计算球队在联赛中排名的概率
Calculate probability of a team ranking inside a league
这个项目的目标是计算每支球队进入前 6 名的概率（剩余的场景，即每支球队在剩余比赛中获胜或输掉但仍然进入前 6 名）所以我制作了一个 3D 列表以输入比赛历史（打过的比赛，我们知道结果）问题是我不知道如何计算球队排名的概率，因为它也取决于其他球队我想找到一个公式或代码来解决它
class Team:
def __init__(self, name, pos):
self.name = name
self.pos = pos
self.w = 0
self.l = 0
self.score = ""
def upd_score(self, history):
# check the rows
for match in history[self.pos]:
if match == ["w"]:
self.w += 1
elif match == ["l"]:
self.l += 1
# check the columns
for match in history:
if match[self.pos] == ["l"]:
self.w += 1
elif match[self.pos] == ["w"]:
self.l += 1
self.score = f"{self.w} - {self.l}"
def get_score(self):
print(f"the score is {self.score} ")
RGE = Team("RGE", 1)
VIT = Team("VIT", 2)
G2 = Team("G2", 3)
MSF = Team("MSF", 4)
AST = Team("AST", 5)
MAD = Team("MAD", 6)
FNC = Team("FNC", 7)
SK = Team("SK", 8)
XL = Team("XL", 9)
BDS = Team("BDS", 10)
MATCH_HISTORY = [
[["X"], [RGE], [VIT], [G2], [MSF], [AST], [MAD], [FNC], [SK], [XL], [BDS]],
[[RGE], ["X"], ["w"], ["w"], ["l"], [""], [""], [""], [""], [""], [""]],
[[VIT], ["w"], ["X"], [""], [""], [""], [""], [""], [""], [""], [""]],
[[G2], ["w"], [""], ["X"], [""], [""], [""], [""], [""], [""], [""]],
[[MSF], ["w"], [""], [""], ["X"], [""], [""], [""], [""], [""], [""]],
[[AST], ["l"], [""], [""], [""], ["X"], [""], [""], [""], [""], [""]],
[[MAD], ["w"], [""], [""], [""], [""], ["X"], [""], [""], [""], [""]],
[[FNC], ["l"], [""], [""], [""], [""], [""], ["X"], [""], [""], [""]],
[[SK], ["w"], [""], [""], [""], [""], [""], [""], ["X"], [""], [""]],
[[XL], ["w"], [""], [""], [""], [""], [""], [""], [""], ["X"], [""]],
[[BDS], ["w"], [""], [""], [""], [""], [""], [""], [""], [""], ["X"]],
]
# SCORE UPDATING
RGE.upd_score(MATCH_HISTORY)
VIT.upd_score(MATCH_HISTORY)
G2.upd_score(MATCH_HISTORY)
MSF.upd_score(MATCH_HISTORY)
AST.upd_score(MATCH_HISTORY)
MAD.upd_score(MATCH_HISTORY)
FNC.upd_score(MATCH_HISTORY)
SK.upd_score(MATCH_HISTORY)
XL.upd_score(MATCH_HISTORY)
BDS.upd_score(MATCH_HISTORY)
计算分数：如果球队在胜利行中，我将输入“w”，如果球队在列中，我将在不能获胜的情况下输入“l”和“X”被填补（球队不能与自己比赛）
顺便说一句，我还是个初学者，所以如果有优化我的代码的方法，请告诉我，如果你有建议，最好解释一下，或者 link 给我一些可以帮助的东西
对于一个团队获胜的基本概率，您可以使用他们的胜利来弥补他们的总损失。
self.w / (self.w + self.l)
要计算团队排名的（同样是非常基本的）概率，只需计算出所有团队的概率并将它们从高到低排序即可。例如
# teams is an array containing instances of your teams
team_win_probs = []
for team in teams:
team_win_probs.append((team.name, team.w / (team.w + team.l)))
team_win_probs.sort(key=lambda p: p[1], reverse=True) # the lambda gets the second elements of the tuple
在这里，我使用了一个元组来耦合球队名称和球队获胜概率，并在 list 的排序参数 key 中使用了一个 lambda 来从 tuple 并根据它排序。
希望对您有所帮助:)
我喜欢这个想法并且忍不住去做，所以这是代码
基本上它会遍历所有尚未完成的比赛存在的所有可能性，并计算前 N 名的每支球队的统计数据（您可以在代码中更改）
唯一的问题是可能性的数量是 2^undone_matches 并且它很快就变高了，所以你不能 运行 程序超过 15 个未完成的匹配...
另一种可能性是不是递归地而是用概率数学来做，但我太懒了 xD
PS: 现在程序不处理分数相等，取相同分数的第一队，如果你愿意，我让你处理:)
import copy
class Team:
def __init__(self, name):
self.name = name
self.w = 0
self.l = 0
def init_scores(self, MH):
for rowIndex in range(0, len(MH[0])):
if MH[rowIndex][0] == self.name:
index = rowIndex
for columnIndex in range(0, len(MH[0])):
result = MH[columnIndex][index]
if result == "w":
self.l += 1
elif result == "l":
self.w += 1
for columnIndex in range(0, len(MH[0])):
if MH[0][columnIndex] == self.name:
index = columnIndex
for rowIndex in range(0, len(MH[0])):
result = MH[index][rowIndex]
if result == "w":
self.w += 1
elif result == "l":
self.l += 1
def toString(self):
r = "| " + self.name.ljust(9) + "|\n"
r += "|" + "----------" + "|\n"
r += "| w: " + str(self.w).ljust(6) + "|\n"
r += "| l: " + str(self.l).ljust(6) + "|\n"
return r
def getScore(self):
return [self.name, self.w]
def createAllPossibilities(MH, topN, results):
coo = emptyCellExist(MH)
if coo[0] >= 0:
cp1 = copy.deepcopy(MH)
cp1[coo[0]][coo[1]] = "w"
createAllPossibilities(cp1, topN, results)
cp2 = copy.deepcopy(MH)
cp2[coo[0]][coo[1]] = "l"
createAllPossibilities(cp2, topN, results)
else:
Teams = []
Teams.append(Team("RGE"))
Teams.append(Team("VIT"))
Teams.append(Team("G2"))
Teams.append(Team("MSF"))
Teams.append(Team("AST"))
Teams.append(Team("MAD"))
Teams.append(Team("FNC"))
Teams.append(Team("SK"))
Teams.append(Team("XL"))
Teams.append(Team("BDS"))
for t in Teams:
t.init_scores(MH)
scores = []
for t in Teams:
scores.append(t.getScore())
for n in range(topN):
best = 0
index = -1
for t in range(len(scores)):
if best < scores[t][1]:
best = scores[t][1]
index = t
scores[index][1] = 0
#print(scores)
results[index] += 1
def emptyCellExist(MH):
for row in range(len(MH[0])):
for cell in range(len(MH[0])):
if MH[row][cell] == "":
return [row, cell]
return [-1, -1]
# current score
MATCH_HISTORY = [ ["X", "RGE", "VIT", "G2", "MSF", "AST", "MAD", "FNC", "SK", "XL", "BDS"],
["RGE", "X", "w", "w", "l", "l", "w", "l", "l", "w", ""],
["VIT", "w", "X", "l", "w", "l", "w", "l", "w", "w", ""],
["G2", "w", "l", "X", "w", "w", "l", "l", "w", "w", ""],
["MSF", "w", "l", "v", "X", "w", "w", "l", "w", "w", ""],
["AST", "l", "l", "l", "l", "X", "l", "l", "l", "", ""],
["MAD", "w", "l", "v", "w", "l", "X", "l", "l", "", ""],
["FNC", "l", "l", "l", "w", "l", "l", "X", "w", "", ""],
["SK", "w", "l", "w", "l", "w", "w", "l", "X", "", ""],
["XL", "w", "l", "w", "w", "l", "l", "w", "w", "X", ""],
["BDS", "w", "l", "w", "w", "l", "w", "w", "l", "", "X"]]
# top teams must be top X
topN = 6
# count the number of matches done and left to do
matchesDone = 0
matchesLeft = 0
for row in MATCH_HISTORY:
for cell in row:
if cell == "w" or cell == "l":
matchesDone += 1
elif cell == "":
matchesLeft += 1
print("matches done : " + str(matchesDone))
print("matches left to do : " + str(matchesLeft))
print("that's " + str(pow(2, matchesLeft)) + " possibilities\n")
if matchesLeft > 20:
print("that's way to much for me")
else:
# if the number of matches left to do is low enought, then start calculating the probabilities
results = [0 for a in range(len(MATCH_HISTORY[0]))]
createAllPossibilities(MATCH_HISTORY, topN, results)
print(MATCH_HISTORY[0][1:])
for a in range(len(results)):
results[a] /= (pow(2, matchesLeft)*topN)
results[a] = int(results[a]*1000)/10
print(results)
while 1:
pass
这个项目的目标是计算每支球队进入前 6 名的概率（剩余的场景，即每支球队在剩余比赛中获胜或输掉但仍然进入前 6 名）所以我制作了一个 3D 列表以输入比赛历史（打过的比赛，我们知道结果）问题是我不知道如何计算球队排名的概率，因为它也取决于其他球队我想找到一个公式或代码来解决它
class Team:
def __init__(self, name, pos):
self.name = name
self.pos = pos
self.w = 0
self.l = 0
self.score = ""
def upd_score(self, history):
# check the rows
for match in history[self.pos]:
if match == ["w"]:
self.w += 1
elif match == ["l"]:
self.l += 1
# check the columns
for match in history:
if match[self.pos] == ["l"]:
self.w += 1
elif match[self.pos] == ["w"]:
self.l += 1
self.score = f"{self.w} - {self.l}"
def get_score(self):
print(f"the score is {self.score} ")
RGE = Team("RGE", 1)
VIT = Team("VIT", 2)
G2 = Team("G2", 3)
MSF = Team("MSF", 4)
AST = Team("AST", 5)
MAD = Team("MAD", 6)
FNC = Team("FNC", 7)
SK = Team("SK", 8)
XL = Team("XL", 9)
BDS = Team("BDS", 10)
MATCH_HISTORY = [
[["X"], [RGE], [VIT], [G2], [MSF], [AST], [MAD], [FNC], [SK], [XL], [BDS]],
[[RGE], ["X"], ["w"], ["w"], ["l"], [""], [""], [""], [""], [""], [""]],
[[VIT], ["w"], ["X"], [""], [""], [""], [""], [""], [""], [""], [""]],
[[G2], ["w"], [""], ["X"], [""], [""], [""], [""], [""], [""], [""]],
[[MSF], ["w"], [""], [""], ["X"], [""], [""], [""], [""], [""], [""]],
[[AST], ["l"], [""], [""], [""], ["X"], [""], [""], [""], [""], [""]],
[[MAD], ["w"], [""], [""], [""], [""], ["X"], [""], [""], [""], [""]],
[[FNC], ["l"], [""], [""], [""], [""], [""], ["X"], [""], [""], [""]],
[[SK], ["w"], [""], [""], [""], [""], [""], [""], ["X"], [""], [""]],
[[XL], ["w"], [""], [""], [""], [""], [""], [""], [""], ["X"], [""]],
[[BDS], ["w"], [""], [""], [""], [""], [""], [""], [""], [""], ["X"]],
]
# SCORE UPDATING
RGE.upd_score(MATCH_HISTORY)
VIT.upd_score(MATCH_HISTORY)
G2.upd_score(MATCH_HISTORY)
MSF.upd_score(MATCH_HISTORY)
AST.upd_score(MATCH_HISTORY)
MAD.upd_score(MATCH_HISTORY)
FNC.upd_score(MATCH_HISTORY)
SK.upd_score(MATCH_HISTORY)
XL.upd_score(MATCH_HISTORY)
BDS.upd_score(MATCH_HISTORY)
计算分数：如果球队在胜利行中，我将输入“w”，如果球队在列中，我将在不能获胜的情况下输入“l”和“X”被填补（球队不能与自己比赛）
顺便说一句，我还是个初学者，所以如果有优化我的代码的方法，请告诉我，如果你有建议，最好解释一下，或者 link 给我一些可以帮助的东西
对于一个团队获胜的基本概率，您可以使用他们的胜利来弥补他们的总损失。
self.w / (self.w + self.l)
要计算团队排名的（同样是非常基本的）概率，只需计算出所有团队的概率并将它们从高到低排序即可。例如
# teams is an array containing instances of your teams
team_win_probs = []
for team in teams:
team_win_probs.append((team.name, team.w / (team.w + team.l)))
team_win_probs.sort(key=lambda p: p[1], reverse=True) # the lambda gets the second elements of the tuple
在这里，我使用了一个元组来耦合球队名称和球队获胜概率，并在 list 的排序参数 key 中使用了一个 lambda 来从 tuple 并根据它排序。
希望对您有所帮助:)
我喜欢这个想法并且忍不住去做，所以这是代码
基本上它会遍历所有尚未完成的比赛存在的所有可能性，并计算前 N 名的每支球队的统计数据（您可以在代码中更改）
唯一的问题是可能性的数量是 2^undone_matches 并且它很快就变高了，所以你不能 运行 程序超过 15 个未完成的匹配...
另一种可能性是不是递归地而是用概率数学来做，但我太懒了 xD
PS: 现在程序不处理分数相等，取相同分数的第一队，如果你愿意，我让你处理:)
import copy
class Team:
def __init__(self, name):
self.name = name
self.w = 0
self.l = 0
def init_scores(self, MH):
for rowIndex in range(0, len(MH[0])):
if MH[rowIndex][0] == self.name:
index = rowIndex
for columnIndex in range(0, len(MH[0])):
result = MH[columnIndex][index]
if result == "w":
self.l += 1
elif result == "l":
self.w += 1
for columnIndex in range(0, len(MH[0])):
if MH[0][columnIndex] == self.name:
index = columnIndex
for rowIndex in range(0, len(MH[0])):
result = MH[index][rowIndex]
if result == "w":
self.w += 1
elif result == "l":
self.l += 1
def toString(self):
r = "| " + self.name.ljust(9) + "|\n"
r += "|" + "----------" + "|\n"
r += "| w: " + str(self.w).ljust(6) + "|\n"
r += "| l: " + str(self.l).ljust(6) + "|\n"
return r
def getScore(self):
return [self.name, self.w]
def createAllPossibilities(MH, topN, results):
coo = emptyCellExist(MH)
if coo[0] >= 0:
cp1 = copy.deepcopy(MH)
cp1[coo[0]][coo[1]] = "w"
createAllPossibilities(cp1, topN, results)
cp2 = copy.deepcopy(MH)
cp2[coo[0]][coo[1]] = "l"
createAllPossibilities(cp2, topN, results)
else:
Teams = []
Teams.append(Team("RGE"))
Teams.append(Team("VIT"))
Teams.append(Team("G2"))
Teams.append(Team("MSF"))
Teams.append(Team("AST"))
Teams.append(Team("MAD"))
Teams.append(Team("FNC"))
Teams.append(Team("SK"))
Teams.append(Team("XL"))
Teams.append(Team("BDS"))
for t in Teams:
t.init_scores(MH)
scores = []
for t in Teams:
scores.append(t.getScore())
for n in range(topN):
best = 0
index = -1
for t in range(len(scores)):
if best < scores[t][1]:
best = scores[t][1]
index = t
scores[index][1] = 0
#print(scores)
results[index] += 1
def emptyCellExist(MH):
for row in range(len(MH[0])):
for cell in range(len(MH[0])):
if MH[row][cell] == "":
return [row, cell]
return [-1, -1]
# current score
MATCH_HISTORY = [ ["X", "RGE", "VIT", "G2", "MSF", "AST", "MAD", "FNC", "SK", "XL", "BDS"],
["RGE", "X", "w", "w", "l", "l", "w", "l", "l", "w", ""],
["VIT", "w", "X", "l", "w", "l", "w", "l", "w", "w", ""],
["G2", "w", "l", "X", "w", "w", "l", "l", "w", "w", ""],
["MSF", "w", "l", "v", "X", "w", "w", "l", "w", "w", ""],
["AST", "l", "l", "l", "l", "X", "l", "l", "l", "", ""],
["MAD", "w", "l", "v", "w", "l", "X", "l", "l", "", ""],
["FNC", "l", "l", "l", "w", "l", "l", "X", "w", "", ""],
["SK", "w", "l", "w", "l", "w", "w", "l", "X", "", ""],
["XL", "w", "l", "w", "w", "l", "l", "w", "w", "X", ""],
["BDS", "w", "l", "w", "w", "l", "w", "w", "l", "", "X"]]
# top teams must be top X
topN = 6
# count the number of matches done and left to do
matchesDone = 0
matchesLeft = 0
for row in MATCH_HISTORY:
for cell in row:
if cell == "w" or cell == "l":
matchesDone += 1
elif cell == "":
matchesLeft += 1
print("matches done : " + str(matchesDone))
print("matches left to do : " + str(matchesLeft))
print("that's " + str(pow(2, matchesLeft)) + " possibilities\n")
if matchesLeft > 20:
print("that's way to much for me")
else:
# if the number of matches left to do is low enought, then start calculating the probabilities
results = [0 for a in range(len(MATCH_HISTORY[0]))]
createAllPossibilities(MATCH_HISTORY, topN, results)
print(MATCH_HISTORY[0][1:])
for a in range(len(results)):
results[a] /= (pow(2, matchesLeft)*topN)
results[a] = int(results[a]*1000)/10
print(results)
while 1:
pass