furthest = 0
#For every player
for player, playerdata in data.items():
#For every yard they kicked a successful field goal
for yard in playerdata['MadeFieldGoals']:
#If current yard is greater than or equal to previous furthest field goal
if yard and yard >= furthest:
#Update furthest field goal
furthest = yard
#Save player name & yards of furthest field goal
tup = (playerdata['Name'], furthest)
players.append(tup)
#Remove every player in list whose field goal is less than furthest
players = list(filter(lambda x: x[1] == furthest, players))
return players
def getPlayerMostNegativeRush():
#Empty list
players = []
#Open json with player info
data = openFileJson('./player_info.json')
#Set maximum for negative yards rushed
lowest = 0
#For every player
for playerid, playerdata in data.items():
#For every yard they rushed
for yards in playerdata['RushYards']:
#If current yard is less than current lowest
if yards != None and yards <= lowest:
#Update lowest yards rushed to current negative yards
lowest = yards
#Save player's name and yards rushed
tup = (playerdata['Name'], lowest)
players.append(tup)
#Remove players who did not rush for the most negative yards
players = list(filter(lambda x: x[1] == lowest, players))
return players
def getPlayersWithMostTeamsInSingleYear():
#Empty list
players = []
#Open json with player info
data = openFileJson('./player_info.json')
#Set minimum size for teams played for in a year
size = 1
#For every player
for playerid, playerdata in data.items():
#For every year they played
for year, yeardata in playerdata['TeamInfo'].items():
#If they played for more teams than anyone else
if len(yeardata) > size:
#Update most number of teams played for
size = len(yeardata)
#Save their name, number of teams played for & in which year
tup = (playerdata['Name'], size, year)
players.append(tup)
#Remove players that have played for less teams than the max
players = list(filter(lambda x: x[1] == size, players))
return players
def writePlayerInfo():
#Empty dictionary
players = {}
#Opens a file for writing
g = open("player_info.json", "w")
#Opens file containing file paths from game_data
with open('files.txt') as f:
#Read every file path (for every game)
for line in f:
#Truncates empty character at end of line
line = line[:27]
#Gets file data
data = openFileJson(line)
#Old season
oldseason = 2009
#Get current season year
year = getSeason(line)
newseason = False
#If new season
if oldseason != year:
newseason = True
oldseason = year
# pull out the game id and game data
for gameid, gamedata in data.items():
if gameid != 'nextupdate':
# go straight for the drives
for driveid, drivedata in gamedata['drives'].items():
if driveid != 'crntdrv':
#For every play
for playid, playdata in drivedata['plays'].items():
#For every player in the play
for playerid, playerdata in playdata[
'players'].items():
#For stats in player during play
for info in playerdata:
#Ignore when playerid is 0
if playerid != '0':
#If player is not in dictionary
if playerid not in players:
#Make player-id a key and empty ditionary as value
players[playerid] = {}
#Add name
players[playerid][
'Name'] = info[
'playerName']
#Add team they are playing for
players[playerid]['Teams'] = []
players[playerid][
'Teams'].append(
info['clubcode'])
#Create key with empty dictionary as value
players[playerid][
'TeamInfo'] = {}
#Create list for current year
players[playerid]['TeamInfo'][
year] = []
#Add team they are playing for in current year
players[playerid]['TeamInfo'][
year].append(
info['clubcode'])
#Creating empty dictionaries
players[playerid][
'RushYards'] = []
players[playerid][
'PassYards'] = []
players[playerid][
'MadeFieldGoals'] = []
#Create a count initialized to 0
players[playerid][
'MissedFieldGoals'] = 0
players[playerid][
'DroppedPasses'] = 0
#If player rushed
if info['statId'] == 10:
players[playerid][
'RushYards'].append(
info['yards'])
#If player passed the ball
if info['statId'] == 15:
players[playerid][
'PassYards'].append(
info['yards'])
#If player made a field goal
if info['statId'] == 70:
players[playerid][
'MadeFieldGoals'].append(
info['yards'])
#If player missed a field goal
if info['statId'] == 69:
players[playerid][
'MissedFieldGoals'] = players[
playerid][
'MissedFieldGoals'] + 1
#If player dropped a passed ball
if info['statId'] == 115 and 'pass' in playdata[
'desc'] and 'dropped' in playdata[
'desc']:
players[playerid][
'DroppedPasses'] = players[
playerid][
'DroppedPasses'] + 1
#If player already in dicitionary
else:
#If player is playing for new team
if info['clubcode'] not in players[
playerid]['Teams']:
players[playerid][
'Teams'].append(
info['clubcode'])
#If its a new season create list for season year
if newseason:
players[playerid][
'TeamInfo'][year] = []
#If playing for new team in same year
if info['clubcode'] not in players[
playerid]['TeamInfo'][
year]:
players[playerid][
'TeamInfo'][
year].append(info[
'clubcode'])
#If player rushed
if info['statId'] == 10:
players[playerid][
'RushYards'].append(
info['yards'])
#If player passed the ball
if info['statId'] == 15:
players[playerid][
'PassYards'].append(
info['yards'])
#If player made a field goal
if info['statId'] == 70:
players[playerid][
'MadeFieldGoals'].append(
info['yards'])
#If player missed a field goal
if info['statId'] == 69:
players[playerid][
'MissedFieldGoals'] = players[
playerid][
'MissedFieldGoals'] + 1
#If player dropped a passed ball
if info['statId'] == 115 and 'pass' in playdata[
'desc'] and 'dropped' in playdata[
'desc']:
players[playerid][
'DroppedPasses'] = players[
playerid][
'DroppedPasses'] + 1
#Writes all game IDs
g.write(json.dumps(players))
def getPenalties(team):
data = openFileJson('./team_info.json')
pens = data[team]['penalties']
return pens
def writeTeamInfo():
teams = {}
#Opens a file for writing
g = open("team_info.json", "w")
#Corrected team abbreviations
abbr = openFileJson('./team_abbrev.json')
#Opens file containing file paths from game_data
with open('files.txt') as f:
#Read every file path
for line in f:
#Truncates empty character at end of line
line = line[:27]
#Gets file data
data = openFileJson(line)
# pull out the game id and game data
for gameid, gamedata in data.items():
if gameid != 'nextupdate':
#Get home and away teams
home = gamedata['home']['abbr']
away = gamedata['away']['abbr']
#Check for correct abbreviation
home = abbr[home]
away = abbr[away]
#If home team not in dictionary, add them & initialize values
if home not in teams:
teams[home] = {}
teams[home]['penalties'] = 0
teams[home]['penalty yards'] = 0
teams[home]['wins'] = 0
teams[home]['losses'] = 0
#Add to penalty counters of home team
teams[home]['penalties'] = teams[home][
'penalties'] + gamedata['home']['stats']['team']['pen']
teams[home]['penalty yards'] = teams[home][
'penalty yards'] + gamedata['home']['stats']['team'][
'penyds']
#If away team not in dictionary, add them & initialize values
if away not in teams:
teams[away] = {}
teams[away]['penalties'] = 0
teams[away]['penalty yards'] = 0
teams[away]['wins'] = 0
teams[away]['losses'] = 0
#Add to penalty counters of away team
teams[away]['penalties'] = teams[away][
'penalties'] + gamedata['away']['stats']['team']['pen']
teams[away]['penalty yards'] = teams[away][
'penalty yards'] + gamedata['away']['stats']['team'][
'penyds']
#Update counts for which teams won and loss
if gamedata['home']['score']['T'] > gamedata['away'][
'score']['T']:
teams[home]['wins'] = teams[home]['wins'] + 1
teams[away]['losses'] = teams[away]['losses'] + 1
elif gamedata['home']['score']['T'] < gamedata['away'][
'score']['T']:
teams[away]['wins'] = teams[away]['wins'] + 1
teams[home]['losses'] = teams[home]['losses'] + 1
#Writes all game IDs
g.write(json.dumps(teams))
#process_folder_images(folder)
#Open given image
im = Image.open(image)
#Convert to RGBA
im = im.convert('RGBA')
#Get dimensions
width, height = im.size
im = resize(im, int(width * size_change))
width, height = im.size
#Open json with player info
data = openFileJson('./color_data.json')
#Create new image to draw on
bg = Image.new("RGBA", (width * size, height * size), "black")
#No previous color because loop has not started
prev_color = None
#For every y in original image
for y in range(height):
#Update pixel for new image
y2 = y * size
#For every x in original image
for x in range(width):
