def __init__(self, *args, **kwargs):
# for initialization, we should load player data and metric system
self.defaultMetrics = DefaultMetrics(rank="", position="")
self.statCategories = kwargs["statCategories"]
#self.statCategories = [attr for attr in dir(self.defaultMetrics.playerDao.getPlayer(key=0).playerStats) if not callable(attr) and not attr.startswith("__") and attr != "type"]
print "Stat Categories: " + str(self.statCategories)
self.positions = ['PG', 'SG', 'SF', 'PF', 'C']
self.statsDao = StatsDao()
self.playerDao = PlayerDao()
self.leagueAverage = self.statsDao.getNbaAverageStat(year="")
def __init__(self, *args, **kwargs):
# Here, are there any variables that we will need?
# rank is what metric we rank by
self.rank = kwargs["rank"]
self.position = kwargs["position"]
self.playerDao = PlayerDao()
self.playerList = self.playerDao.getAllPlayersByKey()
if (self.rank == ""):
self.ranking = self.playerList
else:
self.rankList()
def __init__(self, *args, **kwargs):
# for initialization, we should load player data and metric system
self.defaultMetrics = DefaultMetrics(rank = "", position="")
self.statCategories = kwargs["statCategories"]
#self.statCategories = [attr for attr in dir(self.defaultMetrics.playerDao.getPlayer(key=0).playerStats) if not callable(attr) and not attr.startswith("__") and attr != "type"]
print "Stat Categories: " + str(self.statCategories)
self.positions = ['PG', 'SG', 'SF', 'PF', 'C']
self.statsDao = StatsDao()
self.playerDao = PlayerDao()
self.leagueAverage = self.statsDao.getNbaAverageStat(year = ""); # a StatObj
def __init__(self, *args, **kwargs):
# Here, are there any variables that we will need?
# rank is what metric we rank by
self.rank = kwargs["rank"]
self.position = kwargs["position"]
self.playerDao = PlayerDao()
self.playerList = self.playerDao.getAllPlayersByKey()
if (self.rank == ""):
self.ranking = self.playerList
else:
self.rankList()
class DefaultMetrics:
def __init__(self, *args, **kwargs):
# Here, are there any variables that we will need?
# rank is what metric we rank by
self.rank = kwargs["rank"]
self.position = kwargs["position"]
self.playerDao = PlayerDao()
self.playerList = self.playerDao.getAllPlayersByKey()
if (self.rank == ""):
self.ranking = self.playerList
else:
self.rankList()
def rankList(self):
# This will rank the list based on the position sent in, and by the metric
self.ranking = self.playerDao.getPlayersOfPosition(self.position)
self.ranking.sort(key=lambda x: getattr(x.playerStats, self.rank), reverse=True)
def printList(self):
print self.rank + ": " + str(self.ranking)
class DefaultMetrics:
def __init__(self, *args, **kwargs):
# Here, are there any variables that we will need?
# rank is what metric we rank by
self.rank = kwargs["rank"]
self.position = kwargs["position"]
self.playerDao = PlayerDao()
self.playerList = self.playerDao.getAllPlayersByKey()
if (self.rank == ""):
self.ranking = self.playerList
else:
self.rankList()
def rankList(self):
# This will rank the list based on the position sent in, and by the metric
self.ranking = self.playerDao.getPlayersOfPosition(self.position)
self.ranking.sort(key=lambda x: getattr(x.playerStats, self.rank),
reverse=True)
def printList(self):
print self.rank + ": " + str(self.ranking)
class DefaultSelector:
def __init__(self, *args, **kwargs):
# for initialization, we should load player data and metric system
self.defaultMetrics = DefaultMetrics(rank="", position="")
self.statCategories = kwargs["statCategories"]
#self.statCategories = [attr for attr in dir(self.defaultMetrics.playerDao.getPlayer(key=0).playerStats) if not callable(attr) and not attr.startswith("__") and attr != "type"]
print "Stat Categories: " + str(self.statCategories)
self.positions = ['PG', 'SG', 'SF', 'PF', 'C']
self.statsDao = StatsDao()
self.playerDao = PlayerDao()
self.leagueAverage = self.statsDao.getNbaAverageStat(year="")
# a StatObj
#print self.leagueAverage
'''This is the master selection algorithm. '''
def selectMaster(self, roundNum, fTeamKey=1):
if (int(roundNum) > 3):
print "Selecting the Balanced Team"
rankings = self.selectBalanced(fTeamKey)
else:
print "Selecting the Best Player"
rankings = self.selectBest()
print rankings[0:49]
'''This is the function that will get overridden for different selection methods'''
def selectBest(self):
# This function will select the best player available based on two metrics: best percentage increase, and balance of stats
playersAvailableList = self.playerDao.getAllAvailablePlayers()
greatestIncreaseList = {}
for player in playersAvailableList:
#f.write(str(player) + ":\n")
#print str(player) + ":"
avg = self.calculatePercentage(player)
#f.write("Overall Average: " + str(avg) + "\n")
#print "Overall Average: " + str(avg) + "\n\n"
greatestIncreaseList[str(player)] = avg
return sorted(greatestIncreaseList,
key=greatestIncreaseList.get,
reverse=True)
def selectBalanced(self, fTeamKey):
playersAvailableList = self.playerDao.getAllAvailablePlayers()
balancedStatList = {}
# Calculate a weighted average of the important stats required
fTeamStatLine = self.assessTeam(fTeamKey)
balancedStatList.update(zip(self.statCategories, fTeamStatLine))
sortedDict = sorted(balancedStatList,
key=balancedStatList.get,
reverse=True)
# Now weight the stat category with the index + 1
weight = dict(
zip(sortedDict, [x for x in range(len(self.statCategories))]))
balancedList = {}
for player in playersAvailableList:
avg = self.calculatePercentage(player, weight)
balancedList[str(player)] = avg
return sorted(balancedList, key=balancedList.get, reverse=True)
def calculatePercentage(self, player, weight=None):
# Weight sent in will be a dictionary of stat categories vs index weight
if (weight is None):
weight = dict(
zip(self.statCategories, [1] * len(self.statCategories)))
playerVsAverageList = []
for stat in self.statCategories:
num = (getattr(player.playerStats, stat) * weight[stat] - getattr(
self.leagueAverage, stat)) / getattr(self.leagueAverage, stat)
if (stat == "tov"):
num = num * -1
playerVsAverageList.append(num)
#f.write(stat + ": " + str(num) + "\n")
#print stat + ": " + str(num)
# Now calculate overall percentage which we will return
overallAverage = mean(playerVsAverageList)
return overallAverage
def calculateStatLinePercentages(self, player):
playerVsAverageList = []
for stat in self.statCategories:
num = (getattr(player.playerStats, stat) - getattr(
self.leagueAverage, stat)) / getattr(self.leagueAverage, stat)
if (stat == "tov"):
num = num * -1
playerVsAverageList.append(num)
return playerVsAverageList
'''This function will select the next best player at position'''
def selectBestForPosition(self, position, fTeamKey=0):
ids_l1 = set(x.name
for x in self.playerDao.getAllAvailablePlayers(fTeamKey))
l2 = self.playerDao.getPlayersOfPosition(position)
playersAvailableList = [item for item in l2 if item.name in ids_l1]
return playersAvailableList
'''This function will take the fantasy team and assess the team based on the stat categories'''
def assessTeam(self, fTeamKey=1):
fTeamPlayers = self.playerDao.getFantasyTeam(fTeamKey)
fTeamStatLine = [(0.0, 0.0),
(0.0, 0.0)] + [0] * (len(self.statCategories) - 2)
for fTeamPlayer in fTeamPlayers:
for idx, item in enumerate(self.getStatLine(fTeamPlayer)):
if (self.statCategories[idx] == 'fgp'
or self.statCategories[idx] == 'ftp'
or self.statCategories[idx] == 'fgp3'):
fTeamStatLine[idx] = (fTeamStatLine[idx][0] + item[0],
fTeamStatLine[idx][1] + item[1])
else:
fTeamStatLine[idx] = fTeamStatLine[idx] + item
#fTeamStatLine = [x + y for x,y in zip(fTeamStatLine, self.getStatLine(fTeamPlayer)) if isinstance(x, int)]
# calculate how much above or below average it is against the nba standard
percentageDifference = self.calculateTeamPercentage(
fTeamStatLine, len(fTeamPlayers))
return percentageDifference
def getStatLine(self, player):
statLine = [0] * len(self.statCategories)
for idx, stat in enumerate(self.statCategories):
if (stat == 'fgp'):
statLine[idx] = (player.playerStats.fgm,
player.playerStats.fga)
elif (stat == 'ftp'):
statLine[idx] = (player.playerStats.ftm,
player.playerStats.fta)
elif (stat == 'fgp3'):
statLine[idx] = (player.playerStats.fg3,
player.playerStats.fga3)
else:
statLine[idx] = getattr(player.playerStats, stat)
return statLine
def calculateTeamPercentage(self, teamStatLine, length):
teamPercentage = [0] * len(self.statCategories)
for idx, stat in enumerate(self.statCategories):
if (stat == 'fgp' or stat == 'ftp' or stat == 'fgp3'):
if (teamStatLine[idx][1] != 0):
perc = teamStatLine[idx][0] / teamStatLine[idx][1] * 100
num = (perc - getattr(self.leagueAverage, stat)) / getattr(
self.leagueAverage, stat)
else:
num = (teamStatLine[idx] -
getattr(self.leagueAverage, stat)) / getattr(
self.leagueAverage, stat) * length
if (stat == 'tov'):
num = num * -1
teamPercentage[idx] = num
print "Team Percentage: " + str(teamPercentage)
return teamPercentage
class DefaultSelector:
def __init__(self, *args, **kwargs):
# for initialization, we should load player data and metric system
self.defaultMetrics = DefaultMetrics(rank = "", position="")
self.statCategories = kwargs["statCategories"]
#self.statCategories = [attr for attr in dir(self.defaultMetrics.playerDao.getPlayer(key=0).playerStats) if not callable(attr) and not attr.startswith("__") and attr != "type"]
print "Stat Categories: " + str(self.statCategories)
self.positions = ['PG', 'SG', 'SF', 'PF', 'C']
self.statsDao = StatsDao()
self.playerDao = PlayerDao()
self.leagueAverage = self.statsDao.getNbaAverageStat(year = ""); # a StatObj
#print self.leagueAverage
'''This is the master selection algorithm. '''
def selectMaster(self, roundNum, fTeamKey=1):
if (int(roundNum) > 3):
print "Selecting the Balanced Team"
rankings = self.selectBalanced(fTeamKey)
else:
print "Selecting the Best Player"
rankings = self.selectBest()
print rankings[0:49]
'''This is the function that will get overridden for different selection methods'''
def selectBest(self):
# This function will select the best player available based on two metrics: best percentage increase, and balance of stats
playersAvailableList = self.playerDao.getAllAvailablePlayers()
greatestIncreaseList = {}
for player in playersAvailableList:
#f.write(str(player) + ":\n")
#print str(player) + ":"
avg = self.calculatePercentage(player)
#f.write("Overall Average: " + str(avg) + "\n")
#print "Overall Average: " + str(avg) + "\n\n"
greatestIncreaseList[str(player)] = avg
return sorted(greatestIncreaseList, key=greatestIncreaseList.get, reverse=True)
def selectBalanced(self,fTeamKey):
playersAvailableList = self.playerDao.getAllAvailablePlayers()
balancedStatList = {}
# Calculate a weighted average of the important stats required
fTeamStatLine = self.assessTeam(fTeamKey)
balancedStatList.update(zip(self.statCategories, fTeamStatLine))
sortedDict = sorted(balancedStatList, key=balancedStatList.get, reverse=True)
# Now weight the stat category with the index + 1
weight = dict(zip(sortedDict, [x for x in range(len(self.statCategories))]))
balancedList = {}
for player in playersAvailableList:
avg = self.calculatePercentage(player, weight)
balancedList[str(player)] = avg
return sorted(balancedList, key=balancedList.get,reverse=True)
def calculatePercentage(self, player, weight = None):
# Weight sent in will be a dictionary of stat categories vs index weight
if (weight is None):
weight = dict(zip(self.statCategories, [1]*len(self.statCategories)))
playerVsAverageList = []
for stat in self.statCategories:
num = (getattr(player.playerStats, stat)*weight[stat]-getattr(self.leagueAverage, stat))/getattr(self.leagueAverage, stat)
if (stat == "tov"):
num = num*-1
playerVsAverageList.append(num)
#f.write(stat + ": " + str(num) + "\n")
#print stat + ": " + str(num)
# Now calculate overall percentage which we will return
overallAverage = mean(playerVsAverageList)
return overallAverage
def calculateStatLinePercentages(self, player):
playerVsAverageList = []
for stat in self.statCategories:
num = (getattr(player.playerStats, stat)-getattr(self.leagueAverage, stat))/getattr(self.leagueAverage, stat)
if (stat == "tov"):
num = num*-1
playerVsAverageList.append(num)
return playerVsAverageList
'''This function will select the next best player at position'''
def selectBestForPosition(self, position, fTeamKey = 0):
ids_l1 = set(x.name for x in self.playerDao.getAllAvailablePlayers(fTeamKey))
l2 = self.playerDao.getPlayersOfPosition(position)
playersAvailableList = [item for item in l2 if item.name in ids_l1]
return playersAvailableList
'''This function will take the fantasy team and assess the team based on the stat categories'''
def assessTeam(self, fTeamKey=1):
fTeamPlayers = self.playerDao.getFantasyTeam(fTeamKey)
fTeamStatLine = [(0.0,0.0),(0.0,0.0)] + [0] *(len(self.statCategories)-2)
for fTeamPlayer in fTeamPlayers:
for idx,item in enumerate(self.getStatLine(fTeamPlayer)):
if (self.statCategories[idx] == 'fgp' or self.statCategories[idx] == 'ftp' or self.statCategories[idx] == 'fgp3'):
fTeamStatLine[idx] = (fTeamStatLine[idx][0] + item[0], fTeamStatLine[idx][1] + item[1])
else:
fTeamStatLine[idx] = fTeamStatLine[idx] + item
#fTeamStatLine = [x + y for x,y in zip(fTeamStatLine, self.getStatLine(fTeamPlayer)) if isinstance(x, int)]
# calculate how much above or below average it is against the nba standard
percentageDifference = self.calculateTeamPercentage(fTeamStatLine, len(fTeamPlayers))
return percentageDifference
def getStatLine(self, player):
statLine = [0] * len(self.statCategories)
for idx,stat in enumerate(self.statCategories):
if (stat == 'fgp'):
statLine[idx] = (player.playerStats.fgm, player.playerStats.fga)
elif (stat == 'ftp'):
statLine[idx] = (player.playerStats.ftm, player.playerStats.fta)
elif (stat == 'fgp3'):
statLine[idx] = (player.playerStats.fg3, player.playerStats.fga3)
else:
statLine[idx] = getattr(player.playerStats, stat)
return statLine
def calculateTeamPercentage(self, teamStatLine, length):
teamPercentage = [0] *len(self.statCategories)
for idx,stat in enumerate(self.statCategories):
if (stat == 'fgp' or stat == 'ftp' or stat == 'fgp3'):
if (teamStatLine[idx][1] != 0):
perc = teamStatLine[idx][0]/teamStatLine[idx][1]*100
num = (perc-getattr(self.leagueAverage,stat))/getattr(self.leagueAverage,stat)
else:
num = (teamStatLine[idx]-getattr(self.leagueAverage, stat))/getattr(self.leagueAverage, stat)*length
if (stat == 'tov'):
num = num * -1
teamPercentage[idx] = num
print "Team Percentage: " + str(teamPercentage)
return teamPercentage
'''
Created on 2013-10-09
@author: Ivan
'''
import csv
from PlayerDao import PlayerDao
import MySQLdb
def getDbConnection():
db = MySQLdb.connect(host="localhost", user="******", passwd="watershipdown", db="nba_db")
return db
with open("dataload/ESPN_Master.csv") as csvplayers:
reader2 = csv.reader(csvplayers)
dao = PlayerDao()
playerList = dao.getAllPlayersByKey()
indArr = []
positionArr = []
i = 0
for row in reader2:
row[1] = row[1].replace("'", "''")
# split by | delimiter
elems = row[1].split("|")
j = 0
for elem in elems:
elems[j] = elem.replace('\xa0', ' ')
j = j+1
if (elems[0] in str(playerList)):
# First add the index to it
ind = dao.getPlayerKeyByName(elems[0])
