def simulateGW(gw, SD):
fixtures = fixtureDict[gw]
playerDict = {}
for team, lineup in lineups.items():
for player in lineup:
playerDict[player] = 0
for fixture in fixtures:
print(fixture[0] + '.' * (44 - len(fixture[0] + fixture[1])) + fixture[1])
print(simulate(fixture[0], fixture[1]))
for fixture in fixtures:
for player, pts in simulateBonus(fixture[0], fixture[1], SD).items():
playerDict[player] += pts
print('\n' * 2)
print('Most bonus points:', [(getPlayer(i[0], 'understat', 'name'), i[1]) for i in
sorted(list(playerDict.items()), key=lambda i: i[1], reverse=True)[:10]])
xPtsDB[str(gw)] = {}
for fixture in fixtures:
for player, pts in simulateBonus(fixture[0], fixture[1], SD).items():
if player in lineups[fixture[0]]:
loc = 'h'
elif player in lineups[fixture[1]]:
loc = 'a'
playerDict[player] += simulatePts(getPosition(player, 'understat'), player, loc,
(loc == 'h') * fixture[1] + (loc == 'a') * fixture[0], SD)
xPtsDB[str(gw)][str(player)] = playerDict[player]
print('\n')
for i in sorted(list(playerDict.items()), key=lambda i: i[1], reverse=True):
print(getPlayer(i[0], 'understat', 'name') + '.' * (30 - len(getPlayer(i[0], 'understat', 'name'))) + str(i[1])[
:4] + (
4 - len(str(i[1]))) * '0')
print('Mean among top 21 assets: ' + str(
np.mean([i[1] for i in sorted(list(playerDict.items()), key=lambda i: i[1], reverse=True)[:30]]))[:4])
with open('xPtsDB.json', 'w') as fp:
json.dump(xPtsDB, fp)
def simulateBonus(homeTeam, awayTeam, SD):
homeLineup, awayLineup = lineups[homeTeam], lineups[awayTeam]
xReturns = {player: [] for player in homeLineup + awayLineup}
bonus = {player: [] for player in homeLineup + awayLineup}
for player in homeLineup:
xReturns[player] = simulateReturns(
getPosition(player, 'understat'), player, 'h', awayTeam,
SD) + [getPosition(player, 'understat')]
for player in awayLineup:
xReturns[player] = simulateReturns(
getPosition(player, 'understat'), player, 'a', homeTeam,
SD) + [getPosition(player, 'understat')]
CSOdds = simulateCleanSheet(homeTeam, awayTeam)
trials = 10000
for repeat in range(trials):
homeBPS, awayBPS = {player: 0
for player in homeLineup
}, {player: 0
for player in awayLineup}
for player in homeLineup:
homeBPS[player] += np.random.normal(
baselineDB[homeTeam][str(player)][0],
baselineDB[homeTeam][str(player)][1])
goals = np.random.poisson(xReturns[player][0])
for goal in range(goals):
homeBPS[player] += {
'GKP': 12,
'DEF': 12,
'MID': 18,
'FOR': 24
}[xReturns[player][2]]
if random() < xAConstant:
assist = [[
player, xReturns[player][1]
] for player in [i for i in homeLineup if i != player]]
r = random() * sum([i[1] for i in assist])
for entry in assist:
if r < entry[1]:
homeBPS[entry[0]] += 9
break
r -= entry[1]
if random() < CSOdds[0]:
for player in [
player for player in homeLineup
if xReturns[player][2] == 'GKP'
or xReturns[player][2] == 'DEF'
]:
homeBPS[player] += 12
for player in awayLineup:
awayBPS[player] += np.random.normal(
baselineDB[awayTeam][str(player)][0],
baselineDB[awayTeam][str(player)][1])
goals = np.random.poisson(xReturns[player][0])
for goal in range(goals):
awayBPS[player] += {
'GKP': 12,
'DEF': 12,
'MID': 18,
'FOR': 24
}[xReturns[player][2]]
if random() < xAConstant:
assist = [[
player, xReturns[player][1]
] for player in [i for i in awayLineup if i != player]]
r = random() * sum([i[1] for i in assist])
for entry in assist:
if r < entry[1]:
awayBPS[entry[0]] += 9
break
r -= entry[1]
if random() < CSOdds[1]:
for player in [
player for player in awayLineup
if xReturns[player][2] == 'GKP'
or xReturns[player][2] == 'DEF'
]:
awayBPS[player] += 12
BPS = sorted([(i[0], i[1]) for i in list({
**homeBPS,
**awayBPS
}.items())],
key=lambda x: x[1],
reverse=True)
bonus[BPS[0][0]].append(3)
bonus[BPS[1][0]].append(2)
bonus[BPS[2][0]].append(1)
for player, scores in bonus.items():
bonus[player] = sum(scores) / trials
return bonus
bonus[BPS[1][0]].append(2)
bonus[BPS[2][0]].append(1)
for player, scores in bonus.items():
bonus[player] = sum(scores) / trials
return bonus
if __name__ == '__main__':
print('\n' * 2)
print(
sorted(list(simulateBonus('Leicester', 'West Ham', 10).items()),
key=lambda x: x[1],
reverse=True))
print('\n' * 2)
baselineArray = []
for team in teams:
for player in baselineDB[team]:
baselineArray.append((int(player), baselineDB[team][player][0]))
for i in sorted(baselineArray, key=lambda i: i[1], reverse=True):
if i[1] != 0 or i[0] == 5675:
print(
getPosition(i[0], 'understat'),
getPlayer(i[0], 'understat', 'name') + '.' *
(30 - len(getPlayer(i[0], 'understat', 'name'))) +
str(round(i[1], 1)))
print(
np.mean([
i[1] for i in baselineArray
if getPosition(i[0], 'understat') == 'FOR' and i[1] != 0
]))
def baselineBonus(understat):
poisition = getPosition(understat, 'understat')
mean, sd = 0, 0
GWStats, baselineBPS = [], []
name = getPlayer(understat, 'understat',
'name').replace(' ', '_', 1)
exceptions = {
619: 'Sergio_Ag%C3%BCero',
3293: 'Lucas_Rodrigues Moura da Silva',
1040: 'José Ángel_Esmorís Tasende',
1208: 'Felipe Anderson_Pereira Gomes',
5741: 'Jorge Luiz_Frello Filho',
1663: 'Johann Berg_Gudmundsson',
1676: 'David_Luiz Moreira Marinho',
1724: 'Isaac_Success Ajayi',
2132: 'José Ignacio_Peleteiro Romallo',
2379: 'João Pedro Cavaco_Cancelo',
2383: 'André Filipe_Tavares Gomes',
2446: 'Daniel_Ceballos Fernández',
3303: 'Ricardo Domingos_Barbosa Pereira',
3422: 'João Filipe Iria_Santos Moutinho',
5245: 'Bernardo_Fernandes da Silva Junior',
3635: 'Bernardo Mota_Veiga de Carvalho e Silva',
5543: 'Gabriel Fernando_de Jesus',
5675: 'Ismaïla_Sarr',
579: 'Nathan_Aké',
6122: 'Douglas Luiz_Soares de Paulo',
614: 'Fernando_Luiz Rosa',
6817: 'Frederico_Rodrigues de Paula Santos',
6853: 'Rúben Diogo_da Silva Neves',
6856: 'Rúben Gonçalo_Silva Nascimento Vinagre',
700: 'Willian_Borges Da Silva',
7752: 'Gabriel Teodoro_Martinelli Silva',
87: 'Joelinton Cássio_Apolinário de Lira'
}
if understat in exceptions:
name = exceptions[understat]
url = 'https://raw.githubusercontent.com/vaastav/Fantasy-Premier-League/master/data/2019-20/players/' + name + '_' + str(
getPlayer(understat, 'understat', 'fpl')) + '/gw.csv'
r = requests.get(url)
text = r.iter_lines()
reader = csv.reader(text, delimiter=',')
for line in text:
if str(line) == "b'404: Not Found'":
if understat in exceptions:
print(understat)
return (0, 0)
GWStats.append(str(line)[2:-1].split(","))
for row in GWStats[1:]:
if row != ['']:
if int(row[12]) >= 60:
baselineBPS.append(
int(row[2]) - int(row[8]) *
(12 *
(poisition == 'DEF' or poisition == 'GKP') +
18 * (poisition == 'MID') + 24 *
(poisition == 'FOR')) - int(row[0]) * 9 -
int(row[3]) * 12 *
(poisition == 'DEF' or poisition == 'MID'))
if len(baselineBPS) < 1:
return (0, 0)
return (np.mean(baselineBPS), np.std(baselineBPS))
teamCodes = {team: i for team in teams for i in range(len(teams))}
DB = compileGWs(GWStart, GWEnd)
players = [
player for player in DB if int(player) not in blacklist
and isStarter(int(player), 'understat') == True
]
prob = LpProblem("optimiseTeam", LpMaximize)
useVars = LpVariable.dicts("usePlayer", players, 0, 1, LpBinary)
prob += lpSum([DB[j] * useVars[j] for j in useVars])
prob += lpSum(
priceDB[j] * useVars[j] for j in useVars
) <= TV - 3.9 * (5 - lpSum([
useVars[i] for i in useVars if getPosition(int(i), 'understat') == 'DEF'
])) - 4.3 * (5 - lpSum([
useVars[i] for i in useVars if getPosition(int(i), 'understat') == 'MID'
])) - 4.3 * (3 - lpSum(
[useVars[i]
for i in useVars if getPosition(int(i), 'understat') == 'FOR']))
prob += lpSum([
useVars[i] for i in useVars if getPosition(int(i), 'understat') == 'GKP'
]) == 1
prob += lpSum(
[useVars[i]
for i in useVars if getPosition(int(i), 'understat') == 'DEF']) >= 3
prob += lpSum(
[useVars[i]
for i in useVars if getPosition(int(i), 'understat') == 'DEF']) <= 5
prob += lpSum(
points = []
for GW in range(GWStart, GWEnd + 1):
points.append(xPtsDB[str(GW)][str(name)])
return points
def GWForecast(GW=nextGW):
return sorted([(int(i[0]), i[1]) for i in list(xPtsDB[str(GW)].items())], key=lambda i: i[1], reverse=True)
if __name__ == '__main__':
playerDict = {}
for team, lineup in lineups.items():
for player in lineup:
playerDict[player] = sum(simulatePtsRun(player, 27))
for player in sorted(list(playerDict.items()), key=lambda i: i[1], reverse=True):
print(getPlayer(player[0], 'understat', 'name') + '.' * (
30 - len(getPlayer(player[0], 'understat', 'name'))) + str(round(player[1], 1)))
print('\n')
end = 30
player = 'Martial'
print(sum(simulatePtsRun(getPlayer(player), end, nextGW)), simulatePtsRun(getPlayer(player), end, nextGW))
player = 'Grealish'
print(sum(simulatePtsRun(getPlayer(player), end, nextGW)), simulatePtsRun(getPlayer(player), end, nextGW))
print('\n')
for player in GWForecast(nextGW):
if getPosition(player[0], 'understat') == 'MID':
print(getPlayer(player[0], 'understat', 'name') + '.' * (
30 - len(getPlayer(player[0], 'understat', 'name'))) + str(round(player[1], 2)) + '0' * (
4 - len(str(round(player[1], 2)))))